Forgotten carbon: indirect CO2 in greenhouse gas emission inventories

National governments that are Parties to the United Nations Framework Convention on Climate Change (UNFCCC) are required to submit greenhouse gas (GHG) inventories accounting for the emissions and removals occurring within their geographic territories. The Intergovernmental Panel on Climate Change (IPCC) provides inventory methodology guidance to the Parties of the UNFCCC. This methodology guidance, and national inventories based on it, omits carbon dioxide (CO₂) from the atmospheric oxidation of methane, carbon monoxide, and non-methane volatile organic compounds emissions that result from several source categories. The inclusion of this category of “indirect” CO₂ in GHG inventories increases global anthropogenic emissions (excluding land use and forestry) between 0.5 and 0.7%. However, the effect of inclusion on aggregate UNFCCC Annex I Party GHG emissions would be to reduce the growth of total emissions, from 1990 to 2004, by 0.2% points. The effect on the GHG emissions and emission trends of individual countries varies. The paper includes a methodology for calculating these emissions and discusses uncertainties. Indirect CO₂ is equally relevant for GHG inventories at other scales, such as global, regional, organizational, and facility. Similarly, project-based methodologies, such as those used under the Clean Development Mechanism, may need revising to account for indirect CO₂.     

A comparison of five high-resolution spatially-explicit,fossil-fuel,carbon dioxide emission inventories for the United States

The quantification of fossil-fuel-related emissions of carbon dioxide to the atmosphere is necessary in order to accurately represent carbon cycle fluxes and to understand and project the details of the global carbon cycle. In addition, the monitoring, reporting, and verification (MRV) of carbon dioxide emissions is necessary for the success of international agreements to reduce emissions. However, existing fossil-fuel carbon dioxide (FFCO₂) emissions inventories vary in terms of the data and methods used to estimate and distribute FFCO₂. This paper compares how the approaches used to create spatially explicit FFCO₂ emissions inventories affect the spatial distribution of emissions estimates and the magnitude of emissions estimates in specific locales. Five spatially explicit FFCO₂ emission inventories were compared: Carbon Dioxide Information and Analysis Center (CDIAC), Emission Database for Global Atmospheric Research (EDGAR), Fossil Fuel Data Assimilation System (FFDAS), Open-source Data Inventory for Anthropogenic CO₂ (ODIAC), and Vulcan. The effects of using specific data and approaches in the creation of spatially explicit FFCO₂ emissions inventories, and the effect of resolution on data representation are analyzed using graphical, numerical, and cartographic approaches. We examined the effect of using top-down versus bottom-up approaches, nightlights versus population proxies, and the inclusion of large point sources. The results indicate that the approach used to distribute emissions in space creates distinct patterns in the distribution of emissions estimates and hence in the estimates of emissions in specific locations. The different datasets serve different purposes but collectively show the key role of large point sources and urban centers and the strong relationship between scale and uncertainty.     

Development of a high-resolution spatial inventory of greenhouse gas emissions for Poland from stationary and mobile sources

Greenhouse gas (GHG) inventories at national or provincial levels include the total emissions as well as the emissions for many categories of human activity, but there is a need for spatially explicit GHG emission inventories. Hence, the aim of this research was to outline a methodology for producing a high-resolution spatially explicit emission inventory, demonstrated for Poland. GHG emission sources were classified into point, line, and area types and then combined to calculate the total emissions. We created vector maps of all sources for all categories of economic activity covered by the IPCC guidelines, using official information about companies, the administrative maps, Corine Land Cover, and other available data. We created the algorithms for the disaggregation of these data to the level of elementary objects such as emission sources. The algorithms used depend on the categories of economic activity under investigation. We calculated the emissions of carbon, nitrogen sulfure and other GHG compounds (e.g., CO₂, CH₄, N₂O, SO₂, NMVOC) as well as total emissions in the CO₂-equivalent. Gridded data were only created in the final stage to present the summarized emissions of very diverse sources from all categories. In our approach, information on the administrative assignment of corresponding emission sources is retained, which makes it possible to aggregate the final results to different administrative levels including municipalities, which is not possible using a traditional gridded emission approach. We demonstrate that any grid size can be chosen to match the aim of the spatial inventory, but not less than 100 m in this example, which corresponds to the coarsest resolution of the input datasets. We then considered the uncertainties in the statistical data, the calorific values, and the emission factors, with symmetric and asymmetric (lognormal) distributions. Using the Monte Carlo method, uncertainties, expressed using 95% confidence intervals, were estimated for high point-type emission sources, the provinces, and the subsectors. Such an approach is flexible, provided the data are available, and can be applied to other countries.

     

Emission inventory on company level: lessons from Russia

Developing a transparent,accurate greenhouse gas (GHG) emissionsinventory is the first step toward buildingan effective GHG management system. Todate, GHG inventories have been conductedprimarily at national levels. Theinternationally accepted inventorymethodology developed by theIntergovernmental Panel on Climate Change(IPCC) is oriented to countrywideinventories. The electricity company RAOUESR is the largest single corporateemitter of GHG in the Russian Federation. The company is responsible for about 1/3 ofRussia's CO₂ emissions; RAO's fossil fuelemissions are comparable to the fossil fuelemissions of the United Kingdom. The GHGinventory prepared by RAO is the first suchcorporate emissions inventory undertaken ina non-OECD country. In this article wepresent a detailed independent examinationof the methodology RAO applied for theinventory. We identify the most importantsources of uncertainty and we estimate theuncertainty. The main conclusion of theindependent review is that the methodologyutilized by RAO and the informationsupporting the methodology are reliable andpresent a reasonably accurate company-widepicture of RAO's CO₂ emissions. The shareof other greenhouse gases is negligiblysmall and we did not focus on this fractionof RAO's GHG emissions. As a next step, RAOmay wish to conduct more precisefacility-by-facility inventories in orderto create a robust GHG emission managementsystem.     

Comparison of CH4 emission inventory data and emission estimates from atmospheric transport models and concentration measurements

CH₄ emissions from two sources of emission inventory data i.e. the National Communications and the EDGAR/GEIA database, are compared with emission estimates from six global and two regional atmospheric transport models. The emission inventories were compiled using emission process parameters to establish emission factors and statistical data to derive activity data. The emission estimates were derived from an evaluation of atmospheric transport modelling results and measured concentrations of CH₄. The comparison of emission inventories and the emissions derived from atmospheric transport models shows the largest differences on the global scale to occur in biogenic CH₄ emissions, i.e. by wetlands and biomass burning. Anthropogenic CH₄ emissions due to oil and gas production and distribution, also appear rather uncertain, especially with respect to the spatial distribution of the sources. A comparison of CH₄ emissions on a smaller scale (NW Europe) showed a fair amount of agreement between National Communications, EDGAR data and results of inverse atmospheric modelling. Because most of the CH₄ emissions in this area come from reasonably well-known CH₄ emission sources like ruminants and landfills, this is a good argument. CH₄ emission from some areas in the North Sea was underestimated by inventories. This could be due to CH₄ emissions of oil production platforms in the North Sea.     

Improving the quality of national greenhouse gas inventories

This paper summarises the findings of an Intergovernmental Panel on Climate Change (IPCC) Expert Meeting on Methods for the Assessment of Inventory Data Quality held in Bilthoven, The Netherlands, 5–7 November 1997. Under the Kyoto Protocol of the Climate Convention, reliable inventories of national greenhouse gases (GHG) are needed for verifying compliance. Four approaches are suggested for assessing and improving the quality of greenhouse gas inventories: inventory quality assurance; inventory comparisons; model comparisons; and direct emission measurements. The paper presents recommendations for improving the quality of emission estimates of carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O).     

Quantifying and managing regional greenhouse gas emissions：Waste sector of Daejeon, Korea

A credible accounting of national and regional inventories for the greenhouse gas （GHG） reduction has emerged as one of the most significant current discussions. This article assessed the regional GHG emissions by three categories of the waste sector in Daejeon Metropolitan City （DMC）, Korea, examined the potential for DMC to reduce GHG emission, and discussed the methodology modified from Intergovernmental Panel on Climate Change and Korea national guidelines. During the last five years, DMC＇s overall GHG emissions were 239 thousand tons C02 eq./year from eleven public environmental infrastructure facilities, with a population of 1.52 million. Of the three categories, solid waste treatment/disposal contributes 68%, whilst wastewater treatment and others contribute 22% and 10% respectively. Among GHG unit emissions per ton of waste treatment, the biggest contributor was waste incineration of 694 kg CO2 eq./ton, followed by waste disposal of 483 kg CO2 eq./ton, biological treatment of solid waste of 209 kg CO2 eq./ton, wastewater treatment of 0.241 kg CO2 eq./m3, and public water supplies of 0.067 kg CO2 eq./m3. Furthermore, it is suggested that the potential in reducing GHG emissions from landfill process can be as high as 47.5% by increasing landfill gas recovery up to 50%. Therefore, it is apparent that reduction strategies for the main contributors of GHG emissions should take precedence over minor contributors and lead to the best practice for managing GHGs abatement.     

Analysis of differences between national inventories and an Emissions Database for Global Atmospheric Research (EDGAR)

A comparison is made of national greenhouse gas inventories for the Climate Convention, (including US country study results) and an emissions database for global atmospheric research (EDGAR). The comparison pointed to some gaps in reporting and some large differences within sectors. In most cases the differences can be traced down to the use of different emission factors or the use of national statistics that differed from the internationally available ones. Comparison of inventories may stimulate the scientific exchange of data and increase the consensus on emissions. This comparison of semi-independent databases may therefore reduce uncertainties in emissions estimates. The exercise illustrated the usefulness of standard reporting formats and the availability of background information other than the official National Communications to the Climate Convention. The comparison may lead to major revisions of officially reported methane emissions in several countries.     

四川省2008-2014年水泥行业大气污染物排放清单及时空分布特征

根据收集的四川省水泥行业活动水平数据及排放因子,建立了四川省2008-2014年水泥行业大气污染物排放清单,分析其年际变化趋势,识别时间分布特征,并利用GIS建立了高分辨率的网格化清单.此外,对水泥行业污染物排放的不确定性范围进行了定量估算.结果表明,2008-2014年水泥行业SO₂和NO_x排放显著增长,而PM₁₀和PM_2.5排放呈下降趋势;成都及周边地区以及川东北地区是水泥污染排放的主要贡献地区,大部分城市的污染变化与全省的情况基本一致;新型干法水泥产量比重由2008年的41%增长至2014年的88%,随之各污染物排放占比也显著增长,2014年约达到90%;水泥NO_x排放对空气NO₂质量浓度有一定影响,变化趋势较为一致,相比而言,PM₁₀质量浓度受水泥排放影响较小;水泥产量月变化特征不明显,年初1、2月份产量较低,下半年产量高于上半年;在空间分布上,污染物排放主要集中在德阳-绵阳、眉山-乐山及内江-自贡等地;水泥行业排放清单的不确定性主要来源于污染物去除效率及排放因子的选取,其中,PM_2.5不确定性范围较大,约为-64%~103%,SO₂的不确定性范围较小,为-45%~45%.     

Use of IPCC GHG key sources analysis to Mexico’s environmental policy

Intergovernmental Panel on Climate Change (IPCC) Tier 1 key sources level 1 assessment was applied to the 1994–1994 National Greenhouse Gases (GHG) emission inventory for Mexico in order to identify and analyze the key sources within it. Top key sources were from land use change and energy combustion contributing to about 60% of total national emissions. In addition, a Tier 1 trend assessment revealed some changes with respect to Tier 1 level assessment: Top key sources according to this analysis are waste disposal and delayed emissions from land clearing. Important insight for cost effective preventive mitigation actions can be extracted from this analysis. A comparison with other countries was carried out to find similarities in the GHG national emissions inventories related to common features on economic development.     

Carbon mitigation potential of Indian steel industry

Steel dominates the global metal production accounting for 5 % of increase in Earth’s atmospheric carbon dioxide (CO₂). Today, India is the 4th largest producer of crude steel in the world. The sector contributes around 3 % to the country’s gross domestic product (GDP) but adds 6.2 % to the national greenhouse gas (GHG) load. It accounts for 28.4% of the entire industry sector emissions, which are 23.9% of the country’s total emissions. Being a developing country, India is not obliged to cut its emissions under the Kyoto Protocol to the United Nations Framework Convention on Climate Change (FCCC), but gave voluntary commitment to reduce the emission intensity of its GDP by 20–25 % from the 2005 level by 2020. This paper attempts to find out if the Indian steel sector can help the country in fulfilling this commitment. The sector reduced its CO₂ emissions per ton of steel produced by 58% from 1994 to 2007. The study generates six scenarios for future projections which show that the sector can reduce its emission intensity by 12.5 % to 63 %. But going by the conservative estimates, the sector can reduce emission intensity by 30 % to 53 %. However, actual emissions will go up significantly in every case.     

胜坨油田原油温室气体排放特征及其影响因素

为研究油田开发过程中原油在大气条件下的碳排放特征,完善油气系统潜在温室气体排放清单,以胜利油田典型区块——胜坨油田原油为研究对象,通过改进的静态室-气相色谱及质谱法对原油在大气条件下的自然脱气(排放)过程进行模拟试验研究. 结果表明:CH₄和CO₂是胜坨油田原油溶解气中的两种主要温室气体;将模拟时间(48 h)均分为4个时段,CH₄、CO₂的主要排放阶段为0~12 h,并且其排放量远高于>12~24、>24~36和>36~48 h,其中,不同温度下CH₄、CO₂的最大排放率均出现在0~2 h. 原油在空气中暴露时间的长短及所处大气温度的高低直接影响温室气体的累积排放,CH₄、CO₂的累积排放量均随模拟试验的进行而递增;原油所处环境温度越高,累积排放量越大,3 ℃时CH₄、CO₂的累积排放量分别为12.498、15.071 g/m3,13 ℃时为20.626、21.004 g/m3,27 ℃时为31.353、26.954 g/m3. CH₄、CO₂在不同温度下的相对排放量存在差异,表现为低温(3、13 ℃)条件下CH₄排放量低于CO₂,相对高温(27 ℃)条件下表现相反. 研究显示,原油所处大气环境的温度及暴露时间是影响原油温室气体排放的重要因素.      

No-policy greenhouse gas emission scenarios: revisiting IPCC 1992

A new set of no-policy global greenhouse gas (GHG) emission scenarios was developed using the atmospheric stabilization framework, the same modeling tool that was used to generate the IS92 emission scenarios for the Intergovernmental Panel on Climate Change. Revised assumptions about population and economic growth, combined with updated information on changes in renewable energy supply, the efficiency of energy generation and other factors resulted in changes in GHG emission profiles over the next century, which led to an increase in the estimated global average temperature change as compared to the IS92 scenarios. Model results indicate that the largest increase in emissions, which led to a temperature increase of about 3.4°C by 2100 (relative to 1990), can be expected when a rapid increase in the GNP per capita levels of the non-OECD countries is combined with a low availability of solar/wind and biomass energy resources and slow energy efficiency improvements. The smallest increase in emissions and temperature by 2100 (about 2.5°C) occurred when a relatively slow increase in the GNP per capita in the non-OECD countries was combined with a high availability of renewable energy resources and rapid energy efficiency improvements.     

基于在线监测的江苏省大型固定燃煤源排放清单及其时空分布特征

大气污染物排放清单是了解各地区大气污染物排放及其时空分布,精确模拟该地区环境空气质量的最基础资料.现有大气污染物排放清单的粗时空分辨率,极大地限制了空气质量数值预报的准确性.本研究以江苏省大型固定燃煤源为例,以2012年为基准年,收集江苏省电力企业在线监控系统数据及江苏省大气核查核算表数据,结合相关文献的排放因子,分析了江苏省大型固定燃煤源主要污染物的总排放量和月变化特征.分析结果表明:1 SO2、NOx、TSP、PM10、PM2.5、CO、EC、OC、NMVOC、NH3等大气污染物的排放总量分别达到106.0、278.3、40.9、32.7、21.7、582.0、3.6、2.5、17.3、2.2 kt.2呈现2~3、7~8、12月排放量高,9~10月排放量低的月变化特征,可能原因是2~3月处于春节阶段,为保证节日供应,在此期间居民取暖、用电等都有可能增加;7~8月高温天气用电量增加,12月北方城市冬季燃煤取暖导致的煤炭消耗量增加.另外,由于部分污染物排放因子取自国内外相关文献,是本研究清单不确定性的主要因素.今后的工作可以在排放因子实测更新以及将排放清单纳入空气质量预报模式等方面进行更为深入的研究.     

Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland

The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO₂ emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH₄ emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (-0.64) as the most important variables. The adjusted coefficient is suitable and equals R² = 0.90. For N₂O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N₂O emission is the peat and wood fuel consumption.     

Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland

The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO₂ emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH₄ emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (− 0.64) as the most important variables. The adjusted coefficient is suitable and equals R² = 0.90. For N₂O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N₂O emission is the peat and wood fuel consumption.     

Forest biomass extraction for livestock feed and associated carbon analysis in lower Himalayas,India

Accounting the changes in the net carbon (C) sink-source balance is an important component for greenhouse gas emissions (GHG) inventories. However, carbon emission due to the vegetation biomass extraction for household purposes is generally not accounted in forest carbon budget analysis due to miniscule volume and non-availability of data. However, if vegetation remains in the forests, then vegetation biomass decomposes after natural death and decay and fixes some carbon to soil and releases some directly to the atmosphere. The study attempts to quantify the carbon removal against the biomass extraction for livestock feed by collecting primary data on feed from 316 randomly selected households engaged in livestock rearing in the lower Himalayas, Uttarakhand, India and carbon flow components due to livestock production. The analysis results that average daily forest fodder consumption was 13 kg per Adult Cattle Unit (ACU) and total of 20.31 Million tonnes (Mt) consumption of forest biomass by total livestock of Uttarakhand. This results into absolute annual carbon removal of 3.25 Mt from Uttarakhand forests against the livestock fodder. However, overall carbon flow including the enteric fermentation and manure management system of livestock estimated as per IPCC guidelines, results into emissions of 9.42 Mt CO₂ eq. Therefore, biomass extraction for household purposes should be accounted in regional carbon flow analysis and properly addressed in the GHG inventories of the forests and livestock sector. Suitable measures should be taken for emissions reduction generated due to forest based livestock production.     

Sectoral emission inventories of greenhouse gases for 1990 on a per country basis as well as on 1°×1°

A set of global greenhouse gas emission inventories has been compiled per source category for the 1990 annual emissions of the direct greenhouse gases CO₂, CH₄ and N₂O, as well as of the indirect greenhouse gases (ozone precursors) CO, NO_x and NMVOC, and of SO₂. The inventories are available by sector, both on a per country/region basis and on a 1°×1° grid. Developed by TNO and RIVM for constructing the Emission Database for Global Atmospheric Research (EDGAR) Version 2.0, in co-operation with the Global Emission Inventory Activity (GEIA) of IGAC/IGBP, the inventories meet the needs of both policy-makers and atmospheric modellers. The data sources for activity data, emission factors and grid maps are discussed with the focus on anthropogenic sources of primarily CO₂, CH₄ and N₂O. The estimates of a standard group of anthropogenic sources are presented for each compound per world region.     

The role of biotic carbon stocks in stabilizing greenhouse gas concentrations at safe levels

The goal of the Climate Convention and its Kyoto Protocol is to stabilize greenhouse gas concentrations in the atmosphere at a safe level. This requires both strict limits on emissions from fossil fuels and effective management of biotic carbon stocks. If fossil fuel emissions from 1990 to 2100 are limited to 600 PgC, biotic carbon stocks must increase by 120 PgC to stabilize CO₂ concentrations at 450 ppmv. Establishing an appropriate policy regime to accomplish this goal is complicated by a factor of six discrepancy between estimates of the current biotic sink based on national emissions inventories compared with global carbon cycle model calculations. Appropriate policies must also be designed to create incentives for technological innovation in the energy sector and minimize the risk of granting emission credits for biotic carbon sequestration that proves to be temporary.