# document

id: e39169b6b1f498d67cddab31d7e97f94
created_at: 2023-03-16 14:01:35
updated_at: 2023-03-16 14:01:35
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"options that enable or inhibit their adoption (high confidence). \r\nGeographic location and climate factors may make some technologies, \r\nsuch as solar PV or solar water heaters, impractical (Chang et al. 2009). \r\nCulture can inhibit efficient use of home heating or PV (Sovacool and \r\nGriffiths 2020), low-carbon diets (Dubois et al. 2019), and advanced \r\nfuel choices (Van Der Kroon et  al. 2013). Also, favourable financial \r\nconditions promote the uptake of PV (Wolske and Stern 2018), good \r\nfacilities increase recycling (Geiger et al. 2019), and vegetarian meal \r\nsales increase when more vegetarian options are offered."


id: 8545f80201646c3316075a884257dea9
created_at: 2023-03-16 14:01:35
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"Demand-side measures are fundamental to an integrated approach \r\nto low-carbon energy systems (high confidence). Mitigation options, \r\nsuch as wind parks, CCS, and nuclear power plants, may not be \r\nimplemented when actors oppose these options. Further, end \r\nusers, including consumers, governments, businesses and industry, \r\nwould need to adopt the relevant options, and then use these as \r\nintended; user adoption can be a key driver to scale up markets for \r\nlow-carbon technologies. This section discusses which factors shape \r\nthe likelihood that end users engage in relevant mitigation actions, \r\nfocusing on consumers; strategies to promote mitigation actions are \r\ndiscussed in Section 6.7.6.1."


id: 4212d1eef817ce64206b2588d170ea2a
created_at: 2023-03-16 14:01:35
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"Mitigation actions are more likely when individuals feel capable to \r\nadopt them (Pisano and Lubell 2017; Geiger et al. 2019), which may \r\ndepend on income and knowledge. Low-income groups may lack \r\nresources to invest in refurbishments and energy-efficient technology \r\nwith high upfront costs (Chang et al. 2009; Andrews-Speed and Ma \r\n2016; Wolske and Stern 2018). Yet, higher-income groups can afford \r\nmore carbon-intensive lifestyles (Golley and Meng 2012; Frederiks \r\net al. 2015; Wiedenhofer et al. 2017; Namazkhan et al. 2019; Santillan \r\nVera and de la Vega Navarro 2019; Mi et al. 2020). Knowledge of the \r\ncauses and consequences of climate change and of ways to reduce \r\nGHG emissions is not always accurate, but lack of knowledge is not \r\na main barrier to mitigation actions (Boudet 2019)."


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created_at: 2023-03-16 14:01:35
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"A wide range of actions of end users would reduce carbon emissions \r\nin energy systems (Abrahamse et  al. 2007; Dietz 2013; Hackmann \r\net al. 2014; Creutzig et al. 2018; Grubler et al. 2018), including:"


id: 758567fb8154b415834ec0373e532e8d
created_at: 2023-03-16 14:01:35
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"Motivation to engage in mitigation action, reflecting individuals' \r\nreasons for actions, depends on general goals that people strive for \r\nin their life (i.e., values). People who strongly value protecting the \r\nenvironment and other people are more likely to consider climate \r\nimpacts and to engage in a wide range of mitigation actions than \r\nthose who strongly value individual consequences of actions, such \r\nas pleasure and money (Taylor et al. 2014; Steg 2016). Values affect \r\nwhich types of costs and benefits people consider and prioritise \r\nwhen making choices, including individual, affective, social, and \r\nenvironmental costs and benefits (Gowdy 2008; Steg 2016)."


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"First, people are more likely to engage in mitigation behaviour \r\n(i.e., energy savings, energy efficiency, resource efficiency in buildings, \r\nlow-carbon energy generation) when they believe such behaviour has \r\nmore individual benefits than costs (Harland et al. 1999; Steg and Vlek \r\n2009; Kastner and Stern 2015; Korcaj et al. 2015; Kardooni et al. 2016; \r\nKastner and Matthies 2016; Wolske et al. 2017), including financial \r\nbenefits, convenience, comfort, autonomy, and independence in \r\nenergy supply (Wolske and Stern 2018). Yet, financial consequences \r\nseem less important for decisions to invest in energy-efficiency and \r\nrenewable energy production than people indicate (Zhao et al. 2012)."


id: c1605af6a5132157fe3f597e1915f0ff
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"Second, people are less likely to engage in mitigation behaviours that \r\nare unpleasurable or inconvenient (Steg 2016), and more likely to do \r\nso when they expect to derive positive feelings from such actions \r\n(Smith et al. 1994; Pelletier et al. 1998; Steg 2005; Carrus et al. 2008; \r\nBrosch et al. 2014; Taufik et al. 2016). Positive feelings may be elicited \r\nwhen behaviour is pleasurable, but also when it is perceived as \r\nmeaningful (Bolderdijk et al. 2013; Taufik et al. 2015)."


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"Various factors shape whether such mitigation actions are \r\nfeasible and considered by end users, including contextual factors, \r\nindividual abilities, and motivational factors. Mitigation actions can \r\nbe facilitated and encouraged by targeting relevant barriers and \r\nenablers (Section 6.7.6.1)."


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"Third, social costs and benefits can affect climate action (Farrow et al. \r\n2017), although people do not always recognise this (Nolan et al. 2008; \r\nNoppers et al. 2014). People engage more in mitigation actions when \r\nthey think others expect them to do so and when others act as well "


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"their moral norms to act accordingly, and promotes mitigation \r\nactions (Steg and de Groot 2010; Jakovcevic and Steg 2013; Chen \r\n2015; Wolske et al. 2017)."


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"(Harland et al. 1999; Nolan et al. 2008; Rai et al. 2016). Being part of \r\na group that advocates mitigation encourages such actions (Biddau \r\net al. 2016; Fielding and Hornsey 2016; Jans et al. 2018). Talking with \r\npeers can reduce uncertainties and confirm benefits about adoption \r\nof renewable energy technology (Palm 2017), and peers can provide \r\nsocial support (Wolske et al. 2017). People may engage in mitigation \r\nactions when they think this would signal something positive about \r\nthem (Milinski et  al. 2006; Griskevicius et  al. 2010; Noppers et  al. \r\n2014; Kastner and Stern 2015). Social influence can also originate \r\nfrom political and business leaders (Bouman and Steg 2019); GHG \r\nemissions are lower when legislators have strong environmental \r\nrecords (Jensen and Spoon 2011; Dietz et al. 2015)."


id: df71796676cac8c0b95f855c0a7bf48e
created_at: 2023-03-16 14:01:35
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"Initial mitigation actions can encourage engagement in other \r\nmitigation actions when people experience that such actions are \r\neasy and effective (Lauren et al. 2016), and when initial actions make \r\nthem realise they are a pro-environmental person, motivating them \r\nto engage in more mitigation actions so as to be consistent (van der \r\nWerff et al. 2014; Lacasse 2015, 2016; Peters et al. 2018). This implies \r\nit would be important to create conditions that make it likely that \r\ninitial mitigation actions motivate further actions."


id: 69d47712bbe6e6af4ed6048bd1f65673
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"Fourth, mitigation actions, including saving energy and hot water, \r\nlimiting meat consumption, and investing in energy efficiency, \r\nresource efficiency in buildings, and renewable energy generation \r\nare more likely when people care more strongly about others and the \r\nenvironment (Steg et al. 2015; Van Der Werff and Steg 2015; Wolske \r\net  al. 2017). People across the world generally strongly value the \r\nenvironment (Steg 2016; Bouman and Steg 2019), suggesting that \r\nthey are motivated to mitigate climate change. The more individuals \r\nare aware of the climate impact of their behaviour, the more they \r\nthink their actions can help reduce such impacts, which strengthens "


id: 4c0fa7bae35546dcc7ab48cd9e919755
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"Designing feasible, desirable, and cost-effective energy sector \r\nmitigation strategies requires comparison between the different \r\nmitigation options. One such metric is the cost of delivering one unit \r\nof energy, for example, the levelised cost, or USD MWh-1, of electricity \r\nproduced from different sources. Levelised costs of electricity (LCOE) \r\nare useful because they normalise the costs per  unit of service \r\nprovided. While useful in characterising options in broad strokes, "


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"Table 6.9 | Examples of cost of mitigation for selected electricity options. Results represent variations in mitigation options and displaced fossil generation. LCOEs \r\nare illustrative, but consistent with recent estimates. Negative values mean that the mitigation option is cheaper than the displaced option, irrespective of emissions benefits. \r\nNGCC: natural gas combined cycle."


id: 5c34bb774ee0d63cabb3bc73bf44ac42
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"it is important to acknowledge and understand several caveats \r\nassociated with these metrics, particularly when applied globally. \r\nThey may be constructed with different discount rates; they require \r\ninformation on energy input costs for options that require energy \r\ninputs (e.g.,  fossil electricity generation, biofuels); they depend on \r\nlocal resource availability, for example, solar insolation for solar \r\npower, wind classes for wind power, and rainfall and streamflow for \r\nhydropower; and actual implementation costs may include additional \r\nelements, for example, the costs of managing electricity grids heavily \r\ndependent on VRE electricity sources. These complicating factors vary \r\nacross regions, some depend strongly on the policy environment in \r\nwhich mitigation options are deployed, and some depend on how \r\ntechnologies are constructed and operated."


id: abc3d30f5ae7f2fac2f798b00958f00f
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"The feasibility and desirability of mitigation options extends well \r\nbeyond the market economic costs of installation and operation \r\n(Section  6.4.1). Figure  6.19 summarises the barriers and enablers \r\nfor implementing different mitigation options in energy systems. The \r\nfeasibility of different options can be enhanced by removing barriers \r\nand/or strengthening enablers of the implementation of the options. \r\nThe feasibility of options may differ across context (e.g., region), time \r\n(e.g., 2030 versus 2050), scale (e.g., small versus large) and the long\u0002term warming goal (e.g., 1.5degC versus 2degC)."


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"Many components of the energy system are affected by individual \r\nweather events and climate conditions (Table  6.10). In addition, \r\na range of compounding effects can be anticipated, as the complex, \r\ninterconnected climate and energy systems are influenced by multiple \r\nweather and climate conditions. This raises the question of whether \r\nthe energy system transformation needed to limit warming will be \r\nimpacted by climate change."


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"The impacts of climate change on the energy system can be divided \r\ninto three areas: impacts on the energy supply; impacts on energy \r\nconsumption; and impacts on energy infrastructure. The rest of this \r\nsection focuses on how the future changes in climate drivers might \r\naffect the ability of the energy system transformation needed to \r\nmitigate climate change. The discussion of energy infrastructure in \r\nthis section is limited to electricity system vulnerability."


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"A more direct metric of mitigation options is the cost to reduce \r\none tonne of CO2 or equivalent GHGs, or USD tCO2-eq-1 avoided. \r\nIn  addition to the comparison challenges noted above, this metric \r\nmust account for the costs and emissions of the emitting options that \r\nare being displaced by the low-carbon option. Assumptions about the \r\ndisplaced option can lead to very different mitigation cost estimates \r\n(Table  6.9). Despite these challenges, these metrics are useful for \r\nidentifying broad trends and making broad comparisons, even from \r\nthe global perspective in this assessment. But local information will \r\nalways be critical to determine which options are most cost-effective \r\nin any specific applications."


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"The increased weather dependency of future low-carbon electricity \r\nsystems amplifies the possible impacts of climate change (Staffell \r\nand Pfenninger 2018). However, globally climate change impacts \r\non electricity generation  - including hydro, wind and solar power \r\npotentials  - should not compromise climate mitigation strategies \r\n(high confidence). Many of the changes in the climate system will \r\nbe geographically complex at the regional and local levels. Thus, \r\nregionally climate change impacts on electricity generation could \r\nbe significant. Climate change impacts on bioenergy potentials \r\nare more uncertain because of uncertainties associated with the \r\ncrop response to climate change, future water availability and crop \r\ndeployment. Climate change can reduce the efficiency of thermal \r\npower generation and increase the risk of power plant shutdowns \r\nduring droughts. The potential additional cooling water needs of CCS \r\ncan increase these risks."


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"The impacts of climate change on hydropower will vary by region. \r\nHigh latitudes in the northern hemisphere are anticipated to \r\nexperience increased runoff and hydropower potential. For other \r\nregions, studies find both increasing and decreasing runoff and \r\nhydropower potential. Areas with decreased runoff are anticipated \r\nto experience reduced hydropower production and increased water \r\nconflict among different economic activities (high confidence)."


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"The conclusions regarding climate change impacts on hydropower \r\nvary due to differences in modelling assumptions and methodology, \r\nsuch as choice of the climate and hydrological models, choice of \r\nmetrics (e.g.,  projected production vs hydropower potential), level \r\nof  modelling details between local and global studies, reservoir \r\noperation assumptions. Also important is how hydropower production \r\nmatches up with other reservoir purposes, accounting for other water \r\nand energy users, and how the competing uses are impacted by \r\nclimate change (van Vliet et al. 2016b; Turner et al. 2017). Nonetheless, "


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"Hydropower production is directly related to the availability of water. \r\nChanges in runoff and its seasonality and changes in temperature \r\nand precipitation intensity will influence hydroelectricity production "


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"Figure 6.20 | Global spatial patterns of changes in gross hydropower potential based on climate forcing from five climate models. Changes are shown for \r\nthe 2050s (upper) and the 2080s (lower) for the low-emission scenario (RCP2.6; left) and highest emission scenario (RCP8.5; right) scenarios relative to the control period \r\n(1971-2000). Source: data from van Vliet et al. (2016b)."


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created_at: 2023-03-16 14:01:35
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"Ferreira et al. 2017; de Jong et al. 2019). No robust future changes \r\nin wind resources have been identified in China (Xiong et al. 2019). \r\nHowever, none of the global or regional studies of the effects of climate \r\nchange on wind resources considers the fine-scale dependence of \r\nwind resources on the topography and wind direction (Sanz Rodrigo \r\net al. 2016; Dorenkamper et al. 2020) or the effect of expanding wind \r\nenergy exploitation (Volker et al. 2017; Lundquist et al. 2019). There \r\nis limited evidence that extreme wind speeds, which can damage \r\nwind turbines, will increase due to climate change (Pes et al. 2017; \r\nPryor et  al. 2020). Nevertheless, projected changes in Europe and \r\nNorth America - regions where the most extensive analysis has been \r\nundertaken - are expected to be within the estimates embedded in \r\nthe design standards of wind turbines (Pryor and Barthelmie 2013)."


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"analyses consistently demonstrate that the global impact of climate \r\nchange on hydropower will be small, but the regional impacts will be \r\nlarger, and will be both positive and negative (Figure 6.20). Gross global \r\nhydropower potential in the 2050s has been estimated to slightly \r\ndecrease (Hamududu and Killingtveit 2012) between 0.4% (for the \r\nlow-emission scenario) and 6.1% (for the highest-emission scenario) \r\nfor the 2080s compared to 1971-2000 (van Vliet et al. 2016a)."


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"Climate change will not substantially impact future wind resources \r\nand will not compromise the ability of wind energy to support low\u0002carbon transitions (high confidence). Changing wind variability may \r\nhave a small-to-modest impact on backup energy and storage needs \r\n(low confidence); however, current evidence is largely from studies \r\nfocused on Europe."


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"Long-term global wind energy resources are not expected to \r\nsubstantially change in future climate scenarios (Karnauskas \r\net  al. 2018; Pryor et  al. 2020; Yalew et  al. 2020). However, recent \r\nresearch has indicated consistent shifts in the geographic position of \r\natmospheric jets in the high-emission scenarios (Harvey et al. 2014), \r\nwhich would decrease wind power potentials across the Northern \r\nHemisphere mid-latitudes and increase wind potentials across \r\nthe tropics and the Southern Hemisphere. However, the climate \r\nmodels used to make these assessments differ in how well they can \r\nreproduce the historical wind resources and wind extremes, which \r\nraises questions about the robustness of their predictions of future \r\nwind resources (Pryor et al. 2020)."


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"Climate change is not expected to substantially impact global solar \r\ninsolation and will not compromise the ability of solar energy to \r\nsupport low-carbon transitions (high confidence). Models show \r\ndimming and brightening in certain regions, driven by cloud, \r\naerosol and water vapour trends (Chapter 12 of IPCC AR6 WGI). The \r\nincrease in surface temperature, which affects all regions, decreases \r\nsolar power output by reducing the PV panel efficiency. In  some \r\nmodels and climate scenarios, the increases in solar insolation \r\nare counterbalanced by reducing efficiency due to rising surface \r\nair temperatures, which increase significantly in all models and \r\nscenarios (Jerez et al. 2015; Bartok et al. 2017; Emodi et al. 2019). \r\nIncreases in aerosols would reduce the solar resource available and \r\nadd to maintenance costs (Chapter 12 of IPCC AR6 WGI)."


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"There are many regional studies on changes in wind resources from \r\nclimate change. For Europe, there is medium evidence and moderate \r\nagreement that wind resources are already increasing and will \r\ncontinue to increase in Northern Europe and decrease in Southern \r\nEurope (Carvalho et al. 2017; Devis et al. 2018; Moemken et al. 2018). \r\nFor North America, the various studies have low agreement for the \r\nchanges in future wind resources in part because the year-to-year \r\nvariations in wind resources are often larger than the future change \r\ndue to climate change (Johnson and Erhardt 2016; Chen 2020; \r\nCostoya et al. 2020; Wang et al. 2020b). Studies show increases in \r\nfuture wind resources in windy areas in South America (Ruffato\u0002"


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"climate change will reduce global bioenergy potential by about 16%; \r\nwith CO2 fertilisation, however, climate change increases this potential \r\nby 45% (Haberl et al. 2011). However, newer studies in the USA find \r\nlittle effect of CO2 fertilisation on switchgrass yield (Dolan et al. 2020). \r\nThere is also a considerable uncertainty across climate and crop models \r\nin estimating bioenergy potential (Hager et al. 2014)."


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"Climate change can affect biomass resource potential directly, via \r\nchanges in the suitable range (i.e., the area where bioenergy crops \r\ncan grow) and/or changes in yield, and indirectly, through changes \r\nin land availability. Increases in CO2 concentration increase biomass \r\nyield; climate changes (e.g., temperature, precipitation, and so on) \r\ncan either increase or decrease the yield and suitable range."


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"Climate change will shift the suitable range for bioenergy towards \r\nhigher latitudes, but the net change in the total suitable area is \r\nuncertain (high confidence). Several studies show northward shifts \r\nin the suitable range for bioenergy in the northern hemisphere (Tuck \r\net al. 2006; Barney and DiTomaso 2010; Bellarby et al. 2010; Hager \r\net al. 2014; Wang et al. 2014a; Preston et al. 2016; Conant et al. 2018; \r\nCronin et  al. 2018), but the net effect of climate change on total \r\nsuitable area varies by region, species, and climate model (Barney \r\nand DiTomaso 2010; Hager et al. 2014; Wang et al. 2014a)."


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content:
"Carbon capture may increase cooling water usage significantly, \r\nespecially in retrofits, with up to 50% increase in water usage for coal\u0002fired power plants globally, depending on the CCS technology (Rosa \r\net al. 2020) (Section 6.4). In Asia, planned coal capacity is expected to \r\nbe vulnerable to droughts, sea level rise, and rising air temperatures, \r\nand this may be exacerbated by incorporating carbon capture (Wang \r\net al. 2019c). Recently, however, studies have proposed designs of \r\nCCS with a minimal increase in water requirements (Magneschi et al. \r\n2017; Mikunda et al. 2021)."


id: 91bf7e46198c2b6de9392ac47e8c34e2
created_at: 2023-03-16 14:01:35
updated_at: 2023-03-16 14:01:35
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index: climate_gpt_only_giec
vector_id: 20468
content:
"The effect of climate change on bioenergy crop yields will vary across \r\nregion and feedstock (high confidence); however, in general, yields \r\nwill decline in low latitudes (medium confidence) and increase in \r\nhigh latitudes (low confidence) (Haberl et al. 2010; Cosentino et al. \r\n2012; Preston et  al. 2016; Cronin et  al. 2018; Mbow et  al. 2019). \r\nHowever, the average change in yield varies significantly across \r\nstudies, depending on the feedstock, region, and other factors \r\n(Beringer et al. 2011; Kyle et al. 2014; Mbow et al. 2019; Dolan et al. \r\n2020). Only a few studies extend the modelling of climate change \r\nimpacts on bioenergy to quantify the effect on bioenergy deployment \r\nor its implications on the energy system (Calvin et al. 2013, 2019; \r\nKyle et al. 2014; Thornton et al. 2017). These studies find that changes \r\nin deployment are of the same sign as changes in yield; that is, if \r\nyields increase, then deployment increases."


id: 5c1f3c342d732b3d858f6f99954998dc
created_at: 2023-03-16 14:01:35
updated_at: 2023-03-16 14:01:35
content_type: text
index: climate_gpt_only_giec
vector_id: 12003
content:
"Some of the uncertainty in the sign and magnitude of the impacts \r\nof climate change on bioenergy potential is due to uncertainties \r\nin CO2 fertilisation (the increase in photosynthesis due to increases in \r\natmospheric CO2 concentration) (Haberl et al. 2011; Bonjean Stanton \r\net al. 2016; Cronin et al. 2018; Solaun and Cerda 2019; Yalew et al. \r\n2020). For example, earlier studies found that, without CO2 fertilisation, "


id: 1db91a8f9bfa5469169e2214eec79f5f
created_at: 2023-03-16 14:01:35
updated_at: 2023-03-16 14:01:35
content_type: text
index: climate_gpt_only_giec
vector_id: 2112
content:
"Heating demand will decrease, and cooling demand will increase \r\nin response to climate change. Peak load may increase more than \r\nenergy consumption, and the changing spatial and temporal load \r\npatterns can impact transmission and needs for storage, demands\u0002side management, and peak-generating capacity (high confidence)."


id: f2fc973b37dc0d5c692d6c39e638121c
created_at: 2023-03-16 14:01:35
updated_at: 2023-03-16 14:01:35
content_type: text
index: climate_gpt_only_giec
vector_id: 35751
content:
"Climate change will decrease heating demands, especially in cold \r\nregions, and it will increase cooling demands, especially in warm \r\nregions (Yalew et  al. 2020). Recent studies report significant net \r\nimpacts, with the commercial and industrial sectors and substantial \r\nair condition penetration driving an increase in energy demand \r\n(Davis and Gertler 2015; Levesque et  al. 2018; De Cian and Sue \r\nWing 2019; van Ruijven et al. 2019; Yalew et al. 2020). For example, \r\nglobally, De Cian and Sue Wing (2019) found a 7-17% increase in \r\nenergy consumption due to climate change in 2050, with the range \r\ndepending on the climate change scenario. The overall effects of \r\nclimate change on building energy consumption are regionally \r\ndependent. For example, Zhang et  al. (2019) find that reduced \r\nheating will outweigh increased cooling in the residential buildings \r\nin Europe, but the reverse will be true in China."


id: fcc824117530274b1e02b827ae21d7d5
created_at: 2023-03-16 14:01:35
updated_at: 2023-03-16 14:01:35
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index: climate_gpt_only_giec
vector_id: 37283
content:
"In February 2021, the state of Texas was hit by three major storms and suffered significant scale power outages. More than 4.5 million \r\nhomes and businesses on the Texas electric grid were left without electricity for days, limiting the ability to heat homes during \r\ndangerously low temperatures and leading to food and clean water shortages (Busby et al. 2021). The Texas and other events - for \r\nexample, Typhoon Haiyan in Southeast Asia in 2013; the Australian bush fires in 2019-2020; forest fires in 2018 in California; water \r\nshortages in Cape Town, South Africa in 2018 and the western USA during 2021 - raise the question of whether future low-carbon \r\nenergy systems will be more or less resilient than those of today."


id: 695081c0716289b81cca8bca697f751
created_at: 2023-03-16 14:01:35
updated_at: 2023-03-16 14:01:35
content_type: text
index: climate_gpt_only_giec
vector_id: 14168
content:
"Some characteristics of low-carbon energy systems will make them less resilient. Droughts reduce hydroelectric electricity generation \r\n(Gleick 2016; van Vliet et al. 2016c); wind farms do not produce electricity in calm conditions or shut down in very strong winds \r\n(Petersen and Troen 2012); solar PV generation is reduced by clouds and is less efficient under extreme heat, dust storms, and wildfires \r\n(Perry and Troccoli 2015; Jackson and Gunda 2021). In addition, the electrification of heating will increase the weather dependence \r\nof electricity consumption (Staffell and Pfenninger 2018; Gea-Bermudez et al. 2021). Non-renewable generation, for example, from \r\nnuclear and fossil power plants, are also vulnerable to high temperatures and droughts as they depend on water for cooling (Cronin \r\net al. 2018; Ahmad 2021)."


id: 2160315ea9c2d50b467107bcbd09fb61
created_at: 2023-03-16 14:01:35
updated_at: 2023-03-16 14:01:35
content_type: text
index: climate_gpt_only_giec
vector_id: 2680
content:
"Lightning can cause wildfires or common-mode faults on electricity \r\nsystems associated with vegetation falling on power substations or \r\noverhead lines but is more generally associated with flashovers and \r\noverloads (Balijepalli et al. 2005). Climate change may change the \r\nprobability of lightning-related events (Romps et al. 2014)."


id: 6408994269e9f42f4c39f58a8e669ba7
created_at: 2023-03-16 14:01:35
updated_at: 2023-03-16 14:01:35
content_type: text
index: climate_gpt_only_giec
vector_id: 13306
content:
"While long-term trends are important for electricity system planning, \r\nshort-term effects associated with loss of power can be disruptive and \r\nlead to significant economic losses along with cascading impacts on \r\nhealth and safety. Extreme weather and storms threaten the electricity \r\nsystem in different ways, affecting system resilience, reliability, and \r\nadequacy (Moreno-Mateos et al. 2020). The implications of climate \r\nchange for electricity system vulnerability will depend on the degree \r\nto which climate change alters the frequency and intensity of extreme \r\nweather events. The complex compounding effects of simultaneous \r\nevents (e.g., high winds and lightning occurring at the same time) are \r\nnot well understood."


id: e65423a92c261748a5738cd022c2912a
created_at: 2023-03-16 14:01:35
updated_at: 2023-03-16 14:01:35
content_type: text
index: climate_gpt_only_giec
vector_id: 33727
content:
"Snow and icing can impact overhead power lines by weighing \r\nthem down beyond their mechanical limits, leading to collapse and \r\ncascading outages (Feng et al. 2015). Snow can also lead to flashovers \r\non lines due to wet snow accumulation on insulators (Yaji et al. 2014; \r\nCroce et al. 2018) and snow and ice can impact wind turbines (Davis \r\net  al. 2016). Climate change will lower the risk of snow and ice \r\nconditions (McColl et al. 2012), but there is still an underlying risk \r\nof sporadic acute cold conditions such as those associated with the \r\nwinter storms in Texas in 2021 (Box 6.6)."


id: 1c3c594318cd4292128891a41582a43a
created_at: 2023-03-16 14:01:35
updated_at: 2023-03-16 14:01:35
content_type: text
index: climate_gpt_only_giec
vector_id: 1901
content:
"High wind speeds can shear lines through mechanical failure \r\nor cause lines to collide, causing transient events (Panteli and \r\nMancarella 2015; Yalew et  al. 2020). Hurricane conditions can \r\ndamage electricity system infrastructures, including utility-scale \r\nwind and solar PV plants. Electricity systems may experience high \r\ndemand when lines are particularly at risk from mechanical failure \r\nfrom wind and storm-related effects. However, except for medium \r\nevidence of increases in heavy precipitation associated with tropical \r\ncyclones, there is limited evidence that extreme wind events will \r\nincrease in frequency or intensity in the future (Kumar et al. 2015; \r\nPryor et al. 2020)."


id: 7569e31059006641837584e06bcda552
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 16059
content:
"Flooding poses a threat to the transmission and distribution systems \r\nby inundating low-lying substations and underground cables. Coastal \r\nflooding also poses a threat to electricity system infrastructure. Rising \r\nsea levels from climate change and associated storm surge may also \r\npose a  significant risk for coastal electricity systems (Entriken and \r\nLordan 2012)."


id: 689f908d61e0f12cb329205134a6fe1d
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 14053
content:
"Temperature increases influence electricity load profiles and \r\nelectricity generation, as well as potentially impact supporting \r\ninformation and communication infrastructure. Heat can pose direct \r\nimpacts to electricity system equipment such as transformers. Referred \r\nto as 'solar heat faults', they occur under high temperatures and low \r\nwind speeds and can be exacerbated by the urban heat island effect \r\n(McColl et al. 2012). Increasing temperatures affect system adequacy \r\nby reducing electric transmission capacity, simultaneously increasing \r\npeak load due to increased air conditioning needs (Bartos et al. 2016)."


id: 65580ed3d99ed10bf543d0924145e854
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 13521
content:
"Wildfires pose a  significant threat to electricity systems in dry \r\nconditions and arid regions (Dian et al. 2019). With climate change, \r\nwildfires will probably become more frequent (Flannigan et al. 2013) \r\nand more difficult to address, given that they frequently coincide with \r\ndry air and can be exacerbated by high winds (Mitchell 2013)."


id: c2539d7f9bc4bec9ff33de36c38a2e86
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 28160
content:
"While climate change will affect energy systems (Section 6.5), the reverse is potentially also true: increasing the use of renewable energy \r\nsources could affect local climate. Large solar PV arrays and hydroelectric dams darken the land surface, and wind turbines extract the wind's \r\nkinetic energy near the Earth's surface. Their environmental impacts of renewable energy production are mostly confined to areas close \r\nto the production sources and have been shown to be trivial compared to the mitigation benefits of renewable energy (high confidence)."


id: e3a4d5afaecae3ef65620985ce987745
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 33297
content:
"Wind energy. Surface temperature changes in the vicinity of wind farms have been detected (Smith et al. 2013; Lee and Lundquist \r\n2017; Takle et al. 2019; Xia et al. 2019) in the form of night-time warming. Data from field campaigns suggest that a 'suppression \r\nof cooling' can explain the observed warming (Takle et  al. 2019). Regional and climate models have been used to describe the \r\ninteractions between turbines and the atmosphere and find minor impacts (Vautard et al. 2014). More sophisticated models confirm \r\nthe local warming effect of wind farms but report that the impact on the regional area is slight and occasional (Wang et al. 2019d). \r\nWind turbines alter the transport and dissipation of momentum near the surface but do not directly impact the Earth's energy balance"


id: e8f5ec793cb1765252368405e95aed10
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 34168
content:
"(Fischereit et al. 2021). However, the secondary modifications to the energy and water exchanges have added implications for the \r\nclimate system (Jacobson and Archer 2012)."


id: 29c05edd31f058b4314fc64633b02820
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 4000
content:
"Hydropower. The potential climate impacts of hydropower concentrate on the GHG emissions from organic matter decomposition \r\nwhen the carbon cycle is altered by the flooding of the hydroelectric power plant reservoir (Ocko and Hamburg 2019), but emissions \r\nfrom organic matter decomposition decrease over time. The darker surface of the reservoir, compared to the lighter surrounding land \r\nmay counterbalance part of the reduced GHG emissions by hydropower production (Wohlfahrt et al. 2021). However, these impacts \r\nvary significantly among facilities due to the surrounding land properties and the area inundated by the reservoir."


id: 1d0e369f988b5c956f6608647dc32a99
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 2016
content:
"This section synthesises current understanding of net-zero energy \r\nsystems. Discussions surrounding efforts to limit warming are \r\nfrequently communicated in terms of the point in time at which net \r\nanthropogenic CO2 emissions reach zero, accompanied by substantial \r\nreductions in non-CO2 emissions (IPCC 2018, Chapter 3). Net-zero GHG \r\ngoals are also common, and they require net-negative CO2 emissions \r\nto compensate for residual non-CO2 emissions. Economy-wide CO2 and \r\nGHG goals appear in many government and corporate decarbonisation \r\nstrategies, and they are used in a variety of ways. Most existing carbon\u0002neutrality commitments from countries and sub-national jurisdictions \r\naim for economies with very low emissions rather than zero emissions. \r\nOffsets, carbon dioxide removal (CDR) methods, and/or land sink \r\nassumptions are used to achieve net-zero goals (Kelly Levin et al. 2020)."


id: dacb18371ca1fd4a5b250677c978c981
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 31950
content:
"Limiting warming to well below 2degC requires that CO2 emissions \r\nfrom the energy sector be reduced to near zero or even below \r\nzero (Section  6.7; Chapter  3). Policies, technologies, behaviours, \r\ninvestments, and other factors will determine the speed at which \r\ncountries transition to net-zero energy systems - those that emit very \r\nlittle or no emissions. An understanding of these future energy systems \r\ncan help to chart a course toward them over the coming decades."


id: 587e934622e34092cec129b7aa2cb469
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 11421
content:
"Figure 6.21 | Residual emissions and carbon dioxide removal (CDR) when global energy and industrial CO2 emissions reach net-zero. Residual emissions and \r\nCDR in net-zero scenarios from the AR6 Scenarios Database show global differences across warming levels (light blue = scenarios that limit warming to 1.5degC (>50%) with no \r\nor limited overshoot and scenarios that return warming to 1.5degC (>50%) after a high overshoot; yellow = scenarios that limit warming to 2degC (>67%) and scenarios that limit \r\nwarming to 2degC (>50%); dark blue = scenarios that limit warming to 2.5degC (>50%), scenarios that limit warming to 3degC (>50%), scenarios that limit warming to 4degC (>50%), \r\nand scenarios that exceed warming of 4degC (>=50%)). In each case, the boxes show the 25th to 75th percentile ranges, and whiskers show the 5th and 95th percentiles. Lines \r\nand circles within the boxes denote the median and mean values, respectively."


id: 9bff31db0df30a5603af090110efb539
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 22101
content:
"pathways for different sectors, enumerating opportunities and barriers \r\nfor each, their costs, highlighting robust insights, and characterising key \r\nuncertainties (Davis et al. 2018; Hepburn et al. 2019)."


id: 73f97f7074367a911b9a65ec267f20af
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 15853
content:
"This section focuses on energy systems that produce very little or no \r\nCO2 emissions, referred to in this chapter as 'net-zero energy systems'. \r\nWhile energy systems may not reach net zero concurrently with \r\neconomy-wide CO2 or GHG emissions, they are a useful benchmark \r\nfor planning a path to net zero. Note that the focus here is on energy \r\nsystems with net-zero CO2 emissions from fossil fuel combustion \r\nand industrial processes, but the lessons will be broadly applicable \r\nto net-zero GHG energy systems as well. Net-zero GHG energy \r\nsystems would incorporate the major efforts made to reduce non-CO2\r\nemissions (e.g., CH4 from oil, gas and coal as discussed in Section 6.4) \r\nand would also need to incorporate more CDR to compensate for \r\nremaining non-CO2 GHG emissions. Energy sector emissions in many \r\ncountries may not reach net zero at the same time as global energy \r\nsystem emissions (Figure 6.25 and Cross-Chapter Box 3 in Chapter 3)."


id: 129824351ce490d391a5705a014918bb
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 423
content:
"Configurations of net-zero energy systems will vary by region but \r\nare likely to share several common characteristics (high confidence) \r\n(Figure 6.22). We focus on seven of those common characteristics in \r\nthe remainder of this subsection."


id: dd966ceceeeba39c1213db37a5727518
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 32368
content:
"Net-zero energy systems entail trade-offs across economic, \r\nenvironmental, and social dimensions (Davis et  al. 2018). Many \r\nsocio-economic, policy, and market uncertainties will also influence \r\nthe configuration of net-zero energy systems (Smith et  al. 2015; \r\nvan Vuuren et  al. 2018; Bistline et  al. 2019; Krey et  al. 2019; \r\nAzevedo et al. 2021, Pye et al. 2021). There are reasons that countries \r\nmight focus on one system configuration versus another, including \r\ncost, resource endowments, related industrial bases, existing \r\ninfrastructure, geography, governance, public acceptance, and other \r\npolicy priorities (Section 6.6.4 and Chapter 18 of WGII)."


id: 8752d612ace3d16ec89a1eed046383bc
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 18831
content:
"Explorations of net-zero energy systems have been emerging in the \r\ndetailed systems modelling literature (Azevedo et  al. 2021; Bistline \r\n2021b). Reports associated with net-zero economy-wide targets for \r\ncountries and sub-national entities typically do not provide detailed \r\nroadmaps or modelling but discuss high-level guiding principles, though \r\nmore detailed studies are emerging at national levels (Capros et al. 2019; \r\nWei et al. 2020; Duan et al. 2021; Williams et al. 2021a). Most analysis \r\nhas focused on identifying potential decarbonisation technologies and "


id: 558ec862df4fa249f4c5339941038229
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 10940
content:
"There is considerable flexibility regarding the overall quantity of \r\nliquid and gaseous fuels that will be required in net-zero energy \r\nsystems (high confidence) (Figure 6.22 and Section 6.7.4). This will be \r\ndetermined by the relative value of such fuels as compared to systems \r\nwhich rely more or less heavily on zero-emissions electricity. In turn, \r\nthe share of any fuels that are fossil or fossil-derived is uncertain \r\nand will depend on the feasibility of CCS and CDR technologies and "


id: 2e6dd1259165a4409bc76d20f1370788
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 4750
content:
"long-term sequestration as compared to alternative, carbon-neutral \r\nfuels. Moreover, to the extent that physical, biological, and/or socio\u0002political factors limit the availability of CDR (Smith et al. 2015; Field \r\nand Mach 2017), carbon management efforts may prioritise residual \r\nemissions related to land use and other non-energy sources."


id: a579e9b6db3b9fe1ddf0a529ad5d0a83
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 23603
content:
"other balancing resources discussed in Box 6.8) will be needed to \r\nensure reliability and resource adequacy with high percentages of \r\nwind and solar (Jenkins et al. 2018b; Dowling et al. 2020; Denholm \r\net  al. 2021) though each option involves uncertainty about costs, \r\ntiming, and public acceptance (Albertus et al. 2020)."


id: 9b08cf885e6e8d0daf482c217b7cd878
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 21936
content:
"Electricity systems require a range of different functional roles - for \r\nexample, providing energy, capacity, or ancillary services. As a result, \r\na  range of different types of generation, energy storage, and \r\ntransmission resources may be deployed in these systems (Baik et al. \r\n2021). There are many options for each of these roles, each with their \r\nstrengths and weaknesses (Sections 6.4.3 and 6.4.4), and deployment \r\nof these options will be influenced by the evolution of technological \r\ncosts, system benefits, and local resources (Fell and Linn 2013; Hirth \r\n2015; Bistline et al. 2018; Mai et al. 2018; Veers et al. 2019)."


id: e0d8afc92f4d821720de5c4dce146df9
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 32873
content:
"Net-zero energy systems will rely on decarbonised or net-negative \r\nCO2 emissions electricity systems, due to the many lower-cost options \r\nfor producing zero-carbon electricity and the important role of end\u0002use electrification in decarbonising other sectors (high confidence)."


id: d1e6e959dcb73d6b0f35fa75f195e8cf
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 30548
content:
"System management is critical for zero- or negative-emissions electricity \r\nsystems. Maintaining reliability will increasingly entail system planning \r\nand operations that account for characteristics of supply- and demand\u0002side resources (Hu et al. 2018). Coordinated planning and operations will \r\nlikely become more prevalent across portions of the electricity system \r\n(e.g., integrated generation, transmission, and distribution planning), \r\nacross sectors, and across geographies (EPRI 2017; Konstantelos et al. \r\n2017; Chan et al. 2018; Bistline and Young 2019) (Section 6.4.3)."


id: 31f580453becf73aa0ffae4c735949e
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 5274
content:
"The approach to other sectors could impact on electricity sector planning, \r\nand the role of some technologies (e.g.,  hydrogen, batteries, CCS) \r\ncould depend on deployment in other sectors. CCS offers opportunities \r\nfor CO2 removal when fuelled with syngas or biomass containing \r\ncarbon captured from the atmosphere (Hepburn et al. 2019); however, "


id: 7e46778721a66595f51739df68ea569
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 17429
content:
"power to fuels (PtX) electricity conversion to create low-emissions \r\nsynthetic fuels (Sections 6.6.2.6, 6.4.4, and 6.4.5), which could impact \r\non electricity system planning and operations. Additionally, if DAC \r\ntechnologies are used, electricity and heat requirements to operate \r\nDAC could impact electricity  system investments and operations \r\n(Realmonte et al. 2019; Bistline and Blanford 2021a)."


id: b6e1bafdd9a6ddf71277da849c6deb30
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 26297
content:
"concerns about lifecycle environmental impacts, uncertain costs, and \r\npublic acceptance are potential barriers to widespread deployment \r\n(Section 6.4.2). It is unclear whether CDR options like BECCS will be \r\nincluded in the electricity mix to offset continued emissions in other \r\nparts of the energy system or beyond (MacDowell et al. 2017; Bauer \r\net al. 2018a; Luderer et al. 2018). Some applications may also rely on "


id: adbcf786789f902ebd35394037e8dc81
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"The decreasing cost and increasing performance of renewable energy has generated interest in the feasibility of providing nearly all energy \r\nservices with renewables. Renewable energy includes wind power, solar power, hydroelectric power, bioenergy, geothermal energy, tidal \r\npower, and ocean power. There are two primary frames around which 100% renewable energy systems are discussed: 100% renewable \r\nelectricity systems and 100% renewable energy systems, considering not only electricity but all aspects of the energy system."


id: 62ae2bcbb9e0b60335cb1f60f9c4af38
created_at: 2023-03-16 14:01:36
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content:
"There are many balancing options in systems with very high renewables (Milligan et al. 2015; Jenkins et al. 2018b; Mai et al. 2018; \r\nBistline 2021a; Denholm et al. 2021)."


id: 585e7a8c125e37cd48c4fa2ee70e426d
created_at: 2023-03-16 14:01:36
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content:
"Deployment of integration options depends on their relative costs and value, regulations, and electricity market design. There is \r\nconsiderable uncertainty about future technology costs, performance, availability, scalability, and public acceptance (Kondziella and \r\nBruckner 2016; Bistline et al. 2019). Deploying balanced resources likely requires operational, market design, and other institutional \r\nchanges, as well as technological changes in some cases (Denholm et al. 2021; Cochran et al. 2014). Mixes will differ based on \r\nresources, system size, flexibility, and whether grids are isolated or interconnected."


id: 6e2bd43d836078c81e91b55a1ae20c82
created_at: 2023-03-16 14:01:36
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content:
"Although there are no technical upper bounds on renewable electricity penetration, the economic value of additional wind and \r\nsolar capacity typically decreases as their penetration rises, creating economic challenges at higher deployment levels (Hirth 2013; \r\nGowrisankaran et al. 2016; Cole et al. 2021; Denholm et al. 2021; Millstein et al. 2021). The integration options above, as well as changes \r\nto market design, can mitigate these challenges but likely will not solve them, especially since these options can exhibit declining value \r\nthemselves (De Sisternes et al. 2016; Bistline 2017; Denholm and Mai 2019) and may be complements or substitutes to each other."


id: a61b54c60f5c8e041531e6ee2896319b
created_at: 2023-03-16 14:01:36
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content:
"(Section  6.5.4.4), especially relative to biofuels and hydrogen ('low\u0002carbon fuels') (McCollum et al. 2014; Sachs et al. 2016; Rockstrom et al. \r\n2017), the prospects for which are still quite uncertain (Section 6.4). \r\nThe emergence of CDR technologies and the extent to which they \r\nallow for residual emissions as an alternative to electrification will also \r\naffect the overall share of energy served by electricity (Section 6.6.2.7)."


id: ad8baf9c4f640da9572f4559e5e9bd3f
created_at: 2023-03-16 14:01:36
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"Regions endowed with cheap and plentiful low-carbon electricity \r\nresources (wind, solar, hydropower) are likely to emphasise \r\nelectrification, while those with substantial bioenergy resources \r\nor availability of other liquid fuels might put less emphasis on \r\nelectrification, particularly in hard-to-electrify end uses (medium \r\nconfidence). For example, among a group of Latin American countries, \r\nrelative assumptions about liquid fuels and electricity result in an \r\nelectrification range of 28-82% for achieving a  net-zero energy \r\nsystem (Bataille et  al. 2020). Similarly, the level of penetration of \r\nbiofuels that can substitute for electrification will depend on regional \r\ncircumstances such as land-use constraints, competition with food, \r\nand sustainability of biomass production (Section 6.6.2.4)."


id: 3cc479710068908c858f2906e1c629e
created_at: 2023-03-16 14:01:36
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content:
"Several end uses, such as passenger transportation (light-duty electric \r\nvehicles, two and three wheelers, buses, rail) as well as building \r\nenergy uses (lighting, cooling) are likely to be electrified in net\u0002zero energy  systems (high confidence). Variations in projections of \r\nelectrification largely result from differences in expectations about \r\nthe ability and cost-competitiveness of electricity to serve other end \r\nuses such as non-rail freight transport, aviation, and heavy industry \r\n(McCollum et al. 2014; Bataille et al. 2016; EPRI 2018; Breyer et al. 2019) "


id: 7b3c63905e6f3a301f4720b00e1397ab
created_at: 2023-03-16 14:01:36
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content:
"Electrification of most buildings services, with the possible exception \r\nof space heating in extreme climates, is expected in net-zero energy \r\nsystems (high confidence) (Chapter 9). Space cooling and water heating \r\nare expected to be largely electrified. Building electrification is expected \r\nto rely substantially on heat pumps, which will help lower emissions \r\nboth through reduced thermal requirements and higher efficiencies "


id: 1a606f87fd3fae7ccbe495e574417d0
created_at: 2023-03-16 14:01:36
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content:
"(Mathiesen et al. 2015; Sven et al. 2018; Rissman et al. 2020). The level of \r\nelectrification for heating will depend on the trade-offs between building \r\nor household level heat pumps versus more centralised district heating \r\nnetwork options (Mathiesen et al. 2015; Brown et al. 2018), as well as \r\nthe cost and performance of heat pumps in more extreme climates and \r\nregional grid infrastructure (EPRI 2018; Waite and Modi 2020)."


id: c6d71dca166532b9ea1406bc253af6fc
created_at: 2023-03-16 14:01:36
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content:
"Useful carbon-based fuels (e.g.,  methane, petroleum, methanol), \r\nhydrogen, ammonia, or alcohols can be produced with net-zero CO2\r\nemissions and without fossil fuel inputs (Sections 6.4.4 and 6.4.5). For \r\nexample, liquid hydrocarbons can be synthesised via hydrogenation \r\nof non-fossil carbon by processes such as Fischer-Tropsch (MacDowell \r\net  al. 2017) or by conversion of biomass (Tilman et  al. 2009). The \r\nresulting energy-dense fuels can serve applications that are difficult to \r\nelectrify, but it is not clear if and when the combined costs of obtaining \r\nnecessary feedstocks and producing these fuels without fossil inputs \r\nwill be less than continuing to use fossil fuels and managing the \r\nrelated carbon through, for example, CCS or CDR (Ueckerdt et al. 2021)."


id: f4f1eaaea9baf43c3ad66681a2f6a6e3
created_at: 2023-03-16 14:01:36
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content:
"Costs are the main barrier to synthesis of net-zero emissions fuels \r\n(high confidence), particularly costs of hydrogen (a constituent of \r\nhydrocarbons, ammonia, and alcohols) (Section 6.4.5). Today, most \r\nhydrogen is supplied by steam reformation of fossil methane (CH4\r\ninto CO2 and H2) at a cost of 1.30- USD1.50 kg-1 (Sherwin 2021). \r\nNon-fossil hydrogen can be obtained by electrolysis of water, at \r\ncurrent costs of USD5-7 kgH2\r\n-1 (assuming relatively low electricity \r\ncosts and high utilisation rates) (Graves et  al. 2011; DOE 2020a; \r\nNewborough and Cooley 2020; Peterson et al. 2020). At these costs \r\nfor electrolytic hydrogen, synthesised net-zero emissions fuels would \r\ncost at least USD1.6 per litre of diesel equivalent (or USD6 gallon-1\r\nand USD46  GJ-1, assuming non-fossil carbon feedstock costs "


id: 2437221327645acc48cf09f0caf3f648
created_at: 2023-03-16 14:01:36
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content:
"Net-zero energy systems will need to rely on alternative fuels - notably \r\nhydrogen or biofuels  - in several sectors that are not amenable to \r\nelectricity and otherwise hard to decarbonise (medium confidence)."


id: 43e9fdca63c4f918d131968b551dff85
created_at: 2023-03-16 14:01:36
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content:
"an early stage (Nielander et al. 2015; DOE 2020a). High hydrogen \r\nproduction efficiencies have been demonstrated, but costs, capacity \r\nfactors, and lifetimes need to be improved in order to make such \r\ntechnologies feasible for net-zero emissions fuel production at scale \r\n(McKone et al. 2014; DOE 2020a; Newborough and Cooley 2020)."


id: ef8d3197742e6c3e460b18936dba122f
created_at: 2023-03-16 14:01:36
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content:
"of USD100 per  tonne of CO2 and low process costs of USD0.05 \r\nlitre-1 or USD1.5 GJ-1). Similar calculations suggest that synthetic \r\nhydrocarbon fuels could currently avoid CO2 emissions at a cost of \r\nUSD936-1404 tonne-1 (Ueckerdt et al. 2021). However, economies \r\nof scale are expected to bring these costs down substantially in the \r\nfuture (IRENA 2020c; Ueckerdt et  al. 2021), and R&D efforts are \r\ntargeting 60-80% reductions in costs (to less than USD2 kg-1 (H2)\r\n-1) \r\npossibly by use of less mature but promising technologies such as \r\nhigh-temperature electrolysis and thermochemical water splitting \r\n(Kuckshinrichs et al. 2017; Pes et al. 2017; Schmidt et al. 2017; Saba \r\net al. 2018; DOE, 2018, 2020b). Technologies capable of producing \r\nhydrogen directly from water and sunlight (photoelectrochemical \r\ncells or photocatalysts) are also under development, but are at "


id: 37f952ed87ff08339333f354e08ef636
created_at: 2023-03-16 14:01:36
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content:
"The carbon contained in net-zero emissions hydrocarbons must have \r\nbeen removed from the atmosphere either through DAC, or, in the case \r\nof biofuels, by photosynthesis (which could include CO2 captured from \r\nthe exhaust of biomass or biogas combustion) (Zeman and Keith 2008; \r\nGraves et al. 2011). A number of different groups are now developing \r\nDAC technologies, targeting costs of USD100 per tonne of CO2 or less \r\n(Darton and Yang 2018; Keith et al. 2018; Fasihi et al. 2019)."


id: e0f531cf03676b7f7f3f093da1d46352
created_at: 2023-03-16 14:01:36
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content:
"Hydrogen production costs have historically been prohibitive, but recent technological developments are bringing costs down. These \r\ndevelopments include improvements in hydrogen production technologies in terms of efficiency and capital costs (e.g., steam methane \r\nreforming) (Alrashed and Zahid 2021; Boretti and Banik 2021) and the emergence of alternative production technologies such as \r\nelectrolysers (Dawood et al. 2020). These technological changes, along with decreasing costs of renewable power, are increasing \r\nthe viability of hydrogen. Other improvements in hydrogen-based technologies are also emerging quickly. Gas turbines now run on \r\nblended fuels containing 5-95% hydrogen by volume (GE 2020) and could operate entirely on hydrogen by 2030 (Pflug et al. 2019). \r\nFuel cell costs have decreased by 80-95% since the early 2000s, while power density and durability have improved (Jouin et al. 2016; \r\nIEA 2019e; Kurtz et al. 2019)."


id: 709c41137ac871f3bac6091163998937
created_at: 2023-03-16 14:01:36
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"For hydrogen to support decarbonisation, it will need to be produced from zero-carbon or extremely low-carbon energy sources. \r\nOne such production category is 'green hydrogen'. While there is no unified definition for green hydrogen, it can be produced by \r\nthe electrolysis of water using electricity generated without carbon emissions (such as renewables). Hydrogen can also be produced \r\nthrough biomass gasification with carbon capture and storage (BECCS), leading to negative carbon emissions (Arnaiz del Pozo et al. \r\n2021). Additionally, 'blue hydrogen' can be produced from natural gas through the process of auto-thermal reforming (ATR) or steam \r\nmethane reforming, combined with CCS technology that would absorb most of the resulting CO2 (80-90%)."


id: c71f46f6b4c6c2f3d801e9b482479922
created_at: 2023-03-16 14:01:36
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content:
"and cost-effective, with the potential for large-scale deployment \r\n(Chapters 5, 9, 10, and 11). For this reason, existing studies find that \r\nenergy efficiency and demand reduction strategies will be important \r\ncontributors to net-zero energy systems (Creutzig et al. 2018; Davis \r\net al. 2018; DeAngelo et al. 2021). Lower demand reduces the need \r\nfor low-carbon energy or alternative fuel sources."


id: fa15fe148b36f4f66b871c8ce81e2054
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"Demand-side or demand reduction strategies include technology \r\nefficiency improvements, strategies that reduce energy consumption \r\nor demand for energy services (such as reducing the use of personal \r\ntransportation, often called 'conservation') (Creutzig et al. 2018), and \r\nstrategies such as load curtailment."


id: f5000b6dfb22d8c5eaccf489ecc5faab
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"Characterising efficiency of net-zero energy systems is problematic \r\ndue to measurement challenges (high confidence). Efficiency itself \r\nis difficult to define and measure across full economies (Saunders \r\net al. 2021). There is no single definition of energy efficiency and the "


id: bd6e40c67b5d94630bef60b6a6bcdbff
created_at: 2023-03-16 14:01:36
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vector_id: 27370
content:
"Net-zero energy systems will use energy more efficiently than \r\nthose of today (high confidence). Energy efficiency and energy \r\nuse reduction strategies are generally identified as being flexible "


id: ce97227aa56c869285d8c28f2e76f1d7
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 30043
content:
"dwellings, early retirement of inefficient buildings, smaller floor areas, \r\nand smart controls to optimise energy use in the building, namely for \r\nheating, cooling, LED lighting, and water heating (Chapter 9). End \r\nuses would utilise electricity, or potentially hydrogen, produced from \r\nzero-carbon sources. The use of electricity for heating and cooking \r\nmay often be a less efficient process at converting primary energy to \r\nenergy services than using natural gas, but using natural gas would \r\nrequire CDR in order to be considered net-zero emissions. Changes in \r\nbehaviour may modestly lower demand. Most economies would have \r\nbuildings with more efficient technologies powered by zero-carbon \r\nelectricity, and developing economics would shift from biomass \r\nto electricity, raising their energy consumption as population and \r\nwealth increase under net-zero energy systems."


id: c35ab5ed8513cef6496c5a8ddb6d8af
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content:
"definition understandably depends on the context used (Patterson \r\n1996), which ranges from device-level efficiency all the way to the \r\nefficient use of energy throughout an economy. Broadly, energy\u0002efficient strategies allow for the same level of services or output \r\nwhile using less energy. At the level of the entire economy, measures \r\nsuch as primary or final energy per capita or per GDP are often used \r\nas a  proxy for energy efficiency; these measures reflect not only \r\nefficiency, but also many other factors such as industrial structure, \r\nendowed natural resources, consumer preferences, policies, and \r\nregulations. Energy efficiency and other demand-side strategies \r\nrepresent such a large set of technologies, strategies, policies, market \r\nand consumers' responses and policies that aggregate measures can \r\nbe difficult to define (Saunders et al. 2021)."


id: 1baa167ec6507727c8ddf07e450b14ee
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content:
"Industry has seen major efficiency improvements in the past, but \r\nmany processes are now close to their thermodynamic limits. \r\nElectrification and breakthrough processes (such as producing steel \r\nwith electricity and hydrogen), using recycled materials, using heat \r\nmore efficiently by improving thermal insulation, and using waste \r\nheat for heat pumps, as well using advanced sensors, monitoring, \r\nand visualisation and communication technologies may provide \r\nfurther efficiency improvements (Chapter 11)."


id: 682d75e0a951fe5a8042148f5d97a84
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"Measurement issues notwithstanding, virtually all studies that \r\naddress net-zero energy systems assume improved energy intensity \r\nin the future (high confidence). The overall efficiency outcomes and \r\nthe access to such improvements across different nations, however, \r\nare not clear. Energy consumption will increase over time - despite \r\nenergy efficiency improvements  - due to population growth and \r\ndevelopment (DeAngelo et al. 2021)."


id: 5a68ce4666ea6d480f99ac8546ec94e1
created_at: 2023-03-16 14:01:36
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content:
"Carbon-neutral energy systems are likely to be more interconnected \r\nthan those of today (high confidence). The many possible feedstocks, \r\nenergy carriers, and interconversion processes imply a greater need \r\nfor the integration of production, transport, storage, and consumption \r\nof different fuels (Davis et al. 2018). For instance, electrification is \r\nexpected to play an important role in decarbonising light-duty \r\nvehicles (Chapter 10, Section 6.4.3), yet the electricity and transport \r\nsectors have few direct interactions today. Systems integration and "


id: 7ebcf9c6f0a61e82047b6237e77c8b72
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"is not intended as a replacement for emissions reduction, but rather as \r\na complementary effort to offset residual emissions from sectors that \r\nare not decarbonised and from other low-carbon technologies such as \r\nfossil CCS (McLaren et al. 2019; Gaffney et al. 2020; Iyer et al. 2021)."


id: ad6c25db3c5235df916ed3d5305d980a
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
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content:
"DACCS offers a modular approach to CDR (Creutzig et al. 2019), but \r\nit could be a significant consumer of energy. DAC could also interact \r\nwith other elements of the energy systems as the captured CO2\r\ncould be reused to produce low-carbon methanol and other fuels \r\n(Hoppe et al. 2018; Realmonte et al. 2019; Zhang and Fujimori 2020). \r\nDACCS might also offer an alternative for use of excess electricity \r\nproduced by variable renewables (Wohland et  al. 2018), though \r\nthere are uncertainties about the economic performance of this \r\nintegrated approach."


id: 1657e2e718d3a4c8883528456709fdc3
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"Challenges associated with integrating net-zero energy systems \r\ninclude rapid technological change, the importance of behavioural \r\ndimensions in domains with limited experience and data, policy \r\nchanges and interactions, and path dependence. Technological cost \r\nand public acceptance will influence the degree of integration. Sectoral \r\npathways will likely be adaptive and adjust based on the resolution of \r\nuncertainties over time, and the relative competitiveness will evolve \r\nas the technological frontier evolves, which is a  complex and path\u0002dependent function of deployment, R&D, and inter-industry spillovers. \r\nSupply-side options interact with demand-side measures in increasingly \r\nintegrated energy systems (Sorrell 2015; van Vuuren et al. 2018)."


id: 1fade26773637cce690973040cc1ce17
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updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
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content:
"The transition to net-zero energy systems is not just technological; \r\nit requires shifts in institutions, organisations, and society more \r\ngenerally. As such, it involves institutional changes alongside \r\nchanges in supply, technology, or markets (Andrews-Speed 2016, \r\nPai et al. 2021). Institutional relationships between governments and \r\nenergy sector actors (e.g.,  consumers, electricity companies) affect \r\nthe nature of net-zero systems, as these entities may collaborate \r\non or dispute net-zero goals and measures to achieve them. For \r\nexample, following the Fukushima disaster, Japan placed emphasis \r\non government-utility-public cooperation on use of nuclear power as \r\na means of reducing carbon emissions (Sklarew 2018). Institutions \r\nare instrumental in shaping net-zero energy systems in multiple ways, \r\ncomplemented by and interacting with the behaviours of actors and \r\npolicy regimes in these systems (Figure 6.24)."


id: 41de46495915fbf5cf56d5cde07d2940
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"While CDR is likely necessary for net-zero energy systems, the scale \r\nand mix of strategies is unclear -nonetheless some combination of \r\nBECCS and DACCS are likely to be part of net-zero energy systems \r\n(high confidence). Studies indicate that energy-sector CDR may \r\npotentially remove 5-12 GtCO2 annually globally in net-zero energy \r\nsystems (Fuss et al. 2018) (Figure 6.22; Section 6.7; Chapter 12). CDR "


id: 6399fa188628139e8ee584d3f52efd97
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"One level of institutional interactions reflects embedded institutions, \r\nnorms, beliefs, and ideas that would need to change to support net-zero \r\nenergy systems. This applies, for example, to the objectives of modern \r\neconomies and the potentially contradictory dynamics embedded in "


id: 43c8bdca56511cadb31844604e2c127a
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content:
"(Stern et al. 2016b). Internationally and across different parts of the \r\nenergy system, institutional challenges such as these could become \r\neven more stark and complex (Van de Graaf 2013)."


id: cce2d15b91f0e4df89d3a9eebde5f86e
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vector_id: 29772
content:
"the concept of 'green growth' (Stegemann and Ossewaarde 2018; \r\nStoknes and Rockstrom 2018). The institutional environment  - the \r\npolitical and legal systems that govern exchanges and protect property \r\nrights - would also need to be different in net-zero energy systems. \r\nIn this setting, changing regulations or subsidies that continue to \r\nfavour carbon-intensive systems over the technologies of a net-zero \r\nenergy system might prove difficult (Sovacool 2017). More generally, \r\nnet-zero energy systems will need new regulatory frameworks to \r\nundertake new challenges, from managing a  more interconnected \r\ngrid to adequately governing underground storage of CO2. Institutions \r\nmay also govern specific transactions, such as firms or networks that \r\nsupply energy fuels or services. Current actors are typically resistant \r\nto disruptions, even if such disruptions may broadly benefit society \r\n(Kungl 2015; Schmid et al. 2017; Mori 2018)."


id: 92116b922bf1d26293de2f2d6a54354e
created_at: 2023-03-16 14:01:36
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content:
"Countries have flexibility to pursue options that make the most sense \r\nfor their national circumstances (Figure 6.25). They may emphasise \r\nsupply transformation over demand reduction; deploy different \r\nresources; engage at different levels in international energy trade; \r\nsupport different energy industries; focus on different energy carriers \r\n(e.g., electricity, hydrogen); or focus more on distributed or integrated \r\nsystems, among others. Many factors may influence the long-term \r\nnet-zero energy systems that are appropriate for any country's \r\nnational circumstances, including the following."


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content:
"Future technology. Technological transitions have often been driven \r\nby the relative merits of different technology options. Recent trends in \r\nthe use of PV cells, wind power, and in batteries, for example, have been \r\nspurred by their increasing economic competitiveness (Section 6.3). \r\nYet future technology cannot be fully predicted, so it provides only \r\na partial guide today for charting a path toward future systems."


id: df85080df928579465c28c6794500276
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 32667
content:
"Indigenous energy resources. Countries may emphasise \r\napproaches that take advantage of indigenous energy resources \r\nsuch as solar power, wind, hydroelectric resources, land for bioenergy \r\ncrops, CO2 storage capability, or fossil resources to be used with CCS. \r\nCountries with less abundant resources may put greater emphasis \r\non demand reductions and regional integration. Countries with \r\nresource bases that are easily tradeable, like low-carbon electricity or \r\nbioenergy, may choose to trade those resources rather than use them \r\ndomestically (Box 6.10, Section 6.4.3, 6.4.5)."


id: fcb92af7a474ec45b8e3c9e265232dfe
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 37273
content:
"Current energy system configuration. Future sectoral energy \r\ndemands and the potential for demand-side transformation are \r\npartially determined by existing infrastructure (e.g., building stocks, \r\ntransport infrastructure). Countries with less developed or growing \r\nenergy systems will have more flexibility to create the systems that \r\nbest match their long-term goals, but there may be substantial \r\nchallenges in transitioning directly to the most advanced low-carbon \r\ntechnology options, and countries may have different capacities to \r\nabsorb technology from other countries."


id: 493c3b36bafab5fa05a8b2ec63c8a873
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 8909
content:
"Regional climate. Climate influences heating and cooling demand, \r\nboth of which influence countries' energy demands and energy \r\ninfrastructure to meet those demands (Section 6.5). In addition to \r\ndaily demand profiles, heating and cooling are seasonal, influencing \r\nwhich energy sources may serve these loads and the seasonal \r\nstorage they require. Cooling is almost entirely served by electricity \r\ntoday, and heating has commonly been served by non-electric fuels. \r\nIn low-carbon energy systems, heating may be increasingly served \r\nby electricity (Section 6.6.4), meaning that the influence of regional \r\nclimate may be strongest on countries' electricity systems."


id: 7de0985614722de1eac6e5556d724e26
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 17378
content:
"Technological leadership, economic opportunities, and growth. \r\nCountries may emphasise technologies in which they intend to have \r\ntechnological leadership and a competitive advantage. These could \r\nemerge over time or be based on current areas of opportunity or \r\nleadership. Industrial policy will influence future energy system as \r\ntechnological choices can benefit or hamper incumbents or new \r\nmarket actors."


id: 7599e96755a0c821d7f7b1c351c28daa
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 16093
content:
"Regional integration. Regional integration will allow countries \r\nto bridge energy gaps using external linkages, including regional \r\nelectricity integration and trade in hydrogen, biomass, and other fuels. \r\nCountries with greater integration can rely more heavily on imports \r\nand may therefore rely less on indigenous resources (Box 6.10)."


id: aa44f8b45ab9a48dfeb929a229399c2f
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 24326
content:
"Energy security. Countries emphasising import security will tend \r\nto rely more heavily on indigenous resources (Section  6.3). Some \r\nindigenous resources may raise security of supply issues that will \r\ninfluence energy system configurations. Bioenergy and hydropower, \r\nfor example, can be subject to import climate risks (Section 6.5), and \r\nsignificant integration of VRE technologies will influence electricity \r\nsystem infrastructure and management (Section 6.6.2, Box 6.8)."


id: a1cebe68aa6402a5114d3fc1f2dfc53b
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 23022
content:
"Other factors. Countries will consider a  wide range of other \r\nfactors in building toward low-carbon energy systems. Population \r\ndensity, for example, will influence building and transportation \r\nenergy demands;  economic transitions will influence industrial \r\nenergy  demands. Societal priorities beyond climate, notably SDGs \r\nmay influence technology choices and types of energy systems \r\n(Sections 6.3 and 6.7.7)."


id: 9789e5bb0c82810f98fe27086efbe148
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 21369
content:
"Energy systems are linked across countries in many ways: countries transport crude oil across the ocean in supertankers, pipelines \r\ncarry oil and natural gas across country boundaries, electric power lines cross country boundaries, and countries trade industrial \r\ncommodities that carry embodied energy or that are essential inputs to mitigation technologies. Future systems will generate electricity \r\nusing different mixes of technologies, produce and transport different carriers (e.g., hydrogen or biofuels), and use far less fossil fuel, \r\namong other major changes. Important examples include electricity, hydrogen, and biomass."


id: f52e54c23471dac12122131b3fbc8352
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 36087
content:
"Electricity system integration. Net-zero energy systems will rely more heavily on electricity generated from low-emissions \r\ntechnologies. Given the significant variations in the location of low-carbon electricity resources and the temporal variability of some \r\nrenewable electricity sources, notably solar and wind power, regional electricity grids could reduce overall costs of net-zero energy \r\nsystems (Section 6.4.5). Furthermore, electricity transmission interconnections could significantly reduce local energy balancing costs \r\nand investment in peaking plants needed to meet security of supply requirements, and it could increase system resilience, especially in \r\nthe case of extreme events such as heat waves or cold spells (Fasihi and Bogdanov 2016). Important challenges to regional electricity \r\nintegration include geopolitical concerns from cross-border trade and societal and technological challenges associated with building \r\nnew transmission lines."


id: 9ff0763ce23e674491a6dbcda6041eaa
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 22700
content:
"Hydrogen trade. Hydrogen may play an important role in future net-zero energy systems, particularly in applications where electricity \r\nis not economically advantageous (Box 6.9). Hydrogen can be used to decarbonise regions in which it is produced, and it can also be \r\ntransported long distances to facilitate decarbonisation of sectors distant from sources of low-cost supply. Methods of long-distance, \r\nhigh-volume hydrogen transport could include liquid storage, chemical carriers, and gaseous delivery via pipelines (Section 6.4.5). \r\nIn net-zero systems with substantial wind and solar power generation, hydrogen can be generated through electrolysis and then \r\nshipped to other locations. Important challenges to hydrogen trade include cost-effective low-carbon production, cost of delivery \r\ninfrastructure, storage, and end-use technology costs and safety."


id: 8c3a7ffb74f3d80ebf8cf3aac2d103e5
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 19568
content:
"Trade in biomass. Biomass may also play an important role in net-zero energy systems (Section 6.6.4, Chapter 3). Large-scale bioenergy \r\nproduction and consumption is likely to trigger global biomass trade. Global bioenergy trade volumes presently exceed 1 EJ yr-1, \r\nof which 60% is directly traded for energy purposes (Proskurina et al. 2019a). Established trade mechanisms include wood pellet \r\ntransport, ethanol, and biodiesel (Proskurina et al. 2019b). In a net-zero global energy system, bioenergy trade could be greater than \r\ncurrent trade of coal or natural gas, but less than that of petroleum (Sharmina et al. 2017; Mandley et al. 2020). Some studies indicate "


id: 93d4a9853d556a2d75fd7b9251bfed5b
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 20768
content:
"that Latin America and Africa could become key exporting regions, with the EU, the USA, and East Asia emerging as key importers \r\n(Alsaleh and Abdul-Rahim 2018; Rentizelas et al. 2019). Studies have found that net bioenergy exports could be as high as 10% of \r\nGDP for some Latin American countries, while other regions like the EU may be faced with burgeoning import reliance (Daioglou et al. \r\n2020b; Mahlknecht et al. 2020). In addition to challenges associated with bioenergy production (Section 6.4 and Chapter 7), important \r\nchallenges to biomass trade include differences in sustainability criteria and land/biomass definitions in different jurisdictions, and \r\ndifficulties in establishing consistent monitoring and auditing systems (Lamers et al. 2016)."


id: 1a0733eb389fd861c6e6e14d69d02330
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 1561
content:
"nonetheless support the conclusion that the energy sector will not \r\nbe decarbonised without explicit policy actions to reduce emissions."


id: 1aa1971e8f0a23b0b65546d875d877f6
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 1667
content:
"Figure 6.26 | Projected energy sector GHG emissions for the 1.5degC scenarios (without and with overshoot), and likely below 2degC scenarios (without \r\nand with delayed policy action) during 2020-2050 (Source: AR6 Scenarios Database). Boxes indicate 25th and 75th percentiles, while whiskers indicate 5th and 95th \r\npercentiles. GHG emissions are inclusive of energy sector CO2, CH4, N2O emissions and 80% of global HFC emissions. Number of model-scenario combinations in AR6 Scenarios \r\nDatabase: limit warming to 1.5degC (>50%) with no or limited overshoot: 77; return warming to 1.5degC (>50%) after a high overshoot: 110; limit warming to 2(C (>67%) with \r\naction starting in 2020: 164; limit warming to 2degC (>67%) with NDCs until 2030: 97."


id: b55c5275716f969cc490d3f4e869f0b1
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
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vector_id: 26070
content:
"Figure 6.27 | Net regional (R6) CO2 emissions from energy across scenarios that limit/return warming to 1.5degC (>50%) with no or limited/after a high \r\novershoot, and scenarios that limit warming to 2degC (>67%) with action starting in 2020 or with NDCs until 2030, during 2020-2050 (Source: AR6 Scenarios \r\nDatabase). Boxes indicate 25th and 75th percentiles, while whiskers indicate 5th and 95th percentiles. Most mitigation scenarios are based on a cost-minimising framework \r\nthat does not consider historical responsibility or other equity approaches."


id: 8ee6d4f099831b451275e01c4259e1e6
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"Figure 6.28 | The timing of net-zero emissions for full economy greenhouse gases (GHGs), energy sector CO2, and electricity sector CO2. Boxes indicate \r\n25th and 75th percentiles, centre black line is the median, while whiskers indicate 1.5x the inter-quartile range. The vertical dashed lines represent the median point at which \r\nemissions in the scenarios have dropped by 95% (pink) and 97.5% (purple), respectively. Dots represent individual scenarios. The fraction indicates the number of scenarios \r\nreaching net-zero by 2100 out of the total sample. Source: AR6 Scenario Database."


id: f213e393c8f511f9212d5f9de485d49f
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 35617
content:
"to reduce emissions - if reductions are delayed - a more rapid energy \r\ntransition will subsequently be required to limit warming to 2degC or \r\nlower (Rogelj et al. 2015a, 2018a; IPCC 2018)."


id: b2327f3894270172f32ae76e8720caed
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 25540
content:
"(interquartile range) reach zero globally between 2044 and 2055 \r\n(2052 and 2078) (Figure 6.28). It is likely to be less costly to reduce \r\nnet CO2 emissions close to or below zero in the electricity sector than \r\nin other sectors, because there are relatively more low-emissions \r\noptions in electricity. Sectors such as long-distance transport, air \r\ntransport, and process heat are anticipated to face greater challenges \r\nto decarbonisation than the electricity sector (Clark and Herzog 2014; \r\nRogelj et al. 2015b, 2018b; IPCC 2018; Luderer et al. 2018)."


id: c7db9da3ab3de4572def54045aa8f9e4
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 29022
content:
"The timing of net-zero energy system emissions varies substantially \r\nacross scenarios. In scenarios limiting warming to 1.5degC (>50%) with \r\nno or limited overshoot (2degC (>67%)), the energy system reaches \r\nnet-zero CO2 emissions (interquartile range) from 2060 onwards \r\n(2080-). (Figure 6.28). However, net emissions reach near-zero more \r\nquickly. For example, in scenarios limiting warming to 1.5degC (>50%) \r\nwith no or limited overshoot (2degC (>67%)) net energy system CO2\r\nemissions drop by 95% between 2056 and 2075 (2073 and 2093). \r\nNet full economy GHG emissions reach zero more slowly than net \r\nCO2 emissions. In some scenarios, net energy system CO2 and total \r\nGHG emissions do not reach zero this century, offset by CDR in \r\nother sectors."


id: 32f84007b69531293c9ecb89450d186c
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 5440
content:
"In addition, there are potential options to remove CO2 from the \r\natmosphere in the electricity sector, notably BECCS, which would \r\nallow electricity sector emissions to drop below zero. Without CDR \r\noptions, electricity sector emissions may not fall all the way to zero. \r\nIf CDR is accomplished in other sectors and not in electricity, some \r\nfossil fuel plants may still lead to positive net electricity sector CO2\r\nemissions, even in net-zero economies (Bistline and Blanford 2021b; \r\nWilliams et al. 2021a)."


id: 2a7ff6955f893378996dd34768c42d7
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 4114
content:
"The timing of emissions reductions will vary across the different \r\nparts of the energy sector (Figure 6.28). To decarbonise most cost\u0002effectively, global net CO2 emissions from electricity generation \r\nwill likely reach zero before the rest of the energy sector (medium \r\nconfidence). In scenarios limiting warming to 1.5degC (>50%) with no or \r\nlimited overshoot (2degC (>67%)), net electricity sector CO2 emissions "


id: 9d06d9393b5b5549924aa9443a25e287
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 22247
content:
"We lack sufficient understanding to pin down precise dates at which \r\nenergy system CO2 emissions in individual countries, regions, or \r\nsectors will reach net zero. Net-zero timing is based on many factors \r\nthat are not known today or are bound up in development of key \r\ntechnologies, such as energy storage, bioenergy, or hydrogen. Some "


id: b1765c5e3737cabff52089a846e8c616
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 25416
content:
"countries have low-carbon resource bases that could support deep \r\nemissions reductions, while others do not. Timing is also affected \r\nby the availability of CDR options, whether these options are in the \r\nenergy sector or elsewhere, and the discount rate used to assess \r\nstrategies (Bednar et  al. 2019; Emmerling et  al. 2019). Moreover, \r\nwhile many scenarios are designed to minimise global mitigation \r\ncosts, many other frameworks exist for allocating mitigation effort \r\nacross countries (van den Berg et al. 2019) (Chapter 4)."


id: 4045bf7afd13e45cbce2801115471c69
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 7490
content:
"confidence). Low- and zero-carbon technologies produce 74-82% \r\n(interquartile range) of primary energy in 2050 in scenarios limiting \r\nwarming to 1.5degC (>50%) with no or limited overshoot and 55-68% \r\nin scenarios limiting warming to 2degC (>67%) (Figure 6.29). The share \r\nof low-carbon technologies in global primary energy supply today is \r\nbelow 20% (Chapter 3, Section 6.3, and Figure 6.29). The percentage \r\nof low- and zero-carbon energy will depend in part on the evolution of \r\nenergy demand - the more that energy demand grows, the more energy \r\nfrom low- and zero-carbon sources will be needed, and the higher the \r\npercentage of total primary energy these sources will represent."


id: 94583419c1176b4f5ed269476e41af7a
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 20849
content:
"Low- and zero-carbon sources produce 97-99% of global electricity \r\nin 2050 in scenarios limiting warming to 1.5degC (>50%) with no or \r\nlimited overshoot and 93-97% in scenarios limiting warming to 2degC \r\n(>67%) (Figure 6.29) (medium confidence). Decarbonising electricity \r\ngeneration, in tandem with increasing use of electricity (see below), \r\nis an essential near-term strategy for limiting warming. The increase \r\nin low- and zero-carbon electricity will occur while electricity demand \r\ngrows substantially. Studies have projected that global electricity \r\ndemand will roughly double by 2050 and quadruple to quintuple by \r\n2100 irrespective of efforts to reduce emissions (Bauer et al. 2017; \r\nLuderer et al. 2017; IEA 2019a)."


id: a194a7c5a4d6391bb7217b422efce302
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 22978
content:
"There are multiple technological routes to reduce energy system \r\nemissions (Section 6.6). Here we discuss three of these: (i) decarbonising \r\nprimary energy and electricity generation; (ii) switching to electricity, \r\nbioenergy, hydrogen, and other fuels produced from low-carbon \r\nsources; and (iii) limiting energy use through improvement of \r\nefficiency and conservation. CDR is discussed in Section 6.7.1.3 Fossil \r\nfuel transitions are discussed in Section 6.7.4."


id: a96d217794db33ef8665897f003ab969
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 24187
content:
"Decarbonising primary energy and electricity generation. \r\nLimiting warming to well below 2degC requires a  rapid and dramatic \r\nincrease in energy produced from low- or zero-carbon sources (high "


id: 4a7167cae3dadd8ca73f43aa92ba379d
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 9116
content:
"Figure 6.30 | Shares of low-carbon energy (all sources except unabated fossil fuels) and bioenergy (including both traditional and commercial biomass) \r\nin total primary energy, and solar+wind, CCS and nuclear in electricity for scenarios that limit/return warming to 1.5degC (>50%) with no or limited/after \r\na high, overshoot, and scenarios that limit warming to 2degC (>67%), with action starting in 2020 or NDCs until 2030, during 2030-2050 (Source: AR6 \r\nScenarios Database). Boxes indicate 25th and 75th percentiles while whiskers indicate 5th and 95th percentiles."


id: 46f9b66aa6688c7e19e4eab754e7140a
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 8552
content:
"Nonetheless, it is likely that wind and solar will dominate low-carbon \r\ngeneration and capacity growth over the next couple of decades due \r\nto supporting policies in many countries, and due to their significant \r\nroles in early electric sector decarbonisation, alongside reductions in \r\ncoal generation (Bistline and Blanford 2021b; Pan et al. 2021). Clean \r\nfirm technologies play important roles in providing flexibility and on\u0002demand generation for longer durations, though deployment of these \r\ntechnologies is typically associated with deeper decarbonisation levels \r\n(e.g., beyond 70-80% reductions), which are likely to be more important \r\nafter 2030 in many regions, and with more limited CDR deployment \r\n(Baik et al. 2021; Bistline and Blanford 2021a; Williams et al. 2021a)."


id: c5f32d5a4453a019ae6129cba2768836
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 28720
content:
"Renewable energy, especially generation from solar and wind, is \r\nlikely to have an important role in many low-carbon electricity \r\nsystems. The contributions of wind and solar electricity will depend \r\non their levelised costs relative to other options, integration costs, \r\nsystem value, and the ability to integrate variable resources into the \r\ngrid (Section 6.6). Electric sector technology mixes will vary by region \r\nbut will typically include additional resources such as hydropower, \r\nnuclear power, fossil generation with CCS, energy storage resources, \r\nand geothermal energy, among others. Contributions of different \r\noptions vary widely across scenarios based on different assumptions \r\nabout these factors (Figure 6.30)."


id: d4c39b16e3591a2053056469252bbaae
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"Box 6.11, Figure 2 | Illustrative Mitigation Pathway 1.5-Renewables: Africa (AF) in a scenario that limts warming to 1.5degC (>50%) (AF net-zero \r\neconomy, 2055-2060, AF net-zero energy system 2055-2060). Rapid expansion of non-biomass renewables, high electrification, and a fossil fuel phase-out."


id: a2c09c061dc9e01450224059c9de0899
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"Box 6.11, Figure 3 | Illustrative Mitigation Pathway 1.5-Low Demand: Developed Countries (DEV) in a scenario that limits warming to 1.5degC \r\n(>50%) (DEV net-zero economy, 2055-2060, net-zero energy system 2075-2080). Major reduction of energy demand, high electrification, and gradual \r\nfossil fuel phase-out."


id: 93ff233cc12c40ebe7662e0acbd8a389
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 20792
content:
"Box 6.11, Figure 4 | Illustrative Mitigation Pathway 1.5-Shifting Pathways: Asia and Pacific (APC) in a scenario that limits warming to 1.5degC \r\n(>50%) (APC net-zero economy, 2075-2080, net-zero energy system 2090-2095). Renewables, high electrification, fossil fuel phase-out and low \r\nagriculture, forestry and other land-use (AFOLU) emissions. Reaches net-zero CO2 relatively late."


id: a73df08eaa8fae496c8cc47544a70ee4
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 23826
content:
"Box 6.11, Table 1 | Summary of selected Illustrative Mitigation Pathways energy system characteristics in 2050 for the chosen regions."


id: 8a73bb634abfad81be4155078d244065
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 19318
content:
"Switching to low-carbon energy carriers. Switching to energy \r\ncarriers produced from low-carbon sources will be an important \r\nstrategy for energy sector decarbonisation. Accelerated electrification \r\nof end uses such as light duty transport, space heating, and cooking \r\nis a critical near-term mitigation strategy (Sugiyama 2012; Zou et al. \r\n2015; Rockstrom et al. 2017; IEA 2019f; Waisman et al. 2019; B. Tang \r\net al. 2021). Electricity supplies 48-58% (interquartile range) of the \r\nglobal final energy demand by 2050 in scenarios limiting warming to \r\n1.5degC (>50%) with no or limited overshoot and 36-47% in scenarios \r\nlimiting warming to 2degC (>67%) (Figure 6.29). Globally, the current \r\nlevel of electrification is about 20%."


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content:
"Indirect electrification encompasses the use of electricity to \r\nproduce hydrogen and synthetic fuels (efuels or power fuels). The \r\nextent of indirect electrification of final energy will depend on \r\nresource endowments and other regionally specific circumstances. \r\nAlthough indirect electrification is less efficient compared to direct \r\nelectrification, it allows low-carbon fuels to be imported from regions \r\nwith abundant low-carbon electricity generation resources (Fasihi \r\nand Bogdanov 2016; Lehtveer et al. 2019; Fasihi and Breyer 2020) \r\n(Box 6.10 on regional integration)."


id: 4f8e6de1d8a61a1654b301bfe1867501
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"across buildings, transport, and industry than most other pathways in \r\nthe literature. In some cases, energy demand levels are lower in 2050 \r\n(and later) than in 2019. These lower demands result in less reliance \r\non bioenergy and a more limited role for CDR (Figure 3.18)."


id: f2d332b3616ae2ba686c7123330c07de
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 35727
content:
"While electrifying end uses is a  key decarbonisation strategy, \r\nsome end uses such as long-distance transport (freight, aviation, \r\nand shipping) and energy-intensive industries will be harder to \r\nelectrify. For these sectors, alternative fuels or energy carriers such \r\nas biofuels, hydrogen, ammonia or synthetic methane, may be \r\nneeded (Section 6.6 and Box 6.9). Most scenarios find that hydrogen \r\nconsumption will grow gradually, becoming more valuable when the \r\nenergy system has become predominantly low-carbon (Figure 6.31)."


id: 9bb12e997fea4fd6b6c2a441d455dbdb
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 22055
content:
"Reducing energy demand. Energy service demand is expected \r\nto continue to increase with growth of the economy, but there is \r\ngreat uncertainty about how much it will increase (Bauer et al. 2017; \r\nRiahi et al. 2017; Yu et al. 2018). Given the need to produce low\u0002carbon energy, the scale of energy demand is a critical determinant \r\nof the mitigation challenge (Riahi et al. 2012). Higher energy demand \r\ncalls for more low-carbon energy and increases the challenge; \r\nlower energy demand reduces the need for low-carbon sources \r\nand therefore can ease a  low-carbon transition. Recent studies \r\nhave shown that tempering the growth of energy demand, while \r\nensuring services and needs are still satisfied, can materially affect \r\nthe need for technological CDR (Section 6.7.1.3) (Grubler et al. 2018; \r\nvan Vuuren et al. 2018). Two of the Illustrative Mitigation Pathways \r\n(IMP-SP, IMP-LD) feature substantially lower final energy demand "


id: bbd3387d3539f79be4a1b28aa9c861e2
created_at: 2023-03-16 14:01:36
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vector_id: 27110
content:
"warming to 1.5degC (>50%) with no or limited overshoot and 2-11% \r\nin scenarios that limit warming to 2degC (>67%) with action starting in \r\n2020. Large-scale deployment of CDR allows flexibility in timing of \r\nemissions reduction in hard-to-decarbonise sectors."


id: 2fe79e359718862ca5d6baded9f22edb
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
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vector_id: 4963
content:
"CDR will influence the potential fossil-related stranded assets \r\n(Box 6.13). Availability of low-cost CDR can help reduce premature \r\nretirement for some fossil fuel infrastructure. CDR can allow countries \r\nto reach net-zero emissions without phasing out all fossil fuels. \r\nSpecific infrastructure could also be extended if it is used to burn \r\nbiomass or other non-emitting sources. For example, existing coal\u0002fired power plants, particularly those with CCS, could be co-fired with \r\nbiomass (Woolf et al. 2016; Lu et al. 2019; Pradhan et al. 2021). In \r\nmany scenarios, energy sector CDR is deployed to such an extent that \r\nenergy sector CO2 emissions become negative in the second half of \r\nthe century (Chapter 3)."


id: abe8562e319525e0eac7dab97097041
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"The Global Stocktake is a regularly occurring process under the UN Framework Convention on Climate Change (UNFCCC) in which \r\nefforts will be made to understand progress on, among other things, global mitigation. Collective progress of countries towards the \r\nParis Agreement goal will be assessed and its outcome will inform Parties in updating and enhancing their Nationally Determined \r\nContributions (NDCs). This box explores potential indicators to understand energy system mitigation progress."


id: 6ad28e1f5260116daeb2159ae3d07916
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
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vector_id: 14416
content:
"Beyond these aggregate indicators, a second order assessment would capture more details, such as the electrification rate, share of \r\nrenewables, nuclear, CCS or other low-carbon technologies in electricity generation, land area used for energy production, and the \r\nnumber of EVs or PHEVs. Consumption of coal, oil and gas captures the underlying factors of CO2 emissions. The emphasis of these \r\nindicators could differ across countries in the context of national specific circumstances. Technology- or project-based statistics are \r\nalso useful to check the progress of the low-carbon transition, for example, the number of CCS facilities."


id: 9cb67d8117e286f2ebeacaa38afe9d31
created_at: 2023-03-16 14:01:36
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vector_id: 22190
content:
"A critical challenge in the assessment of energy sector progress is how to measure societal, institutional, and political progress. These \r\nfactors are difficult to quantify, yet they are fundamental determinants of the ability to reduce emissions. Public opinion, special \r\ninterest politics, implications of mitigation for employment, energy subsidies, and energy policies are all critical indicators of progress. \r\nIn addition, while much of the literature focuses on national-level action, mitigation is increasingly being led by cities, states, provinces, \r\nbusinesses, and other sub-national or non-national actors. Understanding the progress of these actors will be critical to assess energy \r\nsystem mitigation progress. New research is needed to better assess these 'societal' indicators and the role of non-national actors."


id: e1f3e19bb67841c8b794c2f9f4c34cc0
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 33046
content:
"oil, gas, and coal extraction and fossil electricity generation \r\n(USD990 billion  yr -1); renewable electricity, primarily solar and \r\nwind (USD340 billion yr -1); nuclear energy (USD40 billion yr -1); \r\nelectricity networks (USD270 billion yr -1); and end-use energy \r\nefficiency (USD270 billion yr -1)."


id: 43f62ee9b2049fd2e47a4add8a5ae7f3
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 8107
content:
"Total global energy investment was roughly USD1940 billion yr -1\r\nin 2019 (IEA 2021f). This total can be broken down into the \r\nfollowing main categories: fossil-related energy supply, including "


id: 83643f0897623627a12d309cfeb0eb92
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 18200
content:
"Figure  6.32 | Global average annual investments from 2023 to 2052 (undiscounted, in USD billion yr -1) for electricity supply sub-sectors and for \r\nextraction of fossil fuels in scenarios that limit warming to 2degC (>67%) or lower (C1-C3) (Source: AR6 Scenarios Database and Chapter 3). Historical \r\ninvestments are also shown for comparison (Source: IEA 2021; approximations are made for hydro and geothermal based on available data; solar and wind values are for 2020). \r\nT&D: transmission and distribution of electricity. Bars show median values across models-scenarios, and whiskers the interquartile ranges. See Chapters 3 and 15 for additional \r\ninformation on investments and finance."


id: 185fcf3b53df6880c9727f4d87bd92a6
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 1330
content:
"over the 2023-2052 timeframe: USD1670 to 3070 billion yr -1 (C1), \r\nUSD1600 to 2780 billion yr-1 (C2), and USD1330 to 2680 billion yr-1\r\n(C3) (see also Section 3.6.1.3)."


id: eb8ef4a1058e916306f4c1504378ed25
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 34563
content:
"Energy investment needs are projected to rise, according to \r\ninvestment-focused scenario studies found in the literature (McCollum \r\net  al. 2018a; Zhou et  al. 2019; Bertram et  al. 2021). While these \r\nincreases are projected to occur in emissions-intensive pathways as \r\nwell as low-carbon pathways, they are projected to be largest in low\u0002carbon pathways. Average annual global energy investments over \r\nthe 2016-2050 period range (across six models) from USD2100 to \r\n4100 billion yr-1 in pathways limiting warming to 2degC (>67%) and \r\nfrom USD2400 to 4700 billion yr-1 in pathways limiting warming to \r\n1.5degC (>50%) with no or limited overshoot (McCollum et al. 2018). \r\nWhatever the scenario, a significant and growing share of investments \r\nbetween now and 2050 will be channelled toward infrastructure build\u0002out in emerging economies, particularly in Asia (Zhou et al. 2019)."


id: 3e324320d924dee58156af87f2ea2698
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 7156
content:
"Beyond these sector-wide numbers, a  key feature of stringent \r\nmitigation pathways is a  pronounced reallocation of investment \r\nflows across sub-sectors, namely from unabated fossil fuels \r\n(extraction, conversion, and electricity generation) and toward \r\nrenewables, nuclear power, CCS, electricity networks and storage, \r\nand end-use energy efficiency (McCollum et  al. 2018a; Bertram \r\net al. 2021; IEA 2021f) (Figure 6.32). Investments in solar, wind, and \r\nelectricity transmission, distribution, and storage increase the most \r\nin mitigation scenarios. Up to 2050, the bulk of these investments \r\nare made in OECD and Asian countries (Figure  6.33). While fossil \r\nfuel extraction investments exhibit a marked downscaling across all \r\nregions, compared to reference scenarios, the declines are especially \r\nstrong in the Middle East, Reforming Economies of Eastern Europe \r\nand the Former Soviet Union (REF), and OECD."


id: d3f13bc19c267637e340d9a622536ce3
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 30861
content:
"More widespread electrification of buildings, transport, and industry \r\nmeans particularly substantial investment in the electricity system. \r\nAccording to C1-C3 pathways in the IPCC's Sixth Assessment \r\nReport (AR6 Scenarios Database), such investments could be at the \r\nfollowing average annual levels (inter-quartile range, USD2015) "


id: e96b100a526790c518aee19e5384a8ae
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 34233
content:
"Figure 6.33 | Regional average annual investments from 2023 to 2052 (undiscounted, in USD billion yr -1) for four of the largest sub-sectors of the energy \r\nsystem in scenarios that limit warming to 2degC (>67%) or lower (C1-C3) (Source: AR6 Scenarios Database and Chapter 3). Historical investments are also \r\nshown for comparison (Source: IEA, 2016). T&D: transmission and distribution of electricity. Extr.: extraction of fossil fuels. Bars show median values across models-scenarios, \r\nand whiskers the inter-quartile ranges. See Chapters 3 and 15 for additional information on investments and finance."


id: 4247dfa162fb2aab6582aec935364b42
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 7829
content:
"Investments into end-use energy efficiency are projected to also \r\nbe substantial in mitigation pathways, potentially upwards of \r\nseveral hundred USD billion yr-1 on average to 2050, compared to \r\nUSD270  billion yr-1 in 2019 (McCollum et  al. 2018a; IEA 2021f). \r\nHowever, the literature is inconsistent in how demand-side \r\ninvestments are calculated, as boundary conditions are less clear \r\nthan for energy supply investments. Taking a broader definition can \r\nresult in estimates that are an order-of-magnitude higher, meaning \r\nas large or larger than supply-side investments (Grubler et al. 2012; \r\nIEA 2021f)."


id: b468757ee7c7f4c68b9c178dffffe079
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 25902
content:
"Future investment patterns will vary by region, as they do now, due to \r\ndifferences in risk profiles, resource endowments and economic and \r\ngovernance structures (Fizaine et al. 2016; Zhou et al. 2019; Ameli, N. \r\net  al. 2021). In rapidly growing countries, investments to support \r\na low-carbon energy system transition will be integrated with those \r\nneeded to meet rapidly increasing energy demands, irrespective of \r\nwhether efforts are made to reduce emissions. In less rapidly growing \r\ncountries (Sun et al. 2019), investments will focus on transitioning \r\ncurrent energy systems to low-carbon configurations. Most current \r\nenergy investments are concentrated in high- and upper-middle\u0002income countries (IEA 2021f), but this will change as investment \r\nneeds continue to grow in today's lower-middle- and low-income \r\ncountries (McCollum et al. 2018a; Zhou et al. 2019; Bertram et al. \r\n2021; IEA 2021f)."


id: 1cfe06a5763b7a5aeddc42daf93a6219
created_at: 2023-03-16 14:01:36
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vector_id: 2011
content:
"Increasing low-carbon investment primarily requires shifting existing \r\ncapital investment through regulation and incentives as well as \r\nremoving existing investment barriers (McCollum et al. 2018; Hafner \r\net al. 2020; Ameli, N. et al. 2021). While there is a considerable amount \r\nof capital in the world, it is not always available to those wishing \r\nto invest in certain projects. Total annual global investment in fixed "


id: 9fe47f13cb30e640a606d8cbb619afc
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 22693
content:
"mitigation will require a major course change from recent history, \r\nlock-in is an important issue for emission reductions in the energy \r\nsector. While lock-in is typically expressed in terms of physical \r\ninfrastructure that would need to be retired early to reach mitigation \r\ngoals, it involves a much broader set of issues that go beyond physical \r\nsystems and into societal and institutional systems (Table 6.11)."


id: f47ad99723609b3569fa67b88b17f930
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"Path dependence refers to resistance to change due to favourable \r\nsocio-economic conditions with existing systems; decisions made in \r\nthe past unduly shape future trajectories. Carbon lock-in is a specific \r\ntype of path dependence (Seto et al. 2016). Given that energy system "


id: 9816814df5e1e9ada4af3a42fa43d0b9
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"Table 6.11 | Lock-in types and typical mechanisms. Source: Kotilainen et al. 2020), Reproduced under Creative Commons 4.0 International Licence."


id: 9283a3d390efe3049939a98138a4c651
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"innovations among policymakers and the wider public. Managing \r\nlow-carbon transitions is therefore not only a  techno-managerial \r\nchallenge (based on targets, policies, and expert knowledge), but \r\nalso a broader political project that involves the building of support \r\ncoalitions that include businesses and civil society (moderate \r\nevidence, high agreement)."


id: fdc175caef550be51c1584628b19b54b
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"A combination of factors - user, business, cultural, regulatory, and \r\ntransnational  - will hinder low-carbon energy transitions. Strong \r\npath dependencies, even in early formative stages, can have lasting \r\nimpacts on energy systems, producing inertia that cuts across \r\ntechnological, economic, institutional and political dimensions (high \r\nconfidence) (Rickards et al. 2014; Vaden et al. 2019) (Chapter 5)."


id: 70e65a53dbd2915e55ca18ffd3637545
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 15395
content:
"Low-carbon transitions involve cultural changes extending beyond \r\npurely technical developments to include changes in consumer \r\npractices, business models, and organisational arrangements. The \r\ndevelopment and adoption of low-carbon innovations will therefore \r\nrequire sustained and effective policies to create appropriate \r\nincentives and support. The implementation of such policies entails \r\npolitical struggles because actors have different understandings and \r\ninterests, giving rise to disagreements and conflicts."


id: 317dd4a0ed30c991418601cfdc2f9673
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 5195
content:
"Energy systems exemplify the ways in which massive volumes of \r\nlabour, capital, and effort become sunk into particular institutional \r\nconfigurations (Bridge et al. 2013, 2018). Several embedded factors \r\naffect large-scale transformation of these systems and make \r\ntechnological diffusion a complex process:"


id: a32fa31351f5315d673272b815eea722
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 23245
content:
"While low-carbon innovation involves systemic change (Geels \r\net  al. 2018), these are typically less popular than energy supply "


id: fa2e49bda16d8853710046060aae75b7
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updated_at: 2023-03-16 14:01:36
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content:
"future (Tong et al. 2019). Coal-fired power plants currently planned or \r\nunder construction are associated with 150-300 GtCO2, of which about \r\n75% and about 10% are located in Asia and the OECD respectively \r\n(Edenhofer et al. 2018; Pfeiffer et al. 2018). If implemented, these new \r\nfleets will further shorten all coal plants' lifetimes by another 10 years \r\nfor meeting climate goals (Cui et al. 2019)."


id: f6ffd3db54f73d605e5b62b3feeab69a
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 36367
content:
"Current investments in fossil infrastructure have committed \r\n500-700  GtCO2 of emissions, creating significant risks for limiting \r\nwarming to 1.5degC (Callaghan 2020) (high confidence). These \r\ncurrent investments combined with emissions from proposed fossil \r\ninfrastructure exceed the emissions required to limit warming to \r\n1.5degC (medium confidence). Existing coal- and gas-fired electricity \r\ngeneration accounts for 200-300 GtCO2 of committed emissions. \r\nEmissions from coal generation are larger than for gas plants(Smith \r\net al. 2019; Tong et al. 2019). The lifetime of coal-fired power plants \r\nis 25-50 years, creating long-lasting risks to climate goals (Erickson \r\nand Tempest 2015). Gas-fired power plants are younger on average \r\nthan coal-fired power plants. Industry sector lock-in amounts for \r\nmore than 100 GtCO2, while buildings and transport sector together \r\ncontribute another 50-100 GtCO2 (Erickson and Tempest 2015)."


id: d5b1537b5af8cca8f8877401cd36c257
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 31141
content:
"Despite the imperative to reduce use of fossil fuels and the multiple \r\nhealth and other benefits from closing coal-based infrastructure \r\n(Portugal-Pereira et al. 2018; Liu et al. 2019a; Karlsson et al. 2020; \r\nRauner et al. 2020; Cui et al. 2021), coal power plants have continued \r\nto be commissioned globally (Jewell et al. 2019; Jakob et al. 2020), \r\nmost notably in Asian countries. Gas power plants also continue to \r\nbe built. In many regions, new fossil electricity generation exceeds \r\nneeded capacity (Shearer et al. 2017)."


id: 40ca0313be27660c4b861c035d8b0037
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 7577
content:
"Existing policies and the NDCs are insufficient to prevent an \r\nincrease in fossil infrastructure and associated carbon lock-in (high \r\nconfidence) (Bertram et  al. 2015; Johnson et  al. 2015). Current \r\ninvestment decisions are critical because there is limited room \r\nwithin the carbon budget required to limit warming to well below \r\n2degC (Kalkuhl et al. 2019; Rosenbloom 2019). Delays in mitigation \r\nwill increase carbon lock-in and could result in large-scale stranded \r\nassets if stringency is subsequently increased to limit warming \r\n(Box 6.11). Near-term implementation of stringent GHG mitigation \r\npolicies are likely to be most effective in reducing carbon lock-in \r\n(Haelg et al. 2018). Near-term mitigation policies will also need to \r\nconsider different energy transition strategies as a result of different \r\nresources and carbon budgets between countries (Lucas 2016; Bos \r\nand Gupta 2018)."


id: 1136deb4fe516d16ef9c9ba6e03206f5
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 185
content:
"Lock-in is also relevant to fossil resources. Both coal and gas \r\nexploration continue, and new permits are being issued, which may \r\ncause economic (Erickson et al. 2018) as well as non-economic issues \r\n(Boettcher et al. 2019)."


id: 4831ba6e067cefd5530414563424abd0
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
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content:
"The nature of lock-in varies across the energy system. For example, lock\u0002in in urban and transport sectors is different from the electricity sector. \r\nBroadly, urban environments involve infrastructural, institutional, and \r\nbehavioural lock-in (Urge-Vorsatz et al. 2018). Addressing lock-in in \r\nthese sectors requires action by multiple stakeholders and is unlikely \r\nwith just technological evolution (Table 6.11)."


id: b0758476a09c5e5216a96a4940eb5ffb
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 25284
content:
"Committed carbon emissions are unevenly distributed. The \r\ndisproportionate high share of committed emissions in emerging \r\neconomies is the result of rapid growth in recent years, which has led \r\nto a comparably young fossil infrastructure with substantial remaining \r\nlife (Shearer et al. 2017). Mature industrialised countries tend to have \r\nolder infrastructures, part of which will be up for retirement in the near "


id: 53362cb1d739f0a156386ffeb8d52f44
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 10560
content:
"Past and present energy sector investments have created \r\ntechnological, institutional, and behavioural path dependencies \r\naligned towards coal, oil, and natural gas (high confidence). In \r\nseveral emerging economies, large projects are planned that address \r\npoverty reduction and economic development. Coal infrastructure \r\nmay be the default choice for these investments without policies to \r\ninvest in low-carbon infrastructure instead (Joshua and Alola 2020; \r\nSteckel et al. 2020). Path dependencies frequently have sustainability \r\nimplications beyond carbon emissions. (Box 6.2 and Section 6.7.7). "


id: 303fb583f7092e73d904a6154ddaa44f
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 5021
content:
"There are several SDG co-benefits associated with decarbonisation of \r\nenergy systems (Section 6.7.7) (Sorgel et al. 2021). For example, coal "


id: f2f76c3c040761e2be253261294aca3a
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 35749
content:
"mining communities frequently experience significant health and \r\neconomic burdens from resource extraction."


id: e1c5074779f495b6b51afb5f33ab0eea
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 33016
content:
"Limiting warming to 2degC (>67%) or lower will result in stranded assets (high confidence). Stranded assets can be broadly defined as assets \r\nthat 'suffer from unanticipated or premature write-offs, downward revaluations or [conversion] to liabilities'. Stranded assets may create \r\nrisks for financial market stability and macro-economic stability (Battiston et al. 2017; Mercure et al. 2018; Sen and von Schickfus 2020), \r\nand they will result in a rapid loss of wealth for the owners of affected assets (Vogt-Schilb and Hallegatte 2017; Ploeg and Rezai 2020)."


id: 252d281cfb31e28a31aca2192cc03328
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 3283
content:
"There are two types of stranded assets: fossil-fuel resources that cannot be burned; and premature retirement of fossil infrastructure \r\n(e.g., power plants). About 30% of oil, 50% of gas, and 80% of coal reserves will remain unburnable if warming is limited to 2degC \r\n(Meinshausen et al. 2009; Leaton 2011; Leaton Ranger 2013; McGlade and Ekins 2015; Bauer et al. 2016; IRENA 2017b; Pye et al. \r\n2020) (high confidence). Significantly more reserves are expected to remain unburned if warming is limited to 1.5degC. Countries with \r\nlarge oil, gas, and coal reserves are most at risk (Caldecott et al. 2017; Ansari and Holz 2020)."


id: 83c7099290a7cc63ed8a623f6766ad6c
created_at: 2023-03-16 14:01:36
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content:
"About 200 GW of fossil fuel electricity generation per year will likely need to be retired prematurely after 2030 to limit warming to 2degC, \r\neven if countries achieve their Nationally Determined Contributions (NDCs) (medium confidence) (Iyer et al. 2015; Johnson et al. 2015; \r\nFofrich et al. 2020). Limiting warming to 1.5degC will require significantly more rapid premature retirement of electricity generation \r\ncapacity (Binsted et al. 2020). Coal- and gas-fired power plants will likely need to retire about 25 years earlier than in the past to limit \r\nwarming to 2degC, and 30 years earlier to limit warming to 1.5degC (Cui et al. 2019; Fofrich et al. 2020). Coal-fired power plants are at \r\nsignificantly greater risk of stranding compared with gas-fired and oil-fired plants (Iyer et al. 2015; Johnson et al. 2015; Fofrich et al. \r\n2020). The risks of stranded power plants are greatest in countries with newer fossil infrastructure."


id: 6e496286bc509068389e85a5f9f7b3ce
created_at: 2023-03-16 14:01:36
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content:
"If warming is limited to 2degC, the discounted economic impacts of stranded assets, including unburned fossil reserves, could be as high \r\nas USD1-4 trillion from 2015 through 2050 (USD10-20 trillion in undiscounted terms) (medium confidence) (IRENA, 2017c; Mercure \r\net al. 2018). About 40% of these impacts correspond to unburned fossil reserves (IRENA 2017b). If warming is limited to 1.5degC, the \r\neconomic impacts of stranded assets are expected to be significantly higher (Binsted et al. 2020)."


id: 2a756b977e4ab581715aa420bcb8c51a
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 4109
content:
"limited or no overshoot, fossil energy provides 59-69% (interquartile \r\nrange) of primary energy in 2030 and 25-40% primary energy in \r\n2050 (AR6 Scenarios Database). In scenarios limiting warming to 2degC \r\n(>67%) with action starting in 2020, fossil energy provides 71-75% \r\n(interquartile range) primary energy in 2030 and 41-57% primary \r\nenergy in 2050 (AR6 Scenarios Database). The timeline for reducing \r\nproduction and usage varies across coal, oil, and gas due to their \r\ndiffering carbon intensities and uses."


id: 89cf2e1ee15cd167d0a544054fa280d1
created_at: 2023-03-16 14:01:36
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content:
"Global fossil fuel use will need to decline substantially by 2050 to \r\nlimit warming to 2degC (>67%), and it must decline substantially by \r\n2030 to limit warming to 1.5degC (>50%) with no or limited overshoot \r\n(high confidence). Failing to reduce global fossil fuel use below \r\ntoday's levels by 2030 will make it more challenging to limit warming \r\nto below 2degC (>67%). (high confidence). Fossil fuel use declines by \r\n260-330 EJ (52-73% from 2020 levels, interquartile range) through \r\n2050 in scenarios that limit warming to 1.5degC (>50%) with no or \r\nlimited overshoot, and 124-231 EJ (24-51% reduction compared \r\nto 2020 levels) in scenarios that limit warming to 2degC (>67%) with \r\naction starting in 2020. This will require a significant reduction in coal, \r\noil and gas investments. Fossil fuels account for about 80% of primary \r\nenergy today. In scenarios limiting warming to 1.5degC (>50%) with "


id: 71b2a277037e6c1752a1414d7ad71b5d
created_at: 2023-03-16 14:01:36
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content:
"Global coal consumption without CCS needs to be largely eliminated \r\nby 2040-2050 to limit warming to 1.5degC (>50%), and 2050-2060 \r\nto limit warming to 2degC (>67%) (high confidence). New investments \r\nin coal-fired electricity without CCS are inconsistent with limiting \r\nwarming to 2degC (>67%) or lower (high confidence) (Edenhofer et al. \r\n2018; Pfeiffer et al. 2018; Spencer et al. 2018; Cui et al. 2019). Coal "


id: 9174ac42da0a2de422ae168f1982db27
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 20420
content:
"earlier retirements of plants based on technical (efficiency), economic \r\n(profitability, local employment) and environmental considerations \r\n(e.g., water scarcity for cooling)."


id: b2e70051c26d38d9279e14dba38ebd
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"Figure  6.35 | Global fossil fuel pathways for scenarios that limit/return warming to 1.5degC (>50%) with no or limited/after a  high, overshoot, and \r\nscenarios that limit warming to 2degC (>67%), with action starting in 2020 or NDCs until 2030, during 2030-2050. Boxes indicate 25th and 75th percentiles \r\nwhile whiskers indicate 5th and 95th percentiles. Results for total consumption are expressed as a percentage relative to 2020 consumption. Results for fossil energy with CCS \r\nare expressed in total energy consumption. Oil use with CCS is not shown here as it remains below 5% of total use. Source: AR6 Scenarios Database."


id: dc0ba3a0a1161b75ecac50935fe82d47
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 32135
content:
"policies, particularly within the UK's Climate Change Act 2008 (Grubb \r\nand Newbery 2018). More generally, the implementation of the NDCs \r\nunder the Paris Agreement are all characterised by diverse climate \r\npolicy mixes."


id: d10d2af4709a3447606dd2266778b4d
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 30428
content:
"There is a  lack of consensus about how CCS might alter fossil \r\nfuel transitions for limiting warming to 2degC (>67%) or lower. CCS \r\ndeployment will increase the shares of fossil fuels associated with \r\nlimiting warming, and it can ease the economic transition to a low\u0002carbon energy system (Muratori et al. 2016; Marcucci et al. 2019). While \r\nsome studies find a significant role for fossil fuels with CCS by 2050 \r\n(Koelbl et al. 2014; Eom et al. 2015; Vishwanathan and Garg 2020), \r\nothers find that retirement of unabated coal far outpaces the \r\ndeployment of coal with CCS (Budinis et al. 2018; Xie et al. 2020; \r\nMcJeon et  al. 2021) Moreover, several studies also project that, \r\nwith availability of CO2 capture technology, BECCS might become \r\nsignificantly more appealing than fossil CCS, even before 2050 \r\n(Muratori et al. 2017; Luderer et al. 2018b)."


id: 8f82b5889d166749f57c706134d0e2ff
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"Policy and governance frameworks are essential for shaping near\u0002and medium-term low-emissions energy system transitions (high \r\nconfidence). While policy interventions are necessary to achieve \r\nlow-carbon energy system transitions, appropriate governance \r\nframeworks are crucial to ensure policy implementation (high \r\nconfidence). The policy environment in energy transition pathways \r\nrelate to climate policy goals, the characteristics of the policy regimes \r\nand measures to reach the policy goals including implementation \r\nlimits and obstacles, and the timing of the climate instrument \r\n(Kriegler et al. 2014b)."


id: 2f913774196ce4987c2be994e862d725
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"The literature discusses a broad set of policy approaches. Environmental \r\neconomics focuses mainly on market-based approaches as the least\u0002cost policy to achieve emission reductions (Kube et al. 2018). Many \r\ncountries, however, have implemented policy mixes with a diverse \r\nset of complementary policies to achieve energy and climate policy \r\ntargets. One example is the German Energiewende, which includes \r\nsubstantial support for renewables, an action plan for energy \r\nefficiency, and phase-out processes for nuclear- and coal-based \r\npower generation next to carbon pricing (Loschel et al. 2019). The \r\nhalving of CO2 emissions in UK power generation reflects multiple "


id: 71ba0c4305624315fe174ee5506514c4
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"still based on cost-optimal evaluation frameworks and include only \r\nlimited analysis of interactions between policy measures. Hence they \r\nare often not describing real-world energy transitions properly, but \r\nrather differences in implied carbon prices, constraints in technology \r\ndeployment, and timing of policies (Trutnevyte 2016)."


id: 2c71accb5f2ad1f3e71df9d29abf2076
created_at: 2023-03-16 14:01:36
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vector_id: 4423
content:
"potential issues of (industrial) competitiveness (Martin et al. 2014; \r\nRosendahl et al. 2017). Energy leakage may become more important \r\nduring low-carbon energy systems. Numerous studies have identified \r\npathways for carbon leakage in electricity markets with incomplete \r\nemission markets (Caron et  al. 2015; Murray and Maniloff 2015; \r\nThurber et al. 2015; Duan et al. 2017; Fell and Maniloff 2017; Qian \r\net al. 2018). Well-designed policy mixes will need to target the whole \r\nlifecycle or value chains, for example, through policies on limiting \r\nfossil fuel extraction (Asheim et al. 2019), or they will need to include \r\nmeasures to limit carbon leakage (e.g. Cosbey et al. 2019)."


id: b952c793d68c2ff879652244187a3c47
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"Members of societies, including individuals, civil society, and \r\nbusinesses, will all need to engage with, and be affected by, low\u0002carbon energy system transitions (high confidence). This raises \r\nquestions about the extent to which different strategies and policy \r\nwould effectively promote mitigation behaviours and the factors that \r\nincrease the social acceptability of mitigation options, policies, and \r\nsystem changes."


id: 1cd8c095b7875657425ed989d01c46a9
created_at: 2023-03-16 14:01:36
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vector_id: 1990
content:
"Interactions between policy measures including their scope, \r\nstringency, and timing, influence the costs of reducing emissions \r\n(Corradini et  al. 2018). In particular, some policy instruments may \r\nlead to lock-in effects (Section 6.7.3), compete with other regulations \r\n(Graaf and Sovacool 2020), or trigger negative policy interactions \r\n(Perino 2015; Jarke-Neuert and Perino 2020). Existing policy mixes \r\noften reflect different political economy constraints, and sometimes \r\nnot well coordinated goals. The resulting policy mixes are often \r\neconomically inefficient. However, comprehensive evaluation of \r\npolicy mixes requires a broader set of criteria that reflect different \r\nconsiderations, such as broader goals (e.g., SDGs) and the feasibility \r\nof policies (high confidence)."


id: 80b14d815d6bf6c176d8beed5e3caa93
created_at: 2023-03-16 14:01:36
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vector_id: 17770
content:
"Climate policy will be particularly effective if it targets key factors \r\ninhibiting, enabling, and motivating mitigation behaviours. As \r\nbarriers differ across mitigation options, regions, and groups, tailored \r\napproaches are more effective (Grubb et al. 2017). When people face \r\nimportant barriers to change (e.g., high costs, legal barriers), policy \r\nwould be needed make low-carbon actions more attractive, or to \r\nmake high-carbon actions less attractive. As people generally face \r\nmultiple barriers for change, combinations of policies would be more \r\neffective (Rosenow et al. 2017)."


id: 9b8b7bef6679438ff75d358a33367ba3
created_at: 2023-03-16 14:01:36
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content:
"Policy mixes might rather emerge piece-by-piece over time out of \r\nindividual policy interventions rather than be designed as a whole from \r\nthe outset (Howlett 2014; Rogge 2017) and may reflect differences \r\nacross jurisdictions and sectors (Howlett 2014). For example, taking \r\ninto account country-specific objectives, failures, and limitations, \r\ncarbon prices may be only one part of a  broader policy mix, and \r\nthereby may not be uniform across countries (Bataille 2020). This lack \r\nof consistency makes it more difficult to assess economic outcomes \r\nsince costs of complementary policies are often less visible and are \r\noften targeted at high-cost mitigation options (Borenstein et al. 2019)."


id: 5d4db91ade25313090dd5a49f528dee1
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content:
"Communicating financial consequences of behaviour seems less \r\neffective than emphasising social rewards (Handgraaf et al. 2013) or \r\nbenefits of actions for people (e.g., public health, comfort) and the \r\nenvironment (Bolderdijk et al. 2013; Asensio and Delmas 2015, 2016; \r\nSchwartz et al. 2015; Ossokina 2020). Financial appeals may have \r\nlimited effects because they reduce people's focus on environmental \r\nconsequences, weaken intrinsic motivation to engage in mitigation \r\nactions, provide a licence to pollute (Agrawal et al. 2015; Bolderdijk \r\nand Steg 2015; Schwartz et al. 2015), and because pursuing small "


id: 37a24548e8d5a673b5c9a751d9df444f
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content:
"Potential future policies are difficult to evaluate due to methodological \r\nchallenges (high confidence). Recent model-based analyses of future \r\npolicy mixes based on 'current policy scenarios' try to implement \r\nexisting policies besides explicit or implicit carbon prices (den Elzen \r\net al. 2016; Rogelj et al. 2016; van Soest et al. 2017; Roelfsema et al. \r\n2020). Many assessments of future low-carbon energy transitions are "


id: fdccb04f5d284600aba335007acd7c92
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content:
"financial gains is perceived not worth the effort (Bolderdijk et  al. \r\n2013; Dogan et al. 2014)."


id: 6c736731a66b803be2b073003884f4c8
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 14688
content:
"Bottom-up approaches can promote mitigation action (Abrahamse \r\nand Steg 2013). Indeed, community energy initiatives can encourage \r\nmembers' low-carbon behaviour (Middlemiss 2011; Seyfang and \r\nHaxeltine 2012; Abrahamse and Steg 2013; Sloot et  al. 2018). \r\nOrganisations can promote mitigation behaviour among their employees \r\nand customers by communicating their mission and strategies to \r\nmitigate climate change (Ruepert et al. 2017; van der Werff et al. 2021)."


id: f55301e090d670ab24733f0f52429280
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content:
"Default options, where a preset choice is implemented if users do not \r\nselect another option, can promote mitigation actions such as energy \r\nsavings, green electricity uptake, and meat-free options (Pichert and \r\nKatsikopoulos 2008; Bessette et al. 2014; Campbell-Arvai et al. 2014; \r\nKunreuther and Weber 2014; Olander and Thogersen 2014; Ebeling \r\nand Lotz 2015; Liebe et al. 2018; Liebe et al. 2021)."


id: d1b46677a1995cf86f11b013f0d0aff1
created_at: 2023-03-16 14:01:36
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content:
"Next, climate policy and low-carbon options are evaluated as more \r\nfair and acceptable when costs and benefits are distributed equally, \r\nand when nature, the environment and future generations are \r\nprotected (Schuitema et al. 2011; Drews and Van den Bergh 2016). \r\nCompensating affected groups for losses due to policy or systems \r\nchanges enhanced public acceptability in some cases (Perlaviciute and \r\nSteg 2014), but people may disagree on which compensation would \r\nbe worthwhile (Aitken 2010b; Cass et al. 2010), on the distribution \r\nof compensation (Devine-Wright and Sherry-Brennan 2019; Leer \r\nJorgensen et al. 2020), or feel they are being bribed (Cass et al. 2010; \r\nPerlaviciute and Steg 2014). Pricing policies are more acceptable \r\nwhen revenues are earmarked for environmental purposes (Steg \r\net  al. 2006; Saelen and Kallbekken 2011) or redistributed towards \r\nthose affected (Schuitema and Steg 2008)."


id: 437cd4227bb9dbb6e53977d675b08ef8
created_at: 2023-03-16 14:01:36
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content:
"Social influence approaches that communicate what other people \r\ndo or think can encourage mitigation actions (Clayton et al. 2015), \r\nas can social models of desired actions (Osbaldiston and Schott \r\n2012; Abrahamse and Steg 2013; Sussman and Gifford 2013; Wolske \r\net al. 2020). Feedback on one's own energy use relative to others \r\ncan be effective (Nolan et al. 2008; Allcott 2011; Schultz et al. 2015), \r\nalthough not always, and effect sizes are small (Abrahamse and Steg \r\n2013) compared to other types of feedback (Karlin et al. 2015)."


id: 95fba2939d3efac86bea5c2efeee292
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content:
"Interventions that capitalise on people's motivation to be consistent \r\ncan promote mitigation actions (Steg 2016). Examples are commitment \r\nstrategies where people pledge to act (Abrahamse and Steg 2013; \r\nLokhorst et al. 2013), implementation intentions where they additionally \r\nexplicate how and when they will perform the relevant action and how \r\nthey would cope with possible barriers (Bamberg 2000, 2002; Rees \r\net al. 2018), and hypocrisy-related strategies that make people aware "


id: 3a6b07eb4d35ca005d6d6a70957ca2a7
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content:
"Climate policy and mitigation options, such as renewable energy \r\nprojects, are also perceived as more fair and acceptable when the \r\npublic (Dietz 2013; Bidwell 2014; Bernauer et  al. 2016b) or public \r\nsociety organisations (Terwel et al. 2010; Bernauer et al. 2016b) could \r\nparticipate in the decision-making (Arvai 2003; Devine-Wright 2005; "


id: f83e5a6659b66d1473cc2e57c0ac1887
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content:
"transitions may still be economically favourable when accounting \r\nfor health impacts and other co-benefits (Gielen et  al. 2019). Past \r\nassessments have quantified the aggregate economic costs for \r\nclimate change mitigation using different metrics, for example, \r\ncarbon prices, GDP losses, investments in energy infrastructure, and \r\nenergy system costs. Assessments of mitigation costs from integrated \r\nassessment and energy system models vary widely. For example, \r\nscenarios include carbon prices in 2030 of less than USD20 tCO2\r\n-1, \r\nbut also more than USD400 tCO2\r\n-1 depending on the region, sector \r\nboundary, and methodology (e.g., Bauer et al. 2016; Brouwer et al. \r\n2016; Oshiro et al. 2017; Vaillancourt et al. 2017; Chen et al. 2019). \r\nThose arise both from different methodologies (Guivarch and Rogelj \r\n2017) and assumptions about uncertainties in key factors that drive \r\ncosts (Meyer et al. 2021)."


id: 8bcb1e57ff05d08c62e9028127ce4a71
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index: climate_gpt_only_giec
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content:
"Terwel et al. 2012; Walker and Baxter 2017; Perlaviciute and Squintani \r\n2020). People are more motivated to participate in decision-making \r\non local projects than on national or general policy goals (Perlaviciute \r\nand Squintani 2020). Public acceptability is also higher when people \r\ncan influence major rather than only minor decisions, particularly \r\nwhen trust in responsible parties is low (Liu et  al. 2019a). Public \r\nparticipation can enhance the quality and legitimacy of decisions by \r\nincluding local knowledge and views that may otherwise be missed \r\n(Dietz 2013; Bidwell 2016)."


id: 530d35a2e698c5c93c3af99ca041dddf
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content:
"Public support is higher when people trust responsible parties \r\n(Perlaviciute and Steg 2014; Drews and Van den Bergh 2016; Michaels \r\nand Parag 2016; Jiang et al. 2018; Liu et al. 2019a). Public support \r\nfor unilateral climate policy is rather strong and robust (Bernauer \r\net al. 2016a), even in the absence of reciprocal commitments by other \r\nstates (Bernauer and Gampfer 2015)."


id: ff6d6c6367781f2979c4c9d6c4ab1774
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content:
"Recent developments, however, raise the prospect that economic \r\noutcomes could be substantially superior to prior estimates, \r\nparticularly if key technologies continue to improve rapidly. In some \r\nregions and circumstances, particularly in the electricity sector, near\u0002term mitigation may lead to superior economic outcomes than \r\ncontinuing to invest in and utilise emissions-intensive infrastructure \r\n(e.g. Brown et  al. 2017; Kumar et  al. 2020). Given the importance \r\nof electricity decarbonisation in near-term mitigation strategies \r\n(Section  6.7.1), decreasing costs of solar PV, wind power, and \r\nbatteries to support their integration, have an outsized influence on \r\nnear-term economic outcomes from mitigation. At the same time, \r\neconomic outcomes may vary across regions depending, among \r\nother things, on the characteristics of the current energy systems, \r\nenergy resources, and needs for integrating VRE technologies."


id: 62de0ab01985423238390a02b33fef7f
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content:
"The attractiveness of energy sector mitigation ultimately depends \r\non the way that it provides benefits and reduces the costs for the \r\nmany different priorities that societies value (Yang et al. 2018a; Wei \r\net al. 2018, 2020). While costs and benefits of climate mitigation are \r\noften considered in the context of pure economic outcomes  - for \r\nexample, GDP effects or changes in value of consumption  - costs \r\nand benefits should be viewed with a  broader lens that accounts \r\nfor the many ways that the energy system interacts with societal \r\npriorities (Karlsson et al. 2020). Climate mitigation is not separate \r\nfrom countries' broader growth and development strategies, but \r\nrather as a key element of those strategies."


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updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 28325
content:
"Cost reductions in key technologies, particularly in electricity and \r\nlight-duty transport, have increased the economic attractiveness of \r\nnear-term low-carbon energy system transitions (high confidence). \r\nThe near-term, economic outcomes of low-carbon energy system \r\ntransitions in some sectors and regions may be on par with or superior \r\nto those of an emissions-intensive future (high confidence). Even in \r\ncases when system costs are higher for low-carbon transitions, these "


id: 1e1707156fe187582c8f77e16adad981
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 2170
content:
"Estimates of long-run mitigation costs are highly uncertain and \r\ndepend on various factors. Both faster technological developments \r\nand international cooperation are consistently found to improve \r\neconomic outcomes (Paroussos et al. 2019). Long-term mitigation is \r\nlikely to be more challenging than near-term mitigation because low-"


id: d006c1785d8756ce7f902869ebfa0542
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 30262
content:
"cost opportunities get utilised first and later efforts would require \r\nmitigation in more challenging sectors (Section  6.6). Advances in \r\nlow-carbon energy resources and carriers such as next-generation \r\nbiofuels, hydrogen produced from electrolysis, synthetic fuels, and \r\ncarbon-neutral ammonia would substantially improve the economics \r\nof net-zero energy systems (high confidence). Current estimates of \r\ncumulative mitigation costs are comparably high for developing \r\ncountries, amounting to up to 2-3% of GDP, indicating difficulties \r\nfor mitigation without adequate support from developed countries \r\n(Dorband et  al. 2019; Fujimori et  al. 2020). In scenarios involving \r\nlarge amounts of stranded assets, the overall costs of low-carbon \r\ntransitions also include the additional costs of early retirements \r\n(Box 6.11)."


id: b96166be3d92dabb576bfedbfdb9737e
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 26708
content:
"transmission losses has been estimated to mitigate 500  MtCO2\r\nper  year globally (Surana and Jordaan 2019). For several other \r\noptions, such as methane mitigation from the natural gas sector, the \r\ncosts of infrastructure refurbishing could be offset with the value of \r\nthe recovered natural gas (Kang et al. 2019)."


id: a788e77cd9136ab3efc25ec6eab87b16
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 23865
content:
"Figure 6.36 | The relationship between total per capita energy use, rate of electrification and human development index (HDI). Improved efficiency has \r\nlowered the energy demand required for meeting a threshold HDI during 2012-2017."


id: b71342fe324f4df008030c5a4030eae4
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 26334
content:
"the added advantage of promoting SDG 6 on clean water (Rathore \r\net al. 2018; Elkadeem et al. 2019)."


id: 86669eabc15c53f52db00ab005c54c3a
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 18688
content:
"Past trends have also indicated that, in some Asian countries, \r\nelectrification has been obtained at lower income levels as compared \r\nto developed countries (Rao and Pachauri 2017), with corresponding \r\nimpacts for development goals. For example, a human development \r\nindex (HDI) greater than 0.7 (Figure  6.36) which signifies high \r\ndevelopment is now possible at close to 30 GJ yr-1 per  person. \r\nThis was attainable only at the energy consumption of 50 GJ yr-1 \r\nper person in preceding decades."


id: 87b9b8dc86c39ede6417d234538caf63
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 18884
content:
"CDR and CCS can create significant land and water trade-offs (high \r\nconfidence). For large-scale CDR and CCS deployment to not conflict \r\nwith development goals requires efforts to reduce implications on \r\nwater and food systems. The water impacts of carbon capture are \r\nlarge, but these impacts can be strategically managed (Magneschi \r\net al. 2017; Liu et al. 2019a; Realmonte et al. 2019; Giannaris et al. \r\n2020c). In addition, high-salinity brines are produced from geologic \r\ncarbon storage, which may be a synergy or trade-off depending on "


id: 9ac3fd56a750c656cbe8c6069acc9bf0
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 21882
content:
"Electrification also improves energy efficiency, with corresponding \r\nimplications for development goals. For example, the availability of \r\nelectric cooking may reduce the cooking primary energy requirement \r\nconsiderably compared to traditional stoves (Yang and Yang 2018; \r\nBatchelor et al. 2019; Khan and Alam 2020) while also promoting \r\nimproved indoor air quality (SDG 3). Similarly, PV-powered irrigation \r\nand water pumping reduces pumping energy demands, which has "


id: d5cde47aad9d800b9180fb21cfa3f35b
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 31154
content:
"Overall, the scope for positive interactions between low-carbon \r\nenergy systems and SDGs is considerably larger than the trade-offs \r\n(Figure 6.37) (McCollum et al. 2018b). Some critical trade-offs include \r\nimpact to biodiversity due to large-scale mineral mining needed for \r\nrenewable infrastructure (Sonter et al. 2020)."


id: 83682faf9aa5a8f2192c7f4ea0b57a5b
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 18205
content:
"Assem Abu Hatab (Egypt/Sweden), Mercedes Bustamante (Brazil), Harry Clark (New Zealand), \r\nPetr Havlik (the Czech Republic), Joanna I. House (United Kingdom), Cheikh Mbow (Senegal), \r\nKarachepone N.  Ninan (India), Alexander Popp (Germany), Stephanie Roe (the Philippines/\r\nthe United States of America), Brent Sohngen (the United States of America), Sirintornthep \r\nTowprayoon (Thailand)"


id: 3e7888c487368ee74ed5b52c4aa404ce
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 7206
content:
"Lillian Aoki (the United States of America), Goran Berndes (Sweden), Katherine Calvin (the \r\nUnited States of America), Annette Cowie (Australia), Vassilis Daioglou (Greece), Andre \r\nDeppermann (Germany), Jeremy P.  Emmet-Booth (Ireland/New Zealand), Shinichiro Fujimori \r\n(Japan), Giacomo  Grassi (Italy/European Union), Viola Heinrich (United Kingdom/Germany), \r\nFlorian Humpenoder (Germany), J.  Boone Kauffman (the United States of America), William \r\nF. Lamb (Germany/United Kingdom), William Laurance (Australia), Sinead Leahy (New Zealand), \r\nSebastiaan Luyssaert (Belgium), Deissy Martinez-Baron (Colombia), Suvadip Neogi (India), \r\nMichael O'Sullivan (United Kingdom), Joeri Rogelj (Belgium/United Kingdom), Todd Rosenstock \r\n(the United States of America), Pete Smith (United Kingdom), Jonas Steinfeld (Germany/Brazil), \r\nFrancesco N. Tubiello (Italy), Pieter Johannes Verkerk (the Netherlands)"


id: 1c1f86e021008cd3eeda149f2393b1cd
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 1883
content:
"Nabuurs, G-J., R. Mrabet, A. Abu Hatab, M. Bustamante, H. Clark, P. Havlik, J. House, C. Mbow, K.N. Ninan, A. Popp, \r\nS. Roe, B. Sohngen, S. Towprayoon, 2022: Agriculture, Forestry and Other Land Uses (AFOLU). In IPCC, 2022: Climate \r\nChange 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the \r\nIntergovernmental Panel on Climate Change [P.R. Shukla, J. Skea, R. Slade, A. Al Khourdajie, R. van Diemen, D. McCollum, \r\nM. Pathak, S. Some, P. Vyas, R. Fradera, M. Belkacemi, A. Hasija, G. Lisboa, S. Luz, J. Malley, (eds.)]. Cambridge University \r\nPress, Cambridge, UK and New York, NY, USA. doi: 10.1017/9781009157926.009"


id: 2036c9d584f7bdb1bbb5eea7acd5d435
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 2510
content:
"boreal regions. Agricultural methane (CH4) and nitrous oxide (N2O) \r\nemissions are estimated to average 157 +- 47.1 MtCH4 yr-1 and \r\n6.6  +- 4.0 MtN2O yr-1 or 4.2 +- 1.3 and 1.8 +- 1.1 GtCO2-eq yr-1\r\n(using IPCC AR6 GWP100 values for CH4 and N2O) respectively \r\nbetween 2010 and 2019. AFOLU CH4 emissions continue to increase \r\n(high confidence), the main source of which is enteric fermentation \r\nfrom ruminant animals (high confidence). Similarly, AFOLU N2O \r\nemissions are increasing, dominated by agriculture, notably from \r\nmanure application, nitrogen deposition, and nitrogen fertiliser use \r\n(high confidence). In addition to being a source and sink for GHG \r\nemissions, land plays an important role in climate through albedo \r\neffects, evapotranspiration and volatile organic compounds (VOCs) \r\nand their mix, although the combined role in total climate forcing is \r\nunclear and varies strongly with bioclimatic region and management \r\ntype. {2.4.2.5, 7.2, 7.2.1, 7.2.3, 7.3}"


id: bd1e642f130659e41c22769e81e40811
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 27321
content:
"AFOLU CO2 emissions fluxes are mainly driven by land use \r\nchange (CO2 LULUCF), and account for about half of total \r\nnet AFOLU emissions. The rate of deforestation has generally \r\ndeclined, while global tree cover and global forest growing \r\nstock levels are likely increasing (medium confidence).\r\nThere are substantial regional differences, with losses of carbon \r\ngenerally observed in tropical regions and gains in temperate and "


id: 8165b712b307e8a1b9bf1b66ed42c5d2
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 17886
content:
"Most mitigation options are available and ready to deploy. Emissions \r\nreductions can be unlocked relatively quickly, whereas CDR needs \r\nupfront investment. Sustainable intensification in agriculture, shifting \r\ndiets, and reducing food waste could enhance efficiencies and reduce \r\nagricultural land needs, and are therefore critical for enabling \r\nsupply-side measures such as reforestation, restoration, as well as \r\ndecreasing CH4 and N2O emissions from agricultural production. In \r\naddition, emerging technologies (e.g.,  vaccines or inhibitors) have \r\nthe potential to substantially increase CH4 mitigation potential \r\nbeyond current estimates. AFOLU mitigation is not only relevant in \r\ncountries with large land areas. Many smaller countries and regions, \r\nparticularly with wetlands, have disproportionately high levels of \r\nAFOLU mitigation potential density. {7.4, 7.5}"


id: 72d16aea7996ad95106b0e052227199e
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 15677
content:
"urgently needed to accelerate the deployment of AFOLU mitigation \r\noptions. These interventions are effective when they include funding \r\nschemes and long-term consistent support for implementation with \r\ngovernments taking the initiative together with private funders and \r\nnon-state actors. {7.6}"


id: 25e5802e63f75f7905938e9bb50e44d4
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 3385
content:
"AFOLU measures that enable mitigation while also contributing \r\nto biodiversity conservation, ecosystem functioning, livelihoods \r\nfor millions of farmers and foresters, and many other Sustainable \r\nDevelopment Goals (SDGs) (high confidence). {7.7}"


id: b4233d18b911f45bc37b13a97cd5702d
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 25857
content:
"Addressing the many knowledge gaps in the development \r\nand testing of AFOLU mitigation options can rapidly advance \r\nthe likelihood of achieving sustained mitigation (high\r\nconfidence). Research priorities include improved quantification \r\nof anthropogenic and natural GHG fluxes and emissions modelling, \r\nbetter understanding of the impacts of climate change on the \r\nmitigation potential, permanence and additionality of estimated \r\nmitigation actions, and improved (real time and cheap) measurement, \r\nreporting and verification. There is a need to include a greater suite of \r\nmitigation measures in IAMs, informed by more realistic assessments \r\nthat take into account local circumstances and socio-economic \r\nfactors and cross-sector synergies and trade-offs. Finally, there is \r\na  critical need for more targeted research to develop appropriate \r\ncountry-level, locally specific, policy and land management response \r\noptions. These options could support more specific NDCs with "


id: 5d5211efca52819c5f12e5bcafea78a8
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 12202
content:
"rate of biodiversity loss, and wider environmental degradation (IPBES \r\n2019b; IPCC 2019). Urgent action to reverse this trend was deemed \r\ncrucial in helping to accommodate the increasing demands on land \r\nand enhance climate change adaptation capacity. There was high \r\nconfidence that global warming was already causing an increase in \r\nthe frequency and intensity of extreme weather and climate events, \r\nimpacting ecosystems, food security, disturbances and production \r\nprocesses, with existing (and new) carbon stocks in soils and biomass \r\nat serious risk. The impact of land cover on regional climate (through \r\nbiophysical effects) was also highlighted, although there was no \r\nconfidence regarding impacts on global climate."


id: 97c0639cce50ead8a424204e4b421209
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 21396
content:
"Since the IPCC Fifth Assessment Report (AR5), the share of AFOLU \r\nto anthropogenic GHG emissions had remained largely unchanged \r\nat 13-21% of total GHG emissions (medium confidence), though \r\nuncertainty in estimates of both sources and sinks of CO2, \r\nexacerbated by difficulties in separating natural and anthropogenic \r\nfluxes, was emphasised. Models indicated land (including the natural \r\nsink) to have very likely provided a net removal of CO2 between 2007 \r\nand 2016. As in AR5, land cover change, notably deforestation, was \r\nidentified as a  major driver of anthropogenic CO2 emissions while \r\nagriculture was a major driver of the increasing anthropogenic CH4\r\nand N2O emissions."


id: db40505edd5044ff4e8f2e7d8c939e77
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 32003
content:
"None the less, the importance of mitigation within AFOLU was \r\nhighlighted in all IPCC reports, with modelled scenarios demonstrating \r\nthe considerable potential role and land-based mitigation forming an \r\nimportant component of pledged mitigation in Nationally Determined \r\nContributions (NDCs) under the Paris Agreement. The sector was \r\nidentified as the only one in which large-scale carbon dioxide removal \r\n(CDR) may currently and at short term be possible (e.g.,  through \r\nafforestation/reforestation or soil organic carbon management). This \r\nCDR component was deemed crucial to limit climate change and its \r\nimpacts, which would otherwise lead to enhanced release of carbon \r\nfrom land. However, the SRCCL emphasised that mitigation cannot \r\nbe pursued in isolation. The need for integrated response options, \r\nthat mitigate and adapt to climate change, but also deal with land \r\ndegradation and desertification, while enhancing food and fibre "


id: e166e0568dce8537be8393b7a34e673b
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 32954
content:
"Land can only be part of the solution alongside rapid emission \r\nreduction in other sectors (IPCC 2019). It was recognised that land \r\nsupports many ecosystem services on which human existence, well\u0002being and livelihoods ultimately depend. Yet over-exploitation of land \r\nresources was reported as driving considerable and unprecedented "


id: dfc80001c35e1d8c48f8d4c95704831d
created_at: 2023-03-16 14:01:36
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content_type: text
index: climate_gpt_only_giec
vector_id: 32701
content:
"security, biodiversity and contributing to other SDGs has been made \r\nclear (IPCC 2019; IPBES 2019a; IPBES-IPCC 2021)."


id: 41973e7aec154907ab5d90b199cba1e4
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 7718
content:
"sectors may in part, be dependent on contributions from land and \r\nthe AFOLU sector, with interactions between all sectors discussed \r\nin Chapter 12. This chapter also has important links with IPCC AR6 \r\nWGII regarding climate change impacts and adaptation. Linkages \r\nare illustrated in Figure 7.1."


id: 21aa0e9515f46d4ca61dadfba6dc6100
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 2724
content:
"As highlighted in both AR5 and the SRCCL, there is a  complex \r\ninterplay between land management and GHG fluxes as illustrated in \r\nFigure 7.2, with considerable variation in management regionally, as \r\na result of geophysical, climatic, ecological, economic, technological, \r\ninstitutional and socio-cultural diversity. The capacity for land\u0002based mitigation varies accordingly. The principal focus of this \r\nchapter is therefore, on evaluating regional land-based mitigation \r\npotential, identifying applicable AFOLU mitigation measures, \r\nestimating associated costs and exploring policy options that could \r\nenable implementation."


id: bbf10d891671f4731693100e1689849d
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 27131
content:
"This chapter assesses GHG fluxes between land and the atmosphere \r\ndue to AFOLU, the associated drivers behind these fluxes, \r\nmitigation response options and related policy, at time scales of \r\n2030 and 2050. Land and its management has important links \r\nwith other sectors and therefore associated chapters within this \r\nreport, notably concerning the provision of food, feed, fuel or fibre \r\nfor human consumption and societal well-being (Chapter  5), for \r\nbioenergy (Chapter 6), the built environment (Chapter 9), transport \r\n(Chapter  10) and industry (Chapter  11). Mitigation within these "


id: 1f8e0fe192ae319b9700f35f411e4a22
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 2396
content:
"Figure 7.1 | Linkage between Chapter 7 and other chapters within this report, as well as to IPCC AR6 WGII. Mitigation potential estimates in this chapter consider \r\npotential emission reductions and removals only within the AFOLU sector itself, and not the substitution effects from biomass and bio-based products in sectors such as Energy, \r\nTransport, Industry, Buildings, nor biophysical effects of, for example, cooling of cities. These are covered in their respective chapters."


id: 352521afae3cc64b85e4d21f0ec040ac
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 5769
content:
"This chapter first outlines the latest trends in AFOLU fluxes and \r\nthe methodology supporting their estimation (Section  7.2). Direct \r\nand indirect drivers behind emission trends are discussed in \r\nSection 7.3. Mitigation measures, their costs, co-benefits, trade-offs, \r\nestimated regional potential and contribution within integrated \r\nglobal mitigation scenarios, is presented in Sections  7.4 and 7.5 \r\nrespectively. Assessment of associated policy responses and links \r\nwith SDGs are explored in Section 7.6. The chapter concludes with \r\ngaps in knowledge (Section 7.7) and frequently asked questions."


id: 6538bda2cb1ec04279aad023e7675831
created_at: 2023-03-16 14:01:36
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content_type: text
index: climate_gpt_only_giec
vector_id: 13496
content:
"The biosphere on land and in wetlands is a source and sink of CO2\r\nand CH4, and a source of N2O due to both natural and anthropogenic \r\nprocesses that happen simultaneously and are therefore difficult \r\nto disentangle (IPCC 2010; Angelo and Du Plesis 2017; IPCC 2019). \r\nAFOLU is the only GHG sector to currently include anthropogenic sinks. \r\nA range of methodological approaches and data have been applied to \r\nestimating AFOLU emissions and removals, each developed for their \r\nown purposes, with estimates varying accordingly. Since the SRCCL (Jia \r\net al. 2019), emissions estimates have been updated (Sections 7.2.2 and \r\n7.2.3), while the assessment of biophysical processes and short-lived "


id: 416ef01e2fa3f0a7fca5ad876c051112
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 7694
content:
"climate forcers (Section 7.2.4) is largely unchanged. Further progress \r\nhas been made on the implications of differences in AFOLU emissions \r\nestimates for assessing collective climate progress (Section 7.2.2.2 and \r\nCross-Chapter Box 6 in this chapter)."


id: 31d05b54a09469c73cd4c30f0d180639
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 5249
content:
"separate by gas and implicitly include CO2 emissions that stem from \r\nthe agriculture part of AFOLU, though these account for a relatively \r\nsmall portion."


id: 6dccdd28c677aeceffe9806fa9964cb2
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 14885
content:
"Total global net anthropogenic GHG emissions from AFOLU were \r\n11.9 +- 4.4 GtCO2-eq yr-1 on average over the period 2010-2019, \r\naround 21% of total global net anthropogenic GHG emissions \r\n(Table 7.1 and Figure 7.3, using the sum of bookkeeping models for \r\nthe CO2 component). When using FAOSTAT/NGHGIs CO2 flux data, \r\nthen the contribution of AFOLU to total emissions amounts to 13% of \r\nglobal emissions."


id: 21b8774b811908805395c8cc20f7c253
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 2734
content:
"National greenhouse gas inventory (NGHGI) reporting following the \r\nIPCC 1996 guidelines (IPCC 1996), separates the total anthropogenic \r\nAFOLU flux into: (i) net anthropogenic flux from Land Use, Land\u0002Use Change, and Forestry (LULUCF) due to both change in land \r\ncover and land management; and (ii) the net flux from Agriculture. \r\nWhile fluxes of CO2 (Section 7.2.2) are predominantly from LULUCF \r\nand fluxes of CH4 and N2O (Section 7.2.3) are predominantly from \r\nagriculture, fluxes of all three gases are associated with both sub\u0002sectors. However, not all methods separate them consistently \r\naccording to these sub-sectors, thus here we use the term AFOLU, "


id: b475cd96c4d0151f80d77e9a00ef3d94
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 25920
content:
"This AFOLU flux is the net of anthropogenic emissions of CO2, CH4 and \r\nN2O, and anthropogenic removals of CO2. The contribution of AFOLU \r\nto total emissions varies regionally with highest in Latin America and \r\nCaribbean with 58% and lowest in Europe and North America with each \r\n7% (Chapter 2, Section 2.2.3). There is a discrepancy in the reported \r\nCO2 AFOLU emissions magnitude because alternative methodological "


id: 46255c624e935ff7d1d6ee39cba0d79c
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 8419
content:
"Table  7.1 | Net anthropogenic emissions (annual averages for 2010-2019a) from Agriculture, Forestry and Other Land Use (AFOLU). For context, the \r\nnet flux due to the natural response of land to climate and environmental change is also shown for CO2 in column E. Positive values represent emissions, negative values \r\nrepresent removals."


id: 1dfefeddb0b6fe5d0bee05d5a1f5e3f
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"a\r\n Estimates are given until 2019 as this is the latest date when data are available for all gases, consistent with Chapter 2, this report. Positive fluxes are emission from land to \r\nthe atmosphere. Negative fluxes are removals."


id: 742c3e7851b61cdc792d235e337ad3f
created_at: 2023-03-16 14:01:36
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"d\r\n Total non-AFOLU emissions are the sum of total CO2-eq emissions values for energy, industrial sources, waste and other emissions with data from the Global Carbon Project \r\nfor CO2, including international aviation and shipping, and from the PRIMAP database for CH4 and N2O averaged over 2007-2014, as that was the period for which data \r\nwere available."


id: 932df687429c4bd34b5d1b6adfc069bb
created_at: 2023-03-16 14:01:36
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"e\r\n The modelled CO2 estimates include natural processes in vegetation and soils and how they respond to both natural climate variability and to human-induced environmental \r\nchanges, for example, the response of vegetation and soils to environmental changes such as increasing atmospheric CO2 concentration, nitrogen deposition, and climate \r\nchange (indirect anthropogenic effects) on both managed and unmanaged lands. The estimate shown represents the average from 17 Dynamic Global Vegetation Models with \r\n1SD uncertainty (Friedlingstein et al. 2020)."


id: 6b90d3c12a71929876e9624d25630509
created_at: 2023-03-16 14:01:36
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content:
"f\r\n The NGHGIs take a different approach to calculating 'anthropogenic' CO2 fluxes than the models (Section 7.2.2). In particular the sinks due to environmental change (indirect \r\nanthropogenic fluxes) on managed lands are generally treated as anthropogenic in NGHGIs and non-anthropogenic in models such as bookkeeping and IAMs. A reconciliation \r\nof the results between IAMs and NGHGIs is presented in Cross-Chapter Box 6 in this chapter. If applied to this table, it would transfer approximately -5.5 GtCO2 yr-1 (a sink) \r\nfrom Column E (which would become -7.0 GtCO2 yr-1) to Column A (which would then be 0.4 GtCO2 yr-1)."


id: 9de61fc342a0294fafd63c281e078f8f
created_at: 2023-03-16 14:01:36
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"g\r\n All values expressed in units of CO2-eq are based on IPCC AR6 100-year Global Warming Potential (GWP100) values with climate-carbon feedbacks (CH4 = 27, N2O = 273) \r\n(Chapter 2, Supplementary Material 2.SM.3; IPCC AR6 WGI Section 7.6)."


id: 4503678c6777eff4b8757d01e9c5218a
created_at: 2023-03-16 14:01:36
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content:
"i\r\n While it is acknowledged that soils are a natural CH4 sink (Jackson et al. 2020) with soil microbial removals estimated to be 30 +- 19 MtCH4 yr-1 for the period 2008-2017 \r\n(according to bottom-up estimates), natural CH4 sources are considerably greater (371 (245-488) MtCH4 yr-1) resulting in natural processes being a net CH4 source (IPCC AR6 \r\nWGI Section 5.2.2). The soil CH4 sink is therefore omitted from Column E."


id: 370e2c0d3a17fbc16a21904084656ab1
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content:
"j Total GHG emissions concerning non-AFOLU sectors and all sectors combined (Columns B and C) include fluorinated gases in addition to CO2, CH4 and N2O. Therefore, total \r\nvalues do not equal the sum of estimates for CO2, CH4 and N2O."


id: df13eb3c60a1a61759d86dab9bf0b7a1
created_at: 2023-03-16 14:01:36
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"approaches that incorporate different assumptions are used \r\n(Section 7.2.2.2). While there is low agreement in the trend of global \r\nAFOLU CO2 emissions over the past few decades (Section 7.2.2), they \r\nhave remained relatively constant (medium confidence) (Chapter 2). \r\nAverage non-CO2 emission (aggregated using GWP100 IPCC AR6 \r\nvalues) from agriculture have risen from 5.2 +- 1.4 GtCO2-eq yr-1 for \r\nthe period 1990 to 1999, to 6.0 +- 1.7 GtCO2-eq yr-1 for the period \r\n2010 to 2019 (Crippa et al. 2021) (Section 7.2.3)."


id: 5d6cf713d57eb6fc2ce52f16af78b7b7
created_at: 2023-03-16 14:01:36
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"and atmospheric observations concur that, when combining both \r\nanthropogenic (AFOLU) and natural processes on the entire land \r\nsurface (the total 'land-atmosphere flux'), the land was a  global \r\nnet sink for CO2 of -6.6 +- 4.6 GtCO2 yr-1 with a range for 2010 to \r\n2019 from -4.4 to -8.4 GtCO2 yr-1. (Rodenbeck et al. 2003, 2018; \r\nChevallier et al. 2005; Feng et al. 2016; van der Laan-Luijkx et al. \r\n2017; Niwa et al. 2017; Patra et al. 2018). The natural land sink is \r\nhighly likely to be affected by both future AFOLU activity and climate \r\nchange (IPCC AR6 WGI Box 5.1 and Figure SPM. 7), whereby under \r\nmore severe climate change, the amount of carbon stored on land \r\nwould still increase although the relative share of the emissions that \r\nland takes up, declines."


id: 169b4427d14313af6512456ed21fa3a0
created_at: 2023-03-16 14:01:36
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"Comparison of estimates of the global net AFOLU flux of CO2\r\nfrom diverse approaches (Figure  7.4) show differences on the \r\norder of several GtCO2 yr-1. When considering the reasons for the \r\ndifferences, and an approach to reconcile them (Grassi et al. 2021) \r\n(Section 7.2.2.3), there is medium confidence in the magnitude of \r\nthe net AFOLU CO2 flux. There is a discrepancy in the reported CO2"


id: b6c569698b6662e990d27fd40ee0e322
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content:
"Figure 7.5 | Regional net flux of CO2 due to AFOLU estimated using different methods for the period 1990-2019 (GtCO2 yr-1). Positive numbers represent \r\nemissions. The upper-central panel depicts the world map shaded according to the IPCC AR6 regions corresponding to the individual graphs.  For each regional panel; \r\nbrown line: Total net flux data from FAOSTAT (Tubiello et al. 2020); yellow line: Net emissions estimates from National Greenhouse Gas Inventories based on country \r\nreports to the UNFCCC for LULUCF (Grassi et al. 2021); dark-blue line: The mean estimate and minimum and maximum (dark-blue shading) from three bookkeeping models. \r\n(Hansis et al. 2015; Houghton and Nassikas 2017; Gasser et al. 2020). Regional estimates from bookkeeping models are available at: https://zenodo.org/record/5548333#.\r\nYVwJB2LMJPY (Minx et al. 2021). See the legend in Figure 7.4 for a detailed explanation of flux components for each dataset."


id: da0d306fab34043eb600553fdfdc36d9
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content:
"Regionally (Figure  7.5), there is high confidence of net emissions \r\nlinked to deforestation in Latin America, Africa and South-East Asia \r\nfrom 1990 to 2019. There is medium confidence in trends indicating \r\na  decrease in net emissions in Latin America since 2005 linked to \r\nreduced gross deforestation emissions, and a small increase in net \r\nemissions related to increased gross deforestation emissions in Africa \r\nsince 2000 (Figure 7.5). There is high confidence regarding the net "


id: 1fc82b6fbee017a3fb89def553f76758
created_at: 2023-03-16 14:01:36
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content:
"AFOLU emissions magnitude because alternative methodological \r\napproaches that incorporate different assumptions are used \r\n(Section  7.2.2.2). While the mean of the bookkeeping and DGVM \r\nmodel's show a  small increase in global CO2 net emissions since \r\nyear 2000, individual models suggest opposite trends (Friedlingstein \r\net al. 2020). The latest FAOSTAT and NGHGI estimates show a small \r\nreduction in net emission. Overall, the trends are unclear."


id: 77d8574d5584abc7cd509850324e73da
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"The bookkeeping models by Houghton and Nassikas (2017), Hansis \r\net al. (2015), and Gasser et al. (2020) and the DGVMs used in the \r\nGlobal Carbon Budget (Friedlingstein et al. 2020) use either the LUH2 \r\ndataset (Hurtt et al. 2020), HYDE (Goldewijk et al. 2017), FRA 2015 \r\n(FAO 2015) or a combination. The LUH2 dataset includes a new wood \r\nharvest reconstruction, new representation of shifting cultivation, \r\ncrop rotations, and management information including irrigation and \r\nfertiliser application. The area of forest subject to harvest in LUH2 \r\nis much less than the area of forest considered 'managed' in the \r\nNGHGIs (Grassi et al. 2018). The model datasets do not yet include \r\nthe FAO FRA 2020 update (FAO 2020a). The DGVMs consider CO2\r\nfertilisation effects on forest growth that are sometimes confirmed \r\nfrom the ground-based forest inventory networks (Nabuurs et al. \r\n2013) and sometimes not at all (van der Sleen et al. 2015)."


id: 638f48cacbbef0eed21b0a54b010eea5
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content:
"AFOLU CO2 sink in Europe due to forest regrowth and known other \r\nsinks in managed forests, and medium confidence of a net sink in \r\nNorth America and Eurasia since 2010."


id: 9bd3d981106d875b52786b3f24d2e0d5
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"The processes responsible for fluxes from land have been divided \r\ninto three categories (IPCC 2006, 2010): (i) the direct human-induced \r\neffects due to changing land cover and land management; (ii) the \r\nindirect human-induced effects due to anthropogenic environmental \r\nchange, such as climate change, CO2 fertilisation, nitrogen deposition, \r\nand so on; and (iii) natural effects, including climate variability and \r\na background natural disturbance regime (e.g., wildfires, windthrows, \r\ndiseases or insect outbreaks)."


id: 934fd8cebaeff2585e116dc49ec11575
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"Further, the DGVMs and bookkeeping models do not include a wide \r\nrange of practices which are implicitly covered by the inventories; for \r\nexample: forest dynamics (Pugh et al. 2019; Le Noe et al. 2020), forest \r\nmanagement including wood harvest (Nabuurs, et al. 2013; Arneth \r\net al. 2017), agricultural and grassland practices (Pugh et al. 2015; \r\nSanderman et al. 2017; Pongratz et al. 2018); or, for example, fire \r\nmanagement (Andela et al. 2017; Arora and Melton 2018)."


id: 7bc75518f55950e9fa10206d0c84dbe0
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"Global models estimate the anthropogenic land CO2 flux considering \r\nonly the impact of direct effects, and only those areas that were subject \r\nto intense and direct management such as clear-cut harvest. It is \r\nimportant to note, that DGVMs also estimate the non-anthropogenic \r\nland CO2 flux (Land Sink) that results from indirect and natural \r\neffects (Table 7.1). In contrast, estimates of the anthropogenic land \r\nCO2 flux in NGHGIs (LULUCF) include the impact of direct effects and, \r\nin most cases, of indirect effects on a much greater area considered \r\n'managed' than global models (Grassi et al. 2021)."


id: 278a3e6f98f79f9623d9c4c8a83665a4
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"Increasingly, higher emissions estimates are expected from DGVMs \r\ncompared to bookkeeping models, because DGVMs include a  loss \r\nof additional sink capacity of 3.3 +- 1.1 GtCO2 yr-1 on average \r\nover 2009-2018, which is increasing with larger climate and CO2 \r\nimpacts (Friedlingstein et al. 2020). This arises because the DGVM \r\nmethodological setup requires a  reference simulation including \r\nclimate and environmental changes but without any land-use change \r\nsuch as deforestation, so DGVMs implicitly include the sink capacity \r\nforests would have developed in response to environmental changes \r\non areas that in reality have been cleared (Gitz and Ciais 2003; \r\nPongratz et al. 2014) (IPCC AR6 WGI Chapter 5)."


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"Carbon emissions from peat burning have been estimated based \r\non the Global Fire Emission Database (GFED4s; van der Werf et al. \r\n2017). These were included in the bookkeeping model estimates and \r\nadded 2.0 GtC over 1960-2019 (e.g.,  causing the peak in South\u0002East Asia in 1998) (Figure  7.5). Within the Global Carbon Budget \r\n(Friedlingstein et al. 2020), peat drainage from agriculture accounted \r\nfor an additional 8.6 GtC from 1960-2019 according to FAOSTAT \r\n(Conchedda and Tubiello, 2020) used by two of the bookkeeping \r\nmodels (Hansis et al. 2015; Gasser et al. 2020)."


id: 84b9f1701968d2f81ff7d2dc059fdb93
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"The FAOSTAT approach is conceptually similar to NGHGIs. FAOSTAT \r\ndata on forests are based on country reports to FAO-FRA 2020 \r\n(FAO 2020a), and include changes in biomass carbon stock in \r\n'forest land' and 'net forest conversions' in five-year intervals. \r\n'Forest land' may include unmanaged natural forest, leading to \r\npossible overall overestimation of anthropogenic fluxes for both \r\nsources and sinks, though emissions from deforestation are likely \r\nunderestimated (Tubiello et al. 2020). FAOSTAT also estimate \r\nemissions from forest fires and other land uses (organic soils), \r\nfollowing IPCC methods (Prosperi et al. 2020). The FAO-FRA 2020 \r\n(FAO 2020b) update leads to estimates of larger sinks in Russia \r\nsince 1991, and in China and the USA from 2011, and larger \r\ndeforestation emissions in Brazil and smaller in Indonesia than \r\nFRA 2015 (FAO 2015; Tubiello et al. 2020)."


id: f7e08c12940d3b9285da5e0121fae25a
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content:
"Remote-sensing products provide valuable spatial and temporal \r\nland-use and biomass data globally (including in remote areas), at \r\npotentially high spatial and temporal resolutions, that can be used to \r\ncalculate CO2 fluxes, but have mostly been applied only to forests at \r\nthe global or even regional scale. While such data can strongly support \r\nmonitoring reporting and verification, estimates of forest carbon \r\nfluxes directly from Earth Observation (EO) data vary considerably \r\nin both their magnitude and sign (i.e., whether forests are a  net \r\nsource or sink of carbon). For the period 2005-2017, net tropical \r\nforest carbon fluxes were estimated as -0.4 GtCO2 yr-1 (Fan et al. \r\n2019); 0.58 GtCO2 yr-1 (Grace et al. 2014); 1.6 GtCO2yr-1 (Baccini \r\net al. 2017) and 2.87 GtCO2 yr-1 (Achard et al. 2014). Differences "


id: d500a34ea8fcc79aae8e2ee35a02c84d
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"Heinrich et al. 2021; Reiche et al. 2021). For example, secondary \r\nforest regrowth in the Brazilian Amazon offset 9 to 14% of gross \r\nemissions due to deforestation1\r\n (Aragao et al. 2018; Silva Junior \r\net al. 2021). Yet disturbances such as fire and repeated deforestation \r\ncycles due to shifting cultivation over the period 1985 to 2017, were \r\nfound to reduce the regrowth rates of secondary forests by 8 to 55% \r\ndepending on the climate region of regrowth (Heinrich et al. 2021)."


id: 15b2381268d155ad82e898738dcdf200
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"can in part be explained by spatial resolution of the datasets, the \r\ndefinition of 'forest' and the inclusion of processes and methods used \r\nto determine degradation and growth in intact and secondary forests, \r\nor the changes in algorithm over time (Palahi et al. 2021). A recent \r\nglobal study integrated ground observations and remote sensing \r\ndata to map forest-related GHG emissions and removals at a high \r\nspatial resolution (30 m spatial scale), although it only provides an \r\naverage estimate of annual carbon loss over 2001-2019 (Harris \r\net al. 2021). The estimated net global forest carbon sink globally was \r\n-7.66 GtCO2 yr-1, being -1.7 GtCO2yr-1 in the tropics only."


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content:
"Remote sensing products can help to attribute changes to \r\nanthropogenic activity or natural inter-annual climate variability \r\n(Fan et al. 2019; Wigneron et al. 2020). Products with higher spatial \r\nresolution make it easier to determine forest and carbon dynamics \r\nin relatively small-sized managed forests (e.g., Y. Wang et al. 2020; "


id: f8ff549ceb4e93845a3f3718baf9eefa
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content:
"There is about 5.5 GtCO2 yr-1 difference in the anthropogenic \r\nAFOLU estimates between NGHGIs and global models (this number \r\nrelates to an IAMs comparison for the period 2005-2015  - see \r\nCross-Chapter Box  6 in this chapter; for comparison with other "


id: d93a256d89e1826f439c1571d75ad35c
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"Authors: Giacomo Grassi (Italy/European Union), Joeri Rogelj (Belgium/Austria), Joanna I. House (United Kingdom), Alexander Popp \r\n(Germany), Detlef van Vuuren (the Netherlands), Katherine Calvin (the United States of America), Shinichiro Fujimori (Japan), Petr \r\nHavlik (Austria/the Czech Republic), Gert-Jan Nabuurs (the Netherlands)"


id: 17a9a7d01086b0954e42e2c46e3e566e
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"The Global Stocktake aims to assess countries' collective progress towards the long-term goals of the Paris Agreement in the light \r\nof the best available science. Historic progress is assessed based on NGHGIs, while expectations of future progress are based on \r\ncountry climate targets (e.g., NDCs for 2025 or 2030 and long-term strategies for 2050). Scenarios consistent with limiting warming \r\nwell-below 2degC and 1.5degC developed by IAMs (Chapter 3) are expected to play a key role as benchmarks against which countries' \r\naggregated future mitigation pledges will be assessed. This, however, implies that estimates by IAMs and country data used to \r\nmeasure progress are comparable."


id: 7e9abb6cea32010be2e670794f44c91a
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content:
"In fact, there is about 5.5 GtCO2 yr-1 difference during 2005-2015 between global anthropogenic land CO2 net flux estimates of IAMs \r\nand aggregated NGHGIs, due to different conceptual approaches to what is 'anthropogenic'. This approach and its implications when \r\ncomparing climate targets with global mitigation pathways are illustrated in this Box Figure 1a-e."


id: 9ca0f5d2eb0859bdff187a4c1f6d52fe
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content:
"By adjusting the original IAM output (Cross-Chapter Box  6, Figure  1a) with the indirect effects from countries' managed forest \r\n(Cross-Chapter Box 6, Figure 1b, estimated by DGVMs, see also Figure 7.6), NGHGI-comparable pathways can be derived (Cross\u0002Chapter Box 6, Figure 1c). The resulting apparent increase in anthropogenic sink reflects simply a reallocation of a CO2 flux previously \r\nlabelled as natural, and thus does not reflect a  mitigation action. These changes do not affect non-LULUCF emissions. However, \r\nsince the atmosphere concentration is a combination of CO2 emissions from LULUCF and from fossil fuels, the proposed land-related \r\nadjustments also influence the NGHGI-comparable economy-wide (all sector) CO2 pathways (Cross-Chapter Box 6, Figure 1d)."


id: 96486a94ae8c52be6bf1d5d509b6f6c2
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"The UNEP's annual assessment of the global 2030 'emission gap' between aggregated country NDCs and specific target mitigation \r\npathways (UNEP 2020), is only affected to a limited degree. This is because some estimates of global emissions under the NDCs \r\nalready use the same land-use definitions as the IAM mitigation pathways (Rogelj et al. 2017), and because historical data of global \r\nNDC estimates is typically harmonised to the historical data of global mitigation pathway projections (Rogelj et al. 2011). This latter \r\nprocedure, however, is agnostic to the reasons for the observed mismatch, and often uses a constant offset. The adjustment described \r\nhere allows this mismatch to be resolved by drawing on a scientific understanding of the underlying reasons, and thus provides a more \r\ninformed and accurate basis for estimating the emission gap."


id: 376fc5ae22e2606dd0aacf338fb3435f
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"The approach to deriving a NGHGI-comparable emission pathways presented here can be further refined with improved estimates of \r\nthe future forest sink. Its use would enable a more accurate assessment of the collective progress achieved and of mitigation pledges \r\nunder the Paris Agreement."


id: 99de08ad998a8cec53c01482732bdd37
created_at: 2023-03-16 14:01:36
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content:
"all countries compile inventories, nor submit annually. Additionally, \r\nNGHGIs may incorporate a  range of methodologies for CH4 and \r\nN2O accounting (e.g., van der Weerden et al. 2016; Ndung'u et al. \r\n2019; Thakuri et al. 2020), making comparison difficult. The analysis \r\nof complete AFOLU emissions presented here, is based on FAOSTAT \r\ndata. For agricultural specific discussion, analysis considers EDGAR, \r\nFAOSTAT and USEPA data."


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"Using FAOSTAT data, the SRCCL estimated average CH4 emissions \r\nfrom AFOLU to be 161.2 +- 43 MtCH4 yr-1 for the period 2007-2016, \r\nrepresenting 44% of total anthropogenic CH4 emissions, with \r\nagriculture accounting for 88% of the AFOLU component (Jia \r\net al. 2019). The latest data (FAO 2021a, 2020b) highlight a trend of \r\ngrowing AFOLU CH4 emissions, with a 10% increase evident between \r\n1990 and 2019, despite year-to-year variation. Forestry and other land \r\nuse (FOLU) CH4 emission sources include biomass burning on forest \r\nland and combustion of organic soils (peatland fires) (FAO 2020c). \r\nThe agricultural share of AFOLU CH4 emissions remains relatively "


id: c8de458e37595525880d60f181c7bffe
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
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content:
"with the average share from agriculture remaining approximately \r\nthe same (96%). Agricultural soils were identified in the SRCCL and \r\nin recent literature as a dominant emission source, notably due to \r\nnitrogen fertiliser and manure applications to croplands, and manure \r\nproduction and deposition on pastures (Jia et al. 2019; Tian et al. \r\n2020). There is agreement within latest data that agricultural soils \r\nremain the dominant source (Figure 7.7)."


id: 863d08c109919b0fb15aff26f7971dd7
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
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vector_id: 18663
content:
"unchanged, with the latest data indicating agriculture to have \r\naccounted for 89% of emissions on average between 1990 and 2019. \r\nThe SRCCL reported with medium evidence and high agreement that \r\nruminants and rice production were the most important contributors \r\nto overall growth trends in atmospheric CH4 (Jia et al. 2019). The latest \r\ndata confirm this in terms of agricultural emissions, with agreement \r\nbetween databases that agricultural CH4 emissions continue to \r\nincrease and that enteric fermentation and rice cultivation remain \r\nthe main sources (Figure  7.7). The proportionally higher emissions \r\nfrom rice cultivation indicated by EDGAR data compared to the other \r\ndatabases, may result from the use of a Tier 2 methodology for this \r\nsource within EDGAR (Janssens-Maenhout et al. 2019)."


id: 5deca7d578189bbb62b8031bf16140b1
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
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content:
"Aggregation of CH4 and N2O to CO2 equivalence (using GWP100 IPCC \r\nAR6 values), suggests that AFOLU emissions increased by 15% between \r\n1990 and 2019, though emissions showed trend variability year to year. \r\nAgriculture accounted for 91% of AFOLU emissions on average over \r\nthe period (FAO 2020b, 2021a). EDGAR (Crippa et al. 2021), FAOSTAT \r\n(FAO 2021a) and USEPA (USEPA 2019) data suggest aggregated \r\nagricultural emissions (CO2-eq) to have increased since 1990, by 19% \r\n(1990-2019), 15% (1990-2019) and 21% (1990-2015) respectively, \r\nwith all databases identifying enteric fermentation and agricultural \r\nsoils as the dominant agricultural emissions sources."


id: c9ead101423a94c5f59df4591360eb71
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 29324
content:
"The SRCCL also noted a  trend of increasing atmospheric N2O \r\nconcentration, with robust evidence and high agreement that \r\nagriculture accounted for approximately two-thirds of overall global \r\nanthropogenic N2O emissions. Average AFOLU N2O emissions were \r\nreported to be 8.7 +- 2.5 MtN2O yr-1 for the period 2007-2016, \r\naccounting for 81% of total anthropogenic N2O emissions, with \r\nagriculture accounting for 95% of AFOLU N2O emissions (Jia et al. \r\n2019). A  recent comprehensive review confirms agriculture as the \r\nprincipal driver of the growing atmospheric N2O concentration (Tian \r\net al. 2020). The latest FAOSTAT data (FAO 2020b, 2021a) document \r\na 25% increase in AFOLU N2O emissions between 1990 and 2019, "


id: b402a7e7b0fb40485bb152ff68279cbc
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"FAOSTAT data (FAO 2020b, 2021a) indicate Africa (+44%), followed \r\nby Southern Asia (+29%) to have the largest growth in AFOLU \r\nCH4 emissions between 1990 and 2019 (Figure  7.8). Eurasia was "


id: 1cb5682c6deb91b1ade0fb933ee882a7
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"Figure 7.8 | Estimated average AFOLU CH4 (top) and N2O (bottom) emissions for three decades according to FAOSTAT data by ten global regions, with \r\ndisaggregation of agricultural emissions (FAO 2020b; 2021a). Note for N2O: emissions from manure deposition and application to soils, crop residues and synthetic \r\nfertilisers are combined under 'Agriculture: Soils'."


id: ad428bb0298e292e5419baee42c7f608
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 24800
content:
"characterised by notable emission reductions (-58%), principally \r\nas a result of a sharp decline (-63%) between 1990 and 1999. The \r\naverage agricultural share of AFOLU emissions between 1990 and \r\n2019 ranged from 66% in Africa to almost 100% in the Middle East."


id: 2827db6ea26b9ce887e5542ce2ea8aa1
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 3725
content:
"The latest data suggest growth in AFOLU N2O emissions in most \r\nregions between 1990 and 2019, with Southern Asia demonstrating \r\nhighest growth (+74%) and Eurasia, greatest reductions (-51%), \r\nthe latter mainly a  result of a  61% reduction between 1990 and \r\n2000 (FAO 2020b, 2021a). Agriculture was the dominant emission \r\nsource in all regions, its proportional average share between 1990 \r\nand 2019 ranging from 87% in Africa, to almost 100% in the Middle \r\nEast (Figure 7.8)."


id: fe9d24714501a0f9c6519531a077b7e8
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 37598
content:
"Studies of biophysical effects have increased since AR5 reaching high \r\nagreement for the effects of changes in land condition on surface \r\nalbedo (Leonardi et al. 2015). Low confidence remains in proposing \r\nspecific changes in land conditions to achieve desired impacts on \r\nlocal, regional and global climates due to: a poor relationship between \r\nchanges in surface albedo and changes in surface temperature (Davin \r\nand de Noblet-Ducoudre 2010), compensation and feedbacks among \r\nbiophysical processes (Bonan 2016; Kalliokoski et al. 2020), climate \r\nand seasonal dependency of the biophysical effects (Bonan 2016), \r\nomittance of short-lived chemical forcers (Unger 2014; Kalliokoski \r\net al. 2020), and study domains often being too small to document \r\npossible conflicts between local and non-local effects (Swann et al. \r\n2012; Hirsch et al. 2018)."


id: 3fa8622b66907b553b832408d03340ef
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 7403
content:
"Figure 7.9 | Association of driver variables with more or less deforestation. Source: reproduced with permission from Busch and Ferretti-Gallon (2017)."


id: 19b1b9e51b521eb3651c39d43eec657a
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 1513
content:
"Globally, the area of the more open, other wooded land is also of \r\nsignificant importance, with almost 1 billion hectares (FAO 2020a). \r\nThe area of other wooded land decreased by 30.6 Mha between \r\n1990 and 2020 with larger declines between 1990-2000 (FAO \r\n2020a). There are still significant challenges in monitoring the \r\narea of other wooded land, largely associated with difficulties in \r\nmeasuring tree-canopy cover in the range of 5-10%.The global area \r\nof mangroves, one of the most productive terrestrial ecosystems \r\n(Neogi 2020a), has also experienced a significant decline (Thomas \r\net al. 2017; Neogi 2020b), with a decrease of 1.0 Mha between 1990 \r\nand 2020 (FAO 2020a) due to agriculture and aquaculture (Bhattarai \r\n2011; Ajonina et al. 2014; Webb et al. 2014; Giri et al. 2015; Thomas \r\net al. 2017; Fauzi et al. 2019). Some relevant direct drivers affecting \r\nemissions and removal in forests and other ecosystems are discussed \r\nin proceeding sections."


id: 57226f6496097e9ca25c209d4f232189
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"Despite a decline in global agricultural area, the latest data document \r\nsome regional expansion between 2000 and 2019, specifically in \r\nAfrica (+3%) and Asia and the Pacific (+1%). Agricultural area \r\ndeclined in all other regions, notably in developed countries (-9%), \r\ndue to multiple factors including among others, urbanisation (see \r\nSection 7.3.1.2)."


id: 380188428db3f3dc6f4e1f4b9940fab9
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 6187
content:
"Rapidly expanding roads, particularly in tropical regions, are linked to forest loss, degradation, and fragmentation because the land \r\nbecomes more generally accessible. Increase of land values of areas adjacent to roads also drives speculation and deforestation \r\nrelated to land tenure (Fearnside 2015). If poorly planned, infrastructure can facilitate fires, illegal mining, and wildlife poaching with \r\nconsequences for GHG emissions and biodiversity conservation. However, some initiatives are providing new approaches for better \r\nplanning and then limit environmental and societal impacts."


id: e837e366187ade8efe8620b1e0393edf
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"Although the number and extent of protected areas has increased markedly in recent decades (Watson et al. 2014), many other \r\nindicators reveal that nature is in broad retreat. For example, the total area of intact wilderness is declining rapidly worldwide (Watson \r\net al. 2016), 70% of the world's forests are now less than 1 km from a forest edge (Haddad et al. 2015), the extent of tropical forest \r\nfragmentation is accelerating exponentially (Taubert et al. 2018). One of the most direct and immediate driver of deforestation and \r\nbiodiversity decline is the dramatic expansion of roads and other transportation infrastructure (Laurance et al. 2014a; Laurance \r\nand Arrea 2017; Alamgir et al. 2017)."


id: e7e523d61fc1116e62e1faf3ddd207c1
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"From 2010 to 2050, the total length of paved roads is projected to increase by 25 million km (Dulac 2013) including large infrastructure\u0002expansion schemes in Asia (Laurance and Arrea 2017; Lechner et al. 2018) and in South America (Laurance et al. 2001; Killeen 2007), \r\nas well as widespread illegal or unplanned road building (Laurance et al. 2009; Barber et al. 2014). For example, in the Amazon, \r\n95% of all deforestation occurs within 5.5 km of a road, and for every km of legal road there are nearly three km of illegal roads \r\n(Barber et al. 2014)."


id: e7fb7b70db217ca7df1648aea3df5ee9
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 33995
content:
"More than any other proximate factor, the dramatic expansion of roads is determining the pace and patterns of habitat disruption and \r\nits impacts on biodiversity (Laurance et al. 2009; Laurance and Arrea 2017). Much road expansion is poorly planned. Environmental \r\nImpact Assessments (EIAs) for roads and other infrastructure are typically too short term and superficial to detect rare species or \r\nassess long-term or indirect impacts of projects (Flyvbjerg 2009; Laurance and Arrea 2017). Another limitation is the consideration \r\nof each project in isolation from other existing or planned developments (Laurance et al. 2014b). Hence, EIAs alone are inadequate \r\nfor planning infrastructure projects and assessing their broader environmental, social, and financial impacts and risks (Laurance et al. \r\n2015a; Alamgir et al. 2017, 2018)."


id: d7fae6993d12608d27ea413125ad8ed4
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 31509
content:
"The large-scale, proactive land-use planning is an option for managing the development of modern infrastructure. Approaches such \r\nas the 'Global Roadmap' scheme (Laurance and Balmford 2013; Laurance et al. 2014a) Strategic Environmental Assessments (Fischer \r\n2007) can be used to evaluate the relative costs and benefits of infrastructure projects, and to spatially prioritise land uses to optimise \r\nhuman benefits while limited new infrastructure in areas of intact or critical habitats. For example, the Global Roadmap strategy has \r\nbeen used in parts of South-East Asia (Sloan et al. 2018), Indochina (Balmford et al. 2016), and sub-Saharan Africa (Laurance et al. \r\n2015b) to devise land-use zoning that can help optimise the many risks and rewards of planned infrastructure projects."


id: 9f9006cd9f916ac572366df6761d79aa
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 22645
content:
"expansion to support a  growing workforce and development of \r\nmineral commodity supply chains (Sonter et al. 2015). The increasing \r\nconsumption of gold in developing countries, increased prices, and \r\nuncertainty in financial markets is identified as driving gold mining \r\nand associated deforestation in the Amazon region (Alvarez-Berrios \r\nand Mitchell Aide 2015; Dezecache et al. 2017; Asner and Tupayachi \r\n2017; Espejo et al. 2018). The total estimated area of gold mining \r\nthroughout the region increased by about 40% between 2012 and \r\n2016 (Asner and Tupayachi 2017). In the Brazilian Amazon, mining \r\nsignificantly increased forest loss up to 70 km beyond mining lease \r\nboundaries, causing 11,670 km2\r\n of deforestation between 2005 and \r\n2015, representing 9% of all Amazon forest loss during this time \r\n(Sonter et al. 2015)."


id: 990ebc393c3b8d950528d3157bb2bbad
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
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content:
"The extent and scale of mining is growing due to increased global \r\ndemand (UNEP 2019). Due to declining ore grades, more ore needs \r\nto be processed to meet demand, with extensive use of open cast \r\nmining. A  low-carbon future may be more mineral intensive with, \r\nfor example, clean energy technologies requiring greater inputs in \r\ncomparison to fossil-fuel-based technologies (Hund et al. 2020). \r\nMining presents cumulative environmental impacts, especially in \r\nintensively mined regions (UNEP 2019). The impact of mining on \r\ndeforestation varies considerably across minerals and countries. \r\nMining causes significant changes to the environment, for example, \r\nthrough mining infrastructure establishment, soil erosion, urban "


id: c046a3f8cffb47a398ec73cb61feae20
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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vector_id: 27811
content:
"Australia (Ward et al. 2020; Gallagher et al. 2021). Lightning plays \r\nan important role in the ignition of wildfires, with the incidence of \r\nlightning igniting wildfires predicted to increase with rises in global \r\naverage air temperature (Worden et al. 2017)."


id: 2c552224798c19123eac074b39c038a6
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 4406
content:
"Mining is also an important driver of deforestation in African and Asian \r\ncountries. In the Democratic Republic of Congo, where the second\u0002largest area of tropical forest in the world occurs, mining-related \r\ndeforestation exacerbated by violent conflict (Butsic et al. 2015). \r\nIn India, mining has contributed to deforestation at a district level, \r\nwith coal, iron and limestone having had the most adverse impact \r\non forest area loss (Ranjan 2019). Gold mining is also identified as \r\na driver of deforestation in Myanmar (Papworth et al. 2017)."


id: b476f4c62dfb642f29b45f015342787e
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 25923
content:
"by 233 Mha (FAO 2020e). In regions representing the majority of \r\nindustrial wood production, forests certified under sustainable forest \r\nmanagement programmes accounted for 51% of total managed \r\nforest area in 2017, an increase from 11% in 2000 (ICFPA 2021)."


id: 80631b56066068db29e269791b9c01b6
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
content_type: text
index: climate_gpt_only_giec
vector_id: 17727
content:
"In addition to livestock, both AR5 and the SRCCL identified paddy \r\nrice cultivation as an important emissions source (Smith et al. 2014), \r\nwith medium evidence and high agreement that its expansion is \r\na key driver of growing trends in atmospheric CH4 concentration (Jia \r\net al. 2019). The latest data indicate the global harvested area of rice \r\nto have grown by 11% between 1990 and 2019, with total paddy \r\nproduction increasing by 46%, from 519 Mt to 755 Mt (FAO 2021c). \r\nGlobal rice production is projected to increase by 13% by 2028 \r\ncompared to 2019 levels (OECD/FAO 2019). However, yield increases \r\nare expected to limit cultivated area expansion, while dietary shifts \r\nfrom rice to protein as a result of increasing per capita income, is \r\nexpected to reduce demand in certain regions, with a slight decline \r\nin related emissions projected to 2030 (USEPA 2019)."


id: 36924e2afa0ac0eaf1df785fa4db9481
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 5977
content:
"Between 1990 and 2019, Africa recorded the greatest increase \r\n(+160%) in area under rice cultivation, followed by Asia and the \r\nPacific (+6%), with area reductions evident in all other regions \r\n(FAO 2021c) broadly corresponding with related regional CH4\r\nemission (Figures  7.3 and 7.8). Data indicate the greatest growth \r\nin consumption (average annual supply per capita) between 1990 \r\nand 2013 to have occurred in Eastern Europe and West Central Asia \r\n(+42%) followed by Africa (+25%), with little change (+1%) observed \r\nin Asia and the Pacific (FAO 2017a). Most of the projected increase \r\nin global rice consumption is in Africa and Asia (OECD/FAO 2019)."


id: 202fbcae681cc06d0bae0135f0e1819f
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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index: climate_gpt_only_giec
vector_id: 2504
content:
"Although there are several potential drivers (McDermott et al. 2010; \r\nAlary et al. 2015), increased livestock production is principally in \r\nresponse to growth in demand for animal-sourced food, driven by \r\na growing human population (FAO, 2019) and increased consumption \r\nresulting from changes in affluence, notably in middle-income \r\ncountries (Godfray et al. 2018). Available data document increases \r\nin total meat and milk consumption by 24 and 22% respectively \r\nbetween 1990 and 2013, as indicated by average annual per capita \r\nsupply (FAO 2017a). Updated data indicate that trends of increasing \r\nconsumption continued between 2014 and 2018 (FAO 2021d). \r\nSustained demand for animal-sourced food is expected to drive \r\nfurther livestock sector growth, with global production projected to \r\nexpand by 14% by 2029, facilitated by maintained product prices and \r\nlower feed prices (OECD/FAO 2019)."


id: ab584ba8fd7c24347118e8b32c2392e5
created_at: 2023-03-16 14:01:36
updated_at: 2023-03-16 14:01:36
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content:
"Figure 7.10 | Trends in average global and regional land area under specific land uses (FAO 2021b), inorganic nitrogen fertiliser use (FAO 2021e) (top) \r\nand number of livestock (FAO 2021c) (bottom) for three decades. For land use classification 'cropland' represents the FAOSTAT category 'arable land' which includes \r\nland under temporary crops, meadow, pasture and fallow. 'Forest' and 'permanent meadow and pasture' follow FAOSTAT categories."


id: 5f3c626f4a1fa33a2cfea1073f072c48
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 12548
content:
"economic and cultural, scientific and technological, and institutional \r\nand governance drivers. These indirect drivers not only interact with \r\neach other at different temporal and spatial scales but are also subject \r\nto impacts and feedbacks from the direct drivers (Barger et al. 2018)."


id: 798a65bcddfb1af3e27ae75795045fc3
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 16694
content:
"Land rights: Land tenure often allows communities to exercise traditional governance based on traditional ecological knowledge, devolved \r\nand dynamic access rights, judicious use, equitable distribution of benefits (Mantyka-Pringle et al. 2017; Wynberg 2017; Thomas et al. 2017), \r\nbiodiversity (Contreras-Negrete et al. 2014) and fire and grazing management (Levang et al. 2015; Varghese et al. 2015)."


id: e112ac986f2203098c272d3934bf5847
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 32909
content:
"Institutions and governance\r\nAgreements and Finance: Since AR5, global agreements were reached on climate change, sustainable development goals, and the \r\nmobilisation of finance for development and climate action. Several countries adopted policies and commitments to restore degraded \r\nland (Barger et al. 2018). The UN Environment Programme (UNEP) and the Food and Agriculture Organization of the UN (FAO), launched \r\nthe UN Decade on Ecosystem Restoration (https://www.decadeonrestoration.org/)."


id: d0b8b21715761186a872fcd9b7bce742
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 30370
content:
"Companies have also made pledges to reduce impacts on forests and on the rights of local communities as well as eliminating deforestation \r\nfrom their supply chains. The finance sector, a crucial driver behind action (Section 7.6, Box 7.12), has also started to make explicit \r\ncommitments to avoiding environmental damage (Barger et al. 2018) and net zero targets (Forest Trends Ecosystem Marketplace 2021), \r\nthough investment is sensitive to market outlook."


id: cfba51fde344dc7c7d5eabd400b2a901
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 30216
content:
"For the 20 land-based mitigation measures outlined in this section, \r\nthe mitigation potential estimates are largely derived from sectoral \r\napproaches, and where data is available, are compared to IAM \r\nestimates. Integrated assessment models and the emissions \r\ntrajectories, cost-effectiveness and trade-offs of various mitigation \r\npathways are detailed in Section  7.5.  It should be noted that the \r\nunderlying literature for sectoral as well as IAM mitigation estimates \r\nconsider GWP100 IPCC AR5 values (CH4 = 28, N2O = 265) as well \r\nas GWP100 IPCC AR4 values (CH4 = 25, N2O = 298) to convert CH4\r\nand N2O to CO2-eq. Where possible, we note the various GWP100"


id: 4774de6c199baae324a592851cfdb12c
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 8630
content:
"options across sectors, including positive and negative effects on \r\nland resources, water, biodiversity, climate, and food security."


id: 8cb4a50163a77ab03870784a164216ef
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 19652
content:
"values (in IAM estimates, and the wetlands and agriculture sections), \r\nhowever in some instances, the varying GWP100 values used across \r\nstudies prevents description of non-CO2 gases in native units as well \r\nas conversion to AR6 GWP100 (CH4 = 27, N2O = 273) CO2-eq values \r\nto aggregate sectoral assessment estimates."


id: 9c4e5507a87bd268ecb2ad656c47cf59
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 22145
content:
"IPCC AR5 (2014). In the AR5, the economic mitigation potential \r\nof supply-side measures in the AFOLU sector was estimated \r\nat 7.18-10.60 GtCO2-eq yr-1 in 2030 with carbon prices up to \r\nUSD100 tCO2-eq-1, about a  third of which could be achieved at \r\n<USD20 tCO2-eq-1 (medium evidence, medium agreement) (Smith \r\net al. 2014). The AR5 provided a  summary table of individual \r\nAFOLU mitigation measures, but did not conduct a  detailed \r\nassessment for each."


id: 9576517df87964811f3631e954a109c1
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 21015
content:
"Land interventions have interlinked implications for climate mitigation, \r\nadaptation, food security, biodiversity, ecosystem services, and other \r\nenvironmental and societal challenges (Section 7.6.5). Therefore, it \r\nis important to consider the net effect of mitigation measures for \r\nachieving both climate and non-climate goals (Section 7.1)."


id: e92851fc391030132a46d95c96cd7455
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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content:
"Potential co-benefits and trade-offs are outlined for each of the \r\n20 land-based mitigation measures in the proceeding sub-sections \r\nand summarised in Figure 7.12. Section 7.6.5. discusses general links \r\nwith ecosystem services, human well-being and adaptation, while \r\nChapter 12 (Section 12.5) provides an in-depth assessment of the land \r\nrelated impacts, risks and opportunities associated with mitigation "


id: 25d3de387ac2c1585dd4803a4126133d
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 3378
content:
"about 50% of the technical potential of 24.2 (4.9-58) GtCO2-eq yr-1 \r\n(Table 7.3). Adding 2.1 GtCO2-eq yr-1 from demand-side measures \r\n(accounting only for diverted agricultural production to avoid double \r\ncounting with land-use change effects), total land-based mitigation \r\npotential up to USD100 tCO2-eq-1 is 13.6 (6.7-23.4) GtCO2-eq yr-1. \r\nThis estimate aligns with the most recent regional assessment (Roe \r\net al. 2021), which found the aggregate global mitigation potential \r\nof supply and demand-side measures to be 13.8 +- 3.1 GtCO2-eq yr-1\r\nup to USD100 tCO2-eq-1 for the period 2020-2050. Across integrated "


id: 90bfc280d42a7365e54c8906324d796b
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 20313
content:
"that do (Sonntag et al. 2016; Doelman et al. 2019). Given the IPCC \r\nWG1 finding that the land sink is continuing to increase although \r\nits efficiency is decreasing with climate change, it will be critical to \r\nbetter understand how future climate will affect mitigation potentials, \r\nparticularly from CDR measures."


id: 2e9b39914efe84cbedee3f484385f63e
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 4776
content:
"Across global sectoral studies, the economic mitigation potential \r\n(up to USD100 tCO2-eq-1) of supply-side measures in AFOLU for the \r\nperiod 2020-2050 is 11.4 mean (5.6-19.8 full range) GtCO2-eq yr-1, "


id: 583cf6dd385988ae3a8968d986d97aa6
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 11387
content:
"near-term emissions reductions, they have less economic potential \r\ndue to costs. Demand-side measures may be able to deliver non-CO2\r\nemissions reductions more cost efficiently."


id: f1020ce876054d391d99a2f30c2b538e
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 35414
content:
"Figure 7.11 (continued): Global and regional mitigation potential (GtCO2-eq yr-1) in 2020-2050 for 20 land-based measures. (a) Global estimates represent \r\nthe mean (bar) and full range (error bars) of the economic potential (up to USD100 tCO2-eq-1) based on a comprehensive literature review of sectoral studies (references are \r\noutlined in the sub-section for each measure in Sections 7.4.2-7.4.5). Potential co-benefits and trade-offs for each of the 20 measures are summarised in icons. (b) Regional \r\nestimates illustrate the mean technical (T) and economic (E) (up to USD100 tCO2-eq-1) sectoral potential based on data from (Roe et al. 2021). IAM economic potential (M) \r\n(USD100 tCO2-eq-1) data is from the IPCC AR6 database."


id: 8d8937ffdd112989ba39cdeec70e413e
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
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vector_id: 19793
content:
"enforcement, forest governance and land tenure, supporting \r\ncommunity forest management and introducing forest certification \r\n(P.  Smith et al. 2019a). Reducing deforestation provides numerous \r\nand substantial co-benefits, preserving biodiversity and ecosystem \r\nservices (e.g., air and water filtration, water cycling, nutrient cycling) \r\nmore effectively and at lower costs than afforestation/reforestation \r\n(Jia et al. 2019). Potential adverse side effects of these conservation \r\nmeasures include reducing the potential for agriculture land \r\nexpansion, restricting the rights and access of local people to forest \r\nresources, or increasing the dependence of local people to insecure \r\nexternal funding. Barriers to implementation include unclear land \r\ntenure, weak environmental governance, insufficient funds, and \r\nincreasing pressures associated to agriculture conversion, resource \r\nexploitation and infrastructure development (Sections 7.3 and 7.6)."


id: ce53f2ee6df4e7601d7e4e50d22c471a
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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content:
"Activities, co-benefits, risks and implementation opportunities \r\nand barriers. Reducing deforestation and forest degradation \r\nconserves existing carbon pools in forest vegetation and soil by \r\navoiding tree cover loss and disturbance. Protecting forests involves \r\ncontrolling the drivers of deforestation (such as commercial and \r\nsubsistence agriculture, mining, urban expansion) and forest \r\ndegradation (such as overharvesting including fuelwood collection, \r\npoor harvesting practices, overgrazing, pest outbreaks, and extreme \r\nwildfires), as well as by establishing well designed, managed \r\nand funded protected areas (Barber et al. 2014), improving law "


id: 553ab5a52a96068dc7c1e618b43d7d0b
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 10872
content:
"Conclusions from AR5 and IPCC Special Reports (SR1.5, SROCC \r\nand SRCCL); mitigation potential, costs, and pathways. Reducing \r\ndeforestation and forest degradation represents one of the most effective \r\noptions for climate change mitigation, with technical potential estimated \r\nat 0.4-5.8 GtCO2 yr-1 by 2050 (high confidence) (SRCCL, Chapters 2 and \r\n4, and Table 6.14). The higher technical estimate represents a complete \r\nhalting of land-use conversion in forests and peatland forests (i.e., \r\nassuming recent rates of carbon loss are saved each year) and includes \r\nvegetation and soil carbon pools. Ranges of economic potentials for \r\nforestry ranged in AR5 from 0.01-1.45 GtCO2 yr-1 for USD20 tCO2\r\n-1\r\nto 0.2-13.8 GtCO2 yr-1 for USD100 tCO2\r\n-1 by 2030 with reduced \r\ndeforestation dominating the forestry mitigation potential LAM and \r\nMAF, but very little potential in OECD-1990 and EIT (IPCC AR5)."


id: 70fad0b66f1c0350a7bb690b1b6815dc
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 15410
content:
"provides multiple co-benefits linked to ecosystem services, biodiversity \r\nand sustainable development (Section  7.6.). Still, ensuring good \r\ngovernance, accountability (e.g., enhanced monitoring and verification \r\ncapacity; Bos 2020), and the rule of law are crucial for implementing \r\nforest-based mitigation options. In many countries with the highest \r\ndeforestation rates, insecure land rights often are significant barriers for \r\nforest-based mitigation options (Gren and Zeleke 2016; Essl et al. 2018)."


id: ca9f0163cb00897040dcfb62d4c2b294
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
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vector_id: 29442
content:
"Conclusions from AR5 and IPCC Special Reports (SR1.5, SROCC \r\nand SRCCL); mitigation potential, costs, and pathways. The AR5 \r\ndid not provide a new specification of A/R potential, but referred to \r\nIPCC AR4 mostly for forestry measures (Nabuurs et al. 2007). The AR5 \r\ndid view the feasible A/R potential from a diets change scenario that \r\nreleased land for reforestation and bioenergy crops. The AR5 provided \r\ntop-down estimates of costs and potentials for forestry mitigation \r\noptions  - including reduced deforestation, forest management, \r\nafforestation, and agroforestry, estimated to contribute between 1.27 \r\nand 4.23 GtCO2 yr-1 of economically viable abatement in 2030 at \r\ncarbon prices up to USD100 tCO2-eq-1 (Smith et al. 2014)."


id: 24f4f962a98baf5690dd0466c9088db9
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 3256
content:
"Critical assessment and conclusion. Based on studies since \r\nAR5, the technical mitigation potential for reducing deforestation \r\nand degradation is significant, providing 4.5 (2.3-7) GtCO2 yr-1\r\nglobally by 2050, of which 3.4 (2.3-6.4) GtCO2 yr-1 is available at \r\nbelow USD100 tCO2\r\n-1 (medium confidence) (Figure  7.11). Over the \r\nlast decade, hundreds of subnational initiatives that aim to reduce \r\ndeforestation related emissions have been implemented across the \r\ntropics (Section 7.6). Reduced deforestation is a significant piece of \r\nthe NDCs in the Paris Agreement (Seddon et al. 2020) and keeping \r\nthe temperature below 1.5degC (Crusius 2020). Conservation of forests "


id: 48d0552d7a79e1112253d31a60000fc8
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 8835
content:
"The SRCCL remained with a  reported wide range of mitigation \r\npotential for A/R of 0.5-10.1 GtCO2 yr-1 by 2050 (medium confidence) \r\n(Kreidenweis et al. 2016; Griscom et al. 2017; Hawken 2017; Fuss et al. \r\n2018; Roe et al. 2019) (SRCCL Chapters 2 and 6). The higher estimate \r\nrepresents a technical potential of reforesting all areas where forests \r\nare the native cover type (reforestation), constrained by food security \r\nand biodiversity considerations, considering above and below-ground "


id: 4363fdd89eac87a66e76da9614d30347
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 8010
content:
"of afforestation and reforestation activities by 2050 is 3.9 \r\n(0.5-10.1) GtCO2 yr-1, and the economic mitigation potential \r\n(<USD100 tCO2\r\n-1) is 1.6   (0.5-3.0)  GtCO2  yr-1 (requiring about \r\n200 Mha). Per hectare a long (about 100 year) sustained effect of \r\n5-10 t CO2 ha-1 yr-1 is realistic with ranges between 1-20 t(CO2) ha-1\r\nyr-1. Not all sectoral studies rely on economic models that account for \r\nleakage (Murray et al. 2004; Sohngen and Brown 2004), suggesting \r\nthat technical potential may be overestimated."


id: 12a48235a14aebb89c7df62cf137a7df
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 431
content:
"Conclusions from AR5 and IPCC Special Reports (SR1.5, SROCC \r\nand SRCCL); mitigation potential, costs, and pathways. In the \r\nSRCCL, forest management activities have the potential to mitigate \r\n0.4-2.1 GtCO2-eq yr-1 by 2050 (medium confidence) (SRCCL: \r\nGriscom et al. 2017; Roe et al. 2019). The higher estimate stems from "


id: a68f13cb7587fd4eb237b9d0c45c60ab
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 23732
content:
"assumptions of applications on roughly 1.9 billion ha of already \r\nmanaged forest  which can be seen as very optimistic. It combines \r\nboth natural forest management as well as improved plantations, on \r\naverage with a small net additional effect per hectare, not including \r\nsubstitution effects in the energy sector nor the buildings sector."


id: a3ec4a44901eba8013d7d9bb791abeb7
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 23350
content:
"(Smyth et al. 2020). In Europe, climate-smart forestry could mitigate \r\nan additional 0.19 GtCO2 yr-1 by 2050 (Nabuurs et al. 2017), in line \r\nwith the regional estimates in (Roe et al. 2021)."


id: 822d47afd31ad28f134fd3c1e3b4fd99
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 18007
content:
"In the tropics, estimates of the pantropical climate mitigation potential \r\nof natural forest management (a light intensity management in \r\nsecondary forests), across three tropical regions (Latin America, \r\nAfrica, Asia), is around 0.66 GtCO2-eq yr-1 with Asia responding for \r\nthe largest share followed by Africa and Latin America (Roe et al. \r\n2021). Selective logging occurs in at least 20% of the world's tropical \r\nforests and causes at least half of the emissions from tropical forest \r\ndegradation (Asner et al. 2005; Blaser and Kuchli 2011; Pearson \r\net al. 2017). Reduced-impact logging for climate (RIL-C; promotion \r\nof reduced wood waste, narrower haul roads, and lower impact \r\nskidding equipment) has the potential to reduce logging emissions \r\nby 44% (Ellis et al. 2019), while also providing timber production."


id: bd3f47083a0ed0a889c1e36892df9143
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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content:
"Developments since AR5 and IPCC Special Reports (SR1.5, \r\nSROCC and SRCCL). The area of forest under management plans \r\nhas increased in all regions since 2000 by 233 Mha (FAO 2020e). The \r\nroughly 1 billion ha of secondary and degraded forests would be ideal \r\nto invest in and develop a sustainable sector that pays attention to \r\nbiodiversity, wood provision and climate mitigation at the same time. \r\nThis all depends on the effort made, the development of expertise, \r\nknow-how in the field, nurseries with adapted provenances, etc as \r\nwas also found for Russian climate-smart forestry options (Leskinen \r\net al. 2020). Regionally, recently updated economic mitigation \r\npotential at USD100 tCO2\r\n-1 have 179-186 MtCO2-eq yr-1 in Africa, \r\n193-313 MtCO2-eq yr-1 in Asia and Pacific, 215-220 MtCO2-eq yr-1 \r\nin Developed Countries , 82-152 MtCO2-eq yr-1 in Eastern Europe \r\nand West-Central Asia, and 62-204 MtCO2-eq yr-1 in Latin America \r\nand Caribbean (Roe et al. 2021)."


id: 3ce0ba04900a11222fb4e874a0147b71
created_at: 2023-03-16 14:01:37
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content:
"Regional studies can take into account the local situation better: \r\nRussia Romanovskaya et al. (2020) estimate the potential of forest \r\nfires management at 220-420 MtCO2 yr-1, gentle logging technology \r\nat 15-59, reduction of wood losses at 61-76 MtCO2 yr-1. In North \r\nAmerica, (Austin et al. 2020) estimate that in the next 30 years, \r\nforest management could contribute 154 MtCO2 yr-1 in the USA and \r\nCanada with 81 MtCO2 yr-1 available at less than USD100 tCO2\r\n-1. In \r\none production region (British Columbia) a cost-effective portfolio of \r\nscenarios was simulated that directed more of the harvested wood \r\nto longer-lived wood products, stopped burning of harvest residues \r\nand instead produced bioenergy to displace fossil fuel burning, and \r\nreduced harvest levels in regions with low disturbance rates. Net \r\nGHG emissions were reduced by an average of -9 MtCO2-eq yr-1"


id: 300ad3d9f1fb52edd45092732ffce860
created_at: 2023-03-16 14:01:37
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content:
"European forests have been regarded as prospering and increasing for the last five decades. However, these views also changed \r\nrecently. Climate change is putting a large pressure on mono species and high stocked areas of Norway spruce in Central Europe \r\n(Hlasny et al. 2021; Senf and Seidl 2021) with estimates of mortality reaching 200 million m3\r\n, biodiversity under pressure, the \r\nMediterranean area showing a weak sector and harvesting pressure in the Baltics and north reaching maxima achievable. A European \r\nstrategy for unlocking the EU's forests and forest sector potential was needed at the time of developing the LULUCF regulation and \r\nwas based on the concept of 'climate-smart forestry' (CSF) (Nabuurs et al. 2017; Verkerk et al. 2020)."


id: 7af9f31a074b01d520fe4f424f1dbb55
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 16938
content:
"The idea behind CSF is that it considers the whole value chain from forest to wood products and energy, illustrating that a wide range \r\nof measures can be applied to provide positive incentives for more firmly integrating climate objectives into the forest and forest \r\nsector framework. CSF is more than just storing carbon in forest ecosystems; it builds upon three main objectives; (i) reducing and/\r\nor removing GHG emissions; (ii) adapting and building diverse forests for forest resilience to climate change; and (iii) sustainably \r\nincreasing forest productivity and incomes. These three CSF objectives can be achieved by tailoring policy measures and actions to \r\nregional circumstances in member states' forest sectors."


id: 38aa95fc6e78ed12dc668ad622d56ef2
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 6286
content:
"The 2015 annual mitigation effect of EU-28 forests via contributions to the forest sink, material substitution and energy substitution is \r\nestimated at 569 MtCO2 yr-1, or 13% of total current EU emissions. With the right set of incentives in place at EU and member states \r\nlevels, it was found that the EU-28 has the potential to achieve an additional combined mitigation impact through the implementation \r\nof CSF of 441 MtCO2 yr-1 by 2050. Also, with the Green Deal and its biodiversity and forest strategy, more emphasis will be placed on \r\nforests, forest management and the provision of renewables. It is the diversity of measures (from strict reserves to more intensively \r\nmanaged systems while adapting the resource) that will determine the success. Only with co-benefits in, for example, nature \r\nconservation, soil protection, and provision of renewables, wood for buildings and income, the mitigation and adaptation measures \r\nwill be successful."


id: db99d9352fb588bbda42d0e5be97fce5
created_at: 2023-03-16 14:01:37
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content:
"Climate-smart forestry is now taking shape across Europe with various research and implementation projects (Climate Smart Forest \r\nand Nature Management, 2021). Pilots and projects are being implemented by a variety of forest owners, some with more attention \r\non biodiversity and adaptation, some with more attention on production functions. They establish examples and in longer term the \r\noutreach to the 16 million private owners in Europe. However, the right triggers and incentives are often still lacking. For example, \r\nadapting the spruce forest areas in Central Europe to climate change requires knowledge about different species, biodiversity and \r\ndifferent management options and eventually use in industry. It requires alternative species to be available from the nurseries, as well \r\nas improved monitoring to assess the success and steer activities."


id: 27d319ebff942b58278e7ce113507e51
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 3675
content:
"Conclusions from AR5 and IPCC Special Reports (SR1.5, SROCC \r\nand SRCCL); mitigation potential, costs, and pathways. In the \r\nSRCCL, fire management is among the nine options that can deliver \r\nmedium-to-large benefits across multiple land challenges (climate \r\nchange mitigation, adaptation, desertification, land degradation, and \r\nfood security) (high confidence). Total emissions from fires have been \r\non the order of 8.1 GtCO2-eq yr-1 in terms of gross biomass loss for \r\nthe period 1997-2016 (SRCCL, Chapter 2, and Cross-Chapter Box 3 \r\nin Chapter  2). Reduction in fire CO2 emissions was calculated to \r\nenhance land carbon sink by 0.48 GtCO2-eq yr-1 for the 1960-2009 \r\nperiod (Arora and Melton 2018) (SRCCL, Table 6.16)."


id: 4ae987377c583425d1e8d9d9cf090f1f
created_at: 2023-03-16 14:01:37
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content:
"Forests. Fire is also a prevalent forest disturbance (Falk et al. 2011; \r\nScott et al. 2014; Andela et al. 2019). About 98 Mha of forest were \r\naffected by fire in 2015, affecting about 4% of the tropical (dry) \r\nforests, 2% of the subtropical forests, and 1% of temperate and \r\nboreal forests (FAO 2020a). Between 2001-2018, remote sensing \r\ndata showed that tree-covered areas correspond to about 29% of \r\nthe total area burned by wildfires, most in Africa. Prescribed fires are \r\nalso applied routinely in forests worldwide for fuel reduction and "


id: 3fdc85cfdb0ce671976c8ff4849a4079
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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content:
"drivers (e.g., commercial and subsistence agriculture, see Section 7.3) \r\nand improving policies and management. In addition to mitigation, \r\nconserving grasslands provide various socio-economic, biodiversity, \r\nwater cycle and other environmental benefits (Claassen et al. 2010; \r\nRyals et al. 2015; Bengtsson et al. 2019). Annual operating costs, and \r\nopportunity costs of income foregone by undertaking the activities \r\nneeded for avoiding conversion of grasslands making costs one of \r\nthe key barriers for implementation (Lipper et al. 2010)."


id: afd94e6ef692d5b94fc447bc107b7314
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 25188
content:
"Critical assessment and conclusion. There is low confidence that \r\nthe global technical mitigation potential for reduced grassland and \r\nsavanna conversion by 2050 is 0.2 (0.1-0.4) GtCO2 yr-1, and the "


id: 7a418abf9770327b1bcb7ecc74e55a71
created_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 16800
content:
"Conclusions from AR5 and IPCC Special Reports (SR1.5, SROCC \r\nand SRCCL); mitigation potential, costs, and pathways. In \r\nthe SRCCL (Chapters 2 and 6), it was estimated that avoided peat \r\nimpacts could deliver 0.45-1.22 GtCO2-eq yr-1 technical potential \r\nby 2030-2050 (medium confidence) (Hooijer et al. 2010; Griscom \r\net al. 2017; Hawken 2017). The mitigation potential estimates cover \r\ntropical peatlands and include CO2, N2O and CH4 emissions. The \r\nmitigation potential is derived from quantification of losses of carbon \r\nstocks due to land conversion, shifts in GHG fluxes, alterations in \r\nnet ecosystem productivity, input factors such as fertilisation needs, \r\nand biophysical climate impacts (e.g., shifts in albedo, water cycles, \r\netc.). Tropical peatlands account for only about 10% of peatland area "


id: c3b4b20dda5d399d198478fd0c30d196
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
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content:
"of this mitigation strategy (Roe et al. 2019). Feasibility of reducing \r\npeatland conversion may depend on countries' governance, financial \r\ncapacity and political will."


id: a62cf3de85dd71c6b1ee92eaf3fa2254
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 23685
content:
"meet 1.5degC-2degC pathways which is unlikely to happen (Leifeld et al. \r\n2019); immediate rewetting and restoration minimises the warming \r\nfrom cumulative CO2 emissions (Nugent et al. 2019)."


id: 25c0377b204a98208f1b952ee76cc844
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 3370
content:
"According to recent data, the technical mitigation potential for global \r\npeatland restoration is estimated at 0.5-1.3 GtCO2-eq yr-1 (Leifeld \r\nand Menichetti 2018; Griscom et al. 2020; Bossio et al. 2020; Roe et al. \r\n2021) (Figure  7.11), with 80% of the mitigation potential derived \r\nfrom improvements to soil carbon (Bossio et al. 2020). The regional \r\nmitigation potentials of all peatlands outlined in Roe et al. (2021) \r\nreflect the country-level estimates from (Humpenoder et al. 2020)."


id: 7f53375ad4276f8b75a8d78cf425412
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 17586
content:
"Climate mitigation effects of peatland rewetting depend on the \r\nclimate zone and land use. Recent analysis shows the strongest \r\nmitigation gains from rewetting drained temperate and boreal \r\npeatlands used for agriculture and drained tropical peatlands (Ojanen \r\nand Minkkinen 2020). However, estimates of emission factors from \r\nrewetting drained tropical peatlands remain uncertain (Wilson et al. \r\n2016; Murdiyarso et al. 2019). Topsoil removal, in combination with \r\nrewetting, may improve restoration success and limit CH4 emissions \r\nduring restoration of highly degraded temperate peatlands (Zak et al. \r\n2018). In temperate and boreal regions, co-benefits mentioned above \r\nare major motivations for peatland restoration (Chimner et al. 2017; \r\nTanneberger et al. 2020a)."


id: 5b5957a82b2e04fce1096d592ab2f78a
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 11876
content:
"Critical assessment and conclusion. Based on studies to date, \r\nthere is medium confidence that peatland restoration has a technical \r\npotential of 0.79 (0.49-1.3) GtCO2-eq yr-1 (median) of which \r\n0.4 (0.2-0.6) GtCO2-eq yr -1 is available up to USD100 tCO2\r\n-1. The large \r\nland area of degraded peatlands suggests that significant emissions \r\nreductions could occur through large-scale restoration especially \r\nin tropical peatlands. There is medium confidence in the large \r\ncarbon stocks of tropical peat forests (1956-14,757 tCO2-eq ha-1) \r\nand large rates of carbon loss associated with land cover change \r\n(640-1650 tCO2-eq ha-1) (Goldstein et al. 2020; Novita et al. \r\n2021). However, large-scale implementation of tropical peatland \r\nrestoration will likely be limited by costs and other demands for these \r\ntropical lands."


id: f7f13d3084c62bb43b8163e030c41a55
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 36524
content:
"Conclusions from AR5 and IPCC Special Reports (SR1.5, SROCC \r\nand SRCCL); mitigation potential, costs, and pathways. Large \r\nareas (0.51 Mkm2\r\n) of global peatlands are degraded of which \r\n0.2 Mkm2 are tropical peatlands (Griscom et al. 2017; Leifeld and \r\nMenichetti 2018). According the SRCCL, peatland restoration could \r\ndeliver technical mitigation potentials of 0.15 - 0.81GtCO2-eq yr-1\r\nby 2030-2050 (low confidence) (Couwenberg et al. 2010; Griscom \r\net al. 2017) (Chapters 2 and 6 of the SRCCL), though there could be \r\nan increase in methane emissions after restoration (Jauhiainen et al. \r\n2008). The mitigation potential estimates cover global peatlands and \r\ninclude CO2, N2O and CH4 emissions. Peatlands are highly sensitive \r\nto climate change (high confidence), however there are currently no \r\nstudies that estimate future climate effects on mitigation potential \r\nfrom peatland restoration."


id: 62b12007b341a194150325690dd04d25
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 13098
content:
"Developments since AR5 and IPCC Special Reports (SR1.5, \r\nSROCC and SRCCL). The most recent literature and reviews indicate \r\nwith high confidence that restoration would decrease CO2 emissions \r\nand with medium confidence that restoration would decrease net \r\nGHG emissions from degraded peatlands (Wilson et al. 2016; Ojanen \r\nand Minkkinen 2020; van Diggelen et al. 2020). Although rewetting \r\nof drained peatlands increases CH4 emissions, this effect is often \r\noutweighed by decreases in CO2 and N2O emissions but depends \r\nvery much on local circumstances (Gunther et al. 2020). Restoration \r\nand rewetting of almost all drained peatlands is needed by 2050 to "


id: dfb50f7d008cc06f6441f8dbd243117c
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 32695
content:
"Recent loss rates of mangroves are 0.16-0.39% yr-1 and are highest \r\nin South-East Asia (Hamilton and Casey 2016; Friess et al. 2019; \r\nHamilton and Casey 2016). Assuming loss of soil carbon to 1 m depth \r\nafter deforestation, avoiding mangrove conversion has the technical \r\npotential to mitigate approximately 23.5-38.7 MtCO2-eq yr-1\r\n(Ouyang and Lee 2020); note, this potential is additional to reduced \r\nconversion of forests (Griscom et al. 2020) (Section  7.4.2.1). \r\nRegional estimates show that about 85% of mitigation potential \r\nfor avoided mangrove conversion is in South-East Asia and Pacific \r\n(32 MtCO2-eq yr-1 at USD100 tCO2\r\n-1), 10% is in Latin American and \r\nthe Caribbean (4 MtCO2-eq yr-1), and approximately 5% in other \r\nregions (Griscom et al. 2020; Roe et al. 2021)."


id: 97fec5e5fe6e80a1d1c131a8a91fdb69
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 21423
content:
"Key uncertainties remain in mapping extent and conversion rates \r\nfor salt marshes and seagrasses (McKenzie et al. 2020). Seagrass \r\nloss rates were estimated at 1-2% yr-1 (Dunic et al. 2021) with \r\nstabilisation in some regions (de los Santos et al. 2019) (AR6 WGII, \r\nSection 3.4.2.5); however, loss occurs non-linearly and depends on \r\nsite-specific context. Tidal marsh extent and conversion rates remains \r\npoorly estimated, outside of the USA, Europe, South Africa, and \r\nAustralia (Mcowen et al. 2017; Macreadie et al. 2019)."


id: bc901ea7c03a0847e6785b976fbc8a28
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 27245
content:
"Critical assessment and conclusion. There is medium confidence\r\nthat coastal wetland protection has a  technical potential of \r\n0.8 (0.06-5.4) GtCO2-eq yr-1 of which 0.17 (0.06-0.27) GtCO2-eq yr-1\r\nis available up to USD100 tCO2\r\n-1. There is a high certainty (robust \r\nevidence, high agreement) that coastal ecosystems have among the \r\nlargest carbon stocks of any ecosystem. As these ecosystems provide \r\nmany important services, reduced conversion of coastal wetlands is \r\na valuable mitigation strategy with numerous co-benefits. However, \r\nthe vulnerability of coastal wetlands to climatic and other anthropogenic \r\nstressors may limit the permanence of climate mitigation."


id: 3543704c75b7917fae6fee4b5c59460b
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 5794
content:
"Developments since AR5 and IPCC Special Reports (SR1.5, \r\nSROCC and SRCCL). Global technical mitigation potential for \r\nconservation of coastal wetlands from recent literature have \r\nfocused on protection of mangroves; estimates range from \r\n0.06-2.25 GtCO2-eq yr-1 (Griscom et al. 2020; Bossio et al. 2020)\r\nwith 80% of the mitigation potential derived from improvements to \r\nsoil carbon (Bossio et al. 2020). Regional potentials (Roe et al. 2021) \r\nreflect mangrove protection; marsh and seagrass protection were not \r\nincluded due to lack of country-level data on marsh and seagrass \r\ndistribution and conversion."


id: 926d85482dd28e98e885696d4bbf1a3d
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 20560
content:
"Global estimates show mangroves have the largest per hectare carbon \r\nstocks (see IPCC AR6 WGII Box 3.4 for estimates of carbon stocks, \r\nburial rates and ecosystem extent for coastal wetland ecosystems). \r\nMean ecosystem carbon stock in mangroves is 3131 tCO2-eq ha-1\r\namong the largest carbon stocks on Earth. Recent studies emphasise \r\nthe variability in total ecosystem carbon stocks for each wetland type, \r\nbased on species and climatic and edaphic conditions (Kauffman \r\net al. 2020; Bedulli et al. 2020; Ricart et al. 2020; Alongi et al. 2020; \r\nF. Wang et al. 2021), and highlight the vulnerability of soil carbon \r\nbelow 1 m depth (Arifanti et al. 2019). Sea level strongly influences \r\ncoastal wetland distribution, productivity, and sediment accretion; \r\ntherefore, sea level rise will impact carbon accumulation and "


id: 912dbbf8de8c3c8133387d452000915a
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 20377
content:
"through enhanced methane and nitrous oxide release and carbonate \r\nformation, and competition with other land uses, including aquaculture \r\nand human settlement and development in the coastal zone (SROCC, \r\nChapter 5). To date, many coastal wetland restoration efforts do not \r\nsucceed due to failure to address the drivers of degradation (van \r\nKatwijk et al. 2016). However, improved frameworks for implementing \r\nand assessing coastal wetland restoration are emerging that emphasise \r\nthe recovery of ecosystem functions (Zhao et al. 2016; Cadier et al. \r\n2020). Restoration projects that involve local communities at all stages \r\nand consider both biophysical and socio-political context are more \r\nlikely to succeed (Brown et al. 2014; Wylie et al. 2016)."


id: 7ba96dec09dadf3406a51f7e4f320d3e
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 17055
content:
"of their total national carbon stock (Donato et al. 2012). Furthermore, \r\nnon-climatic co-benefits can strongly motivate coastal wetland \r\nrestoration worldwide (UNEP 2021a). Major successes in both active \r\nand passive restoration of seagrasses have been documented in \r\nNorth America and Europe (Lefcheck et al. 2018; de los Santos et al. \r\n2019; Orth et al. 2020); passive restoration may also be feasible for \r\nmangroves (Cameron et al. 2019)."


id: ba7e4651dcc6e6feef686b8afe9ee83
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 26877
content:
"There is high site-specific variation in carbon sequestration rates \r\nand uncertainties regarding the response to future climate change \r\n(Jennerjahn et al. 2017; Nowicki et al. 2017) (IPCC AR6 WGII Box 3.4). \r\nChanges in distributions (Kelleway et al. 2017; Wilson and Lotze 2019),\r\nmethane release (Al-Haj and Fulweiler 2020), carbonate formation \r\n(Saderne et al. 2019), and ecosystem responses to interactive climate \r\nstressors are not well-understood (Short et al. 2016; Fitzgerald and \r\nHughes 2019; Lovelock and Reef 2020)."


id: caf0b6fb8d76a7376023c15480d926a8
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 29493
content:
"Conclusions from AR5 and IPCC Special Reports (SR1.5, \r\nSROCC and SRCCL); mitigation potential, costs, and pathways.\r\nThe SRCCL reported that mangrove restoration has the technical \r\npotential to mitigate 0.07 GtCO2 yr-1 through rewetting (Crooks et al. \r\n2011) and take up 0.02-0.84 GtCO2 yr-1 from vegetation biomass \r\nand soil enhancement through 2030 (medium confidence) (Griscom \r\net al. 2017). The SROCC concluded that cost-effective coastal blue \r\ncarbon restoration had a potential of about 0.15-0.18 GtCO2-eq yr-1, \r\na  low global potential compared to other ocean-based solutions \r\nbut with extensive co-benefits and limited adverse side effects \r\n(Gattuso et al. 2018)."


id: f5867494f8a46fff803417edcefb098c
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 36152
content:
"Critical assessment and conclusion. There is medium confidence\r\nthat coastal wetland restoration has a  technical potential of \r\n0.3 (0.04-0.84) GtCO2-eq yr-1 of which 0.1 (0.05-0.2) GtCO2-eq yr-1\r\nis available up to USD100 tCO2\r\n-1. There is high confidence that \r\ncoastal wetlands, especially mangroves, contain large carbon stocks \r\nrelative to other ecosystems and medium confidence that restoration \r\nwill reinstate pre-disturbance carbon sequestration rates. There is low \r\nconfidence on the response of coastal wetlands to climate change; \r\nhowever, there is high confidence that coastal wetland restoration \r\nwill provide a suite of valuable co-benefits."


id: 467e91d42357dfca59412cd2869d6ede
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 8473
content:
"According to recent data, the technical mitigation potential for global \r\ncoastal wetland restoration is 0.04-0.84 GtCO2-eq yr-1 (Griscom et al. \r\n2020; Bossio et al. 2020; Roe et al. 2021) with 60% of the mitigation \r\npotential derived from improvements to soil carbon (Bossio et al. \r\n2020). Regional potentials based on country-level estimates from \r\nGriscom et al. (2020) show the technical and economic (up to \r\nUSD100 tCO2\r\n-1) potential of mangrove restoration; seagrass and \r\nmarsh restoration was not included due to lack of country-level data \r\non distribution and conversion (but see McKenzie et al. 2020 for \r\nupdates on global seagrass distribution). Although global potential is \r\nrelatively moderate, mitigation can be quite significant for countries \r\nwith extensive coastlines (e.g., Indonesia, Brazil) and for small island \r\nstates where coastal wetlands have been shown to comprise 24-34% "


id: 6aebfe325b0eb304775ceb6c7b5fa0ba
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 14442
content:
"Critical assessment and conclusion. In conclusion, there is medium \r\nconfidence that enhanced soil carbon management in croplands has \r\na global technical mitigation potential of 1.9 (0.4-6.8) GtCO2 yr-1, \r\nand in grasslands of 1.0 (0.2-2.6) GtCO2 yr-1, of which, 0.6 (04-0.9) \r\nand 0.9 (0.3-1.6) GtCO2 yr-1 is estimated to be available at up to \r\nUSD100 tCO2\r\n-1 respectively. Regionally, soil carbon management \r\nin croplands and grasslands is feasible anywhere, but effectiveness \r\ncan be limited in very dry regions, and for grasslands it is greatest \r\nin areas where degradation has occurred (e.g.,  by overgrazing) \r\nand soil organic carbon is depleted. Barriers to implementation \r\ninclude regional capacity for monitoring and verification (especially \r\nin developing countries), and more widely through concerns over \r\nsaturation and permanence."


id: 22a03b251e8b265dd048b10b2dbb3abd
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 2903
content:
"and impacts on leakage, indirect land-use change and foregone \r\nsequestration do not apply (since production in not displaced), the \r\nclimate benefits of soil carbon sequestration in croplands can be \r\nnegated if achieved through additional fertiliser inputs (potentially \r\ncausing increased N2O emissions; (Guenet et al. 2021), and both \r\nsaturation and permanence are relevant concerns. When considering \r\nimplementation barriers, soil carbon management in croplands and \r\ngrasslands is a low-cost option at a high level of technology readiness \r\n(it is already widely deployed globally) with low socio-cultural and \r\ninstitutional barriers, but with difficulty in monitoring and verification \r\nproving a barrier to implementation (Smith et al. 2020a)."


id: 942406baf76b0a548607d976d8cc8e6d
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 20818
content:
"and verification, and limited knowledge, standardisation and quality \r\ncontrol, restricting user confidence (Gwenzi et al. 2015)."


id: 12fe879714b2c83586b67b0a00c87371
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 494
content:
"Conclusions from AR5 and IPCC Special Reports (SR1.5, SROCC \r\nand SRCCL); mitigation potential, costs, and pathways. Biochar is \r\ndiscussed as a mitigation option in AR5 and CDR strategy in the SR1.5. \r\nConsideration of potential was limited as biochar is not included in IAMs. \r\nThe SRCCL estimated mitigation potential of 0.03-6.6 GtCO2-eq yr-1\r\nby 2050 based on studies with widely varying assumptions, definitions \r\nof potential, and scope of mitigation processes included (SRCCL, \r\nChapters 2 and 4: (Roberts et al. 2010; Pratt and Moran 2010; Hristov \r\net al. 2013; Lee and Day 2013; Dickie et al. 2014a; Hawken 2017; Fuss \r\net al. 2018; Powell and Lenton 2012; Woolf et al. 2010)."


id: a1d6209173d932b23c6fe902c6a42dd3
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 23025
content:
"Conclusions from AR5 and IPCC Special Reports (SR1.5, \r\nSROCC and SRCCL); mitigation potential, costs, and pathways.\r\nThe SRCCL estimated the global technical mitigation potential of \r\nagroforestry, with medium confidence, to be between 0.08 and \r\n5.6 GtCO2-eq yr-1 by 2050 (Griscom et al. 2017; Dickie et al. 2014a; \r\nZomer et al. 2016; Hawken 2017). Estimates are derived from \r\nsyntheses of potential area available for various agroforestry systems, \r\nfor example, windbreaks, farmer managed natural regeneration, and \r\nalley cropping and average annual rates of carbon accumulation. The \r\ncost-effective economic potential, also with medium confidence, is \r\nmore limited at 0.3-2.4 GtCO2-eq yr-1 (Zomer et al. 2016; Griscom \r\net al. 2017; Roe et al. 2019). Despite this potential, agroforestry is \r\ncurrently not considered in integrated assessment models used for \r\nmitigation pathways (Section 7.5)."


id: d0c819948a35a5cd90f066b201e6da2d
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 30380
content:
"Developments since AR5 and IPCC Special Reports (SR1.5, SROCC \r\nand SRCCL). Updated estimates of agroforestry's technical mitigation \r\npotential and synthesised estimates of carbon sequestration across \r\nagroforestry systems have since been published. The most recent global \r\nanalysis estimates technical potential of 9.4 GtCO2-eq yr-1 (Chapman \r\net al. 2020) of agroforestry on 1.87 and 1.89 billion ha of crop and \r\npasture lands below median carbon content, respectively. This estimate \r\nis at least 68% greater than the largest estimate reported in the SRCCL \r\n(Hawken 2017) and represents a  new conservative upper bound as \r\nChapman et al. (2020) only accounted for above-ground carbon. \r\nConsidering both above- and below-ground carbon of windbreaks, \r\nalley cropping and silvopastoral systems at a  more limited areal \r\nextent (Griscom et al. 2020), the economic potential of agroforestry "


id: d425928fec1a43b3591f48024e1d8461
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 30894
content:
"Critical assessment and conclusion. Biochar has significant \r\nmitigation potential through CDR and emissions reduction, and can \r\nalso improve soil properties, enhancing productivity and resilience \r\nto climate change (medium agreement, robust evidence). There \r\nis medium evidence that biochar has a  technical potential of \r\n2.6 (0.2-6.6) GtCO2-eq yr-1, of which 1.1 (0.3-1.8) GtCO2-eq yr-1 is \r\navailable up to USD100 tCO2\r\n-1. However, mitigation and agronomic \r\nco-benefits depend strongly on biochar properties and the soil to \r\nwhich biochar is applied (strong agreement, robust evidence). While \r\nbiochar could provide moderate to large mitigation potential, it is not \r\nyet included in IAMs, which has restricted comparison and integration \r\nwith other CDR strategies."


id: 78084c58e8e8d721a3c731b9acd3327f
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 16449
content:
"health, regarding infiltration and structural stability (Muchane et al. \r\n2020); reduces ambient temperatures and crop heat stress (Arenas\u0002Corraliza et al. 2018; Sida et al. 2018); increases groundwater \r\nrecharge in drylands when managed at moderate density (Ilstedt \r\net al. 2016; Bargues-Tobella et al. 2020); positively influences human \r\nhealth (Rosenstock et al. 2019); and can improve dietary diversity \r\n(McMullin et al. 2019). Along with previously mentioned barriers, low \r\nsocial capital, assets, and labour availability have been identified as \r\npertinent to adoption. Practically all barriers are interdependent and \r\nsubject to the context of implementation."


id: da3a1e371e91514c51f54c6b40f3939b
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 31857
content:
"was estimated to be only about 0.8 GtCO2-eq yr-1. Variation in \r\nestimates primarily result from assumptions on the agroforestry \r\nsystems including, extent of implementation and estimated carbon \r\nsequestration potential when converting to agroforestry."


id: b7cbbf0ab97dc65efdb6590c0480969d
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 26451
content:
"Critical assessment and conclusion. There is medium \r\nconfidence that agroforestry has a  technical potential of \r\n4.1  (0.3-9.4) GtCO2-eq yr-1 for the period 2020-2050, of which \r\n0.8 (0.4-1.1) GtCO2-eq yr-1 is available at USD100 tCO2\r\n-1. Despite \r\nuncertainty around global estimates due to regional preferences \r\nfor management systems, suitable land availability, and growing \r\nconditions, there is high confidence in agroforestry's mitigation \r\npotential at the field scale. With countless options for farmers and land \r\nmanagers to implement agroforestry, there is medium confidence in \r\nthe feasibility of achieving estimated regional mitigation potential. \r\nAppropriately matching agroforestry options, to local biophysical \r\nand social contexts is important in maximising mitigation and co\u0002benefits, while avoiding risks (Sinclair and Coe 2019)."


id: 28d786efb2df34d289121cbf65ffe0b7
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 3860
content:
"Recent research has also highlighted co-benefits and more precisely \r\nidentified implementation barriers. In addition to aforementioned \r\nco-benefits, evidence now shows that agroforestry can improve soil "


id: bc0602c74f8fb9536e52ffbf8f0769aa
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 27146
content:
"Brazilian farmers are integrating trees into their croplands in various ways, ranging from simple to highly complex agroforestry \r\nsystems. While complex systems are more effective in the mitigation of climate change, trade-offs with scalability need to be resolved \r\nfor agroforestry systems to deliver on their potential. The Brazilian-Dutch CANOPIES project (Janssen 2020) is exploring transition \r\npathways to agroforestry systems optimised for local ecological and socio-economic conditions."


id: 670a2612c5e3bff42e7074f8c9766fdf
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content:
"The climate change mitigation potential of agroforestry systems is widely recognised (Zomer et al. 2016; FAO 2017b) and Brazilian \r\nfarmers and researchers are pioneering diverse ways of integrating trees into croplands, from planting rows of eucalyptus trees in \r\npastures up to highly complex agroforests consisting of >30 crop and tree species. The degree of complexity influences the multiple \r\nfunctions that farmers and societies can attain from agroforestry: the more complex it is, the more it resembles a natural forest with \r\nassociated benefits for its carbon storage capacity and its habitat quality for biodiversity (Santos et al. 2019). However, trade-offs \r\nexist between the complexity and scalability of agroforestry as complex systems rely on intensive manual labour to achieve high \r\nproductivity (Tscharntke et al. 2011). To date, mechanisation of structurally diverse agroforests is scarce and hence, efficiencies of \r\nscale are difficult to achieve."


id: 503077cc31031065265ebc13d1f120f0
created_at: 2023-03-16 14:01:37
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"These synergies and trade-offs between complexity, multifunctionality and scalability are studied in the CANOPIES (Co-existence of \r\nAgriculture and Nature: Optimisation and Planning of Integrated Ecosystem Services) project, a collaboration between Wageningen \r\nUniversity (NL), the University of Sao Paulo and EMBRAPA (both Brazil). Soil and management data are collected on farms of varying \r\ncomplexity to evaluate carbon sequestration and other ecosystem services, economic performance and labour demands."


id: f36da2fb2ef0cba3897ddd1fbdcd9fac
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 35807
content:
"The trade-off between complexity and labour demand is less pronounced in EMBRAPA's integrated crop-livestock-forestry (ICLF) \r\nsystems, where grains and pasture are planted between widely spaced tree rows. Here, barriers for implementation relate mostly to \r\nlivestock and grain farmers' lack of knowledge on forestry management and financing mechanisms5\r\n (Gil et al. 2015). Additionally, linking \r\nthese financing mechanisms to carbon sequestration remains a Monitoring, Reporting and Verification challenge (Smith et al. 2020b)."


id: 6aea2a9227e11ddafd5678102b9f5aad
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 14440
content:
"Lessons\r\nSuccessful examples of how more complex agroforestry can be upscaled do exist in Brazil. For example, on farm trials and consistent \r\ninvestments over several years have enabled Rizoma Agro to develop a citrus production system that integrates commercial and \r\nnative trees in a large-scale multi-layered agroforestry system. The success of their transition resulted in part from their corporate \r\nstructure that allowed them to tap into the certified Green Bonds market (CBI 2020). However, different transition strategies need to \r\nbe developed for family farmers and their distinct socio-economic conditions."


id: d113e239eed88f959ad513cd670ed03d
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 30435
content:
"Conclusions from AR5 and IPCC Special Reports (SR1.5, SROCC \r\nand SRCCL); mitigation potential, costs, and pathways. The AR5 \r\nindicated medium (5-15%) technical mitigation potential from both \r\nfeeding and breeding related measures (Smith et al. 2014). More \r\nrecently, the SRCCL estimated with medium confidence, a  global \r\npotential of 0.12-1.18 GtCO2-eq yr-1 between 2020 and 2050, with \r\nthe range reflecting technical, economic and sustainability constraints \r\n(SRCCL, Chapter 2: Hristov et al. 2013; Dickie et al. 2014a; Herrero \r\net al. 2016; Griscom et al. 2017). The underlying literature used \r\na  mixture of IPCC GWP100 values for CH4, preventing conversion \r\nof CO2-eq to CH4. Improved livestock feeding and breeding were \r\nincluded in IAM emission pathway scenarios within the SRCCL and \r\nSR1.5, although it was suggested that the full mitigation potential of \r\nenteric CH4 measures is not captured in current models (Rogelj et al. \r\n2018b; IPCC 2018)."


id: 9840a3e3e7ca650b1573e90c0e0ec70a
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 21466
content:
"Developments since AR5 and IPCC Special Reports (SR1.5, \r\nSROCC and SRCCL). Recent reviews generally identify the same \r\nmeasures as those outlined in the SRCCL, with the addition of early \r\nlife manipulation of the ruminal biome (Grossi et al. 2019; Eckard \r\nand Clark 2020; Thompson and Rowntree 2020; Beauchemin \r\net al. 2020; Ku-Vera et al. 2020; Honan et al. 2021). There is \r\nrobust evidence and high agreement that chemically synthesised \r\ninhibitors are promising emerging near-term measures (Patra 2016; \r\nJayanegara et al. 2018; Van Wesemael et al. 2019; Beauchemin et al. "


id: 170e4290e0b3a4f75ac6b2e966f4c72a
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 1147
content:
"Critical review and conclusion. Based on studies to date, \r\nusing a  range of IPCC GWP100 values for CH4, there is medium \r\nconfidence that activities to reduce enteric CH4 emissions have \r\na global technical potential of 0.8 (0.2-1.2) GtCO2-eq yr-1, of which \r\n0.2 (0.1-0.3) GtCO2-eq yr-1 is available up to USD100 tCO2-eq-1\r\n(Figure 7.11). The CO2-eq value may also slightly differ if the GWP100 \r\nIPCC AR6 CH4 value was uniformly applied within calculations. Lack \r\nof comparable country and sub-sector studies to assess the context \r\napplicability of measures, associated costs and realistic adoption \r\nlikelihood, prevents verification of estimates."


id: 995d0cc77d55ac3485e6f23210c350a
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 21646
content:
"Conclusions from AR5 and IPCC Special Reports (SR1.5, SROCC \r\nand SRCCL); mitigation potential, costs, and pathways. The AR5 \r\noutlined emissions from rice cultivation of 0.49-0.723 GtCO2-eq yr-1\r\nin 2010 with an average annual growth of 0.4% yr-1. The SRCCL \r\nestimated a global mitigation potential from improved rice cultivation \r\nof 0.08-0.87 GtCO2-eq yr-1 between 2020 and 2050, with the \r\nrange representing the difference between technical and economic \r\nconstraints, types of activities included (e.g.,  improved water \r\nmanagement and straw residue management) and GHGs considered \r\n(Dickie et al. 2014a; Beach et al. 2015; Paustian et al. 2016; Griscom \r\net al. 2017; Hawken 2017) (SRCCL, Chapter 2)."


id: e32f0ed52bb3407fdadc7147c82626b0
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 33238
content:
"Critical assessment and conclusion. There is medium confidence\r\nthat improved rice management has a  technical potential of \r\n0.3  (0.1-0.8) GtCO2-eq yr-1 between 2020 and 2050, of which \r\n0.2 (0.05-0.3) GtCO2-eq yr-1 is available up to USD100 tCO2-eq-1\r\n(Figure 7.11). Improving rice cultivation practices will not only reduce \r\nGHG emissions, but also improve production sustainability in terms \r\nof resource utilisation including water consumption and fertiliser \r\napplication. However, emission reductions show high variability and \r\nare dependent on site specific conditions and cultivation practices."


id: 14831430093c815306a9420ad79b24b8
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 738
content:
"Critical assessment and conclusion. There is medium confidence\r\nthat crop nutrient management has a  technical potential of \r\n0.3 (0.06-0.7) GtCO2-eq yr-1 of which 0.2 (0.05-0.6) GtCO2-eq yr-1\r\nis available up to USD100 tCO2-eq-1. This value is based on GWP100 \r\nusing a  mixture of IPCC values for N2O and may slightly differ if \r\ncalculated using AR6 values. The development of national roadmaps \r\nfor sustainable fertiliser (nutrient) management can help in scaling\u0002up related practices and in realising this potential. Crop nutrient \r\nmanagement measures can contribute not only to mitigation, but food \r\nand nutrition security and wider environmental sustainability goals."


id: ef3b6b69aadba3bc224cc4e83276a66c
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 35108
content:
"A potential risk under certain circumstances, is yield reduction, while \r\nimplementation of practices should consider current soil nutrient \r\nstatus. There are significant regional imbalances, with some regions \r\nexperiencing nutrient surpluses from over fertilisation and others, \r\nnutrient shortages and chronic deficiencies (FAO 2021e). Additionally, \r\ndepending on context, practices may be inaccessible, expensive or \r\nrequire expertise to implement (Hedley 2015; Benson and Mogues \r\n2018) while impacts of climate change may influence nutrient use \r\nefficiency (Amouzou et al. 2019) and therefore, mitigation potential."


id: 9febea2a0dbfa2e7f65339845f5cb957
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 22695
content:
"Conclusions from AR5 and IPCC Special Reports (SR1.5, SROCC \r\nand SRCCL); mitigation potential, costs, and pathways. The \r\nSRCCL broadly identified the same practices as outlined in AR5 \r\nand estimated that improved cropland nutrient management could \r\nmitigate between 0.03 and 0.71 GtCO2-eq yr-1 between 2020 and \r\n2050 (SRCCL Chapter  2) (Dickie et al. 2014a; Beach et al. 2015; \r\nPaustian et al. 2016; Griscom et al. 2017; Hawken 2017)."


id: 9eff2f61ad6ce98c99d8ad442bcfa005
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 22558
content:
"The climate-smart villages (CSV) approach aims to generate local knowledge, with the involvement of farmers, researchers, practitioners, \r\nand governments, on climate change adaptation and mitigation while improving productivity, food security, and farmers' livelihoods \r\n(Aggarwal et al. 2018). This knowledge feeds a global network that includes 36 climate-smart villages in South and South-East Asia, \r\nWest and East Africa, and Latin America."


id: ba1ed1e98e30bb01b04af36d50a586b3
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 26824
content:
"It is expected that agricultural production systems across the world will change in response to climate change, posing significant \r\nchallenges to the livelihoods and food security of millions of people (Kennedy et al. 2014). Maintaining agricultural growth while \r\nminimising climate shocks is crucial to building a resilient food production system and meeting sustainable development goals in \r\nvulnerable countries."


id: e9bb8818a13fc4e73839de533c11a168
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 34271
content:
"The CSV approach seeks an integrated vision so that sustainable rural development is the final goal for rural communities. At the \r\nsame time, it fosters the understanding of climate change with the implementation of adaptation and mitigation actions, as much as \r\npossible. Rural communities and local stakeholders are the leaders of this process, where scientists facilitate their knowledge to be \r\nuseful for the communities and learn at the same time about challenges but also the capacity those communities have built through \r\ntime. The portfolio includes weather-smart activities, water-smart practices, seed/breed smart, carbon-/nutrient-smart practices, and \r\ninstitutional-/market-smart activities."


id: fa2094d3fbf81cd331fadbc5616545af
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 36870
content:
"The integration of technologies and services that are suitable for the local conditions resulted in many gains for food security and \r\nadaptation and for mitigation where appropriate. It was also shown that, in all regions, there is considerable yield advantage when \r\na portfolio of technologies is used, rather than the isolated use of technologies (Govaerts et al. 2005; Zougmore et al. 2014). Moreover, \r\nfarmers are using research results to promote their products as climate-smart leading to increases in their income (Acosta-Alba\r\net al. 2019). However, climatic risk sites and socio-economic conditions together with a lack of resource availability are key issues \r\nconstraining agriculture across all five regions."


id: fb1eb01844e6702de773756a0df8972f
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 37018
content:
"The assessment of the implementation of the CSA options should be done together with community leaders to understand changes \r\nin livelihoods and climate vulnerability. Also, knowledge appropriation by community leaders has led to farmer-to-farmer knowledge \r\nexchange within and outside the community (Ortega Fernandez and Martinez-Baron 2018)."


id: e157faa0788bc339bf94742c7418ca21
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 32946
content:
"(iv) improved storage and application practices, (v) grazing practices \r\nand (vi) alteration of livestock diets to reduce nitrogen excretion \r\n(Mbow et al. 2019; Jia et al. 2019). Implementation of manure \r\nmanagement with other livestock and soil management measures \r\ncan enhance system resilience, sustainability, food security and help \r\nprevent land degradation (Smith et al. 2014; Mbow et al. 2019; \r\nP.  Smith et al. 2019a), while potentially benefiting the localised \r\nenvironment, for example, regarding water quality (Di and Cameron \r\n2016). Risks include increased N2O emission from the application "


id: d76742dd1a51cc0de3d8b141e1abe50f
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 31410
content:
"Activities, co-benefits, risks and implementation opportunities \r\nand barriers. Manure management measures aim to mitigate CH4\r\nand N2O emissions from manure storage and deposition. Mitigation \r\nof N2O considers both direct and indirect (i.e., conversion of ammonia \r\nand nitrate to N2O) sources. According to the SRCCL, measures may \r\ninclude (i) anaerobic digestion, (ii) applying nitrification or urease \r\ninhibitors to stored manure or urine patches, (iii) composting, "


id: 327471f151f140fddb099ce08f5797f9
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 5351
content:
"of manure to poorly drained or wet soils, trade-offs between N2O \r\nand ammonia emissions and potential eco-toxicity associated with \r\nsome measures."


id: f37441d2774c5f351a539991956b8517
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 35813
content:
"restricted in some jurisdictions due to concerns regarding residues \r\nin food products (Di  and Cameron 2016; Eckard and Clark 2020) \r\nwhile limited evidence suggests eco-toxicity risk under certain \r\ncircumstances (Kosler et al. 2019). Some forage crops may naturally \r\ncontain inhibitory substances (Simon et al. 2019, 2020; de Klein et al. \r\n2020), though this warrants further research (Podolyan et al. 2020; \r\nGardiner et al. 2020)."


id: 42f06a53a4999b26c11b480529f6f9fb
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 7925
content:
"Conclusions from AR5 and IPCC Special Reports (SR1.5, SROCC \r\nand SRCCL); mitigation potential, costs, and pathways. The\r\nAR5 reported manure measures to have high (>10%) mitigation \r\npotential. The SRCCL estimated a  technical global mitigation \r\npotential between 2020 and 2050 of 0.01-0.26 GtCO2-eq yr-1, with \r\nthe range depending on economic and sustainable capacity (Dickie \r\net al. 2014a; Herrero et al. 2016) (SRCCL, Chapter 2). Conversion of \r\nestimates to native units is restricted as a mixture of GWP100 values \r\nwas used in underlying studies. Measures considered were typically \r\nmore suited to confined production systems (Jia et al. 2019; Mbow \r\net al. 2019), while improved manure management is included within \r\nIAM emission pathways (Rogelj et al. 2018b)."


id: ab8ab194deefd4d76078b543447a1310
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 24507
content:
"Critical assessment and conclusion. There is medium confidence\r\nthat manure management measures have a global technical potential \r\nof 0.3 (0.1-0.5) GtCO2-eq yr-1, (using a range of IPCC GWP100 values \r\nfor CH4 and N2O), of which 0.1 (0.09-0.1) GtCO2-eq yr-1 is available \r\nat up to USD100 tCO2-eq-1 (Figure  7.11). As with other non-CO2\r\nGHG mitigation estimates, values may slightly differ depending upon \r\nwhich IPCC GWP100 values were used. There is robust evidence and\r\nhigh agreement that there are measures that can be applied in all \r\nregions, but greatest mitigation potential is estimated in Developed \r\nCountries in more intensive and confined production systems."


id: 2b7d71a9cbf4a1ba3b9fb14ba880f473
created_at: 2023-03-16 14:01:37
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content:
"Box 7.5, Figure 1 | Potential mitigation mechanisms and associated management practices. N = nitrogen, SOM = soil organic matter, LUC = land-use \r\nchange. a The farming system approaches outlined are not necessarily mutually exclusive. b Only agricultural emissions are considered. Mitigation may also result from \r\nreduced production of fertilisers and agrochemicals. c Reduced emissions intensity per unit of milk/meat will only result in a reduction in absolute emissions where \r\nincreased productivity facilitates a reduction in animal numbers. 1 = Altieri et al. 2015; 2 = Altieri and Nicholls 2017; 3 = Powlson et al. 2016; 4 = Corbeels et al. \r\n2019; 5 = Lal 2015; 6 = Gonzalez-Sanchez et al. 2019; 7 = Thierfelder et al. 2017; 8 = Hendrickson et al. 2008; 9 = Weindl et al. 2015; 10 = Thornton and Herrero \r\n2015; 11 = Lal al. 2020; 12 = Scialabba and Muller-Lindenlauf 2010; 13 = Goh 2011; 14 = IFOAM 2016."


id: d48375f43764e470c25985c8f9abeb6a
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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content:
"The SRCCL noted both positive and inconclusive results regarding CA and soil carbon, with sustained sequestration dependent on \r\nproductivity and residue returns (Jia et al. 2019; Mirzabaev et al. 2019; Mbow et al. 2019). Recent research is in broad agreement \r\n(Ogle et al. 2019; Corbeels et al. 2020, 2019; Gonzalez-Sanchez et al. 2019; Munkholm et al. 2020) with greatest mitigation potential \r\nsuggested in dry regions (Sun et al. 2020). Theoretically, CA may facilitate improved nitrogen use efficiency (limited evidence) (Lal \r\n2015; Powlson et al. 2016), though CA appears to have mixed effects on soil N2O emission (Six et al. 2004; Mei et al. 2018). CA is \r\nnoted for its adaptation benefits, with wide agreement that CA can enhance system resilience to climate related stress, notably in dry \r\nregions. There is evidence that CA can contribute to mitigation, but its contribution is depended on multiple factors including climate \r\nand residue returns (high confidence)."


id: 9b2e5d10045b0c3e746c05fc6e2f6890
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content:
"The integration of different enterprises in space and time (e.g., diversified cropping, crop and livestock production, agroforestry), \r\ntherefore facilitating interaction and transfer of recourses between systems, is suggested to enhance sustainability and adaptive \r\ncapacity (Hendrickson et al. 2008; Franzluebbers et al. 2014; Lemaire et al. 2014; Weindl et al. 2015; Gil et al. 2017; Olsson et al. 2019; \r\nPeterson et al. 2020; Walkup et al. 2020; Garrett et al. 2020). Research indicates some mitigation potential, including by facilitating \r\nsustainable intensification (Box 7.11), though benefits are likely to be highly context specific (Herrero et al. 2013; Carvalho et al. 2014; \r\nPiva et al. 2014; de Figueiredo et al. 2017; Rosenstock et al. 2014; Weindl et al. 2015; Thornton and Herrero 2015; Descheemaeker et al. \r\n2016; Lal 2020; Guenet et al. 2021). The other systems outlined within this Box may form or facilitate IPS."


id: a74f9dd4132716fa72230921ce24a549
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 23836
content:
"To assess the technical mitigation potentials of Indian agriculture and costs under a business as usual scenario (BAU) and Mitigation \r\nscenario up to 2030 (Sapkota et al. 2019)."


id: bd8138abca76cb96f7a4696d661dc2c9
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 27382
content:
"combined with carbon capture and storage (BECCS) and biochar \r\nproduction, bioenergy systems may provide CDR by durably storing \r\nbiogenic carbon in geological, terrestrial, or ocean reservoirs, or \r\nin products, further contributing to mitigation (Chum et al. 2011; \r\nCabral et al. 2019; Hammar and Levihn 2020; Emenike et al. 2020; \r\nMoreira et al. 2020b; Y. Wang et al. 2020: Johnsson et al. 2020) \r\n(Section 7.4.3.2, Chapters 3, 4, 6 and 12)."


id: 794c1a4b3cfcee6ce8b10d87142c3fa
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 16649
content:
"Activities, co-benefits, risks and implementation \r\nopportunities and barriers. Bioenergy refers to energy products \r\n(solid, liquid and gaseous fuels, electricity, heat) derived from \r\nmultiple biomass sources including organic waste, harvest residues \r\nand by-flows in the agriculture and forestry sectors, and biomass \r\nfrom tree plantations, agroforestry systems, lignocellulosic crops, \r\nand conventional food/feed crops. It may reduce net GHG emissions \r\nby displacing the use of coal, oil and natural gas with renewable \r\nbiomass in the production of heat, electricity, and fuels. When "


id: 727cf67a3191646d9fb2f1756af8e6c7
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 15632
content:
"This section addresses especially aspects related to land use and \r\nbiomass supply for bioenergy and BECCS. The mitigation potential \r\npresented here and in Table 7.3, includes only the CDR component of "


id: eac309339be76fa342c39fbcfc4d4e48
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 34438
content:
"BECCS. The additional mitigation achieved from displacing fossil fuels \r\nis covered elsewhere (Chapters 6, 8, 9, 10, 11 and 12)."


id: 46c0dbc3f9b472b9eaf10314645a0f86
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 8518
content:
"Modern bioenergy systems (as opposed to traditional use of fuelwood \r\nand other low-quality cooking and heating fuels) currently provide \r\napproximately 30 EJ yr-1 of primary energy, making up 53% of total \r\nrenewable primary energy supply (IEA 2019). Bioenergy systems \r\nare commonly integrated within forest and agriculture systems that \r\nproduce food, feed, lumber, paper and other bio-based products. \r\nThey can also be combined with other AFOLU mitigation options: \r\ndeployment of energy crops, agroforestry and A/R can provide \r\nbiomass while increasing land carbon stocks (Sections 7.4.2.2 and \r\n7.4.3.3) and anaerobic digestion of manure and wastewater, to \r\nreduce methane emissions, can produce biogas and CO2 for storage \r\n(Section 7.4.3.7). But ill-deployment of energy crops can also cause \r\nland carbon losses (Hanssen et al. 2020) and increased biomass \r\ndemand for energy could hamper other mitigation measures such as \r\nreduced deforestation and degradation (Sections 7.4.2.1)."


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content:
"Developments since AR5 and IPCC Special Reports (SR1.5, \r\nSROCC and SRCCL). The role of bioenergy and BECCS in mitigation \r\npathways has been reduced as IAM-based studies have incorporated \r\nbroader mitigation portfolios and have explored non-CO2 emissions \r\nreduction and a  wider variation of underlying assumptions about \r\nsocio-economic drivers and associated energy and food demand, \r\nas well as deployment limits such as land availability for A/R and \r\nfor cultivation of crops used for bioenergy and BECCS (Grubler et al. \r\n2018; Van Vuuren et al. 2018)."


id: 8438b61a61309e0d6d502c04e9af5a9c
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
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vector_id: 18338
content:
"Conclusions from AR5 and IPCC Special Reports (SR1.5, SROCC \r\nand SRCCL); mitigation potential, costs, and pathways. Many \r\nmore stringent mitigation scenarios in AR5 relied heavily on bioenergy \r\nand BECCS. The SR1.5 reported a  range for the CDR potential of \r\nBECCS (2100) at 0.5 to 5 GtCO2-eq yr-1 when applying constraints \r\nreflecting sustainability concerns, at a cost of 100-200 USD tCO2\r\n-1\r\n(Fuss et al. 2018). The SRCCL reported a technical CDR potential for \r\nBECCS at 0.4-11.3 GtCO2 yr-1 (medium confidence), noting that \r\nmost estimates do not include socio-economic barriers, the impacts \r\nof future climate change, or non-GHG climate forcing (IPCC. 2019). \r\nThe SR1.5 and SRCCL highlighted that bioenergy and BECCS can be "


id: 59e1aece9be4367320b1c679f7f7463d
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 11645
content:
"Box 7.7, Figure 1 shows emissions associated with biomass supply (residues and crops grown on cropland not needed for food) in \r\n2050, here designated emission-supply curves. The curves are constructed assuming that additional biomass supply consistently comes \r\nfrom the available land/biomass resource that has the lowest GHG emissions, for example, the marginal GHG emissions increase with \r\nincreasing biomass use for bioenergy. Net negative emissions indicate cases where biomass production increases land carbon stocks. "


id: 41dcb8cfd7cf384b5d1e3248487704ba
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 7764
content:
"Box 7.7, Figure 1 | Emissions associated with primary biomass supply in 2050 (residues and crops grown on cropland not needed for food), \r\nas determined from sectoral models (Daioglou et al. 2017; Kalt et al. 2020), and stylised scenarios from the EMF-33 project using Integrated \r\nAssessment Models (Rose et al. 2020). All methods include LUC (direct and indirect) emissions. Emissions associated with Natural Regrowth include counterfactual \r\ncarbon fluxes (see text). The sectoral models include a more detailed representation of the emissions, including lifecycle emissions from fertiliser production. IAM \r\nmodels may include economic feedbacks such as intensification as a result of increasing prices. As an indication: for natural gas the emission factor is around 56, for \r\ncoal around 95 kgCO2 GJ-1."


id: 9e833c7d4f6d60a4df20f9e214baedc6
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
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vector_id: 22474
content:
"One curve (EMF-33) is determined from stylised scenarios using IAMs (Rose et al. 2020). One of the two curves determined from \r\nsectoral models, Constant Land Cover, reflects supply chain emissions and changes in land carbon storage caused by the biomass \r\nsupply system itself. These two curves are obtained with modelling approaches compatible with the modelling protocol used for the \r\nscenarios in the AR6 database, which accounts for the land-use change and all other GHG emissions along a given transformation \r\ntrajectory, enabling assessments of the warming level incurred."


id: 28894e95ea1bbd6046fcd2f7582599a0
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 3797
content:
"The Natural Regrowth curve attribute additional 'counterfactual emissions' to the bioenergy system, corresponding to estimated \r\nuptake of CO2 in a counterfactual scenario where land is not used for bioenergy but instead subject to natural vegetation regrowth. \r\nThis curve does not show actual emissions from the bioenergy system, but it provides insights in the mitigation value of the bioenergy \r\noption compared to alternative land-use strategies. To illustrate, if biomass is used instead of a primary energy source with emission \r\nfactor 75 kgCO2 GJ-1, and the median values in the Natural Regrowth curve are adopted, then the curve indicates that up to about \r\n150 EJ of biomass can be produced and used for energy while achieving higher net GHG savings than the alternative to set aside the \r\nsame land for natural vegetation regrowth (assuming same conversion factor)."


id: a62602502d14bf9ec0316593856556e7
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 23684
content:
"The large ranges in the bars signify the importance of uncertainties and how the biomass is deployed. Variation in energy conversion \r\nefficiencies and uncertainty about magnitude, timing, and permanence of land carbon storage further complicate the comparison. \r\nFinally, not shown in Box 7.7, Figure 1, the emission-supply curves would be adjusted downwards if displacement of emission intensive \r\nenergy was included or if the bioenergy is combined with CCS to provide CDR."


id: 15f8af642435249f4f94af8ed1965ea2
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
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vector_id: 980
content:
"based products, providing climate change mitigation while enabling \r\nmultiple co-benefits including for nature conservation (Nabuurs \r\net al. 2017; Parodi et al. 2018; Springmann et al. 2018; Rosenzweig \r\net al. 2020; Clark et al. 2020; Favero et al. 2020; Hanssen et al. 2020) \r\n(Section 7.4 and Cross-Working Group Box 3 in Chapter 12)."


id: 5f2218787df6960d9ee69157d24a197
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 12521
content:
"Strategies to enhance the benefits of bioenergy and BECCS \r\ninclude (i)  management practices that protect carbon stocks and \r\nthe productive and adaptive capacity of lands, as well as their \r\nenvironmental and social functions (van Ittersum et al. 2013, Gerssen\u0002Gondelach et al. 2015; Moreira et al. 2020b) (ii) supply chains from \r\nprimary production to final consumption that are well managed and \r\ndeployed at appropriate levels (Fajardy et al. 2018; Donnison et al. \r\n2020); and (iii) development of a cross-sectoral agenda for bio-based \r\nproduction within a circular economy, and international cooperation \r\nand governance of global trade in products to maximise synergies \r\nwhile limiting trade-offs concerning environmental, economic \r\nand social outcomes (very high confidence). Finally, the technical \r\nfeasibility of BECCS depends on investments in and the roll-out of \r\nadvanced bioenergy technologies currently not widely available \r\n(Baker et al. 2015; Daioglou et al. 2020b)."


id: 9bad6933f9a4d9fa3842524a7648efb4
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 22052
content:
"Technical land availability does not imply that dedicated biomass \r\nproduction for bioenergy and BECCS is the most effective use of this \r\nland for mitigation. Further, implications of deployment for climate \r\nchange mitigation and other sustainability criteria are context \r\ndependent and influenced by many factors, including rate and total \r\nscale. While governance has a critical influence on outcome, larger \r\nscale and higher expansion rate generally translates into higher risk \r\nfor negative outcomes for GHG emissions, biodiversity, food security \r\nand a  range of other sustainability criteria (Searchinger 2017; \r\nVaughan et al. 2018; Rochedo et al. 2018; de Oliveira Garcia et al. \r\n2018; Daioglou et al. 2019; Junginger et al. 2019; Galik et al. 2020; \r\nStenzel et al. 2020)."


id: 2a959861933027e96b45e41964aaaaef
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 4126
content:
"Activities, co-benefits, risks and implementation opportunities \r\nand barriers. The term 'sustainable healthy diets' refers to dietary \r\npatterns that 'promote all dimensions of individuals' health and well\u0002being; have low environmental pressure and impact; are accessible, \r\naffordable, safe and equitable; and are culturally acceptable' \r\n(FAO and WHO 2019). In addition to climate mitigation gains, "


id: c59b631eb986497e80bfe5194ee74229
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 28670
content:
"for a vegan diet, of 0.01-1.5 for a vegetarian diet, and of 0.1-2.0 for \r\nMediterranean or similar healthy diet."


id: b1c733d73d3474745b40564a22278513
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 25468
content:
"Activities, co-benefits, risks and implementation opportunities \r\nand barriers. Food loss and waste (FLW) refer to the edible parts \r\nof plants and animals produced for human consumption that are \r\nnot ultimately consumed (UNEP 2021b). Food loss occurs through \r\nspoilage, spilling or other unintended consequences due to limitations \r\nin agricultural infrastructure, storage and packaging (Parfitt et al. "


id: 742c9654e988868eec46a1135499328d
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 15875
content:
"Critical assessment and conclusion. There is medium confidence \r\nthat reduced FLW has large global technical mitigation potential \r\nof 2.1 (0.1-5.8) GtCO2-eq yr-1 including savings in the full value \r\nchain and using GWP100 and a range of IPCC values for CH4 and \r\nN2O.  Potentials at 3.7 (2.2-5.1) GtCO2-eq yr-1 are considered \r\nplausible. When accounting for diverted agricultural production only, \r\nthe feasible potential is 0.5 (0.0-0.9) GtCO2-eq yr-1. See the section \r\nabove for the joint land-use effects of food related demand-side \r\nmeasures which increases three-fold when accounting for the land\u0002use effects as well. But this would overlap with other measures and is \r\ntherefore not additive. Regionally, FLW reduction is feasible anywhere \r\nbut its potential needs to be understood in a wider and changing \r\nsocio-cultural context that determines nutrition (high confidence)."


id: 37e6917cdb3dc27010c6566c3a6615e8
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 6169
content:
"Conclusions from AR5 and IPCC Special Reports (SR1.5, SROCC \r\nand SRCCL); mitigation potential, costs, and pathways. In AR5, \r\nreduced FLW was considered as a  mitigation measure that could \r\nsubstantially lower emissions, with estimated mitigation potential of \r\n0.6-6.0 GtCO2-eq yr-1 in the food supply chain (Smith et al. 2014). \r\nIn the SRCCL, the technical mitigation potential of reducing food \r\nand agricultural waste was estimated at 0.76-4.5 GtCO2-eq yr-1\r\n(Bajzelj et al. 2014; Dickie et al. 2014b; Hawken 2017) (SRCCL, \r\nChapter 2 and 6)."


id: 405509180a0f57e409054bdcf4c688f4
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 7504
content:
"Developments since AR5 and IPCC Special Reports (SR1.5, \r\nSROCC and SRCCL). Since the SRCCL, there have been very few \r\nquantitative estimates of the mitigation potential of FLW reductions. \r\nEvidence suggests that reducing FLW together with overall food \r\nintake could have substantial mitigation potential, equating to an \r\naverage of 0.3 tCO2-eq capita-1 (Ivanova et al. 2020). Some regional \r\nsectoral studies indicate that reducing FLW in the EU can reduce \r\nemissions by 186 MtCO2-eq yr-1, the equivalent of around 15% of the \r\nenvironmental impacts (climate, acidification, and eutrophication) \r\nof the entire food value chain (Scherhaufer et al. 2018). In the UK, \r\ndisruptive low-carbon innovations relating to FLW reduction were "


id: 1dfb865dba1b6b0a8acbc241fbacb5dc
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 2148
content:
"The benefits and risks of improved and enhanced improved use of \r\nwood products are closely linked to forest management. First of all, \r\nthe enhanced use of wood products could potentially activate or \r\nlead to improved sustainable forest management that can mitigate "


id: 1a5d3cc89e5566c85edffa33d7559b5e
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 1617
content:
"intensive and non-renewable materials (Sathre and O'Connor 2010; \r\nGeng et al. 2017; Leskinen et al. 2018)."


id: 9bdba5a9fde7f993d07423127a88eb78
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 22077
content:
"and adapt (Verkerk et al. 2020). Secondly, carbon storage in wood \r\nproducts and the potential for substitution effects can be increased \r\nby additional harvest, but with the risk of decreasing carbon storage \r\nin forest biomass when not done sustainably (P. Smith et al. 2019a). \r\nConversely, reduced harvest may lead to gains in carbon storage \r\nin forest ecosystems locally, but these gains may be offset through \r\ninternational trade of forest products causing increased harvesting \r\npressure or even degradation elsewhere (Kastner et al. 2011; Kallio \r\net al. 2018; Pendrill et al. 2019b). There are also environmental \r\nimpacts associated with the processing, manufacturing, use and \r\ndisposal of wood products (Adhikari and Ozarska 2018; Baumgartner \r\n2019). See Section 9.6.4 of this report for additional discussion on \r\nbenefits and risks."


id: 5ae9d49614209cda6e76a2248ca8e922
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 11817
content:
"Conclusions from AR5 and IPCC Special Reports (SR1.5, SROCC \r\nand SRCCL); mitigation potential, costs, and pathways. There \r\nis strong evidence at the product level that wood products from \r\nsustainably managed forests are associated with less greenhouse \r\nemissions in their production, use and disposal over their life-time \r\ncompared to products made from emission-intensive and non\u0002renewable materials. However, there is still limited understanding of \r\nthe substitution effects at the level of markets, countries (Leskinen \r\net al. 2018). The AR5 did not report on the mitigation potential of \r\nwood products. The SRCCL (Chapters 2 and 6) finds that some studies \r\nindicate significant mitigation potentials for material substitution, \r\nbut concludes that the global, technical mitigation potential for \r\nmaterial substitution for construction applications ranges from \r\n0.25-1 GtCO2-eq yr-1 (medium confidence) (Miner 2010; McLaren \r\n2012; Roe et al. 2019)."


id: 4fa511a967806eae41d05dd85d0a9898
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 9964
content:
"This section assesses the literature and data available on potential \r\nfuture GHG dynamics in the AFOLU sector, the cost-effectiveness of \r\ndifferent mitigation measures, and consequences of climate change \r\nmitigation pathways on land-use dynamics as well as relevant \r\nsustainable development indicators at the regional and global level \r\nbased on global integrated models."


id: 47cb354f0a1db637d6ae92d0ff63479
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 8672
content:
"The limited availability or absence of estimates of the future mitigation \r\npotential of improved use of wood products for many world regions \r\nrepresents an important knowledge gap, especially with regards to \r\nmaterial substitution effects. At the product level, wood products are \r\noften associated with lower fossil-based emissions from production, \r\nuse and disposal, compared to products made from emission\u0002"


id: a0bbf2f262207792681e3ac2b80fdbcb
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 22830
content:
"management (Humpenoder et al. 2020) which have the potential to \r\nalter the contribution of land-based mitigation in terms of timing, \r\npotential and sustainability consequences (Frank et al. 2017)."


id: 5e19984186269814634e905804964c51
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
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vector_id: 12332
content:
"Figure 7.14 | Regional change of major land cover types by 2050 (top) and 2100 (bottom) relative to 2020 for scenarios from the AR6 Database with \r\n<1.5degC (C1, C2), <2degC (C3, C4), <3degC (C5, C6) and <4degC (C7) global warming in 2100 (scenario type is indicated by colour). The data is summarised in boxplots \r\n(Tukey style), which show the median (vertical line), the interquartile range (IQR box) and the range of values within 1.5 x IQR at either end of the box (horizontal lines) across all \r\nmodels and scenarios. The number of data points available for each land cover type, scenario type, region and year is shown at the right edge of each panel. Regional definitions: \r\nAFRICA = sub-Saharan Africa, ASIA = Asia, LAM = Latin America and Caribbean, MID_EAST = Middle East, OECD90+EU = OECD 90 and EU, REF = Reforming Economies of \r\nEastern Europe and the Former Soviet Union."


id: bfa54ff7995cdf43006a35e87634b15c
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 27710
content:
"The overall land dynamics in <1.5degC, <2degC and <3degC mitigation \r\npathways are shaped by land-demanding mitigation options such \r\nas bioenergy and afforestation, in addition to the demand for other \r\nagricultural and forest commodities. Bioenergy production and \r\nafforestation take place largely in the (partly) tropical regions ASIA, \r\nLAM and AFRICA, but also in OECD90+EU. Land for dedicated second \r\ngeneration bioenergy crops and afforestation displace agricultural \r\nland for food production (cropland and pasture) and other natural \r\nland. For instance, in the <1.5degC mitigation pathway in ASIA, \r\nbioenergy and forest area together increased by about 2.1 million km2\r\nbetween 2020 and 2100, mostly at the cost of cropland and pasture \r\n(median values). Such large-scale transformations of land use have \r\nrepercussions on biogeochemical cycles (e.g.,  fertiliser and water) \r\nbut also on the economy (e.g.,  food prices) and potential socio\u0002political conditions."


id: f4e50d4a187178255fa6f57d712b74b4
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index: climate_gpt_only_giec
vector_id: 36037
content:
"production are almost exclusively caused by ASIA.  N2O emissions \r\nfrom animal waste management and soils are more equally \r\ndistributed across region."


id: 43647d35bbd237b1e288ae02ec081aa1
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 8011
content:
"In most regions, CH4 and N2O emission are both lower in mitigation \r\npathways that limit warming to 3degC (>50%) or lower (C1-C6) \r\ncompared to scenarios with <4degC (Popp et al. 2017; Rogelj et al. \r\n2018a). In particular, the reduction of CH4 emissions from enteric \r\nfermentation in ASIA and AFRICA is profound. Land-related CO2\r\nemissions, which include emissions from deforestation as well \r\nas removals from afforestation, are slightly negative (i.e., AFOLU \r\nsystems turn into a  sink) in <1.5degC, <2degC and <3degC mitigation \r\npathways compared to <4degC scenarios. Carbon sequestration via \r\nBECCS is most prominent in ASIA, LAM, AFRICA and OECD90+EU, \r\nwhich are also the regions with the highest bioenergy area."


id: 2b4e76129ee7d742d7383ea735efca51
created_at: 2023-03-16 14:01:37
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vector_id: 4251
content:
"Figure 7.14 indicates that regional land-use dynamics in scenarios with \r\n<4degC warming in 2100 are characterised by rather static agricultural \r\nland (i.e., cropland and pasture) in ASIA, LAM, OECD90+EU and \r\nREF, and increasing agricultural land in AFRICA.  Bioenergy area is \r\nrelatively small in all regions. Agricultural land in AFRICA expands at \r\nthe cost of forests and other natural land."


id: 98ab7d2a390e98909b4b59b35e6cdbe7
created_at: 2023-03-16 14:01:37
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content:
"potentials, scenarios are compared to a benchmark scenario which \r\nusually assumes business-as-usual trends and no explicit additional \r\nmitigation efforts. Scenarios have been excluded, if they do not have \r\nan associated benchmark scenario or fail the vetting according to the \r\nAR6 scenario database, or if they do not report carbon prices and CO2\r\nemissions from AFOLU. Scenarios with contradicting assumptions (for \r\nexample, fixing some of the emissions to baseline levels) are excluded. \r\nFurthermore, only scenarios with consistent3\r\n regional and global \r\nlevel results are considered. Mitigation potentials are computed by \r\nsubtracting scenario specific emissions and sequestration amounts \r\nfrom their respective benchmark scenario values. This difference "


id: cfb1a5bc899f429026b1655fbe1f0126
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 30211
content:
"the level of five world regions. This review provides a complementary \r\nview on the economic mitigation potentials estimated in Section 7.4 \r\nby implicitly taking into account the interlinkages between the land\u0002based mitigation options themselves as well as the interlinkages with \r\nmitigation options in the other sectors such as BECCS. The review \r\nsystematically evaluates a  range of possible economic potential \r\nestimates across gases, time, and carbon prices."


id: 3cd1e0dec688de5e265b2fc3022c9758
created_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 6936
content:
"For different models and scenarios from the AR6 database, \r\nthe amount of mitigated emissions is presented together with the \r\nrespective carbon price (Figure  7.15). To determine mitigation "


id: 63f7e47437a801f3e25cebda69645da3
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 13298
content:
"N2O emissions show the smallest economic potential of the \r\nthree different gases in 2030 as well as in 2050. The mitigation \r\npotential increases until a  price range of USD150-200 and to \r\na median value of around 0.6 GtCO2-eq yr-1 mitigation in 2030 and \r\n0.9 GtCO2-eq yr-1 in 2050, respectively, while afterwards with higher \r\nprices the expansion is very limited. Mitigation of CH4 emissions has \r\na  higher potential, also with increasing mitigation potentials until \r\na price range of USD150-200 in both years, with median mitigation \r\nof around 1.3 GtCO2-eq yr-1 in 2030 and around 2.4 GtCO2-eq yr-1\r\nin 2050, respectively. The highest mitigation potentials are observed \r\nfor CO2, but also the highest ranges of observations among the three \r\ngases. In 2030, a median of 4 GtCO2-eq yr-1 mitigation potential is \r\nreported for the price range of USD200-250. In 2050, for the carbon \r\nprice range of between USD100 and USD200, a median of around \r\n4.8 GtCO2-eq yr-1 can be observed."


id: 771e754d02054a3af22e9ab07d7d7075
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 16309
content:
"accounts for the mitigation that can be credited to the carbon price \r\nwhich is applied in a scenario. A few benchmark scenarios, however, \r\napply already low carbon prices. For consistency reasons, a carbon \r\nprice that is applied in a benchmark scenario is subtracted from the \r\nrespective scenario specific carbon price. This may generate a bias \r\nbecause low carbon prices tend to have a stronger marginal impact \r\non mitigation than high carbon prices. Scenarios with carbon prices \r\nwhich become negative due to the correction are not considered. The \r\nanalysis considers all scenarios from the AR6 database which pass \r\nthe criteria and should be considered as an ensemble of opportunity \r\n(Huppmann et al. 2018)."


id: e5681a02799c7e504055f2d5ec2f8b96
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content:
"Economic CO2 mitigation potentials from land-use change and forestry \r\nare larger compared to potentials from non-CO2 gases, and at the \r\nsame time reveal high levels of variation in absolute terms. The 66th \r\npercentile in 2050 goes up to 5.2 GtCO2-eq yr-1 mitigation, while \r\nthe lowest observations are even negative, indicating higher CO2\r\nemissions from land use in scenarios with carbon price compared to \r\nscenarios without (counterintuitive dynamics explained below)."


id: 964b30c3f6da83dccbfb65702030749b
created_at: 2023-03-16 14:01:37
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"In the individual cases, the accounting of all these effects is \r\ndependent on the respective underlying model and its coverage of \r\ninter-relations of different sectors and sub-sectors. The presented \r\npotentials cover a  wide range of models, and additionally, a  wide \r\nrange of background assumptions on macro-economic, technical, \r\nand behavioural developments as well as policies, which the models \r\nhave been fed with. Subsequently, the range of the resulting marginal \r\nabatement costs is relatively wide, showing the full range of expected \r\ncontributions from land-use sector mitigation and sequestration in \r\napplied mitigation pathways."


id: 3859a60cd59b6176d28f02eff7b5319
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 6240
content:
"Land use is at the centre of the interdependencies with other sectors, \r\nincluding energy. Some models see a  strong competition between \r\nBECCS deployment with its respective demand for biomass, and \r\nCO2 mitigation/sequestration potentials in the land sector. Biomass \r\ndemand may lead to an increase in CO2 emissions from land use \r\ndespite the application of a carbon price when land-use expansion \r\nfor dedicated biomass production, such as energy plantations, comes \r\nfrom carbon rich land use/land cover alternatives, or when increased \r\nextraction of biomass from existing land uses, such as forest \r\nmanagement, leads to reduction of the carbon sink (Daioglou 2019; \r\nLuderer et al. 2018) and can explain the high variety of observations \r\nin some cases. Overall, the large variety of observations shows a large \r\nvariety of plausible results, which can go back to different model \r\nstructures and assumptions, showing a  robust range of plausible \r\noutcomes (Kriegler et al. 2015)."


id: 51a373567563f54f77d754765621ebf2
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 10303
content:
"At the global level, the analysis of the economic mitigation potentials \r\nfrom N2O and CH4 emissions from AFOLU (which mainly can be related \r\nto agricultural activities) and CO2 emissions (which mainly can be \r\nrelated to LULUCF emissions) reveals a relatively good agreement of \r\nmodels and scenarios in terms of ranking between the gases. On the \r\nright-hand side panels of Figure 7.15, only small overlaps between \r\nthe ranges (showing the 10-90% intervals of observations) and \r\nmainly for lower price levels, can be observed, despite all differences \r\nin underlying model structure and scenario assumptions."


id: fb3baf486a77c339863d323ec2cddc7d
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 37035
content:
"forestry measures enhancing woody biomass supply for bioenergy may \r\nhave synergies with improving ecosystems conditions, many represent \r\na threat to biodiversity (Camia et al. 2020) (Sections 7.6.5 and 17.3.3.7, \r\nFigure 17.1 and Supplementary Material Table 17.SM.1)."


id: efeaea10b4eb9b8328dfa04601f9462c
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 35251
content:
"Besides the level of biomass supply for bioenergy, the adoption of \r\nSDGs may also significantly impact AFOLU emissions and the land\u0002use sector's ability for GHG abatement (Frank et al. 2021). Selected \r\nSDGs are found to have positive synergies for AFOLU GHG abatement \r\nand to consistently decrease GHG emissions for both agriculture and \r\nforestry, thereby allowing for even more rapid and deeper emissions \r\ncuts. In particular, the decreased consumption of animal products \r\nand less food waste (SDG 12), and the protection of high biodiversity \r\necosystems such as primary forests (SDG 15) deliver high synergies \r\nwith GHG abatement. On the other hand, protection of highly \r\nbiodiverse ecosystems from conversion (SDG 15) limits the global \r\nbiomass potentials for bioenergy (Frank et al. 2021), and while several "


id: a0dc0eb1c82c81cefc721f63d45f35e6
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 22856
content:
"At the regional level (Figure 7.16), the highest potential from non-CO2\r\nemissions abatement, and mostly from CH4, is reported for ASIA with \r\nthe median of mitigation potential observations from CH4 increasing \r\nup to a  price of USD200 in the year 2050, reaching a  median of \r\n1.2 GtCO2-eq yr-1. In terms of economic potential, ASIA is followed \r\nby LAM, AFRICA, and OECD+EU, where emission reduction mainly is \r\nachieved in the livestock sector."


id: 497e09c707f456b9b46e70d6165c731a
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 8951
content:
"Figure 7.16 | Regional mitigation efforts for CO2, CH4 and N2O emissions (in CO2-eq yr-1 using IPCC AR6 GWP100 values) from the AFOLU sector for \r\nincreasing carbon price levels for 2030 and 2050. Underlying datapoints are generated by comparing emissions between a policy scenario and a related benchmark \r\nscenario, mapping these differences with the respective carbon price differences. Boxplots show Medians (vertical line within the boxes), Means (dots), 33%-66% intervals \r\n(box) and 10%-90% intervals (horizontal lines) for respective scenarios of carbon prices implemented in intervals of USD50 from a price of USD0 to USD250. Regions: Asia \r\n(ASIA), Latin America and Caribbean (LAM), Middle East (MIDDLE_EAST), Africa (AFRICA), Developed Countries (OECD 90 and EU) (OECD+EU) and Reforming Economies of \r\nEastern Europe and the Former Soviet Union (REF)."


id: 1e7bc4c7548a63b65197abb31b529539
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 2238
content:
"The highest potentials from land-related CO2 emissions, including \r\navoided deforestation as well as afforestation, can be observed in \r\nLAM and AFRICA with strong responses of mitigation (indicated \r\nby the median value) to carbon prices mainly in the lower range \r\nof displayed carbon prices. In general, CO2 mitigation potentials \r\nshow a wide range of results in comparison to non-CO2 mitigation \r\npotentials, but mostly also a higher median value. The most extreme \r\nranges are reported for the regions LAM and AFRICA. A medium \r\npotential is reported for ASIA and OECD+EU, while REF has the \r\nsmallest potential according to model submissions. These estimates \r\nreflect techno-economic potentials and do not necessarily include \r\nfeasibility constraints which are discussed in Chapter 7.6."


id: aff1daa963ad7bef1b933e765375dfc6
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 25209
content:
"Different mitigation strategies can achieve the net emission reductions \r\nthat would be required to follow a pathway limiting global warming, \r\nwith very different consequences for the land system. Figure  7.17 \r\nshows Illustrative Mitigation Pathways (IMPs) for achieving different \r\nclimate targets highlighting AFOLU mitigation strategies, resulting \r\nGHG and land-use dynamics as well as the interaction with other \r\nsectors. For consistency this chapter discusses IMPs as described in \r\ndetail in chapters 1 and 3 of this report but focusing on the land-use \r\nsector. All pathways are assessed by different IAM realisations and do \r\nnot only reduce GHG emissions but also use CDR options, whereas "


id: 8da76a088700a120e93942c4f602ac64
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 19812
content:
"the amount and timing varies across pathways, as do the relative \r\ncontributions of different land-based CDR options."


id: 151d022e223372d53c00f622239ba4e3
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 833
content:
"Following COP 13 in Bali, effort shifted to advancing policies to \r\nreduce deforestation and forest degradation (REDD+) in developing \r\ncountries. According to Simonet et al. (2019), nearly 65 Mha have \r\nbeen enrolled in REDD+ type programmes or projects funded \r\nthrough a variety of sources, including United Nations Programme \r\non Reducing Emissions from Deforestation and Forest Degradation \r\n(UN-REDD), the World Bank Forest Carbon Partnership Facility, and \r\nbi-lateral agreements between countries with Norway being the \r\nlargest donor. While there has been considerable focus on forest and "


id: 8bf598afd6115bcd92831d38068fcfba
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 19537
content:
"IMP-Ren is similar to IMP Neg-2.0 in terms of socio-economic \r\nsetting (SSP2) but differs substantially in terms of mitigation target \r\nand mitigation efforts in the energy sector. Even under the more \r\nambitious climate change mitigation target (1.5degC with no or low \r\novershoot (OS), C1), the high share of renewable energy in IMP Ren\r\nstrongly reduces the need for large-scale land-based CDR, which is \r\nreflected in smaller bioenergy and afforestation areas compared to \r\nIMP Neg-2.0. However, CH4 and N2O emissions from AFOLU persist \r\nthroughout the century, similar to ModAct scenario and IMP Neg-2.0."


id: f6aecf1e4f775fce6ca1c2a2e9e78aef
created_at: 2023-03-16 14:01:37
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vector_id: 36327
content:
"agricultural project-based mitigation actions, national governments \r\nwere encouraged to incorporate project-based approaches with other \r\nsectoral strategies in their Nationally Appropriate Mitigation Actions \r\n(NAMAs) after 2012. NAMAs reflect the country's proposed strategy \r\nto reduce net emissions across various sectors within their economy \r\n(e.g.,  forests or agriculture). More recently, Nationally Determined \r\nContributions (NDCs) indicate whether individual countries plan to \r\nuse forestry and agricultural policies or related projects amongst a set \r\nof measures in other sectors, to reduce their net emissions as part of \r\nthe Paris Agreement (e.g., Forsell et al. 2016; Fyson and Jeffery 2019)."


id: 55e7498211bbea062a8739ceb632089f
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
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vector_id: 10999
content:
"voluntary offset markets (Hamrick and Gallant 2017a). Although \r\nAFOLU measures have been deployed across a range of projects and \r\nprogrammes globally to reduce net carbon emissions, debate about \r\nthe net carbon benefits of some projects continues (e.g., Krug 2018)."


id: 50b239219c67cfc1430c0ff1858bc865
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 10139
content:
"A new assessment of projects over the last two decades finds \r\nemission reductions or offsets of at least 7.9 GtCO2-eq (using \r\nGWP100 and a mix of IPCC values for CH4 and N2O) over the last 12 \r\nyears due to agricultural and forestry activities (Table 7.4). More than \r\n80% of these emission reductions or offsets have been generated \r\nby forest-based activities. The total amounts to 0.66 GtCO2 yr-1 for \r\nthe period 2010-2019, which is 1.2% of total global, and 5.5% of \r\nAFOLU emissions reported in Table 7.1, over the same time period \r\n(high confidence)."


id: 994630d9dcebb393f8c3672b15b5568c
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 21628
content:
"The many protocols now available can be used to quantify the \r\npotential mitigation to date resulting from various projects or \r\nprograms. For instance, carbon registries issue credits using protocols \r\nthat typically account for additionality, permanence and leakage, thus \r\nproviding evidence that the projects are a net carbon benefit to the \r\natmosphere. Protocol development engages the scientific community, \r\nproject developers, and the public over a  multi-year period. Some \r\nprotocols have been revised multiple times, such as the USA State of \r\nCalifornia's forest carbon protocol, which is in its fifth revision, with \r\nthe latest in 2019 (see http://www.climateactionreserve.org/how/\r\nprotocols/forest/). Credits from carbon registries feed into regulatory \r\nprograms, such as the cap and trade programme in California, or "


id: 8bf608570b2724b13beda4ba111641a5
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 19538
content:
"The array of activities in Table 7.4 includes the Clean Development \r\nMechanism, REDD+ activities reported in technical annexes of \r\ncountry biennial update reports to the UNFCCC, voluntary market \r\ntransactions, and carbon stored as a  result of carbon markets in \r\nAustralia, New Zealand and California in the USA. Although other \r\ncountries and sub-national units have developed programmes \r\nand policies, these three regions are presented due to their focus \r\non forest and agricultural carbon mitigation, their use of generally "


id: bfc69603fe11db78d8e9728ad003c336
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 27730
content:
"For New Zealand, the carbon reduction in Table 7.4 represents forest \r\nremovals that were surrendered from post-1989 forests between 2008 \r\nand the 2020. Unlike offsets in voluntary markets or in California, \r\nwhere permanence involves long-term contracts or insurance \r\npools, forests in the New Zealand market liable for emissions when \r\nharvested or following land-use change. This means sellers account \r\nfor future emission risks related to harvesting when they enter forests \r\ninto carbon contracts. Offset prices were around USD13 tCO2\r\n-1 in \r\n2016 but have risen to more than USD20 tCO2\r\n-1 in 2020."


id: 3fa1514b08f26d5b710e67a2c58a0184
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 7398
content:
"The largest share of emission reductions or carbon offsets in Table 7.4 \r\nhas been from slowing deforestation and REDD+, specifically \r\nfrom efforts in Brazil (86% of total), which substantially reduced \r\ndeforestation rates between 2004 and 2012 (Nepstad et al. 2014), \r\nas well as other countries in Latin America. With the exception of \r\nRoopsind et al. (2019), estimated reductions in carbon emissions from \r\nREDD+ in Table 7.4 are measured relative to a historical baseline. As \r\nnoted in Brazil's Third Biennial Update Report (Ministry of Foreign \r\nAffairs 2019), estimates are made in accordance with established \r\nmethodologies to determine the benefits of results-based REDD+ \r\npayments to Brazil. REDD+ estimates from other countries also have \r\nbeen derived from biennial update reports."


id: 6c23f4867ea6ae7f8a4f8c84e08e38da
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 14644
content:
"Regulatory markets provide the next largest share of carbon removal \r\nto date. Data from the Australia Emissions Reduction Fund are \r\ncarbon credits issued in for agricultural, and vegetation and savanna \r\nburning projects. In the case of California, offset credits from forest \r\nand agricultural activities, using methods approved by a third-party \r\ncertification authority (Climate Action Reserve), have been allowed as \r\npart of their state-wide cap and trade system. Transaction prices for \r\nforest and agricultural credits in California were around USD13 tCO2\r\n-1\r\nin 2018, and represented 7.4% of total market compliance. By the \r\nend of 2018, 80 MtCO2 had been used for compliance purposes."


id: d6d9b57a247db976944088e123df001f
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updated_at: 2023-03-16 14:01:37
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vector_id: 31310
content:
"a\r\n Clean Development Mechanism Registry: https://cdm.unfccc.int/Registry/index.html (accessed 22 June 2021)."


id: e5b1ccb325f6f3b84ff80b90ba006d5e
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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content:
"d\r\n (Hamrick and Gallant 2017a). State of Forest Carbon Finance. Forest Trends Ecosystem Marketplace. Washington, DC, USA.\r\ne\r\n Data for Australia carbon credit units (ACCUs) from Australia Emissions Reduction Fund Registry for agricultural and vegetation and savanna burning projects through \r\nFY2018/19 (downloaded on 24/10/2019): (http://www.cleanenergyregulator.gov.au/ERF/project-and-contracts-registers/project-register) and from Emissions Reduction Fund \r\nauction results to December 2018: (http://www.cleanenergyregulator.gov.au/ERF/auctions-results/december-2018)."


id: d7a8a6f2569e8fe08eba5c7d76bc9b50
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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content:
"f\r\n Data from the California Air Resources Board Offset Issuance registry (https://ww2.arb.ca.gov/our-work/programs/compliance-offset-program) for forestry and agricultural \r\nearly action and compliance credits."


id: 4489b415d7bdf5136111ffbdc6e6e75c
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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index: climate_gpt_only_giec
vector_id: 8209
content:
"g\r\n Surrendered forest carbon credits from post-1989 forests in New Zealand. Obtained from New Zealand Environmental Protection Authority. ETS Unit Movement interactive \r\nreport (Excel based). https://www.epa.govt.nz/industry-areas/emissions-trading-scheme/ets-reports/unit-movement/."


id: 58870cfc2fa9abe3f389ffed09e8ffde
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
content_type: text
index: climate_gpt_only_giec
vector_id: 11428
content:
"h\r\n Obtained 13/08/2020. All non-CO2 gases are converted to CO2-eq using IPCC GWP100 values recommended at the time the project achieved approval by the relevant \r\norganisation or agency."


id: 5e926045fbf2335381b2fb35ca36cac1
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 12413
content:
"Voluntary finance has amounted to USD0.5 billion over a  10-year \r\nperiod for development of forest and agricultural credits. The three \r\nregulatory markets quantified amount to USD2.7 billion in funding \r\nfrom 2010 to 2019. For the most part, this funding has focused on \r\nforest projects and programs, with agricultural projects accounting \r\nfor 5-10% of the total. In total, reported funding for AFOLU \r\nprojects and programmes has been USD4.4 billion over the past \r\ndecade, or about USD569 million yr-1 (low confidence). The largest \r\nshare of the total carbon includes efforts in the Amazon by Brazil. \r\nGovernment expenditures on regulatory programmes and business \r\nexpenditures on voluntary programmes in Brazil (e.g.,  the soy or \r\ncattle moratoriums) were not included in financing estimates due to \r\ndifficulties obtaining that data. If Brazil and CDM (for which we have \r\nno cost estimates) are left out of the calculation, average cost per ton \r\nhas been USD3.20 tCO2\r\n-1."


id: 4f6ad073c203514eed489e9085e1e72
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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content:
"The large number of policy approaches described in Table  7.4 \r\ncombined with efforts by other international actors, such as the \r\nGlobal Environmental Facility (GEF), as well as non-state actors \r\n(e.g.,  eco-labelling programmes and corporate social responsibility \r\ninitiatives) illustrate significant policy experimentation over the last \r\nseveral decades. Despite widespread effort, AFOLU measures have \r\nthus far failed to achieve the large potential for climate mitigation \r\ndescribed in earlier IPCC WG III reports (high confidence). The limited \r\ngains from AFOLU to date appear largely to result from lack of \r\ninvestment and other institutional and social barriers, rather than \r\nmethodological concerns (high confidence)."


id: 730cdd818c3bbb94b0a8d363553bbc91
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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"REDD+/Payment for Ecosystem Services (PES). PES programmes \r\nfor a  variety of ecosystem services have long been utilised for \r\nconservation (e.g.,  Wunder 2007) and may now be as large as \r\nUSD42  billion yr-1 (Salzman et al. 2018). REDD+ emerged in the \r\nearly 2000s and is a widely recognised example of PES programme \r\nfocused on conservation of tropical forests (Table  7.4). However, \r\nour summation of actually paid funds in Table 7.4 is much smaller \r\nthan what is portrayed by Salzman et al. (2018). REDD+ may \r\noperate at the country level, or for specific programmes or forests \r\nwithin a country. As with other PES programs, REDD+ has evolved \r\ntowards a  results-based programme that involves payments that \r\nare conditioned on meeting certain successes or milestones, such as \r\nrates of deforestation (Angelsen 2017)."


id: 3965f38351d6828e42fc6403d4bd64c6
created_at: 2023-03-16 14:01:37
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vector_id: 6410
content:
"Emissions Trading/Carbon Taxes. While emissions trading \r\nprogrammes have been developed across the globe, forest and \r\nagriculture have not been included as part of the cap in any of the \r\nexisting systems. However, offsets from forestry and agriculture \r\nhave been included in several of the trading programs. New Zealand \r\nhas a  hybrid programme where carbon storage in forests can be \r\nvoluntarily entered into the carbon trading program, but once \r\nentered, forests are counted both as a sink for carbon if net gains \r\nare positive, and a  source when harvesting occurs. New Zealand \r\nis considering rules to include agricultural GHG emissions under \r\na future cap (Henderson et al. 2020; see: https://www.agmatters.nz/\r\ntopics/he-waka-eke-noa/)."


id: c4b6779c9e0579ed188ec21555dfd062
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index: climate_gpt_only_giec
vector_id: 28519
content:
"The state of California has developed a  formal cap and trade \r\nprogramme that allows a limited number of forest and agricultural \r\noffset credits to be used under the cap. All offsets must meet protocols \r\nto account for additionality, permanence and leakage. Forest projects \r\nused as offsets in California currently are located in the USA, but \r\nthe California Air Resources Board adopted a tropical forest carbon \r\nstandard, allowing for avoided deforestation projects from outside \r\nthe USA to enter the California market (CARB 2019)."


id: b2db719db999830f05199c29a295c3be
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content:
"While expectations that carbon-centred REDD+ would be a simple \r\nand efficient mechanism for climate mitigation have not been met \r\n(Turnhout et al. 2017; Arts et al. 2019), progress has nonetheless \r\noccurred. Measuring, monitoring and verification systems have been \r\ndeveloped and deployed, REDD readiness programmes have improved \r\ncapacity to implement REDD+ on the ground in over 50 countries, and \r\na number of countries now have received results-based payments."


id: 3d82fafe6313349dcbbe901461cc108c
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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content:
"of permanent grass or woodland cover in the Conservation Reserve \r\nProgram (CRP), which has increased soil carbon sequestration by \r\n3 tCO2 ha-1 yr-1 (Conant et al. 2017; Paustian et al. 2019), as well as \r\nother practices that could lower net emissions. Gross GHG emissions \r\nfrom the agricultural sector in the US, however, have increased since \r\n1990 (USEPA 2020) due to reductions in the area of land in the \r\nUS CRP programme and changes in crop rotations, both of which \r\ncaused soil carbon stocks to decline (USEPA 2020). When combined \r\nwith increased non-CO2 gas emissions, the emission intensity of US \r\nagriculture increased from 1.5 to 1.7 tCO2 ha-1 between 2005 and \r\n2018 (high confidence)."


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"Empirical evidence that REDD+ funding has slowed deforestation \r\nis starting to emerge. Simonet et al. (2019) showed that a REDD+ \r\nproject in Brazil reduced deforestation certainly until 2018, while \r\nRoopsind et al. (2019) showed that country-level REDD+ payments \r\nto Guyana encouraged reduced deforestation and increased carbon \r\nstorage. Although more impact evaluation (IE) analysis needs to be \r\nconducted on REDD+ payments, these studies support the country\u0002level estimates of carbon benefits from REDD+ shown in Table 7.4. \r\nNearly all of the analysis of PES and REDD+ to date has focused \r\non the presence or absence of forest cover, with little to no analysis \r\nhaving been conducted on forest degradation, conservation, or \r\nenhancement of forest stocks."


id: 774e2a65147d91910291f462b971ef3f
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"China has implemented large conservation programmes that have \r\ninfluenced carbon stocks. For example, the Sloping Land Conversion \r\nProgram, combined with other programs, has increased forest cover \r\nand carbon stocks, reduced erosion and increased other ecosystem \r\nservices in China in recent years (Ouyang et al. 2016). As part of Brazil's \r\nnational strategy, numerous practices to reduce GHG emissions from \r\nagriculture, and in particular from the animal agriculture industry, \r\nhave been subsidised. Estimates by Manzatto et al. (2020) suggest \r\nthat the programme may have reduced agricultural emissions by \r\n169 MtCO2 between 2010 and 2020. Given the large technical and \r\neconomic potential for agroforestry to be deployed in Africa, subsidy \r\napproaches could be deployed along with other polices to enhance \r\ncarbon through innovative practices such as regreening (Box 7.10)."


id: a7705b2d46e6b1cf573b5a323cf8a219
created_at: 2023-03-16 14:01:37
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"Regulations on land use include direct controls on how land is \r\nused, zoning, or legally set limits on converting land from one use to \r\nanother. Since the early 2000s, Brazil has deployed various regulatory \r\nmeasures to slow deforestation, including enforcement of regulations \r\non land-use change in the legal Amazon area. Enforcement of these \r\nregulations, among other approaches is credited with encouraging \r\nthe large-scale reduction in deforestation and associated carbon \r\nemissions after 2004 (Nepstad et al. 2014). Empirical evidence has \r\nfound that regulations reduced deforestation in Brazil (Arima et al. \r\n2014) but over time, reversals occurred when enforcement was not \r\nconsistent (Azevedo et al. 2017) (Box 7.9)."


id: 949b65cc71b8c25c98adc709f0c4b432
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"The USA spends USD4 billion yr-1 on conservation programs, or 12% of \r\nnet farm income (Department of Agriculture 2020). In real terms, this \r\nexpenditure has remained constant for 15 years, supporting 12 Mha "


id: 3cdec68361e465d83651c40f0cc39d77
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"the tropical Americas (368.8 TgC yr-1) had the largest contribution, \r\nfollowed by Asia (25.0 TgC yr-1) and Africa (12.7 TgC yr-1). The \r\nauthors concluded that local factors had an important influence on the \r\neffectiveness of protected areas. For example, in the Brazilian Amazon, \r\nprotected area effectiveness is affected by the government agency \r\ncontrolling the land (federal indigenous lands, federal PAs, and state \r\nPAs) (Herrera et al. 2019). Because protected areas limit not just land\u0002use change, but also logging or harvesting non-timber forest products, \r\nthey may be relatively costly approaches for forest conservation \r\n(medium confidence)."


id: 698f5c41045eeefaa97e0f35742998a8
created_at: 2023-03-16 14:01:37
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"Community forest management (CFM) allows less intensive use \r\nof forest resources, while at the same time providing carbon benefits \r\nby protecting forest cover. Community forest management provides \r\nproperty rights to communities to manage resources in exchange \r\nfor their efforts to protect those resources. In many cases, the local \r\ncommunities are indigenous people who otherwise would have \r\ninsecure tenure due to an advancing agricultural frontier or mining "


id: 7db490c344bcd76459b335dd1cf27e43
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"Summary of the case.Indigenous peoples include more than 5000 different peoples, with over 370 million people, in 70 countries \r\non five continents (UNIPP 2012). For example, in Latin America and Caribbean, forests cover more than 80% of the area occupied by \r\nindigenous peoples (330 million hectares) (FAO and FILAC, 2021) which points to their critical role for forest governance (Garnett et al. \r\n2018; Fa et al. 2020). The Menominee people (Wisconsin, USA) practice sustainable forestry on their reservation according to a land \r\nethic integral to the tribal identity. The Tribe calls themselves 'The Forest Keepers', recognising that the connection of their future to \r\nthe sustainable management of the forest that allowed the forest volume standing today to be higher than when timber harvesting\r\nbegan more than 160 years ago. Management practices are based on continuous forest inventories (Mausel et al. 2017)."


id: c0e5c743c6d67617a39fcc9c07e54912
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"Introduction to the case. Forest management and timber harvesting operations began shortly after the Menominee Indian Reservation \r\nwas created by treaty in 1854. The Menominee reservation sits on about 95,000 ha of land in Wisconsin that spans multiple forest types \r\nand is more diverse than adjacent forests. The collectively maintained reservation has 87% of its land under sustained yield forestry."


id: 27543190045e96d42a03f9cf80c33f3f
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"Case description. The Tribe, in the 19th century, had already mastered vegetation manipulation with fire, sustainable forestry, \r\nmultiple-use, ecosystem, and adaptive management. The centrepiece of the Tribe's economy has been its forest product industry, \r\nMenominee Tribal Enterprises (MTE) (Pecore 1992). A balance between growth and removals and continuous forest inventories (CFI) \r\nare central for forest management for the past 160 years, aiming not at very large volumes, but at very high-quality trees. During this \r\nsame period, more than 2.3 billion board feet have been harvested from the same area, equivalent to 0.3 m3\r\n ha-1 yr-1."


id: b3f27b91a511be388ba8ed7ec6a70283
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content:
"Interactions and limitations. In 2013, the Menominee Tribe started a collaboration with the US Forest Service to implement climate \r\nadaptation measures. The Tribe actively works to reduce the risk of forest damage and decided to further promote diversity by \r\nplanting tree seedlings adapted to a warming climate (https://toolkit.climate.gov/case-studies/and-trees-will-last-forever). However, \r\nnew challenges are related to increasing pressures on forest ecosystems such as non-native insects, pathogens, weed invasions, and \r\nthe costs for continuous forest inventories to support long-term forest management. "


id: fd43bc32db5c196bb33840664fcbc69e
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"activity. Other examples are forest owner associations like those \r\ndiscussed in Box 7.8. According to the Rights and Resources Initiative \r\n(2018), the area of forests under community management increased \r\nglobally by 152 Mha from 2002 to 2017, with over 500 Mha under \r\ncommunity management in 2017. Studies have now shown that \r\nimproved property rights with community forest management can \r\nreduce deforestation and increase carbon storage (Deininger and \r\nMinten 2002; Alix-Garcia et al. 2005; Alix-Garcia 2007; Bowler \r\net al. 2012; Blackman 2015; Fortmann et al. 2017; Burivalova et al. \r\n2019). Efforts to expand property rights, especially community forest \r\nmanagement, have reduced carbon emissions from deforestation in \r\ntropical forests in the last two decades (high confidence), although \r\nthe extent of carbon savings has not been quantified globally."


id: b453869c76e4e8c0c5d9492588d8f93f
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"timber harvesting practices, and may reduce emissions from forest \r\ndegradation with reduced impact logging and other approaches \r\n(medium confidence). Forest certification has expanded globally  to \r\nover 440 Mha (Kraxner et al. 2017). As the area of land devoted \r\nto  certification has increased, the amount of timber produced from \r\ncertified land has increased. In 2018, FSC accounted for harvests of \r\n427 million m3\r\n and jointly FSC and PEFC accounted for 689 million m3\r\nin 2016 or around 40% of total industrial wood production (FAO \r\n2018c). There is evidence that reduced impact logging can reduce \r\ncarbon losses in tropical regions (Pearson et al. 2014; Ellis et al. 2019). \r\nHowever, there is conflicting evidence about whether forest certification \r\nreduces deforestation (e.g., Blackman et al. 2018; Tritsch et al. 2020)."


id: 4fef513cbc50b1c318c1208369389f37
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"Supply chain management in the food sector encourages \r\nmore widespread use of conservation measures in agriculture \r\n(high confidence). The number of private commitments to reduce \r\ndeforestation from supply chains has greatly increased in recent \r\nyears, with at least 865 public commitments by 447 producers, \r\nprocessors, traders, manufacturers and retailers as of December, 2020 \r\n(New York Declaration on Forests 2021). Industry partnerships with \r\nNGOs, such as the Roundtable on Sustainable Palm Oil (RSPO), have \r\nbecome more widespread and visible in agricultural production. For \r\nexample, RSPO certifies members all along the supply chain for palm \r\noil and claims around 19% of total production. Similar sustainability \r\nefforts exist for many of the world's major agricultural products, \r\nincluding soybeans, rice, sugar cane, and cattle."


id: be301dd86a2788136090c2e8a4b79381
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"Bioenergy targets. Multiple policies have been enacted at national \r\nand supra-national levels to promote the use of bioenergy in the \r\ntransport sector, and for bioelectricity production. Existing policies \r\nmandate or subsidise the production and use of bioenergy. In \r\nthe past few years, policies have been proposed, put in place or \r\nupdated in Australia (Renewable Energy Target), Brazil (RenovaBio, \r\nNationally Determined Contribution), Canada (Clean Fuel Standard), \r\nChina (Biodiesel Industrial Development Policy, Biodiesel Fuel Blend \r\nStandard), the European Union (Renewable Energy Directive II), the \r\nUSA (Renewable Fuel Standards), Japan (FY2030), Russia (Energy \r\nStrategy Bill 2035), India (Revised National Policy on Biofuels), and \r\nSouth Africa (Biofuels Regulatory Framework)."


id: bdce75fcd73ac390adc4e0a3de6600ac
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"While current policies focus on bioenergy to decarbonise the energy \r\nsystem, some also contain provisions to minimise the potential \r\nenvironmental and social trade-offs from bioenergy production. \r\nFor instance, the EU Renewable Energy Directive (EU-RED II) and \r\nUS Renewable Energy Standard (US-RFS) assign caps on the use \r\nof biofuels, which are associated with indirect land-use change \r\nand food-security concerns. The Netherlands has a stringent set of \r\n36  sustainability criteria to which the certified biomass needs to \r\ncomply. The EU-RED II also sets a timeline for the complete phase\u0002out of high-risk biofuels (Section 7.4.4)."


id: a3f596b9050679998c2126fec33b9593
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"Between 2000 and 2004, deforestation rates in the Brazilian Legal Amazon (is a socio-geographic division containing all nine Brazilian \r\nstates in the Amazon basin) increased from 18,226 to 27,772 km2\r\n yr-1 2008 (INPE, 2021). A  set of public policies designed in \r\nparticipatory process involving federal government, states, municipalities, and civil society successfully reduced deforestation rates \r\nuntil 2012. However, deforestation rates increased after 2013, and particularly between 2019 and 2020. Successful deforestation \r\ncontrol policies are being negatively affected by changes in environmental governance, weak law enforcement, and polarisation of \r\nthe national politics."


id: cde3fad018acf0b88cc5d034c72fdc59
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"In 2004, the Brazilian federal government started the Action Plan for Prevention and Control of Deforestation in the Legal Amazon \r\n(PPCDAm) (Ministry of Environment, Government of Brazil, 2018)."


id: cd872aecc15769f402d98e7017c45c15
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"The PPCDAm was a  benchmark for the articulation of forest conservation policies that included central and state governments, \r\nprosecutor offices, and the civil society. The decline in deforestation after 2008 is mostly attributed to these policy options. In 2012, \r\ndeforestation rates decreased to 4,571 km2\r\n yr-1."


id: 3efab9c166d59b793098065a0626883c
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"However, the country's political polarisation has gradually eroded environmental governance, especially after the Brazilian Forest \r\nCode changes in 2012 (major environmental law in Brazil), the presidential impeachment in 2016, presidential elections in 2018, and \r\nthe start of the new federal administration in 2019. Successful deforestation control policies are being negatively affected by critical \r\nchanges in the political context, and weakening the environmental rule of law, forest conservation, and sustainable development \r\nprogrammes (for example, changes in the Amazon Fund governance in disagreement with the main donors). In 2019, the annual \r\ndeforestation rate reached 10,129 km2\r\n being the first time it surpassed 10,000 km2 since 2008 (INPE, 2021). Besides, there has been \r\nno effective transition from the historical economic model to a sustainable one. The lack of clarity in the ownership of land is still \r\na major unresolved issue in the Amazon."


id: 242837f1f1009d6b3ff85d0c43313f5e
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"The reduction of deforestation in the Brazilian Amazon was possible due to effective political and institutional support for environmental \r\nconservation. The initiatives of the Action Plan included the expansion of the protected areas network (conservation unities and \r\nindigenous lands), improvement of deforestation monitoring to the enforcement of environmental laws, and the use of economic \r\ninstruments, for example, by cutting off public credit for municipalities with higher deforestation rates (Ricketts et al. 2010; Souza et al. \r\n2013; Nepstad et al. 2014; Arima et al. 2014; Blackman and Veit 2018). "


id: 683c641f1327b456878d5dde64e46852
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"The array of public policies and social engagement was a historical and legal breakthrough in global protection. However, the broader \r\npolitical and institutional context and actions to reduce the representation and independent control of civil society movements in \r\ndecision-making bodies weaken this structure with significant increases in deforestation rates, burnings, and forest fires."


id: 5d9ea4f838c5aa1c3765b6c17d117e48
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"More than 200 million trees have regenerated on more than 5 Mha in the Sahel (Sendzimir et al. 2011). The Maradi/Zinder region of \r\nNiger is the epicentre of experimentation and scale up. This vast geographic extent generates significant mitigation potential despite \r\nthe relatively modest per unit area increase in carbon of about 0.4 MgC ha-1 a-1 (Luedeling and Neufeldt 2012). In addition to the \r\ncarbon benefits, these agroforestry systems decrease erosion, provide animal fodder, recharge groundwater, generate nutrition and \r\nincome benefits and act as safety nets for vulnerable rural households during climate and other shocks (Bayala et al. 2014, 2015; \r\nBinam et al. 2015; Sinare and Gordon 2015; Ilstedt et al. 2016)."


id: 6521f1b996ba08c0b5bcaddcb8bd967a
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"A melange of factors contributed to regreening in the Sahel. Increased precipitation, migration, community development, economic \r\nvolatility and local policy reform have all likely played a role (Haglund et al. 2011; Sendzimir et al. 2011; Brandt et al. 2019a; Garrity and \r\nBayala 2019); the easing of forestry regulations has been particularly critical in giving farmers greater control over the management \r\nand use of trees on their land (Garrity et al. 2010). This policy shift was catalysed by greater regional autonomy resulting from \r\neconomic decline and coincided with successful pilots and NGO-led experimentation, cash-for-work, and training efforts to support \r\nchanges in land management (Sendzimir et al. 2011). Participation of farmers in planning and implementation helped align actions \r\nwith local knowledge and goals as well as market opportunities."


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"Regreening takes place when dormant seed or tree stumps sprout and are cultivated through the technique, called Farmer Managed \r\nNatural Regeneration (FMNR). Without planting new trees, FMNR is presumed to be cheaper than other approaches to restoration, \r\nthough comparative economic analysis has yet to be conducted (Chomba et al. 2020). Relatively lower investment costs are believed \r\nto have contributed to the replication across the landscape. These factors worked together to contribute to a groundswell of action \r\nthat affected rights, access, and use of local resources (Tougiani et al. 2009)."


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"Regreening in the Sahel and the consequent transformation of the landscape has resulted from the actions of hundreds of thousands \r\nof individuals responding to social and biophysical signals (Hanan 2018). This is an example for climate change mitigation, where \r\neliminating regulations - versus increasing them - has led to carbon dioxide removal."


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"Additionality, permanence and leakage have been widely discussed \r\nin the forestry and agricultural mitigation literature (Murray et al. \r\n2007), including in AR5 (Section 11.3.2 of the AR5WGIII report) and \r\nearlier assessment reports. Since the earlier assessment reports, \r\nnew studies have emerged to provide new insights on the effect of \r\nthese issues on the credibility of forest and agricultural mitigation. \r\nThis assessment also provides additional context not considered in \r\nearlier assessments."


id: 8582bdc8e6654fa81c6f48ab08286c7a
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"Typically, carbon registries will require that project developers \r\nshow additionality by illustrating that the project is not undertaken \r\nas a  result of a  legal requirement, and that the project achieves \r\ncarbon reductions above and beyond a  business as usual. The \r\nprotocols developed by the California Air Resources Board to ensure \r\npermanence and additionality are strong standards and may even \r\nlimit participation (e.g., Ruseva et al. 2017). The business as usual \r\nis defined as past management actions by the same entity that \r\ncan be verified. Additionality can thus be observed in the future as \r\na  difference from historical actions. This approach has been used \r\nby several countries in their UNFCCC Biennial Update reports to \r\nestablish reductions in carbon emissions from avoided deforestation \r\n(e.g., Brazil and Indonesia)."


id: 95fe9babca450e3cb4b91ebd9d328607
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"The same experimental methods have been applied to analyse \r\nadditionality of the adoption of soil conservation and nutrient \r\nmanagement practices in agriculture. Claassen et al. (2018) find that \r\nprogrammes to promote soil conservation are around 50% additional \r\nacross the USA (i.e., 50% of the land enrolled in soil conservation \r\nprogrammes would not have been enrolled if not for the programme), \r\nwhile Woodward et al. (2016) find that adoption of conservation "


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"tillage is rarely additional. Claassen et al. (2018) find that payments \r\nfor nutrient management plans are nearly 100% additional, although \r\nthere is little evidence that farmers reduce nutrient inputs when they \r\nadopt plans. It is not clear if the same policy approaches would lead \r\nto additionality in other regions."


id: 90f3735fe02f46ca58559e32e0663936
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"To date, there has been significantly less investment in agricultural \r\nprojects than forestry projects to reduce net carbon emissions \r\n(Table  7.4). For example, the economic potential (available up \r\nto USD100 tCO2\r\n-1) for soil carbon sequestration in croplands is \r\n1.9  (0.4-6.8) GtCO2 yr-1 (Section  7.4.3.1), however, less than 2% \r\nof the carbon in Table 7.4 is derived from soil carbon sequestration \r\nprojects. While reductions in CH4 emissions due to enteric fermentation \r\nconstitute a large share of potential agricultural mitigation reported \r\nin Section 7.4, agricultural CH4 emission reductions so far have been \r\nrelatively modest compared to forestry sequestration. The protocols \r\nto quantify emission reductions in the agricultural sector are available \r\nand have been tested, and the main limitation appears to be the \r\nlack of available financing or the unwillingness to re-direct current \r\nsubsidies (medium confidence)."


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"Numerous developing countries have established policy efforts \r\nto abate agricultural emissions or increase carbon storage. Brazil, \r\nfor instance, developed a  subsidy programme in 2010 to promote \r\nsustainable development in agriculture, and practices that would \r\nreduce GHG emissions. Henderson et al. (2020) report that this \r\nprogramme reduced GHG emission in agricultural by up to "


id: 9fdc082b315efdfcba5ecb96a78ba2ac
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"170  MtCO2 between 2010 and 2018. However, the investments in \r\nlow-carbon agriculture in Brazil amounted only 2% of the total funds \r\nfor conventional agriculture in 2019. Programmes on deforestation \r\nin Brazil had successes and failures, as described in Box  7.9. \r\nIndonesia has engaged in a wide range of programmes in the REDD+ \r\nspace, including a  moratorium implemented in 2011 to prevent \r\nthe conversion of primary forests and peatlands to oil palm and \r\nlogging concessions (Wijaya et al. 2017; Tacconi and Muttaqin 2019; \r\nHenderson et al. 2020). Efforts to restore peatlands and forests have \r\nalso been undertaken. Indonesia reports that results-based REDD+ \r\nprogrammes have been successful and have led to lower rates of \r\ndeforestation (Table 7.4)."


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"(Box  7.10). Within several of the NDCs, countries have explicitly \r\nsuggested intensification as an approach to reduce emission in the \r\nlivestock sector. However, it is important to note caveats associated \r\nwith pursuing mitigation via intensification (Box 7.11)."


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"Existing policies focused on GHG management in agriculture \r\nand forestry is less advanced in Africa than in Latin American and \r\nAsia, however, Henderson et al. (2020) report on 10 countries in \r\nsub-Saharan Africa that have included explicit policy proposals \r\nfor reducing AFOLU GHG emissions through their NDCs. These \r\ninclude efforts to reduce N2O emission, increase implementation \r\nof conservation agriculture, improve livestock management, and \r\nimplement forestry and grassland practices, including agroforestry "


id: 79676468c0b8181a289e726ee9a1e927
created_at: 2023-03-16 14:01:37
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"Sustainable intensification (SI) has received considerable attention as a suggested means of pursuing increased overall production, \r\nreducing associated environmental externalities, and potentially releasing agricultural land for alternative uses, such as forestry \r\nor rewilding (Godfray and Garnett 2014; Pretty 2018). The concept was explored within the SRCCL (SRCCL (Mbow et al. 2019), \r\nSection 5.6.4.4 and Cross-Chapter Box 6 in Chapter 5). SI is context specific and dynamic, with no universally prescribed methodology \r\n(HLPE 2019). Equal importance is given to enhancing sustainability as to achieving agricultural intensification. The former aspect is \r\noften challenging to realise, measure and maintain."


id: 596493d77fd41ddb209db96547b2e8d5
created_at: 2023-03-16 14:01:37
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"Preconditions to ensure sustainable intensification\r\nIncreasing the total amount of product produced by improving production efficiency (output per unit of input) does not \r\nguarantee SI. It will only be successful if increased production efficiency translates into reduced environmental and social impacts \r\nas well as increased production. For example, AR5 highlighted a growing emphasis on reducing GHG emissions per unit of product \r\nvia increasing production efficiency (Smith et al. 2014), but reductions in absolute GHG emissions will only occur when production \r\nefficiency increases at a greater rate than the rate at which production increases (Clark et al. 2005)."


id: 4c91f875b2e51b8cf217900e8d84f12e
created_at: 2023-03-16 14:01:37
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"Defined indicators are required. Measurement of SI requires multiple indicators and metrics. It can be assessed at farm, regional or \r\nglobal scales and temporal aspect must be considered. SI may warrant whole system redesign or land reallocation (Garnett et al. 2013; \r\nPretty et al. 2018). Accordingly, there is high agreement concerning the need to consider multiple environmental and social outcomes "


id: 7327ecd60552940982a9f89226db717a
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 15732
content:
"at wider spatial scales, such as catchments or regions (Weltin et al. 2018; Bengochea Paz et al. 2020; Cassman and Grassini 2020). \r\nImpacts may be considered in relative terms (per area or product unit), with relationships potentially antagonistic. Both area- and \r\nproduct unit-based metrics are valid, relevant under different contexts and useful in approaching SI, but do not capture overall impacts \r\nand trade-offs (Garnett 2014). To reduce the risk of unsustainable intensification, quantitative data and selection of appropriate \r\nmetrics to identify and guide strategies are paramount (Garnett et al. 2013; Gunton et al. 2016; Cassman and Grassini 2020)."


id: a2998583223dce6479c29957a75ab63a
created_at: 2023-03-16 14:01:37
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content:
"It is critical that intensification does not drive expansion of unsustainable practices. Increased productivity with associated economic \r\nreward could incentivise and reward agricultural land expansion, or environmentally and socially damaging practices on existing \r\nand former agricultural land (Ceddia et al. 2013; Phalan 2018). Accordingly, coordinated policies are crucial to ensuring desired \r\noutcomes (Godfray and Garnett 2014; Reddy et al. 2020; Kassam and Kassam 2020). Barretto et al. (2013) found that in agriculturally \r\nconsolidated areas, land-use intensification coincided with either a  contraction of both cropland and pasture areas, or cropland \r\nexpansion at the expense of pastures, both resulting in a stable farmed area. In contrast, in agricultural frontier areas, land-use \r\nintensification coincided with expansion of agricultural lands."


id: 7ada331d783ba3d42bceabc38a3fbf78
created_at: 2023-03-16 14:01:37
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content:
"In conclusion, SI within agriculture is needed given the rising global population and the need to address multiple environmental \r\nand social externalities associated with agricultural activities. However, implementation requires strong stakeholder engagement, \r\nappropriate regulations, rigorous monitoring and verification and comprehensive outreach and knowledge exchange programmes."


id: 280da26346cc4805436b5137a1cef050
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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content:
"2020) combined with sustainable management and provision of \r\nagricultural and wood products are widely expected to increase the \r\nterrestrial pool of carbon (Cross-Working Group Box 3 in Chapter 12). \r\nCarbon sequestration policies, sustainable land management (forest \r\nand agriculture), and biomass energy policies can be complementary \r\n(Favero et al. 2017; Baker et al. 2019). However, if private markets \r\nemerge for biomass and BECCS on the scale suggested in the SR1.5, \r\npolicy efforts must ramp up to substantially value, encourage, and \r\nprotect terrestrial carbon stocks and ecosystems to avoid outcomes \r\ninconsistent with many SDGs (high confidence)."


id: 8d77fca5a15d5c86d2c4867f568257cb
created_at: 2023-03-16 14:01:37
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content:
"If biomass energy production expands and shifts to carbon \r\ncapture and storage (e.g.,  BECCS) during the century, there could \r\nbe a  significant increase in the area of crop and forestland used \r\nfor biomass energy production (Sections  7.4 and 7.5). BECCS is \r\nnot projected to be widely implemented for several decades, but \r\nin the meantime, policy efforts to advance land-based measures \r\nincluding reforestation and restoration activities (Strassburg et al. "


id: 7205b994104f72b843aaa3f81708227d
created_at: 2023-03-16 14:01:37
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content:
"by other objectives such as water quality and species protection. \r\nConsiderably less funding has been available for agricultural \r\nprojects aimed at reducing carbon emissions, and outside of \r\nvoluntary markets, there do not appear to be large sources \r\nof  funding emerging either through international organisations, \r\nor national programs. In the agricultural sector, funding for carbon \r\nmust be obtained by redirecting existing resources from non-GHG \r\nconservation to GHG measures, or by developing new funding \r\nstreams (Henderson et al. 2020)."


id: c6b7e787348179d2c9318b0838b73e34
created_at: 2023-03-16 14:01:37
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vector_id: 28831
content:
"Risk and uncertainty. Most approaches to reduce emissions, \r\nespecially in agriculture, require new or different technologies that \r\ninvolve significant time or financial investments by the implementing \r\nlandholders. Adoption rates are often slow due to risk aversion among \r\nagricultural operators. Many AFOLU measures require carbon to be \r\ncompensated to generate positive returns, reducing the likelihood of \r\nimplementation without clear financial incentives. Research to show \r\ncosts and benefits is lacking in most parts of the world."


id: 13939d9eb762807b8bca787c3c488cbf
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 587
content:
"Poverty. Mitigation and adaptation can have important implications \r\nfor vulnerable people and communities, for example, mitigation \r\nactivities consistent with scenarios examined in the SR1.5 could raise \r\nfood and fiber prices globally (Section. 7.5). In the NDCs, 82 Parties \r\nincluded references to social issues (e.g., poverty, inequality, human \r\nwell-being, marginalisation), with poverty the most cited factor \r\n(70 Parties). The number of hungry and food insecure people in the \r\nworld is growing, reaching 821 million in 2017, or one in every nine \r\npeople (FAO 2018b), and two-thirds live in rural areas (Laborde \r\nDebucquet et al. 2020). Consideration of rural poverty and food \r\ninsecurity is central in AFOLU mitigation because there are a large \r\nnumber of farms in the world (about 570 million), and most are "


id: f38a9af3a28131b9f3a8728b48e1adf
created_at: 2023-03-16 14:01:37
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content:
"Scale and accessibility of financing. The largest share of funding \r\nto date has been for REDD+, and many of the commitments to \r\ndate suggest that there will be significant funding in this area \r\nfor the foreseeable future. Funding for conservation programmes \r\nin OECD countries and China affects carbon, but has been driven "


id: 5ea92f1f0bdf34a4e82424392318fd6c
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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content:
"Achieving the large contribution to mitigation that the AFOLU sector can make requires public and private investment. Austin et al. \r\n(2020) estimate that in forestry, USD178 billion yr-1 is needed over the next decade to achieve 5 GtCO2 yr-1, and investments need \r\nto ramp up to USD400 billion yr-1 by 2050 to expand effort to 6 GtCO2 yr-1. Other land-based options, such as mangrove protection, \r\npeatland restoration, and agricultural options would increase this total cost estimate, but have smaller to negligible opportunity costs."


id: 5f9fa59e4270405e99642e5cc381b244
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 12622
content:
"Opportunity costs are a direct financing costs for activities that require land uses to change. For instance a government can encourage \r\nplanting forests on agricultural land by (a) requiring it, (b) setting up a market or market-based incentives, or (c) buying the land and \r\ndoing it themselves. In each case, the required investment is the same - the planting cost plus the net foregone returns of agricultural \r\nrents - even though a different entity pays the cost. Private entities that pay for carbon credits will also bear the direct costs of \r\nplanting plus the opportunity costs. In the case of avoided deforestation, opportunity costs similarly must be paid to individual actors \r\nto avoid the deforestation."


id: 23dc70060d410780933a34e855f8c47d
created_at: 2023-03-16 14:01:37
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content:
"functions between state and non-state actors (Zelli et al. 2017; Phelps \r\net al. 2010). Overlap and duplication in Forest Law Enforcement, \r\nGovernance and Trade (FLEGT) and REDD+ also limits governance \r\neffectiveness (Gupta et al. 2016)."


id: 9ff6d79c60c3fa9ada276d718753452b
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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content:
"smaller than 2 hectares. It is important to better understand how \r\ndifferent mitigation policies affect the poor."


id: f7ada5aa7b708d126c6d842267e530cc
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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content:
"Clear land tenure and land-use rights. Unclear property rights \r\nand tenure insecurity undermine the incentives to improve forest and \r\nagricultural productivity, lead to food insecurity, undermine REDD+ \r\nobjectives, discourage adoption of farm conservation practices, \r\ndiscourage tree planting and forest management, and exacerbate \r\nconflict between different land users (Antwi-Agyei et al. 2015; Felker \r\net al. 2017; Sunderlin et al. 2018; Borras and Franco 2018; Riggs \r\net al. 2018; Kansanga and Luginaah 2019). Some positive signs \r\nexist as over 500 million hectares of forests have been converted \r\nto community management with clear property rights in the past \r\ntwo decades (Rights and Resources Initiative 2018), but adoption of \r\nforest and agricultural mitigation practices will be limited in large \r\nremaining areas with unclear property rights (Gupta et al. 2016)."


id: 8d731f8a73f1945c32a80888428aa6ac
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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content:
"Lack of institutional capacity. Institutional complexity, or lack \r\nthereof, represents a major challenge when implementing large and \r\ncomplex mitigation programmes (e.g., REDD+) in agriculture, forest \r\nand other land uses (Backstrand et al. 2017). Without sufficient \r\ncapacity, many synergies between agricultural and forest programs, \r\nor mitigation and adaptation opportunities, may be missed (Duguma \r\net al. 2014). Another aspect of institutional complexity is the \r\ndifferent biophysical and socio-economic circumstances as well as \r\nthe public and private financial means involved in the architecture \r\nand implementation of REDD+ and other initiatives (Zelli et al. 2017)."


id: d09c6b074dc45b9014bf73b830200bf4
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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vector_id: 30344
content:
"Opportunity for political participation of local stakeholders is barrier \r\nin most places where forest ownership rights are not sufficiently \r\ndocumented (Essl et al. 2018). Since incentives for self-enforcement \r\ncan have an important influence on deforestation rates (Fortmann \r\net al. 2017), weak governance and insecure property rights are \r\nsignificant barriers to introduction of forest carbon offset projects \r\nin developing countries, where many of the low-cost options for \r\nsuch projects exist (Gren and Zeleke 2016). Governance challenges \r\nexist at all levels of government, with poor coordination, insufficient \r\ninformation sharing, and concerns over accountability playing \r\na prominent role within REDD+ projects and programmes (Ravikumar \r\net al. 2015). In some cases, governments are increasingly centralising \r\nREDD+ governance and limiting the distribution of governance "


id: a5b3d1d455782fac0a95ee8ec2144325
created_at: 2023-03-16 14:01:37
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content:
"Implementation of nature-based solution may have local or regionally \r\nimportant consequences for other ecosystem services, some of which \r\nmay be negative (high confidence). Land-use change has important \r\nimplications for the hydrological cycle, and the large land-use shifts \r\nsuggested for BECCS when not carried out in a  carefully planned \r\nmanner, are expected to increase water demands substantially across \r\nthe globe (Stenzel et al. 2019; Rosa et al. 2020). Afforestation can \r\nhave minor to severe consequences for surface water acidification, "


id: ac1e52825809d203d650c9887051ff9e
created_at: 2023-03-16 14:01:37
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content:
"depending on site-specific factors and exposure to air pollution \r\nand sea-salts (Futter et al. 2019). The potential effects of coastal \r\nafforestation on sea-salt related acidification could lead to re\u0002acidification and damage on aquatic biota."


id: 80270148db95181b0ff784493d070f0a
created_at: 2023-03-16 14:01:37
updated_at: 2023-03-16 14:01:37
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content:
"forest mitigation measures, suggesting that climate change presents \r\na formidable challenge to implementation of nature-based solutions \r\nbeyond 2030 (high confidence)."


