Analysis of change in relative uncertainty in GHG emissions from stationary sources for the EU 15

Total uncertainty in greenhouse gas (GHG) emissions changes over time due to “learning” and structural changes in GHG emissions. Understanding the uncertainty in GHG emissions over time is very important to better communicate uncertainty and to improve the setting of emission targets in the future. This is a diagnostic study divided into two parts. The first part analyses the historical change in the total uncertainty of CO₂ emissions from stationary sources that the member states estimate annually in their national inventory reports. The second part presents examples of changes in total uncertainty due to structural changes in GHG emissions considering the GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) emissions scenarios that are consistent with the EU’s “20-20-20” targets. The estimates of total uncertainty for the year 2020 are made under assumptions that relative uncertainties of GHG emissions by sector do not change in time, and with possible future uncertainty reductions for non-CO₂ emissions, which are characterized by high relative uncertainty. This diagnostic exercise shows that a driving factor of change in total uncertainty is increased knowledge of inventory processes in the past and prospective future. However, for individual countries and longer periods, structural changes in emissions could significantly influence the total uncertainty in relative terms.     

The improvement of greenhouse gas inventory as a tool for reduction emission uncertainties for operations with oil in the Russian Federation

The high quality inventory is an important step to greenhouse gas emission mitigation. The inventory quality is estimated by means of the uncertainty analysis. The level of uncertainty depends upon the reliability of activity data and the parameters used. An attempt has been made to improve the accuracy of the estimates through a shift from production-based method (IPCC Tier 1) (IPCC 2000) to enhanced combination of production-based and mass balance methods (IPCC Tier 2) (IPCC 2006) in the estimation of emissions from operations with oil that are key in the national greenhouse gas inventory of the Russian Federation. The IPCC Tier 2 (IPCC 2006) was adapted for the national conditions. The greenhouse gas emissions were calculated for 1990 to 2009 with the use of both methods. The quantitative uncertainty assessment of the calculations was performed, and the outcomes were compared. The comparison showed that the estimates made with the use of higher tier method resulted in higher accuracy and lower uncertainties (26 % respectively compared to previously derived 54 %).     

Spatial GHG inventory at the regional level: accounting for uncertainty

Methodology and geo-information technology for spatial analysis of processes of greenhouse gas (GHG) emissions from mobile and stationary sources of the energy sector at the level of elementary plots are developed. The methodology, which takes into account the territorial specificity of point, line, and area sources of emissions, is based on official statistical data surveys. The spatial distribution of emissions and their structure for the main sectors of the energy sector in the territory of the Lviv region of Ukraine are analyzed. The relative uncertainties of emission estimates obtained are calculated using knowledge of the spatial location of emission sources and following the Tier 1 and Tier 2 approaches of IPCC methodologies. The sensitivity of total relative uncertainty to change of uncertainties in input data uncertainties is studied for the biggest emission point sources. A few scenarios of passing to the alternative energy generation are considered and respective structural changes in the structure of greenhouse gas emissions are analyzed. An influence of these structural changes on the total uncertainty of greenhouse gas inventory results is studied.     

Uncertainty of forest carbon stock changes – implications to the total uncertainty of GHG inventory of Finland

Uncertainty analysis facilitates identification of the most important categories affecting greenhouse gas (GHG) inventory uncertainty and helps in prioritisation of the efforts needed for development of the inventory. This paper presents an uncertainty analysis of GHG emissions of all Kyoto sectors and gases for Finland consolidated with estimates of emissions/removals from LULUCF categories. In Finland, net GHG emissions in 2003 were around 69 Tg (±15 Tg) CO₂ equivalents. The uncertainties in forest carbon sink estimates in 2003 were larger than in most other emission categories, but of the same order of magnitude as in carbon stock change estimates in other land use, land-use change and forestry (LULUCF) categories, and in N₂O emissions from agricultural soils. Uncertainties in sink estimates of 1990 were lower, due to better availability of data. Results of this study indicate that inclusion of the forest carbon sink to GHG inventories reported to the UNFCCC increases uncertainties in net emissions notably. However, the decrease in precision is accompanied by an increase in the accuracy of the overall net GHG emissions due to improved completeness of the inventory. The results of this study can be utilised when planning future GHG mitigation protocols and emission trading schemes and when analysing environmental benefits of climate conventions.     

Regional spatial inventories (cadastres) of GHG emissions in the Energy sector: Accounting for uncertainty

An improvement of methods for the inventory of greenhouse gas (GHG) emissions is necessary to ensure effective control of commitments to emission reduction. The national inventory reports play an important role, but do not reflect specifics of regional processes of GHG emission and absorption for large-area countries. In this article, a GIS approach for the spatial inventory of GHG emissions in the energy sector, based on IPCC guidelines, official statistics on fuel consumption, and digital maps of the region under investigation, is presented. We include mathematical background for the spatial emission inventory of point, line and area sources, caused by fossil-fuel use for power and heat production, the residential sector, industrial and agricultural sectors, and transport. Methods for the spatial estimation of emissions from stationary and mobile sources, taking into account the specifics of fuel used and technological processes, are described. Using the developed GIS technology, the territorial distribution of GHG emissions, at the level of elementary grid cells 2 km?×?2 km for the territory of Western Ukraine, is obtained. Results of the spatial analysis are presented in the form of a geo-referenced database of emissions, and visualized as layers of digital maps. Uncertainty of inventory results is calculated using the Monte Carlo approach, and the sensitivity analysis results are described. The results achieved demonstrated that the relative uncertainties of emission estimates, for CO₂ and for total emissions (in CO₂ equivalent), depend largely on uncertainty in the statistical data and on uncertainty in fuels’ calorific values. The uncertainty of total emissions stays almost constant with the change of uncertainty of N₂O emission coefficients, and correlates strongly with an improvement in knowledge about CH₄ emission processes. The presented approach provides an opportunity to create a spatial cadastre of emissions, and to use this additional knowledge for the analysis and reduction of uncertainty. It enables us to identify territories with the highest emissions, and estimate an influence of uncertainty of the large emission sources on the uncertainty of total emissions. Ascribing emissions to the places where they actually occur helps to improve the inventory process and to reduce the overall uncertainty.     

Comparison of preparatory signal analysis techniques for consideration in the (post-)Kyoto policy process

Our study is a preparatory exercise. We focus on the analysis of uncertainty in greenhouse gas emission inventories. Inventory uncertainty is monitored, but not regulated, under the Kyoto Protocol to the United Nations Framework Convention on Climate Change. Under the Convention, countries publish annual or periodic national inventories of greenhouse gas emissions and removals. Policymakers use these inventories to develop strategies and policies for emission reductions and to track the progress of these policies. However, greenhouse gas inventories contain uncertainty for a variety of reasons, and these uncertainties have important scientific and policy implications. For most countries, the emission changes agreed under the Protocol are of the same order of magnitude as the uncertainty that underlies their combined (carbon dioxide equivalent) emissions estimates. Here we apply and compare six available techniques to analyze the uncertainty in the emission changes that countries agreed to realize by the end of the Protocol’s first commitment period 2008–2012. Any such technique, if implemented, could “make or break” claims of compliance, especially in cases where countries claim fulfillment of their commitments to reduce or limit emissions. The techniques all perform differently and can thus have a different impact on the design and execution of emission control policies. A thorough comparison of the techniques has not yet been made but is needed when expanding the discussion on how to go about dealing with uncertainty under the Kyoto Protocol and its successor.     

Benefits of dealing with uncertainty in greenhouse gas inventories: introduction

The assessment of greenhouse gases emitted to and removed from the atmosphere is high on the international political and scientific agendas. Growing international concern and cooperation regarding the climate change problem have increased the need for policy-oriented solutions to the issue of uncertainty in, and related to, inventories of greenhouse gas (GHG) emissions. The approaches to addressing uncertainty discussed in this Special Issue reflect attempts to improve national inventories, not only for their own sake but also from a wider, systems analytical perspective—a perspective that seeks to strengthen the usefulness of national inventories under a compliance and/or global monitoring and reporting framework. These approaches demonstrate the benefits of including inventory uncertainty in policy analyses. The authors of the contributed papers show that considering uncertainty helps avoid situations that can, for example, create a false sense of certainty or lead to invalid views of subsystems. This may eventually prevent related errors from showing up in analyses. However, considering uncertainty does not come for free. Proper treatment of uncertainty is costly and demanding because it forces us to make the step from “simple to complex” and only then to discuss potential simplifications. Finally, comprehensive treatment of uncertainty does not offer policymakers quick and easy solutions. The authors of the papers in this Special Issue do, however, agree that uncertainty analysis must be a key component of national GHG inventory analysis. Uncertainty analysis helps to provide a greater understanding and better science helps us to reduce and deal with uncertainty. By recognizing the importance of identifying and quantifying uncertainties, great strides can be made in ongoing discussions regarding GHG inventories and accounting for climate change. The 17 papers in this Special Issue deal with many aspects of analyzing and dealing with uncertainty in emissions estimates.     

National greenhouse gas accounts: Current anthropogenic sources and sinks

This study provides estimates of greenhouse gas emissions from the major anthropogenic sources for 142 countries. The data compilation is comprehensive in approach, including emissions from CO, CH₄, and N₂O, and ten halocarbons, in addition to CO₂. The sources include emissions from fossil fuel production and use, cement production, halocarbons, landfills, land use changes, biomass burning, rice and livestock production and fertilizer consumption. The approach used to derive these estimates corresponds closely with the simple methodologies proposed by the Greenhouse Gas Emissions Task Force of the Intergovernmental Panel on Climate Change. The inventory includes a new estimate of greenhouse gas emissions from fossil fuel combustion based principally on data from the International Energy Agency. The research methodologies for estimating emissions from all sources is briefly described and compared with other recent studies in the literature.     

Uncertainty in an emissions-constrained world

Our study focuses on uncertainty in greenhouse gas (GHG) emissions from anthropogenic sources, including land use and land-use change activities. We aim to understand the relevance of diagnostic (retrospective) and prognostic (prospective) uncertainty in an emissions-temperature setting that seeks to constrain global warming and to link uncertainty consistently across temporal scales. We discuss diagnostic and prognostic uncertainty in a systems setting that allows any country to understand its national and near-term mitigation and adaptation efforts in a globally consistent and long-term context. Cumulative emissions are not only constrained and globally binding but exhibit quantitative uncertainty; and whether or not compliance with an agreed temperature target will be achieved is also uncertain. To facilitate discussions, we focus on two countries, the USA and China. While our study addresses whether or not future increase in global temperature can be kept below 2, 3, or 4 °C targets, its primary aim is to use those targets to demonstrate the relevance of both diagnostic and prognostic uncertainty. We show how to combine diagnostic and prognostic uncertainty to take more educated (precautionary) decisions for reducing emissions toward an agreed temperature target; and how to perceive combined diagnostic and prognostic uncertainty-related risk. Diagnostic uncertainty is the uncertainty contained in inventoried emission estimates and relates to the risk that true GHG emissions are greater than inventoried emission estimates reported in a specified year; prognostic uncertainty refers to cumulative emissions between a start year and a future target year, and relates to the risk that an agreed temperature target is exceeded.     

Statistical dependence in input data of national greenhouse gas inventories: effects on the overall inventory uncertainty

An uncertainty assessment of the Austrian greenhouse gas inventory provided the basis for this analysis. We isolated the factors that were responsible for the uncertainty observed, and compared our results with those of other countries. Uncertainties of input parameters were used to derive the uncertainty of the emission estimate. Resulting uncertainty using a Monte Carlo approach was 5.2% for the emission levels of 2005 and 2.4 percentage points for the 1990–2005 emission trend. Systematic uncertainty was not assessed. This result is in the range expected from previous experience in Austria and other countries. The determining factor for the emission level uncertainty (not the trend uncertainty) is the uncertainty associated with soil nitrous oxide N₂O emissions. Uncertainty of the soil N₂O release rate is huge, and there is no agreement even on the magnitude of the uncertainty when country comparisons are made. In other words, reporting and use of N₂O release uncertainty are also different between countries; this is important, as this single factor fully determines a country’s national greenhouse gas inventory uncertainty. Inter-country comparisons of emission uncertainty are thus unable to reveal much about a country’s inventory quality. For Austria, we also compared the results of the Monte Carlo approach to those obtained from a simpler error propagation approach, and find the latter to systematically provide lower uncertainty. The difference can be explained by the ability of the Monte Carlo approach to account for statistical dependency of input parameters, again regarding soil N₂O emissions. This is in contrast to the results of other countries, which focus less on statistical dependency when performing Monte Carlo analysis. In addition, the error propagation results depend on treatment of skewed probability distributions, which need to be translated into normal distributions. The result indicates that more attention needs to be given to identifying statistically dependent input data in uncertainty assessment.     

欧盟减排《责任分担条例》修正案分析与启示

欧盟自1997年起就如何通过市场和行政手段“双轮驱动”控制碳排放总量进行不断探索,并逐步建立了较为成熟的碳排放交易体系及减排责任分担机制,已经取得了良好的减排效果。文中梳理分析《责任分担条例》修正案中关于成员国减排目标更新的内容、目标分配的原则与方法、灵活性机制,归纳了欧盟采用行政手段控制碳排放交易系统未涉及部门的温室气体排放的经验,并对中国如何构建充分考虑市场手段和行政手段的CO₂排放总量控制制度提出政策建议。     

Effects of Greenhouse Gas Emissions on World Agriculture, Food Consumption, and Economic Welfare

Because of many uncertainties, quantitative estimates of agriculturally related economic impacts of greenhouse gas emissions are often given low confidence. A major source of uncertainty is our inability to accurately project future changes in economic activity, emissions, and climate. This paper focuses on two issues. First, to what extent do variable projections of climate generate uncertainty in agriculturally related economic impacts? Second, to what extent do agriculturally related economic impacts of greenhouse gas emissions depend on economic conditions at the time of impacts? Results indicate that uncertainty due to variable projections of climate is fairly large for most of the economic effects evaluated in this analysis. Results also indicate that economic conditions at the time of impact influence the direction and size of as well as the confidence in the economic effects of identical projections of greenhouse gas impacts. The economic variable that behaves most consistently in this analysis is world crop production. Increases in mean global temperature, for example, cause world crop production to decrease on average under both 1990 and improved economic conditions and in both instances the confidence with respect to variable projections of climate is medium (e.g.,67%) or greater. In addition and as expected, CO₂ fertilization causesworld crop production to increase on average under 1990 and improved economic conditions. These results suggest that crop production may be a fairly robust indicator of the potential impacts of greenhouse gas emissions.A somewhat unexpected finding is that improved economic conditions are not necessarily a panacea to potential greenhouse-gas-induced damages, particularly at the region level. In fact, in some regions, impacts of climate change or CO₂ fertilization that are beneficial undercurrent economic conditions may be detrimental under improved economic conditions (relative to the new economic base). Australia plus New Zealand suffer from this effect in this analysis because under improved economic conditions they are assumed to obtain a relatively large share of income from agricultural exports. When the climate-change and CO₂-fertilization scenariosin this analysis are also included, agricultural exports from Australia plus New Zealand decline on average. The resultant declines in agricultural income in Australia plus New Zealand are too large to be completely offset by rising incomes in other sectors. This indicates that regions that rely on agricultural exports for relatively large shares of their income may be vulnerable not only to direct climate-induced agricultural damages, but also to positive impacts induced by greenhouse gas emissions elsewhere.     

Contributions of individual countries?? emissions to climate change and their uncertainty

We have compiled historical greenhouse gas emissions and their uncertainties on country and sector level and assessed their contribution to cumulative emissions and to global average temperature increase in the past and for a the future emission scenario. We find that uncertainty in historical contribution estimates differs between countries due to different shares of greenhouse gases and time development of emissions. Although historical emissions in the distant past are very uncertain, their influence on countries?? or sectors?? contributions to temperature increase is relatively small in most cases, because these results are dominated by recent (high) emissions. For relative contributions to cumulative emissions and temperature rise, the uncertainty introduced by unknown historical emissions is larger than the uncertainty introduced by the use of different climate models. The choice of different parameters in the calculation of relative contributions is most relevant for countries that are different from the world average in greenhouse gas mix and timing of emissions. The choice of the indicator (cumulative GWP weighted emissions or temperature increase) is very important for a few countries (altering contributions up to a factor of 2) and could be considered small for most countries (in the order of 10%). The choice of the year, from which to start accounting for emissions (e.g. 1750 or 1990), is important for many countries, up to a factor of 2.2 and on average of around 1.3. Including or excluding land-use change and forestry or non-CO₂ gases changes relative contributions dramatically for a third of the countries (by a factor of 5 to a factor of 90). Industrialised countries started to increase CO₂ emissions from energy use much earlier. Developing countries?? emissions from land-use change and forestry as well as of CH₄ and N₂O were substantial before their emissions from energy use.     

Verification of compliance with GHG emission targets: annex B countries

The focus of this study is on the preparatory detection of uncertain greenhouse gas (GHG) emission changes (also termed emission signals) under the Kyoto Protocol. Preparatory signal detection is a measure that should be taken prior to/during negotiation of the Protocol. It allows the ranking of countries under the Protocol according to their realized versus their agreed emission changes and in terms of both certainty and credibility. Controlling GHGs is affected by uncertainty and may be costly. Thus, knowing whether each nation is doing its part is in the public interest. At present, however, countries to the United Nations Framework Convention on Climate Change (UNFCCC) are obliged to include in the reporting of their annual inventories direct or alternative estimates of the uncertainty associated with these, consistent with the Intergovernmental Panel on Climate Change’s (IPCC) good practice guidance reports. As a consequence, inventory uncertainty is monitored, but not regulated, under the Kyoto Protocol. Although uncertainties are becoming increasingly available, monitored emissions and uncertainties are still dealt with separately. In our study we analyze estimates of both emission changes and uncertainties to advance the evaluation of countries and their performance under the Protocol. Our analysis allows supply and demand of emissions credits to be examined in consideration of uncertainty. For the purpose of our exercise, we make use of the Undershooting and Verification Time concept described by Jonas et al. (Clim Change doi:10.1007/s10584-010-9914-6, 2010).     

Scientific uncertainty and climate change: Part II. Uncertainty and mitigation

In public debate surrounding climate change, scientific uncertainty is often cited in connection with arguments against mitigative action. This article examines the role of uncertainty about future climate change in determining the likely success or failure of mitigative action. We show by Monte Carlo simulation that greater uncertainty translates into a greater likelihood that mitigation efforts will fail to limit global warming to a target (e.g., 2 °C). The effect of uncertainty can be reduced by limiting greenhouse gas emissions. Taken together with the fact that greater uncertainty also increases the potential damages arising from unabated emissions (Lewandowsky et al. 2014), any appeal to uncertainty implies a stronger, rather than weaker, need to cut greenhouse gas emissions than in the absence of uncertainty.     

Responsibility for Past and Future Global Warming: Uncertainties in Attributing Anthropogenic Climate Change

During the negotiations on the Kyoto Protocol, Brazil proposed a methodology to link the relative contribution of Annex I Parties to emission reductions with the relative contributions of Parties to the global-mean temperature increase. The proposal was not adopted during the negotiations but referred to the Subsidiary Body for Scientific and Technological Advice for consideration of its methodological aspects. In this context we analyze the impact of model uncertainties and methodological choices on the regionally attributed global-mean temperature increase. A climate assessment model has been developed to calculate changes in greenhouse gas concentrations, global-mean temperature and sea-level rise attributable to individual regions. The analysis shows the impact of the different choices in methodological aspects to be as important as the impact of model uncertainties on a region's contribution to present and future global temperature increases. Choices may be the inclusion of the anthropogenic non-CO₂ greenhouse gas emissions and/or theCO₂ emissions associated with land-use changes. When responsibility to global temperature change is attributed to all emitting Parties, the impacts of modeling uncertainties and methodological choices on contributions of individual Parties are considerable. However, if relative contributions are calculated only within the group of Annex I countries, the results are less sensitive to the uncertainty aspects considered here.     

The impact of biofuel-induced food-price inflation on dietary energy demand and dietary greenhouse gas emissions

Dramatic increases in liquid biofuel production have led to concerns about associated impacts on food prices, with many modeling studies showing significant biofuel-related price inflation. In turn, by changing patterns of food demand, biofuel production may indirectly influence greenhouse gas emissions. We estimated changes to dietary energy (calorie) demand and greenhouse gas emissions embodied in average diets under different biofuel-related food-price scenarios for Brazil, China and the United States, using food-price projections and food-price elasticities. Average energy demand decreased in all countries, from about 40 kcal per person per day in Brazil under a moderate price inflation scenario – a reduction of 1% relative to the (2009) reference scenario – to nearly 300 per day in the United States with high price inflation – almost 8% of reference levels. However, emissions per calorie increased slightly in all three countries. In terms of total greenhouse gas emissions, the results are suggestive of overall reductions only in the United States, where average reductions ranged from about 40 to 110 kg of carbon dioxide equivalent emissions per person per year. In China, the direction of impact is unclear, but the net change is likely to be small. Brazilian results were sensitive to parameter values and the direction and magnitude of impact is therefore uncertain. Despite the uncertainty, even small changes (positive or negative) in individual dietary emissions can produce large changes at the population level, arguing for the inclusion of the dietary pathway in greenhouse gas accounting of liquid biofuels.     

国土空间总体规划温室气体核算模型

城市的低碳发展对于应对气候变化及实现我国“碳达峰、碳中和”目标起着至关重要的作用。在新的国土空间规划体系下,国土空间总体规划对城市的低碳发展影响重大。为解决现有的城市温室气体核算中存在的问题,使总体规划促进城市低碳发展,构建了国土空间总体规划温室气体核算模型。该模型基于“空间布局—用地类型—部门划分—模型方法”的框架,采用自上而下与自下而上相结合的方法,与国土空间规划要素紧密结合;建立了市域和中心城区两个层次的碳排放核算方法,并解决了中心城区的碳排放核算问题,可进行国际间比较;解决了总体规划能源预测不完善的问题,提出了不同的核算方法供灵活选择,与完全基于用地类型的方法相比,降低了不确定性。最后基于模型提出了评估总体规划低碳发展水平的核心指标与参考指标。     

南京和长三角地区CO_2与CH_4人为排放清单估算的不确定性分析

目前温室气体清单的编制主要基于IPCC方法,该方法用于特定城市或区域清单编制时可能会引起较大的不确定性,而目前对城市/区域尺度清单的不确定性的分析还存在很大的欠缺。本文通过南京市和长三角温室气体排放因子甄选,应用IPCC方法计算了2009年南京市和长三角的人为温室气体排放量,并以其为个例利用蒙特卡洛方法开展城市和区域尺度的温室气体人为排放清单不确定性的初步探究。研究结果表明:南京市CH4和CO2排放量的95%的概率分布范围分别为(1.08~1.86)×105t和(6.50~7.41)×107t,不确定性分别为-21.74%~34.78%和-7.01%~5.87%;长三角CH4和CO2排放量的95%的概率分布范围分别为(4.07~5.89)×106t和(1.62~1.82)×109t,不确定性分别为-15.60%~22.24%和-6.04%~5.34%。     

Principles of monitoring of anthropogenic greenhouse gas emissions and sinks

Principles and substantiation of a system of monitoring anthropogenic greenhouse gas emissions and sinks are considered. The basic task of the system is to estimate the anthropogenic contribution to the atmospheric greenhouse gas concentrations and possible climate effect. The major attention is paid to the system of indirect or “computational” monitoring of anthropogenic greenhouse gases. A multifunctional information system is described in the context of its application for solving a number of other ecological problems. It can be used as an instrumental basis for estimating ecological efficiency of measures aimed at reducing emissions and increasing greenhouse gas uptake. The effect should be considered in totality for all greenhouse gases and most hazardous pollutants. Monitoring of anthropogenic greenhouse gas emissions and sinks includes observations (using modeling) of integral indicators of ecosystems and can be used as part of ecological monitoring (for example, dynamics of soil carbon balance of agroecosystems and forest cenoses). The connection of the monitoring of anthropogenic greenhouse gas emissions and sinks with the satellite monitoring enlarges the possible applications of this information system.