Factors Determining Recent Changes Of Emissions Of Air .
Service Contract onMonitoring and Assessmentof Sectorial Implementation Actions(ENV.C.3/SER/2011/0009)Factors determiningrecent changes of emissionsof air pollutants in EuropeTSAP Report #2Version 1.0Peter Rafaj, Markus Amann,Janusz Cofala, Robert SanderIIASAJune 2012
The authorsThis report was written by Peter Rafaj, Markus Amann, Janusz Cofala, RobertSander from the International Institute for Applied Systems Analysis (IIASA).AcknowledgementsThis report was produced under the Service Contract on Monitoring andAssessment of Sectorial Implementation Actions (ENV.C.3/SER/2011/0009) of DG‐Environment of the European Commission.DisclaimerThe views and opinions expressed in this paper do not necessarily represent thepositions of IIASA or its collaborating and supporting organizations.The orientation and content of this report cannot be taken as indicating theposition of the European Commission or its services.
Executive SummaryTo support the European Commission in the review of the 2005 Thematic Strategyon Air Pollution, this report revisits the baseline scenario that was presented in2005 in view of today’s knowledge, in particular taking into account the impactsof the economic crisis on economic and energy development, and real‐lifeexperience with newly implemented emission regulations.It compares the final baseline emission projection developed in 2005 within theClean Air For Europe (CAFE) programme for the Thematic Strategy on Air Pollutionagainst the recent baseline projection prepared for the revision of the ThematicStrategy in 2012 (the TSAP‐2012 baseline).The report reviews the assumptions on main drivers of emission changes, i.e.,demographic trends, economic growth, changes in the energy intensity of GDP,switches to other fuels, and application of dedicated emission control measures.For most of these drivers, reality has developed rather different compared towhat has been assumed in 2005.In reality, SO2 emissions in the old Member States in 2010 were 5% lower thanwhat was projected by CAFE. NH3 was 10% and VOC 3% lower. NOx exceeded theCAFE projection by 7%, and PM2.5 by 10%. Larger differences occurred for thenew Member States, where SO2 was 30% and NH3 16% below the levels suggestby CAFE. NOx was 11% higher, and PM2.5 and VOC 21% higher than estimatedearlier.For 2020, the TSAP‐2012 baseline projection expects for the EU‐27 about 20% lessSO2 emissions than the earlier CAFE baseline, with application of dedicatedemission controls as the dominating factor for lower emissions. NOx would be 5‐7% lower, depending on the assumptions on the effectiveness of the new vehicleemission standards. The PM projection is about 10% higher, while smallerdifferences emerge for VOC and NH3.Many of these changes are smaller than differences in the actual drivers. In manycases, higher effectiveness of dedicated emission controls compensated the lowerthan expected decline in total energy consumption as well as the delay in thephase‐out of coal.A re‐analysis of air pollution control costs based on the actual statistics suggestsfor 2010 6% higher costs earlier estimated, mainly due to higher consumption ofcoal that required more emission control efforts.For 2020, emissions of the new TSAP‐2012 baseline (without additional measures)are substantially higher than the indicative targets for emission reductionsestablished by the Thematic Strategy in 2005. As a consequence, theenvironmental targets established by the TSAP for the protection of humanhealth, eutrophication and forest acidification would not be met by the TSAP‐2012 baseline without additional measures.3
More information on the InternetMore information about the GAINS methodology and interactive access to input dataand results is available at the Internet at http://gains.iiasa.ac.at.4
Table of contents1Introduction. 72Methodology and data sources. 932.1Determinants of emission changes . 92.2Factors that led to emission changes in the past . 102.3Data sources . 11Results . 133.1Comparison of assumptions on key drivers . 133.1.1GDP and population . 133.1.2Fuel prices. 143.1.3Energy intensities . 143.1.4Fuel mix . 153.1.5Changes in air quality legislation . 163.2Impacts on emissions . 173.2.1SO2 emissions . 173.2.2NOx emissions . 203.2.3PM2.5 emissions . 243.2.4NH3 emissions . 273.2.5VOC emissions . 293.3Costs of air pollution abatement . 314Distance to the 2005 TSAP targets for air quality . 335Conclusions. 355
List of acronyms6boeBarrel of oil equivalentCAFEThe ‘Clean Air for Europe’ programme of the European CommissionCAPRICommon Agricultural Policy Regionalised Impact ModelECEuropean CommissionEU‐15The 15 Member States of European Union before 2004GAINSGreenhouse Gas and Air Pollution Interactions and Synergies ModelGDPGross domestic productIIASAInternational Institute for Applied Systems AnalysisktkilotonsNECNational Emission CeilingsNH3AmmoniaNMS‐12New Member States of European Union that joined after 2004NOxNitrogen oxidesPM2.5Fine particulate matterRAINSRegional Acidification Information and Simulation ModelSO2Sulphur dioxideTSAPThematic Strategy on Air PollutionUS‐ United States dollarVOCVolatile organic compoundsyrYear
1IntroductionIn its 2005 Thematic Strategy on Air Pollution (TSAP), the European Commissionoutlined a road map to attain ‘levels of air quality that do not give rise to significantnegative impacts on, and risks to human health and environment’ (CEC, 2005a). Itestablished health and environmental objectives and outlined emission reductionpathways that would achieve these targets in a cost‐effective way. These scenariosemployed the best estimates of future economic development at that time, based onprevailing expectations on the implementation rates and effectiveness of existingand new policies (CEC, 2005b).In 2011, the European Commission has launched a comprehensive review andrevision of its air policy, in particular of the 2005 Thematic Strategy on Air Pollutionand its related legal instruments.To support the European Commission in the review, this report presents a re‐analysisof the scenarios that were presented in 2005 in view of today’s knowledge, inparticular taking into account the impacts of the economic crisis on economic andenergy development, and real‐life experience with newly implemented emissionregulations.This report compares the final baseline emission projection developed in 2005 withinthe Clean Air For Europe (CAFE) programme for the Thematic Strategy on AirPollution (Amann et al., 2005a) against the recent baseline projection prepared forthe revision of the Thematic Strategy in 2012 (the TSAP‐2012 baseline), which ispresented in TSAP Report #1 (Amann et al., 2012). It addresses five air pollutants,i.e., SO2, NOx, PM2.5, NH3 and VOC. The comparison includes the year 2010, forwhich actual statistical information is now available. Thereby, the report illustrateshow over the last 10 years the European Union (EU) has moved along the foreseentrajectory towards achievement of the interim targets defined in the NationalEmission Ceilings (NEC) directive (CEC, 2001).The report also addresses projections up to 2020, for which expectations havechanged since 2005. The analysis examines assumptions taken in 2005 against themost recent developments and assumptions incorporated in the TSAP‐2012 baseline.This report presents a quantitative decomposition of the major factors thatdetermine the development of air pollutant emissions. By comparing the actualtrends and recent projections of the driving factors against the evolution that hasbeen anticipated in 2005, the analysis reveals the degree to which the developmentmaterialized as foreseen, and quantifies the implications of the various factors thatevolved in unexpected directions.The analysis is carried out for each EU Member State; however, results are reportedfor groups of countries, i.e., the old Member States (EU‐15) and the new MemberStates (NMS‐12) that joined the EU after 2004.7
Finally, the analysis compares costs for emission controls as estimated in 2005 by theThematic Strategy with the recent estimates of the baseline projection for the 2012revision of the Thematic Strategy.This report is organized as follows. The following section provides a brief overview ofthe methods and data used for the study to lay the foundations for the subsequentquantitative analyses. Section 3 compares the actual development of emissionsbetween 2000 and 2010 as well as the recent baseline projection up to 2020 againstthe earlier expectations. It highlights the most important factors that led to differentdevelopment. The final section presents conclusions and discusses policyimplications of the main findings.This report presents draft findings from the first phase of the Service contract. Itshould provide a basis for consultations with experts from different stakeholders,whose feedbacks will be incorporated into the final version of the report to bepresented by the end of 2012.8
2Methodology and data sourcesThe development of emission over time is influenced by a variety of factors. First,emissions are directly related to the level of emission generating activities (e.g.,energy consumption or transport volumes), which in itself is influenced by thedevelopment in different sectors the economy, and the energy intensity of economicactivities. Furthermore, the composition of fuel consumption has significant impactson emissions, as different fuels emit different quantities of air pollutants. In addition,dedicated measures to control the release of emissions (e.g., through end‐of‐pipeemission control technologies) is a critical determinant of the final emission level(Rafaj et al., 2010). Some of these factors are subject to dedicated environmentalpolicies (e.g., the application of end‐of‐pipe emission control measures), while othersare usually not directly influenced by environmental policies (e.g., economic growth).To quantify the importance of targeted abatement measures and autonomousdevelopments such as changes in the energy structure, overall economic growth andtechnological advances, a decomposition analysis is performed. In a first step, therelationships between these factors are clarified. These equations are then appliedto data for all Member States to quantify the importance of the different factors indifferent regions.2.1 Determinants of emission changesIn a general form, total emissions in a region (EMIS) can be described as a product ofthree factors, i.e., population, per‐capita income, and emissions per unit of GDP: GDP EMIS EMIS POP * * POP GDP All these factors evolve over time, and influence the development of total emissions.The first two terms are usually beyond the direct impact of environmental policies,which affect mainly the third term (i.e., EMIS/GDP). This term includes autonomoustechnological progress, structural changes in the national economies, behaviouralchanges and dedicated environmental policies. To reveal the importance of theseindividual components that can lead to changes in the emission density of GDP, thisidentity is extended. We decompose it into three factors that relate to (i) changes inenergy use per GDP, (ii) the share of different fuel types in total energy use, and(iii) emission rates of per unit of fuel type. Thereby, , emission changes relative to aselected base year can be described as: ENE EMIS EMIS GDP * * * * (1 eff ) * X ENE GDP where the following factors are distinguished:Energy intensity (ENE/GDP), i.e., the energy requirement (ENE) for a unit of grossdomestic product (GDP). Changes in energy intensities determine overall energy9
consumption, and influence the resulting emission levels (EMIS). The time evolutionof the differences in energy intensities across countries reflects variations in socio‐economic structures as well as in behavioural patterns.The efficiency of the energy system (Δη), i.e., the efficiency by which primary energy(e.g., coal, crude oil) is converted into different forms of final energy (e.g.,electricity). Changes over time occur from improved efficiencies of convertingprimary fuels into electricity, of the combustion of final energy carriers in theindustry, transport or household sectors, and finally from efficiency improvements ofend‐use devices such as vehicles or light bulbs. Efficiency improvements are eithermandated by regulations or emerge in response to fuel availability and price signals.The fuel mix of different energy forms affects emission intensities. Changes overtime due occur from inter‐fossil fuel switching and changes in the fraction of non‐fossil fuels in the energy supply. Substitution of traditional fuels with electricity andheat belongs to this mitigation component too. Fuel switches can be triggered byenvironmental regulations, but more importantly by cost considerations andconvenience.Emission control measures reduce the amount of pollutants emitted per unit ofenergy through end‐of‐pipe measures, as well as through improved fuel quality dueto, for example, lower sulphur contents of coal or heating oil. Changes in emissionfactors over time can also be influenced by modified import patterns and byexploration of resources with different characteristics. The resulting emissioncoefficient depends on the removal efficiency (eff) of an abatement measureadopted at a specific application rate (X).With these factors, we capture the key reasons that can lead to different emissions,i.e., overall economic changes, changes in the energy structure, and dedicatedapplication of emission control measures.2.2Factors that led to emission changes in the pastOur formulation is useful to isolate the impacts of dedicated environmental policyinterventions from other driving forces. For this purpose, we compute fourhypothetical emission scenarios in which we keep one or several of these factors atthe level that has been observed for a selected base year:1. First, a hypothetical upper limit for emissions is calculated assuming absenceof any factors that change the emission intensities of GDP. Such an emissionpath would result from the growth in GDP with constant energy intensity ofGDP, unchanged fuel mix, and no further emission control measures beyondwhat was implemented in the base year. This trajectory reflects only changesin GDP, and will be used as a reference against which the impacts of theother factors can be quantified.2. In the following step, an emission trajectory is calculated for the actualdevelopment of total primary energy use, but keeping fuel mix and emission10
factors for each fuel type constant at the base year level. By comparing tothe first (GDP) trajectory, this path reveals the impacts of a decouplingbetween GDP growth and energy consumption on emissions. These changesin the energy intensities of GDP result from shifts in the sectorialcomposition of GDP as well as from efficiency improvements in the energysystems.3. Third, a trajectory is calculated that accounts for the changes in fuel mix,while keeping emission factors for each fuel type unchanged compared tothe base year value. Comparison to the second trajectory quantifies theimpacts of fuel substitution (e.g., the replacement of coal by natural gas) onemissions. Fuel substitution occurred in some cases in response toenvironmental legislation, but most likely in many cases due to other factors.4. Finally, the contribution of dedicated emission control measures to totalemission changes is derived from a fourth trajectory, which calculates actualemissions by applying observed and projected trends to all factors, includingthe changes in emission factors for each fuel type.A comparison of the differences between these trajectories, the impact of thefollowing four drivers on emission can be quantified:2.3 Overall economic growth The decoupling between GDP and energy use Changes in the fuel mix of total energy composition Application of dedicated emission control measures.Data sourcesTo calculate emissions from 2000 to 2020 in five‐year intervals, this analysis employsinformation from different statistics, databases and models. While the assessment isconducted for all Member States individually, results are presented for twoaggregated regions, i.e., the old Member States (EU‐15), and the 12 new MemberStates that joined the EU after 2004.As a basis, the analysis uses the final 2005 baseline scenario for the CAFE programmedocumented in the CAFE Report #6 (Amann et al. 2005a). This scenario incorporatedthe ‘With climate measures’ energy projection developed with the PRIMES energymodel (Mantzos and Zeka‐Paschou, 2004). Implemented in the GAINS/RAINS model(Amann et al., 2011), these detailed energy balances, macroeconomic projections,transport and industrial activities up to 2020 have been complemented with theGAINS emission factors for the decomposition analysis. Emission factors for the baseyear 2000 and consecutive years have been extracted from databases of RAINS andGAINS models that have been used for the original CAFE nsWeb/).11
The available data do not provide sufficient detail that would allow a fullquantification of the role of efficiency improvements. While data on changes inconversion efficiencies are available for the power sector, they are lacking for end‐use devices and appliances. Therefore, energy intensity and efficiency improvementshad to be treated together in this analysis.This CAFE projection is then compared against the recent baseline scenario for the2012 revision of the Thematic Strategy on Air Pollution, that is presented in TSAPreport #1 (Amann et al., 2012). Energy balances and macro‐economic data such asGDP, energy intensity and population growth are harmoni
Pollution (Amann et al., 2005a) against the recent baseline projection prepared for the revision of the Thematic Strategy in 2012 (the TSAP‐2012 baseline), which is presented in TSAP Report #1 (Amann et al., 2012). It addresses five air pollutants, i.e., SO2, NOx, PM2.5, NH3 and VOC. The comparison includes the year 2010, for
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