Errors and uncertainties in a gridded carbon dioxide emissions inventory

Emission inventories (EIs) are the fundamental tool to monitor compliance with greenhouse gas (GHG) emissions and emission reduction commitments. Inventory accounting guidelines provide the best practices to help EI compilers across different countries and regions make comparable, national emission estimates regardless of differences in data availability. However, there are a variety of sources of error and uncertainty that originate beyond what the inventory guidelines can define. Spatially explicit EIs, which are a key product for atmospheric modeling applications, are often developed for research purposes and there are no specific guidelines to achieve spatial emission estimates. The errors and uncertainties associated with the spatial estimates are unique to the approaches employed and are often difficult to assess. This study compares the global, high-resolution (1 km), fossil fuel, carbon dioxide (CO₂), gridded EI Open-source Data Inventory for Anthropogenic CO₂ (ODIAC) with the multi-resolution, spatially explicit bottom-up EI geoinformation technologies, spatio-temporal approaches, and full carbon account for improving the accuracy of GHG inventories (GESAPU) over the domain of Poland. By taking full advantage of the data granularity that bottom-up EI offers, this study characterized the potential biases in spatial disaggregation by emission sector (point and non-point emissions) across different scales (national, subnational/regional, and urban policy-relevant scales) and identified the root causes. While two EIs are in agreement in total and sectoral emissions (2.2% for the total emissions), the emission spatial patterns showed large differences (10~100% relative differences at 1 km) especially at the urban-rural transitioning areas (90–100%). We however found that the agreement of emissions over urban areas is surprisingly good compared with the estimates previously reported for US cities. This paper also discusses the use of spatially explicit EIs for climate mitigation applications beyond the common use in atmospheric modeling. We conclude with a discussion of current and future challenges of EIs in support of successful implementation of GHG emission monitoring and mitigation activity under the Paris Climate Agreement from the United Nations Framework Convention on Climate Change (UNFCCC) 21st Conference of the Parties (COP21). We highlight the importance of capacity building for EI development and coordinated research efforts of EI, atmospheric observations, and modeling to overcome the challenges.

     

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.     

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.

     

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).     

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%.     

Greenhouse gas emission factors for land use and land-use change in Southeast Asian peatlands

Tropical peat swamp forests, which are predominantly located in Southeast Asia (SEA) and play a prominent role as a global carbon store, are being intensively degraded and converted to agricultural lands and tree plantations. For national inventories, updated estimates of peat emissions of greenhouse gases (GHG) from land use (LU) and land-use change in the tropics are required. In this context, we reviewed the scientific literature and calculated emission factors of peat net emissions of carbon dioxide (CO₂), methane (CH₄) and nitrous oxide (N₂O) in seven representative LU categories for SEA i.e. intact peat swamp forest, degraded forest (logged, drained and affected by fire), mixed croplands and shrublands, rice fields, oil palm, Acacia crassicarpa and sago palm plantations. Peat net CO₂ uptake from or emissions to the atmosphere were assessed using a mass balance approach. The balance included main peat C inputs through litterfall and root mortality and outputs via organic matter mineralization and dissolved organic carbon. Peat net CO₂ loss rate from degraded forest, croplands and shrublands, rice fields, oil palm, A. crassicarpa and sago palm plantations amounted to 19.4?±?9.4, 41.0?±?6.7, 25.6?±?11.5, 29.9?±?10.6, 71.8?±?12.7 and 5.2?±?5.1 Mg CO₂ ha^?1 y^?1, respectively. Total peat GHG losses amounted to 20.9?±?9.4, 43.8?±?6.8, 36.1?±?12.9, 30.4?±?10.6, 72?±?12.8 and 8.6?±?5.3 Mg CO₂-equivalent ha^?1 y^?1 in the same LU categories, respectively. A single land-clearing fire would result in additional emissions of 493.6?±?156.0 Mg CO₂-equivalent ha^?1.     

Impacts of international trade on carbon flows of forest industry in Finland

Finland is a forested country with a large export oriented forest industry. In addition to domestic forest extraction, roundwood is imported, thus displacing the environmental impacts of harvests. In this paper, we analyse the international carbon flows of forest industries in Finland from a consumption-based perspective. Quantitative analyses are available on trade embedded emissions of CO₂ from fossil fuel combustion, and here we address in a similar way the impact of trade on the carbon budget of the forest products sector in Finland. Carbon flows through the forest industry system increased substantially between 1991 and 2005. We show that the annual carbon balance related to forests and forest industry system in Finland functioned as a sink in 1991, whereas in 2005 the system was a sink on a national level, but not on a global level. Through calculating the carbon content in traded forest industry products and emissions embodied in forest industry activities, we further show that the direct impacts of the forest industry in Finland are only a minor fraction of the total CO₂ emissions related to Finnish production. Nearly all of the emissions were caused due to production of exports. Yet, direct carbon dioxide emissions of the industrial production are reported to Finland in the production based inventories.     

城市能源碳排放估算方法探究

作为目前世界上最大的碳排放国家,中国在2015年巴黎气候变化大会上做出承诺,到2030年碳排放量要达到峰值并且单位GDP排放要在2005年水平上下降60%～65%.但现阶段中国碳排放数据主要集中在省级和国家层面,城市作为碳减排措施实施的主要区域,由于基础数据缺乏,长久以来没有完整的碳排放清单.为解决这一问题,本文构建了一套城市级CO_2排放估算方法.该方法从各省能源平衡表(EBT)出发,采取从省级到市级的比例分配方法,选取最为贴近城市碳排放的指标数据,对42个地级市2012年的能源消费型碳排放情况进行估算,并与中国高分辨率碳排放数据(CHRED)进行对比,发现差异均在10%以内,验证了该方法的准确性.同时揭示了此类自上而下的估算方法所带来的区域性差异,并且进一步分析了采用不同来源的化石燃料的排放因子所可能导致的不确定性,建议之后的研究在进行中国城市碳排放核算时采取最恰当的本地化化石燃料排放因子.本文为获得在时间尺度和空间尺度上均连续的中国城市碳排放数据提供了参考方法和合理思路,也能为在城市层面制定科学的碳减排措施提供可靠的数据支撑.     

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.     

Analyzing the efficacy of subtropical urban forests in offsetting carbon emissions from cities

Urban forest management and policies have been promoted as a tool to mitigate carbon dioxide (CO₂) emissions. This study used existing CO₂ reduction measures from subtropical Miami-Dade and Gainesville, USA and modeled carbon storage and sequestration by trees to analyze policies that use urban forests to offset carbon emissions. Field data were analyzed, modeled, and spatially analyzed to compare CO₂ sequestered by managing urban forests to equivalent amounts of CO₂ emitted in both urban areas. Urban forests in Gainesville have greater tree density, store more carbon and present lower per-tree sequestration rates than Miami-Dade as a result of environmental conditions and urbanization patterns. Areas characterized by natural pine-oak forests, mangroves, and stands of highly invasive trees were most apt at sequestering CO₂. Results indicate that urban tree sequestration offsets CO₂ emissions and, relative to total city-wide emissions, is moderately effective at 3.4 percent and 1.8 percent in Gainesville and Miami-Dade, respectively. Moreover, converting available non-treed areas into urban forests would not increase overall CO₂ emission reductions substantially. Current CO₂ sequestration by trees was comparable to implemented CO₂ reduction policies. However, long-term objectives, multiple ecosystem services, costs, community needs, and preservation of existing forests should be considered when managing trees for climate change mitigation and other ecosystem services.     

The Tropical Peatland Plantation-Carbon Assessment Tool: estimating CO2 emissions from tropical peat soils under plantations

Land use change on Indonesian peatlands contributes to global anthropogenic greenhouse gas (GHG) emissions. Accessible predictive tools are required to estimate likely soil carbon (C) losses and carbon dioxide (CO₂) emissions from peat soils under this land use change. Research and modelling efforts in tropical peatlands are limited, restricting the availability of data for complex soil model parameterisation and evaluation. The Tropical Peatland Plantation-Carbon Assessment Tool (TROPP-CAT) was developed to provide a user friendly tool to evaluate and predict soil C losses and CO₂ emissions from tropical peat soils. The tool requires simple input values to determine the rate of subsidence, of which the oxidising proportion results in CO₂ emissions. This paper describes the model structure and equations, and presents a number of evaluation and application runs. TROPP-CAT has been applied for both site specific and national level simulations, on existing oil palm and Acacia plantations, as well as on peat swamp forest sites to predict likely emissions from future land use change. Through an uncertainty and sensitivity analysis, literature reviews and comparison with other methods of estimating soil C losses, the paper identifies opportunities for future model development, bridging between different approaches to predicting CO₂ emissions from tropical peatlands under land use change. TROPP-CAT can be accessed online from www.redd-alert.eu in both English and Bahasa Indonesia.     

Estimating emissions from crop residue open burning in China based on statistics and MODIS fire products

With the objective of reducing the large uncertainties in the estimations of emissions from crop residue open burning, an improved method for establishing emission inventories of crop residue open burning at a high spatial resolution of 0.25°× 0.25° and a temporal resolution of1 month was established based on the moderate resolution imaging spectroradiometer(MODIS) Thermal Anomalies/Fire Daily Level3 Global Product(MOD/MYD14A1). Agriculture mechanization ratios and regional crop-specific grain-to-straw ratios were introduced to improve the accuracy of related activity data. Locally observed emission factors were used to calculate the primary pollutant emissions. MODIS satellite data were modified by combining them with county-level agricultural statistical data, which reduced the influence of missing fire counts caused by their small size and cloud cover. The annual emissions of CO_2, CO, CH_4,nonmethane volatile organic compounds(NMVOCs), N_2O, NO_x, NH_3, SO_2, fine particles(PM2.5),organic carbon(OC), and black carbon(BC) were 150.40, 6.70, 0.51, 0.88, 0.01, 0.13, 0.07, 0.43,1.09, 0.34, and 0.06 Tg, respectively, in 2012. Crop residue open burning emissions displayed typical seasonal and spatial variation. The highest emission regions were the Yellow-Huai River and Yangtse-Huai River areas, and the monthly emissions were highest in June(37%).Uncertainties in the emission estimates, measured as 95% confidence intervals, range from a low of within ±126% for N_2O to a high of within ± 169% for NH_3.     

Anthropogenic land use substantially increases riverine CO2 emissions

Carbon dioxide (CO₂) emissions from inland waters to the atmosphere are a pivotal component of the global carbon budget. Anthropogenic land use can influence riverine CO₂ emissions, but empirical data exploring cause-effect relationships remain limited. Here, we investigated CO₂ partial pressures (pCO₂) and degassing in a monsoonal river (Yue River) within the Han River draining to the Yangtze in China. Almost 90% of river samples were supersaturated in CO₂ with a mean ± standard deviation of 1474 ± 1614 µatm, leading to emissions of 557 - 971 mmol/m²/day from river water to the atmosphere. Annual CO₂ emissions were 1.6 - 2.8 times greater than the longitudinal exports of riverine dissolved inorganic and organic carbon. pCO₂ was positively correlated to anthropogenic land use (urban and farmland), and negatively correlated to forest cover. pCO₂ also had significant and positive relationships with total dissolved nitrogen and total dissolved phosphorus. Stepwise multiple regression models were developed to predict pCO₂. Farmland and urban land released nutrients and organic matter to the river system, driving riverine pCO₂ enrichment due to enhanced respiration in these heterotrophic rivers. Overall, we show the crucial role of land use driving riverine pCO₂, which should be considered in future large-scale estimates of CO₂ emissions from streams. Land use change can thus modify the carbon balance of urban-river systems by enhancing river emissions, and reforestation helps carbon neutral in rivers.     

The evolution of CO<Subscript>2</Subscript> emissions in international trade for major economies: a perspective from the global supply chain

Employing global multi-regional input–output models, this paper revisits the carbon dioxide (CO₂) emission trade (including exports and imports) and assesses their positions in the national emissions of 14 major countries with large national emissions or large emission trades during 1995–2009. It especially explores the evolution of the emission trades of these countries from both continuous time series and comparative perspectives, in order to provide an explanation for CO₂ emission spillovers across countries. The main findings obtained were as follows: (1) China was the largest CO₂ exporter to other countries, accounting for over 20 % of global exports since 2005; the CO₂ exports of the United States of America (USA), Germany, and Japan varied slightly over this time period, but overall, their proportions had decreased. (2) The CO₂ imports of the USA were the largest, occupying around 20 % of the global CO₂ imports; meanwhile, China’s CO₂ imports increased rapidly and ranked the second largest. (3) For Chinese Taiwan, its proportion of CO₂ exports in production-based emissions ranked the highest while that of the USA ranked the lowest; highly CO₂ import-dependent countries with an over 40 % proportion of CO₂ imports in its consumption-based emissions included France, Germany, Italy, and Spain, while China, India, and Russia remained the lowest, distinguished from their physical energy imports. These results suggested that the global policy makers should take the CO₂ emissions in trade into consideration when carefully accounting for national emissions inventories.     

2005-2009年我国省域CO2排放特征研究

利用IPCC的参考方法测算并比较分析了2005-2009年我国30个省(市、自治区)的CO₂排放总量、人均排放量、排放强度、综合能源排放系数等重要指标,并在此基础上,依据人均GDP、第二产业比重和能源利用结构与碳排放强度的关系,将各省(市、自治区)划分为不同的CO₂排放类型。研究结果表明,省域间各指标差异较大,影响碳排放的因素也不尽相同。省域减排的政策、途径和措施须充分考虑各自的经济发展水平、产业结构和能源利用结构等因素。     

Carbon dioxide emissions from spring ploughing of grassland in Ireland

Grassland re-seeding or land-use change requires ploughing, which may enhance carbon dioxide (CO₂) emissions from soil. This study observed the short to intermediate-term (37 days) effects of ploughing on CO₂ emissions from poorly drained grassland using automated soil respiration chambers. Immediately after ploughing, a brief peak in CO₂ emissions from soil occurred with a maximum observed flux of 6.91 g CO₂ m⁻² h⁻¹. Contradictory to other reported results, ecosystem respiration after ploughing was lower on the ploughed than on the grass site. After including estimates of photosynthesis in the analysis, ploughing led to significantly higher net CO₂ emissions than from grassland. The main mechanism of C loss during ploughing was most likely due to a reduction in gross primary production rather than enhanced soil respiration.     

Greenhouse gas emissions from oilfield-produced water in Shengli Oilfield, Eastern China

Greenhouse gas(GHG) emissions from oil and gas systems are an important component of the GHG emission inventory. To assess the carbon emissions from oilfield-produced water under atmospheric conditions correctly, in situ detection and simulation experiments were developed to study the natural release of GHG into the atmosphere in the Shengli Oilfield,the second largest oilfield in China. The results showed that methane(CH4) and carbon dioxide(CO2) were the primary gases released naturally from the oilfield-produced water.The atmospheric temperature and release time played important roles in determining the CH4 and CO2emissions under atmospheric conditions. Higher temperatures enhanced the carbon emissions. The emissions of both CH4 and CO2from oilfield-produced water were highest at 27°C and lowest at 3°C. The bulk of CH4 and CO2was released from the oilfield-produced water during the first release period, 0–2 hr, for each temperature, with a maximum average emission rate of 0.415 g CH4/(m3·hr) and 3.934 g CO2/(m3·hr), respectively. Then the carbon emissions at other time periods gradually decreased with the extension of time. The higher solubility of CO2 in water than CH4 results in a higher emission rate of CH4 than CO2over the same release duration. The simulation proved that oilfield-produced water is one of the potential emission sources that should be given great attention in oil and gas systems.     

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.     

碳底物含量对厌氧条件下水稻土N2、N2O、NO、CO2和CH4排放的影响

理解底物碳氮对厌氧条件下水稻土排放氮素气体——氮气(N2)、氧化亚氮(N2O)和一氧化氮(NO)以及二氧化碳(CO2)和甲烷(CH4)的影响,有助于制定合理的温室气体减排措施,定量了解反硝化产物组成对碳底物水平的依赖性,也有助于氮转化过程模型研发中制定正确的关键过程参数选取方法或参数化方案.本研究采用粉砂壤质水稻土为研究对象,设置对照(CK)和加碳(C+)两个处理,前者的初始硝态氮和可溶性有机碳(DOC)含量分别为~50 mg·kg-1和~28 mg·kg-1,后者的分别为~50 mg·kg-1和~300 mg·kg-1.采用氦环境培养-气体及碳氮底物直接同步测定系统,研究了完全厌氧条件下碳底物水平对上述气体排放的影响.结果表明,CK处理无CH4排放,而C+处理可观测到CH4排放;C+处理的综合增温潜势显著高于CK处理(P<0.01);NO、N2O和N2排放量占这3种氮素气体排放总量的比重,在CK处理分别约为9%、35%和56%,在C+处理分别约为31%、50%和19%,处理间差异显著(P<0.01).由此表明,碳底物水平可显著改变所排放氮素气体的组成;对于旱地阶段硝态氮比较丰富的水稻土,避免在淹水前或淹水期间施用有机肥,有利于削减温室气体排放.     

Uncertainty in Agricultural CH<Subscript>4</Subscript> AND N<Subscript>2</Subscript>O Emissions from Finland – Possibilities to Increase Accuracy in Emission Estimates

According to the United Nations Framework Convention on Climate Change (UNFCCC) and Kyoto Protocol under it, industrial countries have to estimate their greenhouse gas emissions annually, and assess the uncertainties in these estimates. In Finland, agricultural methane (CH₄) and nitrous oxide (N_2O) emissions represent 7% of anthropogenic greenhouse gas emissions, and globally the share is much higher. Agriculture is one of the most uncertain emission categories (representing over 20% of greenhouse gas inventory uncertainty in Finland), due to both high natural variability of the emission sources and poor knowledge of the emission-generating processes. In this paper, we present an uncertainty estimate of agricultural CH₄ and N₂O emissions from Finland in 2002. Uncertainties were estimated based on measurement data, literature and expert judgement, and total uncertainty in agriculture was calculated using Monte Carlo simulation. According to the calculations, agricultural CH₄ and N₂O emissions from Finland were 3.7 to 7.8 Tg carbon dioxide (CO₂) equivalents, 5.4 Tg being the mean value.Estimates of CH₄ emissions are more reliable than those of N₂O. N₂O from agricultural soils was the most uncertain emission category, and the uncertainty was not reduced by using available national measurement data of N₂O fluxes. Sensitivity study revealed that the uncertainty in total agricultural inventory could be 7% points lower, if more accurate emission estimation methods were used, including 1) improved data collection in area estimates of organic soils, 2) climate-specific methods for N₂O from agricultural soils as already presented in literature, and 3) more detailed CH₄ estimation methods for enteric fermentation which can be achieved by investigating national circumstances and digestible systems of animals in more detail.