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National emissions reported to the UNFCCC and to the EU Greenhouse Gas Monitoring Mechanism
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Prod-ID: DAT-13-en
Created 13 Nov 2009 Published 11 Jun 2010 Last modified 11 Sep 2015
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Topics: Climate change mitigation
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Data on greenhouse gas emissions and removals, sent by countries to UNFCCC and the EU Greenhouse Gas Monitoring Mechanism (EU Member States)
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National greenhouse gas inventories (IPCC Common Reporting Format sector classification)
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Field Definition
Country_code International Country code (ISO 3166-1-Alpha-2 code elements) varchar(4) Yes
Pollutant_name Short name of pollutant varchar(40) Yes
Sector_code Sector code varchar(15) Yes
Year Year varchar(20) Yes
Country Country name varchar(53) No
Emissions Emission unit numeric(13) No
Format_name Name of guideline varchar(100) No
Notation Notation key varchar(40) No
Parent_sector_code Parent sector code varchar(15) No
Sector_name Sector name varchar(75) No
Unit Unit the measure value varchar(40) No
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Pollutants: CO2, CH4, N2O in Gg (1000 tonnes). Pollutants: HFCs, PFCs, SF6 in Gg CO2 equivalent. Aggregate: All greenhouse gases in Gg CO2 equivalent.
The European Topic Centre on Air and Climate Change (27 May 2010 and 10 June 2010), national submissions to UNFCCC or to EU Monitoring Mechanism of CO2 and other greenhouse emissions.
Directorate-General for Environment (DG ENV)
United Nations Framework Convention on Climate Change (UNFCCC)
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Data compiled and held by ETC/ACC are annual emissions of CO2, CH4, N2O, HFCs, PFCs, SF6 from individual countries. Sectoral data (IPCC classification) is provided for the following main source categories: Energy, Industrial Processes, Solvent and Other Product Use, Agriculture, Land-Use Change and Forestry, Waste, Other, CO2 emissions from Biomass, International bunkers and Multilateral Operations.
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Produced Indicators
Assessment Part Is energy consumption decreasing in Europe?
Assessment Part How rapidly are transport-related emissions of tropospheric ozone precursors declining?
Assessment Part How rapidly are energy-related (except transport) emissions of tropospheric ozone precursors declining?
Assessment Part Are energy-related emissions of ozone precursors decreasing?
Assessment Part How much can increased efficiency in transformation help reduce CO2 emissions in Europe?
Assessment Part
What are the main explanatory factors behind CO2 emissions trends in the industry sector in Europe?
What are the main explanatory factors behind CO2 emissions trends in the household sector in Europe?
How much can increased efficiency in transformation help reduce CO2 emissions in Europe?
Assessment Part How have greenhouse gas emissions from transport in Europe evolved?
What progress is being made in reducing emissions of ozone precursors across Europe?
How do different sectors and processes contribute to emissions of ozone precursors?
Is the use and production of energy having a decreasing impact on the environment?
Are energy related greenhouse gas emissions decreasing?
Produced figures
Figure CO2 emission savings per year for EU–27 at different transformation efficiencies compared to current 2009 efficiency CO2 emission savings per year for EU-27 at different transformation efficiencies compared to current 2009 efficiency
Figure Structure of CO2 emissions from thermal power plants in EU-27, 2009 How to read the figures: Left-top: % Share of fuel input (TJ) by type (liquid, solid, gaseous, biomass and other fuels) into 1A1a public electricity and heat production. Left-bottom: Implied emission factor for each fuel above (tCO2 / TJ), taken from EEA (2009) Right-top: Average efficiency of transformation in EU-27. Numerator = 101109 Output from district heating plants + 101121 Output from public thermal power stations Denominator = 101009 Input to district heating plants + 101021 Input to public thermal power stations Right-bottom: % Share of CO2 emissions by fuel type (liquid, solid, gaseous, biomass and other fuels into 1A1a public electricity and heat production)
Figure Changes (%) in emissions of ozone precursors by sector, 1990-2009, EEA-32 The figure shows the emissions methane CH4; carbon monoxide CO; non-methane volatile organic compounds NMVOCs; and nitrogen oxides NOx.
CO2 emissions in EU countries (1990, 2009) The figure shows the CO2 emissions in the industry in EU Countries
Figure Drivers of EU GHG emissions from energy supply, 1990–2008 -
Figure Decomposition analysis of direct CO2 emission trends from EU households, 1990–2008 Each bar shows the contribution of a single driver on GHG emission trends during a determined period. The thick short black lines indicate the combined effect of all emission drivers, i.e. the overall GHG emission trend during the period considered.
Figure GHG emission from energy use per sector and per gas, 1990–2008 Manufacturing industries and construction = CRF category 1A2, Primary and tertiary sector = CRF category 1A4a+1A4c+1A5, Households = CRF category 1A4b.
Figure Drivers of CO2 emissions from passenger cars in the EU, 1990–2008 Passenger km: The number of km covered by people is represented as passenger km, and includes road, rail, air and ship transport of passengers. Passenger km on road: Passenger km on road do not include passenger km on rail, air and ship transport of passengers.
Figure Drivers of direct CO2 emissions from EU households, 1990–2008 Final energy consumption, fuel consumption, fossil fuel consumption and CO2 emissions are temperature corrected. Indirect emissions, related to the production of public electricity or heat used by households, are not included.
Figure Decomposition analysis of CH4 emission trends from enteric fermentation of cattle in the EU, 1990–2008 Each bar shows the contribution of a single driver on GHG emission trends during a determined period. The thick short black lines indicate the combined effect of all emission drivers, i.e. the overall GHG emission trend during the period considered.
Figure Gross electricity generation by fuel in the EU The figure on the right represents a zoom of the figure on the left, for renewable sources only.
Figure Drivers of N2O emissions from EU agricultural soils, 1990–2008 -
Figure Decomposition analysis of N2O emission trends from EU agricultural soils, 1990–2008 Each bar shows the contribution of a single driver on GHG emission trends during a determined period. The thick short black lines indicate the combined effect of all emission drivers, i.e. the overall GHG emission trend during the period considered.
Figure Drivers of CO2 emissions from road freight transport in the EU, 1990–2008 -
Figure Decomposition analysis of CO2 emission trends from passenger cars in the EU, 1990–2008 Each bar shows the contribution of a single driver to CO2 emission trends during a determined period. The thick short black lines indicate the combined effect of all emission drivers, i.e. the overall GHG emission trend during the period considered.
Figure Decomposition analysis of CO2 emission trends from public electricity and heat production in the EU, 1990–2008 Each bar shows the contribution of a single driver on GHG emission trends during a determined period. The thick short black lines indicate the combined effect of all emission drivers, i.e. the overall GHG emission trend during the period considered.
Figure Drivers of direct GHG emissions from EU manufacturing and construction industries, 1990–2008 Indirect emissions, related to the production of public electricity or heat used by the manufacturing and construction industries, are not included.
Figure Decomposition analysis of direct CO2 emission trends from EU manufacturing and construction industries, 1990–2008 Each bar shows the contribution of a single driver on GHG emission trends during a determined period. The thick short black lines indicate the combined effect of all emission drivers, i.e. the overall GHG emission trend during the period considered.
Figure Drivers of CH4 emissions from enteric fermentation of cattle in the EU, 1990–2008 -
Figure Main drivers of total GHG emissions in the EU, 1990–2008 -
Figure Top-down decomposition analysis of total GHG emission trends in the EU, 1990–2008 Each bar shows the contribution of a single driver on GHG emission trends during a determined period. The thick short black lines indicate the combined effect of all emission drivers, i.e. the overall GHG emission trend during the period considered.
Figure Change in energy-related emissions of ozone precursors by country, 1990-2008 The graph shows the change in energy-related emissions of ozone precursors (NOx, NMVOC, CO and CH4) each weighted by an ozone formation factor prior to aggregation to represent their respective ozone forming potentials. The relative impact of the combined contribution of NOx, NMVOC, CO and CH4 to ozone formation can be assessed based on their tropospheric ozone forming potentials (TOFP): nitrogen oxides 1.22, non-methane volatile organic compounds 1.0, carbon monoxide 0.11 and methane 0.014 (de Leeuw 2002).
Figure Contribution of different sectors (energy and non-energy) to total emissions of tropospheric ozone precursors, 2008, EEA-32 The figure shows the emission of NOx, NMVOC, CO and CH4 in 2008
Changes (%) in emissions of ozone precursors by source category, 1990-2008, EEA-32 The figure shows the emissions methane CH4; carbon monoxide CO; non-methane volatile organic compounds NMVOCs; and nitrogen oxides NOx.
Figure CO2 emissions in EU countries (1990, 2008) The figure shows the CO2 emissions in the industry in EU Countries
Figure CO2 emissions per m2 for space heating The graph compares by country the level of CO2 emissions for space heating per m2 for 2 years : 1990 and 2008 (direct and indirect emissions). 1990 and 2008 data are climate corrected against each country's long-term average climate, whereas the last series is climate corrected and scaled against the EU long-term average climate to account for temperature differences between countries.
Figure Variation in direct CO2 emission from household (EU27) Variations in CO2 emissions from household and the explanatory effects.
Figure CO2 emissions per dwelling, climate corrected (EU-27) CO2 emissions per dwelling: direct and indirect emissions
CO2 emission savings per year for EU-27 at different transformation efficiencies compared to current 2008 efficiency CO2 emission savings per year for EU-27 at different transformation efficiencies compared to current 2008 efficiency
Structure of CO2 emissions from thermal power plants in EU-27, 2008 How to read the figures: Left-top: % Share of fuel input (TJ) by type (liquid, solid, gaseous, biomass and other fuels) into 1A1a public electricity and heat production. Left-bottom: Implied emission factor for each fuel above (tCO2 / TJ), taken from EEA (2008) Right-top: Average efficiency of transformation in EU-27. Numerator = 101109 Output from district heating plants + 101121 Output from public thermal power stations Denominator = 101009 Input to district heating plants + 101021 Input to public thermal power stations Right-bottom: % Share of CO2 emissions by fuel type (liquid, solid, gaseous, biomass and other fuels into 1A1a public electricity and heat production)
Figure Greenhouse gas emissions in the EU-27 by sector in 2008, and changes between 1990 and 2008 The figures shows the total greenhouse (GHG) emissions in the EU-27 by sector and the changes between 1990 and 2008
Domestic GHG emissions in EU-15 and EU-27 between 1990 and 2008 The figure shows the trends in EU greenhouse gas emissions compared to 1990/base year
Greenhouse gas emissions (Kyoto gases) per country (combustion and non-combustion emissions), 2007 Greenhouse gas emissions (Kyoto gases) per country split between combustion and non-combustion emissions, 2007
Total greenhouse gas emissions by sector (%) in EU-27, 2007 Annual emissions of CO2, CH4, N2O, HFC, PFC and SF6 in the UNFCCC reporting format are converted to their global warming potential GWP (100 year time horizon) for addition and comparison with the Kyoto Protocol targets: 1 t CH4 = 21 t CO2-equivalent, 1 t N2O = 310 t CO2-equivalent, 1 t SF6 = 23 900 t CO2-equivalent. HFCs and PFCs have a wide range of GWPs depending on the gas and emissions are already reported in tonnes CO2-equivalent. International transport emissions (Memo items: international aviation and international maritime transport) are shown in the chart because they are the fastest growing source of emissions in the EU. They are however not included in the national totals reported as part of the national greenhouse gas inventories under the UNFCCC.
Changes (%) in greenhouse gas emissions by source category in the EU, 1990-2007 International bunkers are international transport emissions (Memo items: international aviation and international maritime transport) and are shown in the chart because they are the fastest growing source of emissions in the EU. They are however not included in the national totals reported as part of the national greenhouse gas inventories under the UNFCCC. The sector LULUCF (Land use, land use change and forestry) is not included in the national totals under the UNFCCC either. LULUCF in the EU is a net carbon sink, resulting from higher removals by sinks than emissions from sources. A positive change in LULUCF means a reduction in emissions (i.e. a removal of emissions).
Emissions intensity of sulphur dioxide from public conventional thermal power production Emissions intensity is calculated as the amount of pollutant produced (in tonnes) from public electricity and heat production divided by the output of electricity and heat (in toe) from these plants.
Figure Emissions intensity of carbon dioxide from public conventional thermal power production Emissions intensity is calculated as the amount of pollutant produced (in tonnes) from public electricity and heat production divided by the output of electricity and heat (in toe) from these plants.
Emissions intensity of nitrogen oxides from public conventional thermal power production Emissions intensity is calculated as the amount of pollutant produced (in tonnes) from public electricity and heat production divided by the output of electricity and heat (in toe) from these plants.
Emissions intensity of public conventional thermal power production, EEA-32 The emissions intensity of conventional public thermal power production is the level of Carbon dioxide (CO2), Sulphur dioxide (SO2) or Nitrogen oxides (NOX) emissions per unit of power (electricity and heat) produced by public thermal power stations. The emission intensities are calculated as the ratio of CO2, SO2 and NOX emissions from public power production to the output of electricity and heat from public conventional thermal power production. Public thermal power stations generate electricity and/or heat for sale to third parties, as their primary activity. They may be privately or publicly owned. No data are available for Luxembourg and so data for this country is not included in the chart.
CO2, SO2 and NOx emissions and electricity and heat production, EEA-32 CO2, SO2 and NOx emissions and electricity and heat production in the EEA-32, during the period 1990-2007
Figure Greenhouse gas emissions per capita and per unit of GDP in purchasing power standards in 2008 Climate change mitigation chapter SOER 2010
Figure Fuel use and CO2 emissions from heating in European households Climate change mitigation chapter SOER 2010
Figure Fuel use and CO2 emissions from public electricity and heat production in EU-27 Climate change mitigation chapter SOER 2010
Figure Change in GHG emissions by main gas in EU-27, 1990–2008 and breakdown by gas in 2008 Climate change mitigation chapter SOER 2010
Figure Change in GHG emissions by main sector in EU-27, 1990–2008 and breakdown by sector, 2008 Climate change mitigation chapter SOER 2010
Figure CO2 emissions from diesel and gasoline in the EU-27, 1990–2008 Climate change mitigation chapter SOER 2010
Figure Overview of top decreasing/increasing GHG sources in the EU–27, 1990–2008 Climate change mitigation chapter SOER 2010
Figure Change in greenhouse gas emissions by EU Member States, 1990–2008 and share of emissions in 2008 Climate change mitigation chapter SOER 2010
Figure Absolute GHG emissions in the EU-27, 1970–2009 Climate change mitigation chapter SOER 2010
Estimated impact of different factors on the reduction in emissions of Carbon dioxide (CO2) from public electricity and heat production between 1990 and 2007, EEA-32 The chart shows the estimated contributions of the various factors that have affected emissions from public electricity and heat production (including public thermal power stations, nuclear power stations, hydro power plants and wind plants).
Change in total GHG emissions from transport EU-15 refers to 15 old EU Member States prior to May 2004 (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain, Sweden, and the United Kingdom), EFTA-3 to the three EFTA countries (Liechtenstein, Norway and Switzerland), New EU-12 to 12 new EU Member States as of January 2007 (Bulgaria, Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Romania, Slovakia and Slovenia) and CC-2 to the two candidate countries Turkey and Iceland.
Figure Total GHG emissions from transport EU-15 refers to 15 old EU Member States prior to May 2004 (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain, Sweden, and the United Kingdom), EFTA-3 to the three EFTA countries (Liechtenstein, Norway and Switzerland), New EU-12 to 12 new EU Member States as of January 2007 (Bulgaria, Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Romania, Slovakia and Slovenia) and CC-2 to the two candidate countries Turkey and Iceland.
Sector contributions of ozone precursor emissions (EEA member countries) The contribution made by different sectors to emissions of the tropospheric (ground-level) ozone precursors.
Emission trends of tropospheric (ground-level) ozone precursors (EEA member countries, EU-27) This chart shows past emission trends of nitrogen oxides (NOx), non-methane volatile organic compunds (NMVOC), carbon monoxide (CO) and methane (CH4) in the EEA-32 and EU-27 group of countries. In addition - for the EU-27 - the aggregated Member State 2010 emission ceilings for NOx and NMVOC are shown.
Change in CH4 emissions 1990-2008 (EEA member countries) The reported change in methane (CH4) emissions for each country, 1990-2008.
Contribution to total change in CH4 emissions for each sector (EEA member countries) The contribution made by each sector to the total change in methane (CH4) emissions between 1990 and 2008.
Change in CH4 emissions for each sector 1990-2008 (EEA member countries) Percentage change in methane (CH4) emissions for each sector between 1990 and 2008.
Used in indicators
Indicator Specification
Energy efficiency and energy consumption in the household sector Household energy consumption, covers all energy consumed in households for space heating, water heating, cooking and electricity. Figures are reported either aggregated or disaggregated according to the end use categories named and as a total figure or per dwelling or m 2 of housing area. Climate fluctuates from one year to another. When the data is flagged as climate corrected, the data is normalized to reflect similar weather conditions. Consumption in useful energy per degree-day corrects for difference in heating equipment efficiency (which varies according to the fuel uses) and climate. Energy efficiency indices (ODEX) can be defined as a ratio between the actual energy consumption of the sector in year t and the sum of the implied energy consumption from each underlying sub-sector/ end use in year t (based on the unit consumption of the sub-sector with a moving reference year. The evaluation of energy savings in household is carried out at the level of three end uses (heating, water heating and cooking) and five large appliances (refrigerators, freezers, washing machines, dishwashers and TVs). For each end use, the following indicators are used to measure efficiency progress: heating — unit consumption per m 2 per dwelling equivalent to central heating at normal climate; water heating — unit consumption per dwelling with water heating; and cooking — unit consumption per dwelling. The average energy consumption per m 2 per dwelling equivalent to central heating is used to leave out the impact of the diffusion of central heating. The effect of (heating) behaviour was estimated by assuming that technical progress cannot be reversed Household CO 2 -emissions covers the direct CO 2 emitted by fuel combustion.
Energy efficiency and energy consumption in industry Specific consumption per tonne produced : Energy consumption divided by the physical production (for steel, cement , paper) Energy efficiency index of industry (ODEX) is a weighted average of the specific consumption index of 10 manufacturing branches; the weight being the share of each branch in the sum of the energy consumption of these branches in year t and the sum of the implied energy consumption from each underlying industrial branches in year t (based on the unit consumption of the sub-sector with a moving reference year). CO2 emissions from energy uses split between direct emissions and indirect emissions: Direct emissions refer to emissions from the combustion of coal, gas and oil products (source: EEA inventories 2009); Indirect emissions (or electricity related) refer to emissions in the power sector corresponding to the electricity consumption in the sector Indirect CO2 = E ind/E tot * CO2 ie with E : electricity consumption (ind for industry, tot for all sectors) (source ODYSSEE database); CO2 ie : CO2 emissions from public electricity and heat production ( source EEA, inventories 2009)
Energy efficiency and energy consumption in the transport sector Energy efficiency progress (Figure 1) is measured from the ODEX indicator. This index aggregates the unit consumption trends for each transport mode in a single indicator for the whole sector. It is calculated at the level of 8 modes or vehicle types: cars, trucks, light vehicles, motorcycles, buses, total air transport, rail, and water transport. For cars, energy efficiency is measured by the specific consumption, expressed in litre/100km; for the transport of goods (trucks and light vehicles), the unit consumption per ton-km is used, as the main activity is to move goods; for other modes of transport various indicators of unit consumption are used, taking for each mode the most relevant indicator given the statistics available: toe/passenger for air, goe/pass-km for passenger rail, goe/ton-km for transport of goods by rail and water, toe per vehicle for motorcycles and buses. The variation of the weighted index of the unit consumption by mode between t-1 and t is defined as follows It /It -1= 1/( It -1/It) with : energy share EC i (consumption of each mode i in total transport consumption); unit consumption index UC i (ratio : consumption related to traffic or specific consumption in l/100 km for cars); t refers the current year, t-1 to the previous year. The value at year t can be derived from the value at the previous year by reversing the calculation: It /It -1= 1/( It -1/It) ODEX is set at 100 for a reference year and successive values are then derived for each year t by the value of ODEX at year t-1 multiplied by It /It -1. The energy consumption variation of passenger transport in Figure 4 is broken down into 3 explanatory effects: activity effect (increase in traffic), modal shift effect (from private transport to public transport modes) and energy savings (change in specific consumption per unit of traffic). A positive "modal shift effect" means that the share of public passenger transport in passenger traffic is decreasing (shift from public transport to cars) or the road in total freight traffic is increasing (shift from rail-water to road): this offsets energy savings. CO2 emissions for total transport are split into 2 explanatory effects (Figure 6): an activity effect due to an increase in traffic of passengers and freight, CO2 savings due to the reduction in the specific emissions of vehicles per unit of traffic.
Energy and non-energy related greenhouse gas emissions Annual emissions of CO 2 , CH 4 , N 2 O, HFC, PFC and SF 6 in UNFCCC reporting format (In Mt = million tonnes) converted to their global warming potential (100 year time horizon) for addition and comparison with the Kyoto Protocol targets (1 t CH 4 = 21 t CO 2 -equivalent, 1 t N 2 O = 310 t CO2-equivalent, 1 t SF 6 = 23 900 t CO 2 -equivalent. HFCs and PFCs have a wide range of GWPs depending on the gas and emissions are already reported in t CO 2 -equivalent). For CO 2 only, the (national) totals do not include emissions from biomass burning or emissions or removals from land-use change and forestry (LUCF). The energy sector is responsible for energy-related emissions, such as those arising from fuel combustion activities and fugitive emissions from fuels. Fuel combustion activities include: energy industries, manufacturing industries and construction, transport, other sectors and other stationary or mobile emissions from fuel combustion. Fugitive emissions from fuels include: solid fuels and oil and natural gas. 'Energy production' includes 'Energy industries' (i.e. public electricity and heat production, petroleum refining and the manufacture of solid fuels) and 'Fugitive emissions' (i.e. emissions from production, processing, transmission, storage and use of fuels, in particular coal-mining and gas production). 'Transport' includes road transportation, national civil aviation, railways and navigation, and other non-road transportation. In accordance with UNFCCC and UNECE guidelines, emissions from international aviation and navigation are not included. 'Industry' includes fossil fuel combustion (for heat and electricity) in manufacturing industries and construction (such as iron and steel, and non-ferrous metals). 'Households' includes fossil fuel combustion in households. 'Services sector' includes fossil fuel combustion (for heat and electricity) from small commercial businesses, public institutions, agricultural businesses and military. Non-energy related emissions include 'Industry' (i.e. processes in manufacturing industries and construction without fossil fuel combustion including production and consumption of fluorinated gases), 'Agriculture' (i.e. domestic livestock (dairy and non-dairy cattle) keeping, in particular manure management and enteric fermentation and emissions from soils) 'Waste' (i.e. waste management facilities, in particular landfill sites and incineration plants and 'Other non-energy' (i.e. solvent and other product use).
Emission intensity of public conventional thermal power electricity and heat production Historical emissions of CO 2 , NOx and SO 2 from the reporting format category 1A1a - Public electricity and heat production. Output from public thermal power stations covers gross electricity generation and any heat also produced by public thermal power stations. Public thermal power stations generate electricity and/or heat for sale to third parties as their primary activity. They may be privately or publicly owned. The gross electricity generation is measured at the outlet of the main transformers, i.e. the consumption of electricity in the plant auxiliaries and in transformers is included. Emissions intensity is calculated by dividing the emissions of each pollutant from public electricity and heat production (sector 1A1a) by the output from public thermal power stations.
Emissions from public electricity and heat production - explanatory indicators (ENER 009) Historical emissions of CO2, NOX and SO2 from the common reporting format category 1A1a Public electricity and heat production. Output from public thermal power stations covers gross electricity generation and any heat also produced by public thermal power stations. Public thermal power stations generate electricity and/or heat for sale to third parties, as their primary activity. They may be privately or publicly owned. The gross electricity generation is measured at the outlet of the main transformers, i.e. the consumption of electricity in the plant auxiliaries and in transformers is included.
Energy efficiency and energy consumption in industry Specific consumption per tonne produced : Energy consumption divided by the physical production (for steel, cement , paper) Energy efficiency index of industry (ODEX) is a weighted average of the specific consumption index of 10 manufacturing branches; the weight being the share of each branch in the sum of the energy consumption of these branches in year t and the sum of the implied energy consumption from each underlying industrial branches in year t (based on the unit consumption of the sub-sector with a moving reference year). The 10 branches considered in the calculation are: chemical, steel, non ferrous, cement, other non metallic, paper, food, machinery, transport equipment and textile. For steel, cement and paper, energy savings are calculated using specific consumption per tonne produced; for the other branches, the indicator used is the ratio on energy consumption related to production index. The variation of the weighted index of the unit consumption between t-1 and t is defined as follows: It -1/It = SUMi ECi,t *(UCi,t/UCi.t-1) with : energy share EC i (consumption of each branch i in total industry consumption); unit consumption index UC i (ratio : consumption related to production index or ratio : consumption related to physical production of steel, cement and paper) t refers the current year, t-1 to the previous year The value at year t can be derived from the value at the previous year by reversing the calculation: It /It -1= 1/( It -1/It) ODEX is set at 100 for a reference year and successive values are then derived for each year t by the value of ODEX at year t-1 multiplied by It /It -1 CO 2 emissions from energy uses split between direct emissions and indirect emissions: Direct emissions refer to emissions from the combustion of coal, gas and oil products (source: EEA inventories 2009) Indirect emissions (or electricity related) refer to emissions in the power sector corresponding to the electricity consumption in the sector Indirect CO 2 = E ind/E tot * CO 2 ie with E : electricity consumption (ind for industry, tot for all sectors) (source ODYSSEE database); CO 2 ie : CO 2 emissions from public electricity and heat production ( source EEA, inventories 2009) CO 2 emissions from energy uses split between direct emissions and indirect emissions: Direct emissions refer to emissions from the combustion of coal, gas and oil products (source: EEA inventories 2009); Indirect emissions (or electricity related) refer to emissions in the power sector corresponding to the electricity consumption in the sector Indirect CO 2 = E ind/E tot * CO 2 ie with E : electricity consumption (ind for industry, tot for all sectors) (source ODYSSEE database); CO 2 ie : CO 2 emissions from public electricity and heat production ( source EEA, inventories 2009)
Energy efficiency and energy consumption in the transport sector Energy efficiency progress (Figure 1) is measured from the ODEX indicator. This index aggregates the unit consumption trends for each transport mode in a single indicator for the whole sector. The energy consumption variation of passenger transport in Figure 5 is broken down into 3 explanatory effects: activity effect (increase in traffic), modal shift effect (from private transport to public transport modes) and energy savings (change in specific consumption per unit of traffic). A positive "modal shift effect" means that the share of public passenger transport in passenger traffic is decreasing (shift from public transport to cars) or the road in total freight traffic is increasing (shift from rail-water to road): this offsets energy savings. CO2 emissions for total transport are split into 2 explanatory effects (Figure 7): an activity effect due to an increase in traffic of passengers and freight, CO2 savings due to the reduction in the specific emissions of vehicles per unit of traffic.
Energy efficiency and energy consumption in the household sector Household energy consumption, covers all energy consumed in households for space heating, water heating, cooking and electricity. Figures are reported either aggregated or disaggregated according to the end use categories named and as a total figure or per dwelling or m2 of housing area. Climate fluctuates from one year to another. When the data is flagged as climate corrected, the data is normalized to reflect similar weather conditions. Consumption in useful energy per degree-day corrects for difference in heating equipment efficiency (which varies according to the fuel uses) and climate. Energy efficiency indices (ODEX) can be defined as a ratio between the actual energy consumption of the sector in year t and the sum of the implied energy consumption from each underlying sub-sector/ end use in year t (based on the unit consumption of the sub-sector with a moving reference year. Household CO2-emissions covers the direct CO2 emitted by fuel combustion.
Energy efficiency in transformation EU-27 Share of primary energy by fuel type and, share of final energy consumption by sector and energy losses Share of energy losses, own consumption of the energy industry and final energy available for final consumption in primary energy, by Member State Structure in the efficiency of transformation and distribution of energy from primary energy consumption to final energy consumption, EU-27, 2009 Structure of CO 2 emissions from thermal power plants in EU-27, 2009 % share of input fuels into conventional thermal power plants Implied emission factors by fuel type – total fuel input by type to conventional thermal power plants (TJ) divided by CO 2 emissions from plants by fuel type Average efficiency for conventional thermal plant (total fuel inputs divided by total electricity and heat output) Share of CO 2 emissions by input fuel type. CO 2 emission savings per year for EU-27 at different transformation efficiencies compared to current 2009 efficiency
Energy and non-energy related greenhouse gas emissions
Emissions of ozone precursors This indicator tracks trends since 1990 in anthropogenic emissions of ozone precursor pollutants: nitrogen oxides (NO x ), carbon monoxide (CO), methane (CH 4 ) and non methane volatile organic compounds (NMVOCs), each weighted by their respective tropospheric ozone-forming potential. The indicator also provides information on the sources of emissions from a number of sectors: Energy industries; road and other transport; industry (processes and energy); other (energy); fugitive emissions; waste; agriculture and other (non energy).
Greenhouse gas emission trends This indicator presents anthropogenic greenhouse gas emissions in Europe from 1990 onwards. It analyses the trends (total and by sector) in relation to the European Community and Member States Kyoto targets for the period 2008-2012. Definitions (from UNFCCC) Emissions: the release of greenhouse gases and/or their precursors into the atmosphere over a specified area and period of time. Greenhouse gases: those gaseous constituents of the atmosphere, both natural and anthropogenic, that absorb and re-emit infrared radiation. Sink: any process, activity or mechanism which removes a greenhouse gas, an aerosol or a precursor of a greenhouse gas from the atmosphere. Source: any process or activity which releases a greenhouse gas, an aerosol or a precursor of a greenhouse gas into the atmosphere. Emissions by sources and removals by sinks of greenhouse gases are calculated according to the Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories (see Methodology ), as agreed upon by the Conference of the Parties to the UNFCCC. Scope Gases All the greenhouse gases covered by the Kyoto Protocol (CO 2 , CH 4 , N 2 O, SF 6 , HFCs and PFCs). This does not include the greenhouse gases that are also ozone-depleting substances and which are controlled by the Montreal Protocol (see CSI 006 ). In order to be aggregated, non-CO 2 gases are weighed by their respective global warming potential and presented in CO 2 -equivalent units. Emission sources The indicator provides information on emissions from the main anthropogenic greenhouse gas sources, distributed by main emitting sectors (according IPCC nomenclature): energy supply and use (including energy industry, fugitive emissions, energy use by industry and by other sectors, excluding the transport sector); transport; industry (processes, i.e. not including emissions from fossil fuel combustion for energy use); agriculture; waste; other (non-energy). Unless otherwise mentioned, the indicator does not cover emissions from international bunkers (international aviation and maritime transport), which are not covered by the Kyoto Protocol. In particular, these emissions are not taken into account in the total greenhouse gas emissions reported at national and EU levels. Emissions from land use, land-use change and forestry (LULUCF) are not included in total greenhouse gas emissions. Geographical area The indicator covers all 27 Member States from the European Union. Some figures also include information concerning other EEA Member States. Period covered The indicator covers annual emissions since 1990.
Emissions of ozone precursors (version 1) This indicator tracks trends since 1990 in anthropogenic emissions of ozone precursors: Nitrogen oxides, carbon monoxide, methane and non methane volatile organic compounds, each weighted by their tropospheric ozone-forming potential. The indicator also provides information on emissions by sectors: Energy industries; road and other transport; industry (processes and energy); other (energy); fugitive emissions; waste; agriculture and other (non energy).
69c4be530d66541bbadc5dae4cd7b33c
DAT-13-en
08 Jun 2009 - National emissions reported to the UNFCCC and to the EU Greenhouse Gas Monitoring Mechanism
03 Feb 2007 - National emissions reported to the UNFCCC and to the EU Greenhouse Gas Monitoring Mechanism
27 Jan 2007 - Trends in emissions of greenhouse gases (IPCC sector classification)
20 Dec 2004 - Trends in emissions of greenhouse gases (IPCC sector classification)
26 Jul 2004 - Trends in emissions of greenhouse gases (IPCC sector classification)
Austria Belgium Bulgaria Croatia Cyprus Czechia Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Italy Latvia Liechtenstein Lithuania Luxembourg Malta Netherlands Norway Poland Portugal Romania Slovakia Slovenia Spain Sweden Switzerland Turkey United Kingdom
For references, please go to https://www.eea.europa.eu/data-and-maps/data/national-emissions-reported-to-the-unfccc-and-to-the-eu-greenhouse-gas-monitoring-mechanism-4 or scan the QR code.
PDF generated on 20 Jan 2022, 06:02 AM
Filed under: PFC CO2 CSI SF6 air emissions N2O HFC ghg emissions methane
Filed under: PFC, CO2, CSI, SF6, air emissions, N2O, HFC, ghg emissions, methane
Code for developers


text:
Q: Missing x-axis group names in ggplot2 I'm trying to output a figure but cannot get the group name labels on the x-axis.
My file looks like this (there are 28 groups for description and 4000 for phenotype):
> head(phe)
  description                                phenotype                        p
1 Psychiatric Attention deficit hyperactivity disorder 0.1100099999999999966782
2 Psychiatric Attention deficit hyperactivity disorder 0.5403200000000000224887
3 Psychiatric Attention deficit hyperactivity disorder 0.3870999999999999996447
4 Psychiatric                 Autism spectrum disorder 0.6267700000000000493117
5 Psychiatric                         Bipolar disorder 0.3073100000000000275868
6 Psychiatric          Anxiety disorder (case/control) 0.5001299999999999634781
3939 Neurological               Retrolenticular part of internal capsule radial diusivities 0.14951999999999998625100
3940 Neurological                            Splenium of corpus callosum radial diusivities 0.26679999999999998161471
3941 Neurological                                Superior corona radiata radial diusivities 0.54986999999999996990852
3942 Neurological                   Superior fronto-occipital fasciculus radial diusivities 0.28690999999999999836575
3943 Neurological                       Superior longitudinal fasciculus radial diusivities 0.59540999999999999481304
3944 Neurological                                       Sagittal stratum radial diusivities 0.04544200000000000322364
3945 Neurological                                    Uncinate fasciculus radial diusivities 0.37778000000000000468958

and my code looks like this:
ylim <- abs(floor(log10(min(phe$p)))) + 2
nCHR <- length(unique(phe$description))

axis.set <- phe %>%
  group_by(description) %>%
  summarize(center = n() / 2)
sig=0.05/nrow(phe)

phewasplot <- ggplot(phe, aes(x=phenotype, y=-log10(p), label=description, color=as.factor(description), size=-log10(p))) +
  geom_point(alpha=0.75) +
  geom_hline(yintercept = -log10(sig), color = "grey40", linetype = "dashed") +
  scale_x_discrete(label = axis.set$description, breaks = axis.set$center) +
  scale_y_continuous(expand = c(0,0), limits = c(0, ylim)) +
  scale_size_continuous(range = c(0.5,3)) +
  labs(x = "Phenotypes",
       y = "-log10(p)") +
  theme_minimal() +
  theme(
    legend.position = "none",
    panel.border = element_blank(),
    panel.grid.major.x = element_blank(),
    panel.grid.minor.x = element_blank(),
    axis.text.x = element_text(angle = 90, size = 8, vjust = 0.5)
  )

Essentially what I have is this:

What I actually want is something like this:

redpajama_set_name: RedPajamaStackExchange


I am Canadian and going to Belize for 5 months. I understand I need to get a 90 day visa and then report to an immigration office in San Pedro once a month. Is this correct? Also, I am near Toronto...Do I go to Embassy of Belize for application?
There is no 90 day visa, you get 30 days renewable indefinitely.
Thats not true. Its not indefinitely. After 6 months they will start asking for proof of income, and can and have revoked any further visas if you cant comply. They may not do this to everyone but they do it to a lot.
Yes, I agree, you have to renew every 30 days........but I thought that you could do that for 12 months.........correct me if I'm wrong.
but all you do is go to Mex/Guat for a day or so and return. Clock starts ticking again.
That won't work always: I once went to Tikal twice in a row and by re-entering Belize the second time, the immigration officer gave me a 2 week visa, stating "I was traveling up and down too much". No discussion.
You have to go to immigration every month. First 6 months it costs 50 BZD after that 100 BZD every time. Theoretically you can do that indefinitely, but the longer you stay without applying for PR or work permit, the more questions they will ask.
If you're travelling with a Canadian passport, you don't need to apply for a visa before leaving Canada or entering Belize.
When you land at the airport in Belize, your first stop is Immigration where your passport will be stamped (half-page size) allowing a maximum stay of 30 days -- no fee. Note that it's 30 days and not one month. If coming from Mexico, it will be a similar procedure.
On the last working day before the 30 days is up, go to the nearest Immigration office and ask for a new stamp (another half-page in your passport). You might be asked to show your return ticket and proof of funds (I never was, but you will have to provide your address in Belize) so be prepared for that possibility.
The fee for the new stamp is BZ$50 per stamp for the first 6 months and then BZ$100 per stamp (unless the fees have changed recently).
An Immigration office is located in each of the six Districts of Belize, and there's one on Ambergris Caye.
You won't need to leave Belize in order to get a new stamp, but you might want to make a trip to Mexico or Guatemala during your stay. In that case, I'd time those trips to begin when one of the monthly stamps is about to expire. When you return to Belize, you might get a new stamp for free (but you might not).
The border by Guat is dicey for new visas. That is where Debbie was hassled.
There is a sizable gringo community there who skips the visa thing by traveling in Guat and expecting a new visa after each trip.
The Mex border is a better choice.
You may not like San Pedro Immigration. If you go there they will not let you go to the city after that to renew after thirty days.
We always got new visas in the city.
Last edited by Dane; 04/25/14 11:50 AM.


This page is to create awarness for people to know what happens at the time of removal. At the time of transaction we provide a unique reciepts that is only made for Old Cars Recycling Pty Ltd. We take care of all the paper work and provide you back the plates and registration, for an online RTA disposal enquiry Click here .
We Recycle Old, Damaged Cars to create a sustainable environment where future generations be satisfied.
We value customer feedback and comments to create a better service.
If you want a sustainable environment and to use our Free Car Removal Service and to get Cash For Scrap Cars don't forget to call us on 0456 878 334 or fill in the Form and we will get back to you as soon as possible.


So last night, Megan and i spent quite awhile discussing her idea for a "telephone"-type story that adults could do. We decided that doing such a thing via e-mail with a moderator, a few rules and an opt-in group of writers would be best and that it would probably even work. cool, huh? So soon, well be posting/e-mailing out a massive request to get writers for this project.
In the meanwhile, Im going to be working on my own new project a little, hoping to start witha solid and interesting introduction to one of the characters. Also, I have to get my script printed out to PDF today–thats the next step towards getting it produced. Sometimes the little steps are the biggest pains to take.


I just stumbled across someone else who is having the same issue as me…when my Macbook wakes up from sleep I can no longer double-tap to right click. Seems petty, but it has an insane ability to piss me off. Well, knowing that someone has had to put up with the same problem, I was driven to come up with a simple fix.
This will re-enable secondary clicking every minute (poor solution, but it works). If someone knows if it's possible to trigger a script when coming out of sleep/hibernate, please let me know in the comments.


With Quota Control, you can control how many respondents do you want for each option in your survey. For example, if you would like to have an equal distribution of males and females in your survey, and you are sending out your survey to 100 people: Quota Control allows you to put a limit on the number of people responding to each option and optionally terminating the survey based on the criteria.
In the following example, if the "Male" option is chosen more than 3 times, the survey is terminated for those respondents.
How do I enable Quota Control?
Check the box Enable Quota and set up the required Quota under Quota Limit. Select the branching options (Terminate Survey / Quota Overlimit / Thank You page). And click 'Save Logic'.
What is 'Enable Minimum Quota'?
'Enable Minimum Quota' option is only applicable to Multi-select question type. When 'Enable Minimum Quota' is enabled for multi-select question, if the respondent selects more than one option but one of the option's quota is full and the other options they select would allow them to continue, survey will not terminate and user will be allowed to continue to next question.
For example for the question given below if the respondent only select Visa when the quota is full survey will terminate for over quota. If respondent selects Visa and Mastercard and only the Visa quota is full, both answers will be recorded in the data and the respondent will continue to next question.
How can I enable 'Minimum Quota' for multi-select question?


Fuel Storage Services for the non-retail market is our "niche." Our complete turnkey services, coupled with our extensive experience with the unique requirements of the non-retail market of this industry (usually governmental and large private fleets), give us a real edge in designing and building the right solution for your facility. We specialize in the design, maintenance, repair, removal and construction of underground and aboveground storage tank systems (USTs/ASTs).
CEI is intimately familiar with the existing Storage tank regulations, including all aspects of the permitting, regulatory inspection and regulatory enforcement process.
CEI's tank design/build projects have included installation of conventional (e.g., E10) and alternative technology (e.g., biodiesel) petroleum systems.
We designed and managed the removal of approximately 1,725 linear feet of underground waste oil piping and the replacement of 13 underground storage tanks at an active and congested bus maintenance facility.


Combining many loves.. poached eggs with melted leeks. This is breakfast for dinner on crack.
Fun factoid – the Welsh first joined forces with that delicious Allium, the leek, during a battle against those pesky Saxon invaders under the direction of.. Saint David! They wore them to identify who was a fellow Welshman to prevent crossfire. Clever Cymru. Yay for Wales! Cymru am byth! Eat welshcakes… et cetera. The leek is such a glorious vegetable it deserves celebrating more than once a year on St. David's Day. Like a giant, milder, sweeter spring onion, it makes a great bedfellow with my other great love… butter.
I first cooked this recipe before the publication of Thomasina Miers' Home Cook, she'd featured this recipe in her then weekly column, The weekend cook.
Given my penchant for eggs and breakfast food any time of the day, I had to try this recipe for poached eggs with melted leeks and chipotle-tahini dressing. True to the ethos of Home Cook, the recipe was reasonably fuss-free but SO delicious. Surprisingly, the recipe only has two ingredients that could be a bit of a faff to source. I've had some Za'atar lurking in my store cupboard for too long so was thankful to open it finally. I made an approximation of the Chipotle in Adobo by making a quick mix of tomato puree, white wine vinegar, smoked paprika, cumin, garlic and oregano. This quick mix saved me from having to locate a paste that would inevitably just sit turning rancid in my fridge.
With the leeks melting in some salted butter, I quickly made the dressing while the poaching pan was coming to a boil. The dressing was little more than a quick fork together. The only think left to do was poach the eggs and toast the bread. Simple indeed. Poaching was a method of egg cooking I've avoided till I discovered Dan Doherty's seemingly foolprood method in Toast Hash Roast Mash (the man knows his eggs). The rest was just a haphazard assembly job. Its nigh on impossible to make splodges of dressing and poached eggs look elegant so I won't lose much sleep over the mess posted below.. As you can see, I used good old granary bread instead of Miers' sourdough because it's a midweek evening and I'm not going to any artisan bakeries after work.
My God though, messy as it looked, it was GOOD EATING. The dressing was an absolute knockout. Citrussy, hot, nutty, smoky and a bit creamy. It really elevated the dish. Miers' said this dish was influenced by her Mexican travels (chipotle), her time around Shepherd's Bush (tahini) and her Nan in Wales (leeks). True fusion food. I wasn't convinced it would really work together. It is after all like eating hummus and eggs. Like some sort of wondrous gastronomic alchemy, it's a knockout. The dressing would also be great to liven up a sad salad or as a party dip. Perhaps a bit too punchy to just spoon into one's mouth although I did give this a good go.
The full recipe can be found here, or alternatively buy the cookbook for more Breakfast for Dinner ideas.


text:
Q: why it throws java.lang.classCastException this is my class and I want to sort my stack but it will throw an exception please help me thanks!
public class jj {
    public static void main(String[] args){
        Stack<Integer> s = new ImplimentingAStackUsingAnArrayOfAGivenSizeN(5);
        s.push(1);
        s.push(3);
        s.push(5);
        s.push(2);
        s.push(4);
        Collections.sort((List<Integer>) (s));
        System.out.println(s);
        while (!s.isEmpty()) {
            System.out.println(s.pop());
        }
    }
}

the stack traces:
Exception in thread "main" java.lang.ClassCastException:
datastructurechapter5.ImplimentingAStackUsingAnArrayOfAGivenSizeN
cannot be cast to java.util.List at datastructurechapter5.jj.main(jj.java:24)
   `Collections.sort((List<Integer>) (s));`
Java Result: 1
BUILD SUCCESSFUL (total time: 2 seconds)

A: I'd assume you are using (and extending) a wrong Stack. Make sure you have
import java.util.Stack;

If the Stack is some class of yours, you'd have to define it to impelement List:
public class Stack implements List {..}

But that would be a lot of work, so use java.util.Stack
Note: As Jesper commented, you'd better use java.util.Deque (perhaps ArrayDeque)


text:
У́лица Со́фьи Ковале́вской — улица в южной части города Ярославля, в посёлке Тропино. Проходит от Ямской улицы до Туговской.

История
Образована в 1954 году. Названа в честь Софьи Ковалевской (1850—1891) — математика и механика, первой в мире женщины-профессора.

Улица имеет частную застройку.

Ссылки

 Улица на карте Яндекс Улица на карте Google

Примечания

Софьи Ковалевской
Улицы по алфавиту

redpajama_set_name: RedPajamaWikipedia


"The Beyond" not only used to have another title, but its director used to have another name. First released in 1981 as "Seven Doors of Death," directed by Louis Fuller, it now returns in an "uncut original version" as "The Beyond," directed by Lucio Fulci.
Fulci, who died in 1996, was sort of an Italian Hershell Gordon Lewis. Neither name may mean much to you, but both are pronounced reverently wherever fans of zero-budget schlock horror films gather. Lewis was the Chicago-based director of such titles as "Two Thousand Maniacs," "She-Devils on Wheels" and "The Gore-Gore Girls." Fulci made "Zombie" and "Don't Torture the Duckling." Maybe that was a temporary title, too.
"The Beyond" opens in "Louisiana 1927," and has certain shots obviously filmed in New Orleans, but other locations are possibly Italian, as was (probably) the sign painter who created the big "DO NOT ENTRY" sign for a hospital scene. It's the kind of movie that alternates stupefyingly lame dialogue with special effects scenes in which quicklime dissolves corpses and tarantulas eat lips and eyeballs.
The plot involves ... excuse me for a moment, while I laugh uncontrollably at having written the words "the plot involves." I'm back. The plot involves a mysterious painter in an upstairs room of a gloomy, gothic Louisiana hotel. One night carloads and boatloads of torch-bearing vigilantes converge on the hotel, and kill the painter while shouting, "You ungodly warlock!" Then they pour lots of quicklime on him, and we see a badly made model of his body dissolving.
Time passes. A woman named Liza (played by Catriona MacColl, who was named "Catherine" when the director was named "Louis"), inherits the hotel, which needs a lot of work. Little does she suspect it is built over one of the Seven Doors of Evil that lead to hell. She hires a painter, who falls from a high scaffold and shouts "The eyes! The eyes!" Liza's friend screams, "This man needs to get to a hospital!" Then there are ominous questions, like "How can you fall from a 4-foot-wide scaffold?" Of course, one might reply, one can fall from anywhere, but why did he have a 4-foot-wide scaffold? Next Liza calls up Joe the Plumber (Giovanni de Nava), who plunges into the flooded basement, wades into the gloom, pounds away at a wall, and is grabbed by a horrible thing in the wall, which I believe is the quicklimed painter, although after 50 years it is hard to make a firm ID.
Let's see. Then there is a blind woman in the middle of a highway with a seeing-eye dog, which later attacks her (I believe this is the same woman who was in the hotel in 1927), and a scene in a morgue, where the wife of one of the victims (the house painter, I think, or maybe Joe) sobbingly dresses the corpse (in evening dress) before being attacked by acid from a self-spilling jar on a shelf.
But my favorite scene involves the quicklime-decomposed corpse, which is now seen in a hospital next to an oscilloscope that flat-lines, indicating death. Yes, the rotting cadaver is indeed dead--but why attach it, at this late date, to an oscilloscope? Could it be because we'll get a shot in which the scope screen suddenly indicates signs of life? I cannot lie to you. I live for moments like that.
Fulci was known for his gory special effects (the Boston critic Gerald Peary, who has seen several of his films, cites one in which a woman vomits up her intestines), and "The Beyond" does not disappoint. I have already mentioned the scene where the tarantulas eat eyeballs and lips. As the tarantulas tear away each morsel, we can clearly see the strands of latex and glue holding it to the model of a corpse's head. Strictly speaking, it is a scene of tarantulas eating makeup.
In a film filled with bad dialogue, it is hard to choose the most quotable line, but I think it may occur in Liza's conversations with Martin, the architect hired to renovate the hotel. "You have carte blanche," she tells him, "but not a blank check!" The movie is being revived around the country for midnight cult showings. Midnight is not late enough.


text:
ODV / Obituaries
FUNERAL PRINTING
GEO Marker
(click the image to view the full program)
John Edward Norman 1955 – 2021
John Edward Norman
March 17, 1955 – April 28, 2021
John Edward Norman 66, of Beaumont, TX; passed Apr. 28, 2021.
A Memorial Service will be held 10AM, May 08, 2021 at Proctor's Mortuary 3520 Washington Blvd. Beaumont, TX.
John was born in Beaumont, Texas on March 17, 1955 to Elnora Jules-Norman-Robinson and Roosevelt Norman Sr.
John grew up in The Pear Orchard neighborhood Of Beaumont, Texas. John attended Hebert high school where he participated in football. John Graduated from Hebert High School in the year of 1973. John was known for his very enthusiastic spirit. Growing up John and his brothers better known as "The Norman Boys" learned and perfected their craft in carpentry work and roofing. John continued this work all throughout his adult life as well. John was called home on April 28, 2021 at his family's Homestead in Beaumont Texas.
John was preceded in death by his parents Elnora Jules-Norman-Robinson, Roosevelt Norman Sr, his step father James Robinson, His brother Murray Norman and His sister Florence Norman.
John leaves behind his children Yolanda Viney, Terell Norman and Melaney Norman-Smith(George) all of Dallas, Texas. His grandchildren Nyla Viney, Damien Martinez, and Kobie Norman all of Dallas, Texas; he leaves behind a great friend and the mother of his children Marie Viney of Dallas Texas. John also leaves behind his siblings Roosevelt Norman Jr (Lori), Mary Norman-Davis-Mitchell(Larry), and Lawerence Norman all of Beaumont Texas and Shelia Lightfoot-Plumbar(Sylvester) of Houston Texas. John also leaves behind an aunt, a host of nieces, nephews, cousins, and friends.
Share your condolences:
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Call 832-819-5663 for more information about Design and Print Services in Southeast Texas

redpajama_set_name: RedPajamaCommonCrawl


text:
Красное — озеро в Койбальской степи в Бейском районе Хакасии. Одно из искусственно созданных при строительстве Койбальской оросительной обводнительной системы на базе большого озера с солоноватой водой до 2,5 г/литр, известное как Эстонское (по названию существовавшего до 1950-х поселения на его берегах).

Находится в 75 километрах от Абакана и 4 километрах от села Новониколаевка.

Играет роль водоприёмника сбросных вод из Уйской оросительной системы. В системе орошения озеро — аварийный водоприёмник из магистрального канала Койбальской оросительной системы. С созданием Койбальской оросительной системы к ранее существовавшим функциям озера добавились функции обводнительные.

Площадь водного зеркала — 0,77 км², объём воды — 1,3 км³, длина береговой линии около 4 км, максимальная глубина — до 10 м.

На берегах озера — несколько животноводческих построек, зарыбляется сиговыми породами и используется для полива пастбищ.

Также в озере водится сазан, плотва, окунь и карась.

Литература
 Энциклопедия Республики Хакасия : [в 2 т.] / Правительство Респ. Хакасия; [науч.-ред. совет.: В. А. Кузьмин (пред.) и др.]. — Абакан : Поликор, 2007. Т. 1 : [А — Н]. — 2007. — 430, [2] с. : ил., портр. — Библиогр. в конце слов. ст. — С. 312.

Озёра Бейского района
Бассейн Енисея


The Insurance Place, Inc. is committed to providing its customers with superior service for all of their insurance needs and treating all people with respect and understanding. There are other agencies who provide insurance, but none of them offer the service you can expect from The Insurance Place, Inc. Our mission is to help you identify your business and personal insurance needs, and then find the most cost-effective solutions available.
The Insurance Place, Inc. was founded by Lori Schultz in 1983 as an independent insurance agency. The company remains family-owned and operated. Her business has always been located in Lakewood; however, the agency serves clients throughout the state of Colorado.
I am proud to say I grew up in the great state of South Dakota, specifically Mitchell – home to the world's only Corn Palace! I moved to Lincoln, Nebraska and started my insurance career in the claims department of Union Insurance. In 1974, I moved to Colorado and worked at a Lakewood insurance agency for over 7 years. I started The Insurance Place, Inc. on July 1, 1983! I have two daughters and then gained another daughter and son when I married Jim Ziegler. Together we now have 4 grandchildren. I love to travel, especially to Florida to be able to walk along the beach. Tex, our office mascot, joined the family in 2011 and loves his self-appointed role of agency welcoming committee.
Before joining The Insurance Place, I worked for over 34 years in manufacturing and high tech. When not working on insurance, I enjoy music, popular science, reading, swimming, golf, cycling, and most especially, grandchildren! With the grandkids Lori and I can enjoy crafts, Calvin & Hobbs, soccer, football, Dork Diaries, guitar playing, Goodnight Moon, swimming and snow skiing. YouTube keeps me up to date on science developments in quantum field theory, physics and string theory. YouTube is also great in the gym for watching the Rat Pack, Perry Mason, Rocky & Bullwinkle and on and on. I am also the dedicated family resource for fixing computer problems.
I started working for Lori in 2004, after working for Safeco Insurance for five years in a variety of positions, including claims, policy service, and quality assurance. I have really enjoyed the small office environment where we can get to know our customers and help them find the coverage they need. I grew up as the youngest of a large family from a small Iowa town. In 2014, all 44 of us got together in Nags Head, NC to celebrate my parents 80th birthdays & 60th wedding anniversary. I moved to Colorado in 1998 with my daughter, Jaci. She is now off to college in Boston, so I find myself talking a lot more to our dog, Aysia, and spending more time on the garden. I also enjoy volunteering in the nursery at church to get my baby fix. I love that Denver is such a sports town and cheer for all the local teams, unless the Broncos are playing my longtime favorites, the San Francisco 49ers!
I am originally from Kentucky and first started working in insurance in 1993 when my husband and I were newly married and moved to the Denver area. I worked for The Insurance Place a majority of my time in Denver until we relocated to Nebraska in 2001. For the next 10 years, I worked as an administrative assistant, substitute teacher, and Starbucks barista as we got to experience living in areas such as Cody, WY, Seattle, and Las Vegas. In 2011, we came back to Denver and I was able to rejoin Lori & Jim as the account manager for commercial lines. I now enjoy working for The Insurance Place remotely. In 2014, our family decided to embrace the mobile lifestyle more fully, so moved into a fifth wheel camper and hit the road. Our "home on wheels" is currently parked in sunny Golden Valley, AZ, approximately 15 miles from Kingman. Our family, which now includes our son, James, and his boxer, Sugar, are thoroughly enjoying the warmer temperatures of the desert winter! I love the flexibility of being able to work with the great staff at The Insurance Place and still be able to see the world with my family.
I was born and raised here in Colorado with my 3 brothers. I came from a large family. Now, I have a family of my own which includes my husband, 2 boys and 1 daughter, the youngest. I have been working for The Insurance Place since 2012. Before coming to work here I was a stay at home parent, which is a full time job in itself. My time away from work is spent with my children's education and sports activities. I am very proud to say that my kids excel in their academics, as well as their sports. Our weekends, and some weekdays, are filled with golf lessons, baseball, football, and softball along with dance/cheerleading for my fashionista daughter. I am also a team mom for my youngest son's football team, while my husband is the Tiny Mite and flag football director of our sports organization.
I am Lori's oldest daughter and, over the years, I have moved up from stamping files as a little girl to a licensed agent. Working for a small independent insurance agency is enjoyable because I have the opportunity to develop relationships with our clients and better understand their insurance needs. I also enjoy the flexibility of working for The Insurance Place, Inc. remotely. I live on a small farm in Berthoud, CO with my husband, 2 sons, and growing list of animals (2 dogs, 1 cat, 1 fish, 4 goats, 1 llama, 5 rabbits, 3 ducks, and 40+ chickens). The dairy goats are my favorite! I am gardening and learning to can, as well as making new types of cheese. Also, some of our clients may remember Layla, my black Lab and our first office mascot. Layla loves being able to chase her ball on the farm. No one has been able to throw it all the way across our property yet!
I am Lori's youngest daughter and started working at The Insurance Place in 2009. I have been working hard on helping us transition the old paper files to electronic documents. I have also learned the agency bookkeeping to make sure that our customers' payments are accurately recorded. When not working, I enjoy visiting my dad and dog, Lana, in Idaho to take advantage of the great outdoors. I graduated from Red Rocks Community College a couple years ago. I still care for Sunny, my 28 year old snake, which was my kindergarten classroom pet. I love attending races at Bandimere, so you may see me there during the summer.


text:
'use strict';

var header = require('./');

describe('basicAuthHeader(user, pass)', function(){
  describe('with a password param', function(){
    it('should return the password in the base64 encoding', function(){
      var expected = 'Basic ' + (new Buffer('user:pass')).toString('base64');
      header('user', 'pass').should.eql(expected);
    });
  });

  describe('without a password param', function(){
    it('should not return the password in the base64 encoding', function(){
      var expected = 'Basic ' + (new Buffer('user')).toString('base64');
      header('user').should.eql(expected);
    });
  });
});

redpajama_set_name: RedPajamaGithub


text:
Q: Why do some websocket connections to localhost work in Firefox but not in Chrome? I'm working on a project with a React frontend that talks to an express backend.  The client makes REST calls as well as websocket connections to the server.  The client is using react-use-websocket to make the socket connection and the server is using ws to handle it.
In the dev environment, the express server and a webpack dev server (via Create React App) are running in a node 16 docker container, serving the page on localhost:3000.
When using Firefox 102, everything works fine.  The server returns the page, the client code makes the websocket connection to ws://localhost:3000/user and then starts receiving messages.
When using Chrome 103, the server returns the page, but the websocket never connects.  It sits there in a pending state and eventually times out.  react-use-websocket then tries to open it again, with the same result.  I added listeners to the hook and do see error and close events.  The error doesn't contain any info.  The close event shows { isTrusted: true, wasClean: false, code: 1006, reason: '', type: 'close' }.  Code 1006 seems to mean that the browser closed the connection "abnormally", but the reason is blank.
With Chrome, the server never seems to get the upgrade event that's part of connecting the websocket, so it seems like the browser is blocking the connection entirely.
What's strange is that the webpack live reload socket connection works just fine in Chrome.  It makes a call to ws://localhost:3000/sockjs-node and gets the Upgrade response, with a status of 101 Switching Protocols.  It then receives its normal messages.
Any idea why webpack's socket connection works in Chrome but the client's doesn't?  This clearly isn't just a Chrome vs. Firefox issue, as webpack works, so there must be some way to configure the socket so that Chrome will let it through to localhost.  AFAICT, the requests are sending the same headers in both cases.


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ACTUAL CASE HISTORY*: We hear it, see it, read it and are told it nearly every day: "At will employment means that you can be fired at any time for any reason." You see it in Employee Handbooks. You hear it in discussions and negotiations. You even read it in Court decisions.
Those who know the truth understand that the so-called "At Will" doctrine of employment is way overblown. It has many, many exceptions, limitations and conditions, and more "holes" are created in this outdated concept each and every day by intelligent legislators, wise judges and fed-up juries.
Instead, understand that there are legally acceptable – as well as legally unacceptable – times to terminate an employee's job.
And understand, too, that there are legally acceptable – as well as legally unacceptable – reasons to terminate an employee's job.
The list below of "117 Reasons an 'At Will' Employee Cannot Be Fired" sets forth many of the limitations, conditions and exceptions to "At Will" employment. And this list is not exhaustive; many, many more limitations, conditions and exceptions exist. I'd estimate there are hundreds, if not thousands, of more reasons, too. They can be found in municipal ordinances, city statutes, agency regulations, decisions by Judges and verdicts of juries. And more will inevitably arise as time goes on based on common sense, fundamental fairness, and basic civil, human and moral rights.
Don't believe "The Big 'At Will' Lie." If you do, you'll be deceived into believing you have no way to stand up for yourself if your employment is terminated. And that would be a shame, for standing up for yourself at work – and standing up for what is right at work – is far easier today than it has ever been before.
So, next time you or a close one are terminated at work, don't accept "We can do anything we want because you are an 'at will' employee," because it is just not true.
WHAT YOU CAN DO: Review this "brief " list of "117 Reasons an 'At Will' Employee Cannot Be Fired." And always remember that there exist many more exceptions, conditions and limitations of an employer's ability to terminate an employee's job.
If an employment agreement purports to create an "at will" employment relation, but provides the employee a certain "term" of employment.
If an agreement purports to create an "at will" employment relation, but provides that the employer will give the employee a certain "notice" before firing.
If an agreement purports to create an "at will" employment relation, but provides that the employer will permit the employee some kind of "hearing" before termination.
If an agreement purports to create an "at will" employment relation, but provides that the employer will provide the employee some kind of appeal process before termination.
If an employee was orally assured his or her job was not to be terminated, and he or she relied on such assurance(s).
If the federal Worker Adjustment and Retraining Notification Act ("WARN") is applicable, as it requires 60 days of notice before termination can be effective.
If an Employee Handbook purports to create an "at will" employment relation, but sets forth a policy of notice or hearing before termination.
In order to prevent an employee from attaining vested pension rights.
Because an employee is of a certain race.
Because an employee has filed a complaint of alleged race discrimination.
Because an employee has participated in an investigation of alleged race discrimination.
Because an employee has filed a lawsuit alleging illegal race discrimination.
Based on the color of an employee's skin.
Because an employee has filed a complaint of discrimination based on color of skin.
Because an employee participated in an investigation of alleged discrimination based on color.
Because an employee has filed a lawsuit alleging violation of laws prohibiting discrimination based on color.
Because an employee is a certain gender.
Because an employee has filed a complaint of alleged gender discrimination.
Because an employee has participated in an investigation of alleged gender discrimination.
Because an employee has filed a lawsuit alleging illegal gender discrimination.
Because of an employee's age.
Because an employee has filed a complaint of alleged age discrimination.
Because an employee has participated in an investigation of alleged age discrimination.
Because an employee has filed a lawsuit alleging illegal age discrimination.
Because an employee has a disability.
Because an employee is perceived to have a disability.
Because an employee has filed a complaint of alleged disability discrimination.
Because an employee has participated in an investigation of alleged disability discrimination.
Because an employee has filed a lawsuit alleging illegal disability discrimination.
Because an employee has requested an accommodation for a disability.
Because an employee has been provided an accommodation for a disability.
Because an employee is of a certain national origin.
Because an employee has filed a complaint of alleged national origin discrimination.
Because an employee has participated in an investigation of alleged national origin discrimination.
Because an employee has filed a lawsuit alleging illegal national origin discrimination.
Because an employee is pregnant.
Because an employee has filed a complaint of alleged pregnancy discrimination.
Because an employee has participated in an investigation of alleged pregnancy discrimination.
Because an employee has filed a lawsuit alleging illegal pregnancy discrimination.
In some locales, because an employee is of a certain sexual orientation.
In some locales, because an employee has complained of discrimination based on sexual orientation.
In some locales, because an employee has participated in an investigation of alleged discrimination on the basis of sexual orientation.
In some locales, because an employee has filed a lawsuit alleging illegal sexual orientation discrimination.
In some states, because an employee has used certain social network websites or engaged in other after-work social activities.
Because the employee is of a certain religion.
Because the employee has filed a complaint of alleged religious discrimination.
Because an employee has requested an accommodation to engage in certain religious activities or observances.
Because the employee has participated in an investigation of alleged religious discrimination.
Because an employee has filed a lawsuit alleging illegal religious discrimination.
Because the employee has complained of a hostile work environment.
Because the employee has participated in an investigation of alleged hostile work environment.
Because an employee has filed a lawsuit alleging illegal hostile work environment.
Because an employee has objected to sexual harassment.
Because an employee has filed a complaint about sexual harassment.
Because an employee has participated in an investigation of sexual harassment.
Because an employee has filed a lawsuit alleging sexual harassment.
Because the employee has filed a complaint about a refusal to pay overtime when it is due.
Because the employee's spouse has filed a complaint about a refusal to pay overtime when it is due.
Because the employee's fiancé has filed a complaint about a refusal to pay overtime when it is due.
Because an employee, an employee's spouse or an employee's fiancé has filed a lawsuit alleging a refusal to pay overtime when it is due.
Because an employee has filed a complaint about other violations of wage and hour laws, including violation of minimum wage.
Because the employee has objected to the accounting, bookkeeping or accounting practices of a publicly traded company, under the federal Sarbanes Oxley law.
If a company has a policy against retaliation for objecting to impropriety, dishonesty or illegality, and the employee has objected to one of them.
If the employee is called up to provide military reserve duty.
Because the employee must serve jury duty.
Because the employee has objected to an employer's violation of the federal Health Information Protection and Accountability Act ("HIPAA").
In some locales, due to the employee's physical appearance.
In some locales, due to the employee's marital or family status.
In response to the employee's speaking out publicly on a matter of public concern if the employee is a public employee.
Because the employee has filed a claim for Worker's Compensation.
Because the employee has filed a claim for Unemployment Benefits.
Because the employee has filed a complaint of dangerous workplace conditions with state or federal agencies.
In many states because the employee has previously been arrested or in jail for a charge that does not reflect on his or her ability to do the job.
In many states, due to the employee's medical history.
Due to the employee's genetic testing information.
In some states because an employee engages in certain social or recreational activities unrelated to his or her job duties.
In some states, because an employee smokes cigarettes.
Because the employee needs a reasonable period of time to vote.
Because the employee has requested the forms to apply for a Family and Medical Leave Act ("FMLA") leave of absence.
Because an employee has filed a request for a FMLA leave of absence.
Because an employee has taken a FMLA leave of absence.
In most circumstances before an employee on FMLA leave has returned to his or her job.
Because an employee has made a complaint about not receiving equal pay based on gender, race or age.
Because an employee has filed a lawsuit for not receiving equal pay based on gender, race or age.
Because an employee has participated in an investigation of alleged violations of equal pay.
If an employee is a union member and the union contract requires a certain reason for firing be established before firing.
If an employee is a union member and the union contract requires a certain process be completed before a firing can take place.
Because an employee has joined a union.
If a union member filed a union contract grievance.
Because the employee has participated in union organizing activities.
Because the employee has participated in union operating activities.
Because an employee refuses to engage in a criminal act.
Because an employee refuses to engage in a fraudulent act.
Because an employee refuses to engage in an act that is likely to cause harm or damage to a person.
Because an employee refuses to engage in an act that a state law prohibits, such as a request to commit perjury at a trial.
Because an employee has reported a violation of law, such as reporting an employer engaging in illegal child labor.
Because an employee has acted in the public interest, such as joining the National Guard or performing jury duty.
Because an employee has exercised a right under law, such as filing a claim for worker's compensation.
In some states when an employer has acted in bad faith, such as to avoid having to pay an employee his or her earned retirement benefits.
In some states when an employer has acted in bad faith, such as to avoid having to pay a salesperson commissions that he or she has earned.
In some states if an attorney refuses to violate legal ethics.
Because an employee filed for bankruptcy protection.
Because an employee has bad debts.
Because an employee's wages are garnished by a court.
Because an employee filed a complaint under the federal Clean Air Act of 1970.
Because an employee filed a complaint under the federal Energy Reorganization Act of 1974.
Because an employee filed a complaint under the federal Occupational Safety and Health Act of 1970.
Because an employee filed a complaint under the federal Safe Drinking Water Act of 1974.
Because an employee filed a complaint under the federal Solid Waste Disposal Act of 1965.
Because an employee filed a complaint under the federal Toxic Substance Control Act of 1970.
Because an employee filed a complaint under the federal Comprehensive Environmental Response, Compensation and Liability Act of 1980.
Because an employee filed a complaint under the federal Water Pollution Control Act of 1972.
Because an employee filed a complaint of unsafe mining practices under federal mine safety laws.
Because an employee filed a complaint of unsafe railroad practices under federal railroad safety laws.
For refusing to participate in a polygraph test under federal laws.
For the results of a polygraph test under federal laws.
It is my experience over the years that "The Big 'At-Will' Lie" is responsible for discouraging employees from using the many legal rights available to them to stand up for themselves – and for what is right – at work. It is my hope that this will be a "wake up call" to those who have been lulled into believing they can be "terminated any time for any reason." It is just not true.
SkloverWorkingWisdom™ emphasizes smart negotiating – and navigating – for yourself at work. Negotiation and navigation of work and career issues require that you think "out of the box," and avoid risks at every point in your career. Knowing that you have rights and remedies available to you is the place to start, for it is the "knowledge platform" upon which you can stand when treated improperly or illegally. Knowing ways to avoid disputes is even more advantageous. Learning the "in's and out's" of doing so is what we are here to help you with. Now it's up to you.
Always be proactive. Always be creative. Always be persistent. Always be vigilant. And always do what you can to achieve for yourself, your family, and your career. Take all available steps to increase and secure employment "rewards" and eliminate or reduce employment "risks." That's what our SkloverWorkingWisdom™ is all about.
© 2011, Alan L. Sklover All Rights Reserved. Commercial Use Prohibited.
This entry was posted on Thursday, October 13th, 2011 at 1:00 am You can follow any responses to this entry through the RSS 2.0 feed. You can post a comment, Share this article with a friend, print this page or trackback from your own site.


text:
Doctoral student develops award-winning ohmic curing technique for making pipes
KEDM Public Radio
Published August 8, 2022 at 11:39 AM EDT
1 of 1 — doctoral student.jpg
Stephen Gordon of Shreveport
Engineering Materials and Infrastucture Systems doctoral student and member of the Louisiana Tech University chapter of the North American Society for Trenchless Technology (NASTT) Stephen Gordon of Shreveport has developed an "Ohmic Curing Technique for GPC Pipe" to create pipes for underground construction from low carbon emission geopolymer materials.
Geopolymers, green alternatives to cement, are composed of industrial waste and take a long time to cure. The ohmic heating technique decreases curing time by using electricity to heat the geopolymer evenly. The process reduces the time it takes geopolymer materials to dry to a fraction of the time it takes traditional cement to cure. Using this research, crews can replace damaged roadways and rapidly cast pipes with geopolymers faster than with conventional cement methods.
Last spring, Gordon won the Trenchless Research Competition at the 2022 NASTT No-Dig Show for a poster presentation on the novel technique. At the time, the curing process he developed took roughly 30 minutes to complete. Over the last few months, Gordon and his advisor, Dr. Shaurav Alam, Assistant Professor of Civil Engineering, Construction Engineering Technology, and member of the Trenchless Technology Center (TTC), have changed the geopolymer mix to cut that time frame in half.
Gordon, Alam, and key members of the Advanced Materials Research Lab at the TTC on Louisiana Tech's campus presented the technique to the U.S. Army Engineer Research and Development Center using a small-scale 3-D printable beam mold also developed in the lab.
"Without the support of Dr. Shaurav Alam, Dr. John Matthews [Director of the TTC and Associate Professor of Civil Engineering, Construction Engineering Technology, and Engineering and Technology Management], Dr. Collin Wick [Associate Dean of College of Engineering and Science Graduate Studies and Research], and the TTC, my research would not have developed into what it is now," Gordon said. "The TTC and the wider College of Engineering and Science at Louisiana Tech University have given me many opportunities to expand and develop as an engineer. It was through the TTC that I was given the opportunity to travel to Milwaukee to attend the No-Dig Show. I am very proud to have won the award for Louisiana Tech University and the Trenchless Technology Center."
"Stephen is always an outside-the-box thinker," Alam added. "We started thinking about the possibilities of geopolymerization using ohmic curing. His CRAZY mind developed the setup and the fundamental efforts to make it happen. If properly made, this rapid curing geopolymerization has the potential to reduce pavement construction time by several folds."
"In the time Stephen has been a graduate student at Louisiana Tech, he has been a truly outstanding student that continues to impress with his demeanor, academics, and accomplishments," Wick said. "I am confident that he has a bright future."
KEDM News Doctoral StudentLouisiana Tech Universityengineering


In the woods, one day, a tree was born.
It was a stranger, alone and forlorn, it did not belong there.
It was beautiful, people said, with thick branches.
they tortured it to death.
trying to blossom with grace.
not even one good soul, not even one truth!
It was the last hope and winter came back heavy.
frost in its branches and the tree went parched.
and this was, now, its last time.
"Alone I lived and alone I die!


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