2011 Kelly work example Technical report - Evaluation of Ireland's non-traded sector target via gains ireland
N-ETS 2020*Ireland s Non-Traded Sector TargetAn analysis of abatement potentials and costs in respect of Ireland s 2020 Non-Traded Sector Target using the GAINS Ireland modelling systemSummer, 2011*Extended Version
N-ETS 2020*Ireland s Non-Traded Sector Target*Extended VersionAn analysis of abatement potentials and costs in respect of Ireland s 2020 Non-TradedSector Target using the GAINS Ireland modelling systemSummer, 2011AP EnvEcon IMP Ireland TeamDr Andrew Kelly Dr Luke Redmond Dr Fearghal KingUCD IMP Ireland TeamDr Miao Fu
3 | P a g eAcknowledgementsThis piece has been compiled by AP EnvEcon as part of the IMP Ireland project. The IMP Ireland projectis funded by the Environmental Protection Agency with co-funding from AP EnvEcon. The EnvironmentalProtection Agency funding is provided as part of the Science, Technology, Research and Innovation forthe Environment (STRIVE) Programme 2007-2013. The programme is financed by the Irish Governmentunder the National Development Plan 2007-2013. It is administered on behalf of the Department of theEnvironment, Heritage and Local Government by the Environmental Protection Agency which has thestatutory function of co-ordinating and promoting environmental research. The authors are extremelygrateful to the Environmental Protection Agency and the Department of Environment, Heritage and LocalGovernment for their support, without which this work would not be possible.In addition, the authors are extremely grateful to a number of individuals and their organisations for theirinput and thoughts in regard to the development of this piece. At IIASA, the team would like to thankFabian for his support in setting up the optimisations, Lena for support on CH4, Wilfried on N2O, Jens ontransport and Zig on agriculture generally. Also thanks go to Janusz on energy calibration queries, andRobert for all the technical support in adjusting the GAINS Ireland system in new ways. In Ireland, theteam would like to thank Frank McGovern and Gemma O’ Reilly of the EPA for their thoughts on the earlydevelopment of the piece. With particular thanks for technical input to Martin Howley of SEAI, MattClancy and Jim Scheer of SEAI’s energy modelling group, Liam Kinsella of DAFF and both Bernard Hydeand Stephan Leinert of the EPA for their many replies and valuable insights. This report advances theGAINS Ireland work in the context of climate policy analysis considerably. The exercise has also identifiedmany parameters and components where further research or evidence is required to facilitate or validatenational measurements and thereafter to enhance national representation in the GAINS Ireland system.Views expressed are those of the authors alone.
Table of ContentsExecutive Summary ................................................................................................................. 41. Introduction ............................................................................................................................. 6Methodology and Report Overview ......................................................................................... 82. The NETS Challenge............................................................................................................ 11The Traded Sector (ETS) and Non-Traded Sector (NETS)..................................................... 11Ireland’s NETS Target.............................................................................................................123. The GAINS Model Framework ............................................................................................15Overview of GAINS framework...............................................................................................15Emissions in GAINS................................................................................................................16Abatement options in GAINS..................................................................................................18Cost in GAINS ........................................................................................................................20ETS and NETS Sectors in GAINS........................................................................................... 244. The GAINS Model Setup for this Analysis.......................................................................... 25Baseline Scenario ................................................................................................................... 26Sector: Agriculture .................................................................................................................28Sector: Commercial, Residential, Heat.................................................................................. 29Sector: Waste.......................................................................................................................... 32Sector: Process ....................................................................................................................... 33Sector: Transport ................................................................................................................... 335. Results.................................................................................................................................... 35Sensitivity...............................................................................................................................40
2 | P a g e6. Note on Additional Mitigation Options and LULUCF........................................................40Additional technical potential of the menu of measures ........................................................41Non-technical and behavioural policy measures................................................................... 42LULUCF – Carbon Sinks in NETS process............................................................................ 437. Conclusions ............................................................................................................................ 468. References and Bibliography.............................................................................................. 499. Appendix – Marginal Abatement Cost Measures............................................................... 53
3 | P a g eAcknowledgementsThis piece has been compiled by AP EnvEcon as part of the IMP Ireland project. The IMP Ireland projectis funded by the Environmental Protection Agency with co-funding from AP EnvEcon. The EnvironmentalProtection Agency funding is provided as part of the Science, Technology, Research and Innovation forthe Environment (STRIVE) Programme 2007-2013. The programme is financed by the Irish Governmentunder the National Development Plan 2007-2013. It is administered on behalf of the Department of theEnvironment, Heritage and Local Government by the Environmental Protection Agency which has thestatutory function of co-ordinating and promoting environmental research. The authors are extremelygrateful to the Environmental Protection Agency and the Department of Environment, Heritage and LocalGovernment for their support, without which this work would not be possible.In addition, the authors are extremely grateful to a number of individuals and their organisations for theirinput and thoughts in regard to the development of this piece. At IIASA, the team would like to thankFabian for his support in setting up the optimisations, Lena for support on CH4, Wilfried on N2O, Jens ontransport and Zig on agriculture generally. Also thanks go to Janusz on energy calibration queries, andRobert for all the technical support in adjusting the GAINS Ireland system in new ways. In Ireland, theteam would like to thank Frank McGovern and Gemma O’ Reilly of the EPA for their input on thedevelopment of the piece. With particular thanks for technical input to Martin Howley of SEAI, MattClancy and Jim Scheer of SEAI’s energy modelling group, Liam Kinsella of DAFF and both Bernard Hydeand Stephan Leinert of the EPA for their many replies and valuable insights. This report advances theGAINS Ireland work in the context of climate policy analysis considerably. The exercise has also identifiedparameters and components where further research or evidence is required to facilitate or validatenational measurements and thereafter to enhance national representation in the GAINS Ireland system.Views expressed are those of the authors alone.
4 | P a g eExecutive SummaryThis report presents an analysis of Ireland’s Non-ETS (NETS) target challenge. The original NETS targetswere principally established on the basis of ability to pay in 2005, specifically considering the GDP percapita of a member state as an indicator of the capacity to invest in further abatement and the likely rateof future growth. The recent international economic turmoil has altered the backdrop to the NETS targetsignificantly. In particular the Irish economic outlook in 2011 is far removed from the expectations heldjust a few years ago. On the environmental front, the latest official inventory figures from theEnvironmental Protection Agency in 2011 confirm notable falls in emission levels. The continuance ofvarious policy measures and initiatives has certainly contributed to these achievements. However, thepersistent global economic issues and Ireland’s position to the fore of the ongoing European crisis haveplayed a major role in reducing economic activity, stalling growth and thereby curtailing emission levelsin Ireland. This ‘silver lining’ to the crisis is however set against a further cloud in the sense thatinvestment and finance is constrained and the need to grow business, economic activity and create jobswill remain the priority at national and individual levels. This is not to suggest that core objectives ofeconomic growth, energy efficiency and increased abatement may not be achieved in parallel. However,the case for efficiency and proposed abatement policies and actions, particularly in regard to cost, must bemade clear with the means of action facilitated in terms of finance, access and information.Evidence is required now that informs the choice of abatement options and identifies pathways towardscompliance. In presenting this information we must also reconcile the cost of investments and actionswith the combined savings from efficiency, abatement and contribution towards compliance withenvironmental objectives. This report engages the GAINS Ireland model to evaluate a pathway to NETScompliance in 2020. The official 2011 ‘with measures’ energy scenario has been paired with officialagricultural forecasts of 2011 to provide a baseline activity forecast in the GAINS Ireland model. Theprincipal calibration challenge in this process lay in configuring the ‘menu’ of abatement options in themodel prior to analysis. This involved adjusting the existing, expected and possible abatement measuresin the modelling system so as to reflect what is, and what else might be done in Ireland and at what cost.The abatement menu calibration is a blend of own in-house estimations, official national estimations, andinternationally defined estimates for measures. The type of measure captured is broad but not exhaustive,and it is important to acknowledge that non-technical or behavioural measures (e.g. carbon tax) generallyremain exogenous to the model. The outcomes of such policies can be integrated, but the measuresthemselves are not included formally in the abatement menu due to the complexity associated withdetermining their impact, feasibility and cost for the optimisation process used in this analysis.The primary outcome of the analysis suggests that from the ‘With Measures’ (WM) baseline starting pointand excluding LULUCF, the NETS target of 37.4M tonnes of CO2e in 2020 cannot be met via the defined
5 | P a g emenu of options where measures up to a marginal cost limit of €502005 per tonne of CO2e are taken. Norcan it be met where all of the non-exclusive menu options1 are taken, at marginal costs up to €2252005 pertonne of CO2e. The results show that the €50 cap on marginal abatement cost delivers NETS emissions of42.2M tonnes, whereas the unrestricted marginal cost cap scenario delivers a NETS emissions outcome of40.4M tonnes. The inability of the optimisations to achieve the target in 2020 also signals additionalconcern for the interim targets from 2013 to 2020 which are not analysed in this report. As part ofextended assessments it was found that only where we substitute the national ‘With Additional Measures’(WAM) scenario into the model setup and allow a marginal abatement cost of €200 per tonne of CO2e canwe achieve the 37.4M tonnes target.However, whilst the headline results are not particularly encouraging, there are four key conclusions fromthis report in respect of Ireland’s efforts to address this challenge. Firstly, the analyses do not represent allthat can be done. The model excludes certain policy interventions (e.g. revisions to the carbon tax) thatcould also contribute to progress on the target, and there remains additional extension and calibration ofthe abatement menu to be conducted over time. Furthermore, there is certainly untapped potential in thetransport sector that has not been adequately captured in this first calibration of the model. Secondly,whilst the target is not met under the WM analysis, the cost assessment from a social planner perspectiveindicates no net annual cost, due to cumulative cost savings on certain measures, where the package ofmeasures up to a marginal cost of €150 per tonne are taken. This is encouraging, but highlights that whilstsocial cost analyses indicate worthwhile actions, barriers such as information asymmetry and financingpersist from a private investment perspective that require innovative solutions. Thirdly, whilst the WMoptimisations fail to achieve the NETS target, the impact on over compliance for the ETS sector is notable.Similarly there would be strong co-benefits with transboundary air pollution policy objectives wheresignificant progress is made on the NETS target. Finally, whilst the process has identified many areaswhere additional data and evidence are required; there is cause for optimism in respect of this calibrationchallenge. A number of potential sources for these data are identified, and the progressive collating andintegration of this information into the model framework will offer a still stronger analytical tool fornavigating a pathway to compliance with NETS from 2013 to 2020. In summary, the GAINS Irelandmodel offers an excellent framework into which developed research and evidence may be integrated, andwill thereby provide a robust methodological platform on which to build both dynamic compliancestrategies and sound negotiation positions for both climate and transboundary air pollutioncommitments. Specifically in the climate context, GAINS Ireland is being developed to provide robusttechnical support in regard to the NETS annual target challenges, including the requisite ‘corrective plans’that will be necessary where an annual target is missed in the 2013 to 2020 period.1 In other words measures that may be combined – not all controls are additive. For example, if we already have 100% of a stage 2control, we cannot also add more of a stage 1 control to obtain further emission reductions in that situation.
6 | P a g e1. IntroductionIt is a globally shared goal to prevent dangerous climate change. The EU has adopted a positionwhereby global temperature rise would be held as far as possible under a 2°C rise beyond pre-industrial levels. This target has been clearly communicated to the UNFCCC and sets theEuropean Union apart as a global leader in climate protection. The actions necessary withinEurope to contribute towards attainment of this goal are defined under EU climate changepolicy, whereby member states are currently required to collectively reduce the EU’s greenhousegas emissions by 20% relative to 1990 by 2020 over the period 2013-2020. The effort could beincreased to 30% should there be a significant commitment in terms of climate ambition fromother major developed nations, however, currently the target remains as 20%. In order toachieve the objective of a 20% reduction in greenhouse gas emissions in a cost effective mannerthe European Commission emphasised a need for all sectors of the economy to contribute toachieving these emission reductions2. The EU agreed specific targets for the ETS (traded) andNETS (non-traded) sectors as follows:• A 21% reduction in ETS sector emissions by 2020 compared to 20053. This reductionwill be achieved through the allocation of an annually declining single EU wideallowance cap across all ETS sectors between 2013 and 2020. There are no countryspecific targets for ETS emissions.• An overall 10% reduction in NETS emissions by 2020 compared to 2005 levels. EachMember State has agreed a specific emissions limit for the 2013-2020 period.2 Point 1 of “Position of the European Parliament adopted at first reading on 17 December 2008 with a view to the adoption ofDecision No .../2009/EC of the European Parliament and of the Council on the effort of Member States to reduce their greenhousegas emissions to meet the Community’s greenhouse gas emission reduction commitments up to 2020”; European ParliamentClimate & Energy Package Text3 2005 was used as the reference year as it was the most recent year for which reliable data was available. It includes verifiedemissions at installation level within the EU ETS, as well as the overall GHG emissions of Member States as officially reported to theUnited Nations Framework Convention on Climate Change.
7 | P a g eThis report is focused on Ireland’s NETS challenge. The Irish ETS sector is also evaluated asimportant interactions exist between the ETS and NETS sectors. However, as the ETS is closelyregulated by Europe, with the established participation of market players, it presents less of adirect concern for member state policymakers. In contrast, the non-traded sector targetscomprise a challenging set of responsibilities for many individual Member State policy makerswho must manage these complex multi-agent sectors. Co-benefits for other areas (e.g.transboundary air pollution) that are captured within the GAINS modelling system are notpresented in this analysis in order to maintain the focus on the NETS challenge.The principal objective of this report is to undertake an analysis of Ireland’s NETS targetchallenge, and to identify potential pathways ‘towards’ compliance. The approach is to utilise aconfiguration of the ‘full4’ capacities of the GAINS Ireland model5,6 to determine the scope andcosts of potential abatement and mitigation options from the relevant NETS sectors in regard togreenhouse gas emissions. Optimisation analysis is used to constrain the system to the specifictargeted outcome. Specifically, the optimisation focuses on identifying a least cost pathway toattainment of the NETS target in Ireland in 2020. The principal analysis is derived from theGAINS Ireland model framework, calibrated with the most recent national ‘with measures’energy forecast (SEAI, 2010) and agricultural data provided in 2011 from the EPA projectionsunit. A sensitivity calibrated on the ‘with additional measures’ energy forecast7 is also run, withsummary results discussed. Under the following subheading we provide a brief up frontintroduction to the key methodological concepts that must be understood from the outset inreading through the report.4 To date the GAINS model has rarely been run in a full mode whereby the model engages all abatement options (e.g. fuel switchingand efficiency changes, in addition to technical options) and pollutants in an assessment. This mode, in a climate context, is acomparatively more recent development of the system and yet requires a considerable effort for refined calibration to individualmember states. For the purpose of this report, the IMP team have engaged closely with IIASA and national experts in order toestablish an initial calibration platform for analyses. Further national research and effort will be required over time to develop andsustain this system for ongoing usage.5 See Policymeasures.com Literature and Guides for GAINS Ireland by the IMP Ireland team6 Also see Reports and Publications by the IIASA team7 Also known as the NEEAP/NREAP scenario
8 | P a g eMethodology and Report OverviewThe analysis in this report draws principally on the GAINS Ireland Model and associatedmethodologies of the GAINS modelling framework.8 The GAINS model is a techno-economicintegrated assessment model focused on climate and transboundary air pollution policy. In thecontext of this report there are three principal components to the model operations that areparticularly relevant to understanding and interpreting the analysis presented in this work.These are activities, controls and optimisation.ActivitiesThis defines the activities in regard to energy use, agricultural data (e.g. herd, fertiliser use) andprocesses such as waste treatment or cement manufacture. These data represent the majordrivers of emission levels. In this report, activity levels have been based upon recent officialnational data where available. Specifically, the activity component of the model has beencalibrated with the most recently available national data on agriculture (direct correspondenceSpring 2011, EPA) and energy activity (SEAI, 20109). Supplemental information on otheremission drivers such as population, waste generation and cement production have also beensourced from official data and included as available. All data in the model are forecast out to a2020 time horizon. The principal energy scenario choice is the ‘With Measures’ or Baselinescenario. It includes defined measures in place, and does not presume success with a number ofrelevant targets e.g. national energy efficiency targets or renewable target. A sensitivity using the‘With Additional Measures10’ scenario is also run to indicate the estimated cost and abatementpotentials from a more advanced starting point in terms of renewable deployment and energyefficiency progress.ControlsThe control component relates to the ‘menu’ of abatement controls or other actions availablewithin the calibrated model to control emissions. These controls are detailed in the system interms of what is currently in place, what is expected in 2020, and what is believed technicallyfeasible by 2020. Each individual control is linked to a specific abatement potential per unit ofrelevant activity, a corresponding abatement cost function and also the associated synergies or8 For specific reference material on GAINS Ireland approaches see AP EnvEcon (2008 & 2010), and for information on the generalmodel framework, see for example Hoglund-Isaksson et al. (2009) and Klaassen et al. (2004).9 Actual data files for energy forecasts were sourced from the EPA directly10 Defined also as the NEEAP/NREAP scenario in the national projections (SEAI, 2010).
9 | P a g etrade-offs with other measures and pollutants. The GAINS Ireland model benefits from a core ofinternational research in its design and default calibration of this menu. National specificstudies have also been used where available to refine the model in line with national researchand evidence. Though there are many analytical gaps in the national research of ‘options’ andtheir cost and potential. Specifically the preparatory work for this analysis has focused upon:a) Reflecting those measures implicit within the national activity scenarios mentioned11So as to limit the risk of double counting of abatement potential in the analysisb) Researching and defining appropriate boundaries for the potentials of abatementcontrolsSo as to more appropriately reflect what can be done in Irelandc) Refining and adjusting the cost, efficiency and abatement potentials of measuresSo as to improve confidence in the cost and abatement results generated by the modelOptimisationsThe linked structure of activities, costs and controls in GAINS, is what allows the optimisationsto determine outcomes such as a cost-effective pathway to a given emission constraint12 or themaximum abatement progress that can be achieved for a given investment. The analyticalapproach within this report is to run three optimisations over the 2011 ‘with measures’ scenarioas follows:• Cost-Optimal Baseline (COB)An optimised baseline which selects measures with negative or zero marginal abatement cost toreconfigure the baseline to a ‘no regret’ starting point where savings would be greater than cost.• Maximum Feasible Reduction (MFR)This run presents the maximum level of emission reductions that may be achieved from theanalytical perspective of the model. Whilst the title suggests no limit on cost, in practicemeasures range up to €2502005 per tonne of CO2. No measures above this cost are included inthe menu of abatement options.11 For example, accounting for the effect of implicit energy efficiency progress in the two scenarios used. Reflecting the energy changeis straight forward, reflecting the controls used to achieve this is more complex.12 Alternatively, in cases where the target cannot be met with all measures the optimisation will return inter alia the remaining gapthat must be closed.
10 | P a g e• Least Cost Optimisation (LCO)The LCO is an optimised scenario constrained to find the least cost pathway to achieving theNETS target with a cap imposed on the marginal cost of measures of €502005 per tonne of CO2.The focus for the optimisations above is the with measures scenario, however, summary resultsfrom a sensitivity analysis that runs the same optimisations over the more ambitious13 ‘withadditional measures’ scenario for 2011 are also presented. These indicate a more advancedstarting point in terms of closing the gap to the NETS target, given higher renewablepenetrations, achievement of national efficiency targets and so forth. Whilst additionalmeasures are captured in the model calibration for the WAM scenario, the outcomes still delivera lower level of emissions in 2020 as the WAM includes certain options (e.g. high EVpenetration) and rates of progress (e.g. energy efficiency) beyond the current setup of the model.The report is structured as follows. Section 2 provides the contextual setting for the report,describing the climate change challenge facing the EU and Ireland and how this challenge hasbeen distributed between the traded and non-traded sectors. Section 3 describes the modalitiesof the GAINS model. Detailing how the model handles emissions, cost calculations and the splitand interactions between the traded and non-traded sectors in the model framework. Section 4describes the research and setup of the GAINS Ireland model for the analyses. Sections 5presents modelled optimisation results, and section 6 offers a brief discussion of furtherabatement potential. The latter includes areas where additional data is required to refine thenational abatement potential in the model (e.g. transport and electric vehicles), and areas wheremeasures that lie outside the methodological framework of the model exist (e.g. carbon taxation)that can support further progress towards the NETS targets. These are discussed with referenceto related research nationally by the IMP Team and others. Section 7 concludes.13 In terms of energy efficiency and renewable penetration
11 | P a g e2. The NETS ChallengeIreland must comply with legally binding greenhouse gas (GHG) emissions reductioncommitments established under the European Union’s (EU) Climate and Energy (C&E)package and subsequent Effort Sharing Decision (ESD).14 The C&E package requires the EUEmissions Trading Scheme15 (ETS) sectors (principally the power sector and heavy industry) toreduce emissions levels in 2020 by 21% relative to 2005. The ESD requires Ireland to reduce theGHG emissions of its non-ETS (NETS) sectors (e.g. agriculture, transport, waste, residential &commercial, heat) in 2020 by 20% relative to 2005 levels. The European Commission hashowever stated that Member State NETS sector targets could be further increased should asuitably ambitious international agreement to replace the Kyoto Protocol be reached. For nowhowever, Ireland’s NETS challenge remains at a level of 20% below 2005 levels in 2020. Inquantitative terms this amounts to a threshold on NETS emissions in 2020 of 37.4 Mt CO2e(EPA 2011a) with annually declining, and still legally binding, NETS emission limits from 2013to 2020 to support the drive to a compliance trajectory. We acknowledge the significance andimmediacy of the challenge posed by these inter-annual targets from 2013, however, in thisanalysis we focus on the end point of 2020.The Traded Sector (ETS) and Non-Traded Sector (NETS)At present the ETS covers CO2 emissions from large emitters in the heat and power generationindustry and in selected energy intensive industrial sectors.16 A size threshold based onproduction capacity or output was used to determine which installations in the covered sectorsparticipated in the trading scheme. This process resulted in the ETS being confined to CO2emissions from combustion installations with a rated thermal input in excess of 20 MW (exceptfor municipal or hazardous waste incinerators), oil refineries, production and processing offerrous metals, manufacture of cement (capacity > 500 tonnes/day), manufacture of lime(capacity > 50 tonnes/day), ceramics including brick, glass, and pulp, paper and board (>20tonnes per day). The ETS sector covers approximately 50% of the EU’s CO2 emissions and 40%14 Effort Sharing Decision (ESD) adopted jointly by the European Parliament and the Council - Effort Sharing Decision15 See IMP Ireland Report on ETS at www.policymeasures.com16 The Netherlands is the only Member State to utilise the ETS directive’s provision allowing Member States to include additionalnational greenhouse gases in the trading scheme. The Netherlands has ‘opted in’ emissions from nitrous oxide.
12 | P a g eof total greenhouse gas emissions.17 The aviation sector is scheduled to join the ETS in 2012. Theentry of the ETS into a third phase in 2013 will see further expansion of the scheme to includeadditional sectors (petrochemicals, ammonia and aluminum) and gases (nitrous oxide andperfluorocarbons).The NETS sector essentially captures what remains. Specifically, it encompasses the agriculture,transport, residential & commercial heat, waste and ‘light’ industry sectors. The Commissionidentified non-ETS sector targets for Member States on the basis of GDP per capita, with someacknowledgement of abatement potential18. The underlying principle being one of solidaritybetween Member States and the need to allow for balanced and sustainable economic growthacross the EU. Member States with relatively low per capita GDP and high per capita GDPgrowth expectations were permitted to increase their emissions relative to 1990 while those withrelatively high GDP per capita must reduce their emissions.Ireland’s NETS TargetIn determining emissions targets for Member State NETS and ETS sectors, the European Unionassigned Ireland a target requiring it to reduce its non-traded sector greenhouse gas emissionsby 20% relative to 2005 by 2020. As noted, Ireland’s 20% NETS target equates to a 2020emissions level of 37.4Mt CO2e.Emission reductions for the non-ETS sector will take place between 2013 and 2020. Under theClimate and Energy package the European Commission foresee a linear emissions reductionpath for the national targets for the NETS sector over the period from 2013 to 2020. As a resultof the “effort sharing” approach under the Climate and Energy package Member States annualbinding emission budgets were determined in accordance with the Commission’s emissionreduction path. Member State emissions will be subject to annual monitoring and compliancechecks to ensure EU greenhouse gas emissions gradually move towards agreed 2020 targets(European Commission, 2008a). The European Commission have warned that if in any given17 See European Commission - ETS Description & Statistics18 Specifically the GAINS model was used to inform the abatement capacities in respect of the agricultural sector
13 | P a g eyear a Member States’ NETS emissions are greater than those permitted under the “effortsharing” emission budgets then it will be forced to take corrective action. Underachievedemission reductions will have to be realised in the following year with a deduction from aMember State’s emission allocation budget in the following year equal to the amount in tonnesof the emissions reduction underachievement multiplied by a penalty factor of 1.08. In addition,Member States will have to submit a corrective plan to the Commission detailing the measuresand timeframe for getting back on track with a view to meeting their 2020 target (EuropeanCommission, 2008a). For the analysis in this paper we focus on the final year performance in2020. However, we acknowledge the relevance of establishing an appropriate compliancetrajectory from 2013 onwards, and the potential for penalties and credible revision plans toaffect the challenge in this area into the future.Figure 1 Ireland’s NETS Sector 2013 – 2020 Greenhouse Emissions Pathways (EPA 2012)Figure 1 illustrates the NETS challenge facing Ireland. The data presented are based on theofficial national emissions forecast (EPA 2012). From Figure 1 it is evident that the NETS sectoris forecast to exceed its emissions target (37.4MtCO2e) from 2016 onwards. According to theEPA (2012) ‘With Measures’ NETS emissions are forecast to be 45.3MtCO2e in 2020, thusexceeding the 2020 target by 7.8MtCO2e. These projections exclude carbon sinks19 (which would19 Carbon sinks, encompassing the storage and removal of greenhouse gas emissions associated with land use, land use change andforestry (LULUCF), are currently excluded from use by Member States as part of their abatement strategy to comply with the 20200.0010.0020.0030.0040.0050.002013 2014 2015 2016 2017 2018 2019 2020MtonnesCO2eNETS Target Estimate*NETS Emissions (WAM) 2012 ex sinksNETS Emissions (WM) 2012 ex sinks
14 | P a g eamount to approximately 4.8Mt in 2020 (EPA 2011a,b, 2012). The with measures scenarioreports higher emissions than would be found under the more ambitious ‘with additionalmeasures’ scenario. By way of international comparison, it is clear from Figure 2 that therelative challenge faced by Ireland within the non-traded sector is amongst the greatest inEurope, with a required reduction in emissions of 20% on 2005 levels.Figure 2: Official Non-traded sector 2020 emissions targets, relative to 2005 levelsWhen combined the ETS and non-ETS targets will in 2020, result in an overall reduction inemission levels by 14% compared to 2005. This is equivalent to a reduction of 20% compared to1990. Failure to agree on a new legally binding international climate agreement at Cancunmeant that the EU 20% emissions reduction target for 2020 remains unchanged for the timebeing. At least until the next COP gathering in Durban 2011, or pending some alternative policydevelopment of significance such as the approach to be taken to carbon sinks in Europe andtargets. The European Commission is currently engaged in a consultation process to determine how carbon sinks might beincorporated into Member States’ emissions target compliance strategies.-20%-15%-10%-5%0%5%10%15%20%
15 | P a g econnected revisions to ambition levels. By association then the emissions targets assigned by theEU to individual Member States to help the Union collectively achieve its emissions target havealso remained unchanged following COP16.3. The GAINS Model FrameworkSection 3 is structured into five headings describing a number of aspects of the GAINS modelframework in brief that are of particular importance in regard to the analysis presented in thisreport20. These are:• A general overview of the model framework• The model handling of emissions• The model handling of abatement options• The model approach to cost estimation• The model approach to ETS and NETS disaggregation and interactionOverview of GAINS frameworkThe GAINS model provides an analytical framework to evaluate scenarios in respect ofemissions, abatement options, costs and impacts (Klaassen et al., 2005 and Amann et al.,200921). The model incorporates exogenous information on energy and agricultural activity aswell as an internationally researched and evolving menu of abatement options and their costs.The model evaluates multiple pollutants, effects and their interactions, simultaneously offeringdecision support in respect of climate and transboundary air pollution policy negotiation andstrategy. Hoglund-Isaksson et al. (2009) provide a concise ‘4-step’ description of the GAINSmethodology as used with a focus on GHG and climate. They describe how the GAINS model:20 As detailed previously, additional documentation and literature from the IMP Ireland work and IIASA can be sourced online aslinked in footnote 6 and 7.21 The GAINS model includes all 6 greenhouse gases covered under the Kyoto Protocol (CO2, CH4, N2O, HFCs, PFCs, SF6) andcovers all anthropogenic sources that are included in the emission reporting of Annex I countries to UNFCCC (Energy, IndustrialProcesses, Agriculture, Waste, and from LULUCF). GHG pollutants are presented in millions of tonnes of CO2 equivalents. Coveredair pollutants within GAINS include SO2, NOx, NMVOC, NH3, CO, PM.
16 | P a g eI. Adopts exogenous projections of future economic development and implied activitylevels in terms of energy consumption, transport demand, industrial production andagricultural activities as a starting point.II. Develops a corresponding baseline projection of greenhouse gas emissions for 2020/30with information derived from national GHG inventories and in collaboration withnational expert teams to validate country specific model input data assumptions.III. Estimates, with a bottom-up approach, for each economic sector in each country thepotential emission reductions that could be achieved through to 2030 as a result of theapplication of the available mitigation measures.22IV. Quantifies the associated costs that would emerge for these measures under the specificnational conditions.In addition to these steps, a non-linear optimisation process has also been developed to work inconjunction with the GAINS model framework. The optimisation process affords the capacity tosolve modelled scenarios to defined constraints such as emission limits, effect limits or costlimits. This is achieved by not only utilising the information mentioned in the ‘4-step’ processabove, but also taking account of further abatement potentials and constraints, pollutant andeffect interaction, and costs and applicability that are captured in the wider modelling system. Itis this scope of the GAINS model that allows the optimisation process to deliver such valuabledecision support for the development of cost-effective multi-pollutant, multi-effect pollutioncontrol strategies.23Emissions in GAINSAt a basic level, the individual processes for emissions estimation in GAINS entail a straightforward calculation involving a number of key parameters. These parameters are describedbelow in Box 1. Effectively the process takes account of the level of energy used for a givenactivity, the default emissions associated with that activity, and the presence and performance ofany abatement controls.22 GAINS model analysis presently covers a 40 year period (1990 - 2030) in five year intervals. Our focus in this report is on 2020.23 A description of the optimisation component of the model and its application within the context of this paper is presented insection 6.
17 | P a g eBox 1: Primary elements of emission calculationActivity Level24 The amount of energy used for a particular activity25Fuel Type The fuel type providing the energy for the activityUnabated Emission Factor26 The emission factors for the activity assuming no abatement technologyTechnology The abatement technology in place for a given activityCapacity ControlledThe proportion of an activity covered by a given “control measure”. This can bea technological measure or a fuel switching measureAbated Emission Factor The emissions factor for all pollutants after abatementA more elegant presentation of the emission estimation form is provided by Wagner et al. (2010)who describe how the calculations are performed at the micro-level in the GAINS modellingsystem. Equation 1 details the function used in GAINS to estimate emission levels:27Emissions𝑐,𝑝 = ∑ 𝑏∈𝑆∑ 𝑓∈𝐹𝑐,𝑏∑ 𝑝∈𝑃𝑏,𝑓∑ 𝑡∈𝑇𝑏,𝑓,𝑝 EF𝑐,𝑏,𝑓,𝑡,𝑝 ∗ 𝑥𝑐,𝑏,𝑓,𝑡 + em𝑐,𝑝𝑜….Equation 1Equation 1 is composed of three components: (1) EFi, s, f, t, p; (2) xi, s, f, t; and (3) emoi ,p. Withinequation 1 the EFi, s, f, t, p parameter represents the pollutant (p) specific emission factor (EF) oftechnology t, applied in sector s with activity f, in country i. For a respective greenhouse gas (p)the third term - emoi ,p - is a constant term that describes residual emissions in country i in the24 There is often confusion regarding the dual use of the word activity in the GAINS modelling context. Activity in the model is usedto describe the fuel type involved in a given process. Thus activity level would be the petajoules of fuel used. However, activity issometimes also used in the more common sense to describe a polluting activity e.g. 4 stroke passenger cars are a subsectoralpolluting activity.25 In the case of agriculture, the activity level often refers to animal numbers, and the activity type relates to the type of animal e.g.dairy cattle or poultry.26 Emission factors for a given activity are reported as kilotons of CO2 per unit of fuel. In the GAINS model, fuels and energy sourcesare reported in petajoules. For the F Gases, emission factors are reported in units of CO2 equivalents.27 Wagner et al. (2010) provide a detailed description of all mathematical formulae used in the formulation of the GAINSmethodology. Equation 1 represents the emissions calculation formula from Wagner et al. (2010). Details of the componentscomprising equation 1 are sourced from Wagner et al. (2010).
18 | P a g ebase year 2005 and is used for calibration against national greenhouse gas inventories. Thesecond component of equation 1, xi, s, f, t, represents the technology specific activity dataparameter of the GAINS emissions calculation process. The technology specific activity dataparameter is the product of two model variables:xi, s, f, t = qi, s, f, t * xai, s, f ......Equation 2qi, s, f, t is the application rate or control strategy variable. This variable represents the rate ofapplication (q) of technology t, applied in sector s with activity f, in country i. The xai, s, f variableprovides activity data on activity f in sector s in country i.Abatement options in GAINSThe GAINS model covers multiple pollutants and incorporates multiple abatement options ofrelevance to both air pollutants and greenhouse gases. Details of the options are evolvingregularly, however, Klaassen et al., 2005 offers a useful reference for the scope of abatementoptions within the model. Prior to discussing the types of measures in the GAINS menu, wedefine five categories of generic abatement measures for GHG reduction.1. Technical measures (e.g. application of carbon capture and storage)2. Energy efficiency measures (e.g. application of insulation to homes)3. Lower carbon substitution measures (e.g. swapping away from coal to gas)4. Technology deployment measures (e.g. displacing petrol cars with electric vehicles)5. Behavioural change measures (e.g. carbon taxation, behavioural regulation)In this list, the full GAINS model can capture the role of a broad set of measures in categories 1to 4. However, behavioural change measures, or non-technical measures, remain apart from themodel and require exogenous analysis if their role is to be incorporated into a given scenario.Whilst the outcomes of such analysis can be fed back into the process, this can often present anumber of challenges (AP EnvEcon, 2010d) and such measures are unlikely to feature in the
19 | P a g eGAINS optimisation process in the foreseeable future for these reasons. The important point ofthis however, is that whilst the GAINS model can reflect behavioural change, it does notincorporate all the possible behavioural change options into its considerations of potentialindependently, and therefore policymakers should remain aware of the potential offered by suchnon-technical or behavioural measures where seeking to drive a path towards compliance. Werevisit these points in the results and conclusion sections.In terms of further considerations on the type of options that are incorporated as options intothis analysis then, there are a few points to make. Many measures are considered in the GAINSmodel, and detail of efforts to calibrate individual sectors is presented in section 4. The maincategories of measures in this analysis are briefly outlined in Box 2 and an extended summarycan be found in Amann et al., 2009 with additional detail on scope available via the onlineGAINS glossary. However, there are also some specific notes in regard to certain measures forthis analysis. These are that:1. Fuel switching to biofuels is included as an option in the analysis, allowing 10% higherfor first generation than the baseline.2. Switching to wind power is included as an option up to 8.75pj beyond baseline3. Solar and geothermal potentials are not included at this point4. CHP for domestic heating and cooling is not included at this point
20 | P a g eBox 2 : Main categories of abatement measures used in the NETS analysisSector Types of MeasurePower Plants Fuel switching, CHP, efficiency improvements, IGCCResidential and Commercial3 stage energy saving packages for HVAC and appliance use in new and oldhouses, apartments, commercial buildingsIndustryFuel switching, good practices, 3 stage energy saving packages, various N2Oand F-gas controlsTransport Advanced engines, efficiency improvements, hybrids, plug-ins, electricsWasteWaste diversion and treatment options, flaring and utilisation of gas,wastewater management, waste burning regulationAgricultureFertiliser application controls, animal feed, anaerobic digestion, advancedagro-chemicals, precision farmingCost in GAINS28Principally the GAINS mitigation cost methodology operates on the basis of two generalassumptions. In the first instance GAINS estimates abatement values by approximatingmitigation costs at production level as opposed to consumer price level. Specifically, GAINSfocuses on pure technology, investment and operational costs, ignoring transaction costs.Wagner et al. (2010) highlight that by employing such an approach GAINS takes the socialplanner’s perspective in that all costs are taken net of transfer costs, such as taxes, subsidies andprofits. The reason for ignoring such transfer costs is that they do not represent actual resourceuse costs. Secondly, the GAINS methodology assumes the existence of a free market forabatement equipment. Winiwarter (2005) and Tohka (2005) note how the free market must beaccessible to all countries under the same conditions so that capital investments for a specifictechnology can be specified as being independent of the country29. A further important choice in28 A detailed description of the handling and role of cost data in the GAINS model is provided in AP EnvEcon, 2010a.29 The accessibility of options does not preclude the possibility in the model of restricting certain options as inapplicable in a givencountry for a defined reason. This is also known as applicability in the context of the GAINS model.
21 | P a g ethe model is the specific interest rate used in respect of investment costs. By default, the GAINSmodel uses a social interest rate of 4% €2005, in order to reflect societal costs and returns30.In regard to what is counted when it comes to cost, GAINS differentiates expenditure costsassociated with individual abatement options into three cost components:1. Investment Costs2. Fixed Operating Costs3. Variable Operating CostsFor each of these categories the model utilises a broad range of data parameters in the costcalculation process with data parameters generally classed as either “common” or “countryspecific”. Klaassen et al. (2005) point out how some parameters are considered common to allcountries with country specific parameters characterising the type of capacity operated in agiven country and its respective operating regime.31The model calculates annual mitigation costs per unit of activity level. Costs are then expressedper tonne of pollutant abated.32 However, Hoglund-Isaksson and Mechler (2005) emphasisethat although based on the same principles, due to sectoral differences (and the structure ofparameters) the methodologies for estimating costs can vary by sectoral source and pollutanttype. As a result the GAINS cost methodology differs for specific cases. Here we present twoexamples of cost estimation – one for a stationary combustion source (Box 3) and one for amobile source (Box 4). A more comprehensive review of cost methodology by the IMP Irelandteam is available in a separate guidance report (AP EnvEcon, 2010a) which highlights furthervariations when it comes to agriculture, efficiency measures and so on.30 The system is however flexible and alternative higher rates can be introduced e.g. 20% that would be more representative ofprivate investor cost perspectives.31 Examples of country specific parameters include: type, size and operating conditions of installations; national fuel consumptiontrends; vehicle mileage; emissions factors and removal efficiencies; and prices of labour, electricity, fuels and other inputs, andwaste disposal/treatment. Common data parameters generally refer to: technology specific data including unit investment costs,fixed operation and maintenance costs, removal efficiencies; and variable cost data relating to energy, labour and materials demand.32 Costs are generally expressed in constant € values of a given year (e.g. 2000, 2005).
22 | P a g eBox 3 : Costs from Stationary Combustion Sources3333 Stationary combustion sources refer to immobile pollution sources such as power plants or industrial boilers.Investment CostThe investment module equation first calculates all costs accumulated prior to the operationalisation of an abatementtechnology. In equation 3 the form of the function is described by coefficients cif and civ, with bs representing boilersize, v flue gas volume, and r as the retrofitting cost factor.𝐼 = �𝑐𝑐 𝑓+𝑐𝑐 𝑣𝑏𝑏� ∗ 𝑣 ∗ (1 + 𝑟) .......Equation 3Investments are then annualised over the technical lifetime of the plant lt at a real interest rate of q.𝐼 𝑎𝑎= 𝐼 ∗(𝐼+𝑞) 𝑙𝑙∗𝑞(𝐼+𝑞) 𝑙𝑙− 𝐼.......Equation 4Operating CostOperating costs incorporate both fixed expenditures as well as variable operating costs. Fixed operation (OMfix) costsrefer to maintenance, repair and administrative expenditures. Since these costs are not related to combustion plantuse GAINS simplifies these into a form where they are a percentage (f) of the total investment I:𝑂𝑂 𝑓𝑓𝑓= 𝐼 ∗ 𝑓 .......Equation 5Variable costs (OMvar) incorporate a broader set of parameters and can be pollutant or technology specific.Unit Mitigation Costs1Unit mitigation costs are determined on the basis of previously calculated investment and operation costs (Equation6). Klaassen et al. (2004) note that all mitigation expenditures are related to an activity unit and in the case ofstationary sources this unit is a unit of fuel input (measured in PJ). As part of the unit cost calculation process GAINSconverts all investment related costs to fuel input by applying a capacity utilisation factor (pf):1𝐶 𝑃𝑃 =𝐼 𝑎𝑎+ 𝑂𝑂 𝑓𝑓𝑓𝑝𝑝+ 𝑂𝑂 𝑣𝑣𝑣 .......Equation 6Once GAINS calculates costs per unit of activity (cPJ) the model can then estimate cost effectiveness of an abatementoption (cPMk) by estimating the unit cost per tonne of abated emissions:1.𝐶 𝑃𝑃k =𝐶 𝑃𝑃(𝑒𝑒∗ 𝛽).......Equation 7
23 | P a g eBox 4 Costs from Mobile Sources3434 Mobile sources include all forms of emission sources which are mobile. These sources thus include trucks, cars, planes, trains andships.Investment Cost ModuleCalculation of mobile source investment costs broadly follows the same basic approach as for stationary sources.However, unlike stationary sources where investment costs are calculated per unit of production capacity mobilesource investment costs are estimated per vehicle. The key parameters in the mobile investment equation are thecontrol technology (t), transport sector/vehicle category (j) and the implementation country (i). Klaassen et al.(2004) identify that the costs of applying a given control strategy in the transport sector includes addedinvestment cost, the cost of any change in fuel consumption as a result of the control, and the increase inmaintenance costs as a proportion of the total investment. Investment costs are annualised in accordance withequation 8:1 using the following function,𝐼𝑖,𝑗𝑎𝑎= 𝐼𝑗,𝑡 ∗(1+𝑞)𝑙𝑙 𝑖,𝑗,𝑘∗𝑞(1+𝑞)𝑙𝑙 𝑖,𝑗,𝑘− 1.......Equation 8Operating CostsGAINS treats mobile operating costs in the same fashion as stationary sources. Operating costs account for a fewpotential issues with a new technology for a mobile source. The fixed cost component reflects a potential increasein maintenance costs.1 The variable cost component includes parameters detailing changes in fuel costs as a resultof the implementation of a given control measure.Unit Mitigation CostsMobile source unit mitigation costs follow the same approach as stationary sources. The distinction between bothsource types is that mobile unit costs are time dependent (t). Mobile activity unit costs (cePJ) are estimated on thebasis of equation 9:𝑐𝑐 𝑃𝑃,𝑖,𝑗 =𝐼𝑖,𝑗𝑎𝑎+ 𝑂𝑂𝑖,𝑗𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑖,𝑗 (𝑡)+ 𝑂𝑂𝑖,𝑗𝑒(𝑡) .......Equation 9From equation 9 unit abatement costs (cni, j) are calculated on the basis of equation 10:𝑐𝑐𝑖,𝑗 =𝑐𝑐𝑖,𝑗 (𝑡)𝑒𝑒𝑖,𝑗∗ 𝛽.......Equation 10
24 | P a g eETS and NETS Sectors in GAINSThe ETS applies only to CO2 emissions from certain covered sectors with coverage presently notextending to a number of significant economic polluting sectors, e.g. transport or agriculture.From an emissions perspective Ireland’s non-traded sector covers all CH4, N2O and FGASemissions across all economic sectors as well as CO2 emissions from those sectors not coveredby the ETS. Scenario analysis within the GAINS model framework provides detailed informationon emissions trends, activity levels and control strategies for all sectors of the economy, thusincluding both ETS and non-ETS sectors. For an evaluation of the ‘NETS’ target, we must definefor the model the points at which to disaggregate the sectors and activities in a binarydistribution of ETS or NETS. The IMP Ireland team, have applied a ‘splitting file’ to the modelwhich filters results between the two groupings. The specific disaggregation is informedprincipally by the EPA’s 2011 Monitoring Mechanism report (EPA, 2011). Ultimately thesplitting file approach enables revisions to the split as necessary down to a sub-sectoraltechnology level if necessary.For now, the split applied assigns all transport, commercial, residential, agricultural and wasteactivity to the NETS, and all power generation to the ETS. The ground on which a split occurs isIndustry, wherein broadly the split transfers all large and heavy industry activity to the ETS andthe balance to the NETS. The approach here is not entirely straight forward as the aggregationand grouping of sectoral activities in GAINS is not the same as used in national forecasting andreporting. Nonetheless, a review the Monitoring Mechanism Report (MMR) ManufacturingIndustries & Construction (MIC) sector in comparison with the GAINS industrial sector offereda means of approximating the balance for industrial activity in the ETS and NETS. Specificallythe MMR allocates 55% of MIC CO2 emissions to the traded sector with 45% to the non-traded.For the purpose of this report we therefore allocate 55% of GAINS industry emissions to thetraded sector and 45% to the non-traded. Splits can be reviewed and adjusted via the splittingfile as necessary into the future.
25 | P a g e4. The GAINS Model Setup for this AnalysisThe GAINS Ireland model is used in this report to evaluate abatement options and costs forIreland in regard to progressing towards compliance with the NETS target in 2020. Thisapproach draws on the same international methodology and model used within Europe toinform prior work in regard to the non-traded sectors for the European Commission. However,in this instance the approach has been to further refine and recalibrate the model, whereevidence is available nationally, in order to present an interim assessment based on a hybrid ofinternational model conditions as well as nationally developed parameters and assumptions.In this section the approach to the general model setup (the baseline scenario used), as well ascalibration for individual sectors is described to provide a clear context for the analyticalconfiguration. In regard to the latter, the principal sectoral challenges involved defining thevariety of attributes necessary for defining the ‘menu’ of abatement controls (their cost,potential and expected penetration) for each sector. The choices and decisions here with regardto calibration are obviously of particular relevance to the ultimate cost and abatement potentialoutcomes identified by the GAINS Ireland model in section 5. In a number of cases the work hashighlighted information deficits to be addressed in further research, which will supportincreasingly refined and robust estimations of pathways and potentials. Indeed, arguably theprincipal interim constraint is in regard to data as opposed to methodology. For example,measures targeting the domestic sector would benefit from a robust micro level evidence base onthe characteristics and performance of households in terms of heating and appliance use. In thisregard pending initiatives such as smart metering in Ireland, may offer heretofore unavailabledata that dramatically enhances our knowledge of the sector. Similar changes have occurred inthe past and have been of significant benefit to research, modelling and policy analysis. Forexample, the interrogation of the national car test data to deliver robust disaggregated annualvehicle mileage data has fed into a range of policy (e.g. Kelly et al., 2009) and modelling analysis(Daly and Ó’ Gallachóir, 2011) research pieces.However, whilst additional data is desirable and something to be pursued progressively overtime, at this point the study represents a significant step forward in this process, being the first
26 | P a g enationally revised version of the GAINS model to have been developed in collaboration withIIASA for such a NETS analysis. With sustained effort the system can be iteratively enhanced toprovide regular and more rapid reviews of a given combination of strategy, economic and policypathways. A feature that will be of particular value as we plan, negotiate and respond to thestringent NETS GHG targets from 2013 onwards35.Baseline ScenarioThe energy and agricultural data used for the baseline scenario in this study is developed basedon official “With Measures” (WM) scenario data sourced via the Irish EPA in 2011. The scenariocombines the latest official national energy projections of SEAI (SEAI, 2010), as well as thelatest agricultural activity forecasts from Teagasc and the Department of Agriculture. The EPAadd additional value to these data by formatting them in a manner that is consistent with the in-house methodologies developed by the IMP Ireland team (AP EnvEcon 2009 and 2010c) toadopt national data into the GAINS Ireland model.Whilst the activity data are the same, the methodologies and aggregation of data in the GAINSIreland system are distinct from those used in official national projections. For these reasons,the emissions calculated in the GAINS Ireland model for the WM 2011 scenario differ somewhatfrom those in official national projections. The absolute value can vary, and the distribution ofemissions at higher levels of resolution can also vary. The variations are however generally wellunderstood, which may raise the question as to why these are not corrected. The principalreasons are:1. Aggregation and categorisation differences due to the model framework cannot becorrected without fundamentally altering the GAINS Ireland model structure anddeviating away from the core GAINS Europe structure. As a result it is better tounderstand where such variations exist and consider their relevance, if any, ininterpretation of results.35 This is also not to omit the particular strength of the model in regard to integrated modelling of both climate and transboundaryair pollution policy. Thereby informing policy action in two major thematic areas and in a manner that affords insight into thesynergies and trade-offs of a given course of action.
27 | P a g e2. Methodological differences in terms of the detail for emission estimation can lead tovariation. For example where one process uses a more detailed bottom-up methodologyas compared with a broader approach of say using population as a driver of emissionoutcomes. In some cases the model has not yet been adapted to higher tier analysis, andin some cases national analysis is on a lower tier pending additional official research anddata. For these reasons variations can exist, that we expect to ultimately reconcile.3. Source variations can also add to the difference in emission outcomes. For example,where the model considers a specific source of emissions that may not be required orofficially noted in national forecasts, this can lead to a variation. Once again, over timewe expect these variations will be reconciled, however official changes are complex.In terms of the key emission variations then to note for this analysis, these are as follows:1. Official WM CO2e projections for 2020 are 64.05Mt362. GAINS Ireland WM CO2e projections for 2020 are 65.10Mt37Agricultural milk yield emissions from GAINS account for the majority of the variation(contributing an additional 0.94Mt to the GAINS Ireland estimate) with some remainingdiscrepancy with N2O and other sources such as waste incineration contributing the balance.There are also aggregation variations particularly in areas such as industry and power, whereGAINS combines emission sources in a different manner to national methodologies, and alsotransport and agriculture, where the assignment of agricultural fuel use varies. Nonetheless, theIMP Ireland team conduct regular emission comparison assessments between GAINS Ireland36 This is the set of 2011 national projections (EPA 2011a) that use comparable data to the GAINS Scenario used37 Specifically the starting emissions point for the optimisation analyses is 65.10Mt CO2e - porting from the GAINS Ireland model tothe GAMS process entails some rounding and other processing which leads to minor variation.
28 | P a g eand official national projections to understand variations, to guide corrections and to recordacknowledged variations38.In the context of this study we are satisfied with the agreement between the scenarios, and notethat GAINS reports a starting emission level in 2020 of 1.05Mt CO2e more than is reportednationally. Thus were we to force the use of official national projections, the starting distance tothe NETS target of 37.4Mt CO2ewould of course be reduced accordingly.Sector: AgricultureIn calibrating the GAINS Ireland model for this analysis, some additional efforts were requiredto formally reconcile the GAINS model representation of the sector. The principal adjustmentswere required in relation to N2O emission levels, N2O control implementation potentials, CH4abatement control implementation potentials, and CH4 control emission reduction potentials.Cost data used drew principally on the GAINS Ireland model.Specifically, in relation to N2O it was noted that the baseline emissions of N2O from indirectsources were considerably higher (over 2m tonnes of CO2e) in the GAINS system than incorresponding national forecasts. Following consultation with colleagues nationally andinternationally it was determined that this was attributable to the GAINS model following theIPCC default of a 30% fraction of nitrogen being leached on pasture and in the paddock. InIreland however, national research recommends an equivalent 10% leaching rate and this isused in official estimations and projections. An exercise was subsequently undertaken to refinethe package of related emission factors and controls for N2O in GAINS Ireland to match moreclosely with the national methodology39. Further changes were also made in respect of controlpotentials for N2O to approximate evidence provided from the DAFF in respect of N2O emissioncontrol potentials40.38 The emission comparison reports are delivered exclusively to the IMP Ireland project steering group and are produced subsequentto each new scenario loaded into GAINS Ireland where comparable national projections are available.39 In practice, correcting for this variation presented a complication as this core value in the GAINS model was somewhat hardcodedinto the system. As an interim workaround, the package of reduced emission factors for the N sources were calculated, loaded andinitialised in the system to balance the baseline emissions in this case.40 Specifically work for the preferred policy measures group by DAFF and Teagasc.
29 | P a g eIn regard to CH4 the principal challenge was to adjust the performance of certain categories ofCH4 abatement control (e.g. forms of anaerobic digestion) as well as defining their potentialdeployment in Ireland. For technical reasons, the approach taken was to allow the potential formeasures to be set at 100% (maximum deployment). However, the abated emission factor forthese controls was revised into a consolidated value which reflected limitations on potential indiscussions with both IIASA and DAFF. At this stage in the model development, the measuresfor CH4 have been synthesised into the following two primary categories:• Feed adjustments (a synthesis of options principally reliant on dietary oils)• Anaerobic digestion (specifically community scale AD)The model was further refined to account for updated milk yields, animal housing day estimatesand the scale and eligibility of farms for controls. In respect of agriculture one particularvariation between national forecasts and the GAINS Ireland modelling system, mentionedearlier, was not reconciled, but was simply acknowledged. This relates to the higher emissionsconnected with increased levels of milk yield from the dairy herd.Sector: Commercial, Residential, HeatThe calibration of the GAINS Ireland model to assess the energy saving potential and associatedcost of measures for the residential, commercial and heat (RESCOM hereafter) sectors posed asignificant challenge. The IMP Ireland team engaged closely with IIASA to conduct this firstnationally focused revision of these parameters for use in the GAINS Ireland model. In order todescribe the calibration, we must first explain the structure of RESCOM in the model withregard to GHG emissions and controls. Efficiency measures for RESCOM in the GAINS Irelandmodel are aggregated under two categories:• HVAC needs (i.e. heating, ventilation, and air conditioning)• Other needs (i.e. water heating, cooking, small and large household appliances)
30 | P a g eIn terms of sub-sectoral structure, the GAINS Ireland model describes building units asapartments, houses or commercial buildings, and as either new (2005 onwards) or ‘existing’(pre 2005) in terms of age. For each sub-category activity (e.g. housing heating, apartmentwater heating) the model requires us to define a starting representative energy intensity valuefor each relevant parameter from the year 2005.In terms of abatement and efficiency controls, the model uses a three stage efficiency controlconcept as the indicator of progress for each activity. The first stage control delivers apercentage reduction in the base energy intensity at a defined cost, and so on for the subsequentstages. In the model we also define the potential for a given stage in a given year. This essentiallyrestricts the level of abatement to a certain share of the market in a given timeframe. Forexample the model may be programmed to limit the amount of insulation retrofitting that maytake place in a given time period.The efficiency stages themselves should not be interpreted too strictly, but rather should beviewed as three point representations on a curve of potential efficiency (and associated cost) fora given activity. In order to calibrate the RESCOM sector for this analysis then we requiredstarting energy intensities, stock characteristics and controls as well as defined efficiency stagesand costs.We began the task with independent assessments of energy intensities related to HVAC. Giventhe lack of official evidence, two separate approaches were taken to generate a range forconsideration. In the first approach we compiled energy balance data (from SEAI), activebuilding stock (DOELG, census, CSO, construction data), average floor area (DOELG, planningapplications) and persons per household (CSO) to estimate the heating and other energyrequirements of the sector (e.g. megajoules per M2 for heating). In the second approach weutilised modified building energy rating (BER) data with expert input (SEAI SSU) to derive anindicator with which to estimate certain disaggregated parameters, such as spatial energyintensities, energy used for water heating and so on. .
31 | P a g eRelevant national literature and reports were used to fill other data gaps and to provide contextand broader validation for this work. Specifically sectoral energy reports from the statisticalsupport unit of the SEAI, building and retrofitting reports from SEAI, statistics and forecastsfrom the CSO, SEAI, DOELG and EPA, research papers from Perez-Lombard et al., (2007),Dineen and O’ Gallachoir (2010) and Regan and O’Gallachoir (2011), and direct correspondencewith the Energy Research Group of University College Dublin. In regard to cost data, applianceefficiency stage cost data were drawn from the international calibration of GAINS, whereas costestimates for retrofitting and new construction were based on broad industry estimates andinsurance prices (e.g. architect estimate of rebuild cost for passive retrofit standard).These two approaches and the associated literature review offered an indicative basis fromwhich to decide on a starting point for calibration of the model. In essence compiling a timeseries under approach 1 and snapshots under approach 2, offered the means of suggesting howmuch energy we should expect our domestic sector to be using in 2020 where we projectparameters (e.g. house numbers, population, house size) on that time horizon.The second stage however, was to reconcile the outcomes of these independent assessments ofenergy intensities and controls in order to finally align the model calibration with nationalforecasts of energy. In this process, the associated energy requirements that the model nowestimated would be in use in future years were considered in contrast to the latest official energyforecasts for the sector from the Sustainable Energy Authority of Ireland. The developed modelparameters were then adjusted (through control efficiency, control share and energy intensityadjustments) to reconcile values with the baseline (with measures) and white paper (withadditional measures) scenarios of SEAI41 in a consistent manner across both scenarios. Otherfactors such as degree day statistics and climate type were also defined in the modellingframework. The GAINS Ireland model was thereby calibrated to reconcile with national energyforecasts, but there are two important notes for future research in this area:41 This work highlighted an area for future research whereby the GAINS Ireland modelling work should work closely with SEAI andothers to ensure that the representation of the building stock, energy performance and energy forecasts are consistent across theboard.
32 | P a g e1. The extent to which national forecasts adequately capture and represent the expected HVAC,housing stock and appliance developments needs to be understood more clearly to ensure thatreconciliations are meaningful. Bottom-up methodologies of energy demands and theirrelationship to top-down models of national energy demand are important.2. There are many combinations of measures, intensities and efficiencies that can deliver a givenenergy outcome. It is hoped that over time new research and increased penetration of smartmetering and other data sources will provide more detailed evidence on which to base futurecalibrations.Thus, whilst good progress has been made in this process within the GAINS Ireland framework,it remains clear that there is a paucity of evidence both nationally and indeed internationallywith which to calibrate and estimate costs and potentials in these sectors into the future at anaggregate scale. The high volumes of heterogeneous units (buildings) operating under differentconditions and for varied purposes within these sectors create much of this challenge, with thevariations in appliances and technology deployment adding a further level of detail. Aconclusion of this initial work is that further efforts should be made in regard to researching newdata and collating and reconciling existing outcomes from different studies and reports.Sector: WasteThe calibration of the waste sector has drawn on prior efforts to calibrate this sector for analysisby the authors, the team at IIASA and the Irish EPA in 2009 and again in 201142. This involvedidentifying official volumes of waste and projections, and assigning appropriate splits in the typeand source of waste generated. Specific adjustments were made in the recent work to correct thelevel of Municipal Solid Waste (MSW) as well as the representation of domestic waste water andindustrial waste water.42 Specifically those principally involved being, Dr. J.A. Kelly of AP EnvEcon, Dr. L. Hoglund-Isaksson of IIASA, and Dr. B. Hyde ofthe EPA.
33 | P a g eHowever, emissions in the calibrated scenario remain approximately 0.2Mtonnes of CO2e belowofficial estimates43. Much of this is explained by the differing expectations for incineration andother technologies in the waste market as it develops to 2020. GAINS requires a reasonablydetailed perspective on the volumes, type, source and technologies of waste management intothe future. Therefore expectations on the penetration and performance of specific controls willinform any future reconciliation. A matter for consideration under further work is the expecteddirectional development of the waste sector in Ireland, as this will influence the type of activityand relevant abatement controls into the future. Specifically, a major consideration is theexpected scale of incineration development, and the corresponding development of the wastesector and associated processing technologies into the future. The international review of wastemanagement policy44 (2009) offers some insight, however, the authors feel their remains someparticular uncertainty in this market place to be considered for further work.Sector: ProcessThe process ‘sector’ in GAINS refers specifically to non-energy processes that contributeemissions. Principally in Ireland this relates to cement and lime production. The GAINS modelutilises a ‘process’ emission factor to calculate associated emissions, and so the two parametersrequired for a process are the controlled emission factor and the amount processed. Theapproach nationally differs somewhat, and so for GAINS Ireland a hybrid approach was used forthis analysis. In terms of controlled emission factor, this was determined on the basis of impliedemission factors reported through the national inventory team, and adjusted for expectedimprovements over time. In regard to activity, the IMP team projected revised cementproduction levels for 2020 to a level of just over 4m tonnes for this analysis. Downwardrevisions to this estimate may be warranted in further work on this topic.Sector: TransportIn regard to transport and GHG emissions, GAINS requires information on three separate areasas follows:43 In the context of the overall NETS target, the waste sector is one of the less significant contributors.44 Report available from DOECLG
34 | P a g e1. Fuel efficiency and investment costs of propulsion technologiesThe technologies are classified according to their key propulsion concept. However eachtechnology represents a whole package of single measures including aerodynamics, rollingresistance, auxiliaries, vehicle weight, etc. Costs are given as extra manufacturing, operating andmaintenance costs relative to a baseline vehicle.2. Baseline penetration rates for new technologies in road transportPenetration rates for each new (propulsion) technology in the road transport sector for thebaseline scenario are required. The penetration rate together with the fuel efficiency of therespective technology determines the average fuel efficiency of the respective vehicle layer (i.e.vehicle category per fuel type).3. Maximum penetration rates for new technologies in road transportThe maximum feasibility is constrained by rate of uptake of new vehicles, which depends on theturnover of the fleet. It is limited by behaviour, costs, technical feasibility, regulations, etc. Thepenetration rate together with the fuel efficiency of the respective technology determines theaverage fuel efficiency of the respective vehicle layer (i.e. vehicle category per fuel type). Hence,the maximally feasible penetration rates determine the lower limit of the fuel efficiency for eachtime period.For this report, estimates of vehicle stock by year are obtained from the TREMOVE Irelandmodel, and from CSO figures on vehicle registration, which are now available by CO2 emissionband. By deriving a vehicle depreciation rate, and including the new registration of second handvehicles, estimates on vehicle stock are calculable out to 2020. It is worth noting also that theseestimates from TREMOVE Ireland include the effects of several recent tax policies affecting thetransport sector. Namely these include the carbon tax on fuel, the new motor tax, and theremodelled VRT rates for private vehicles based on CO2 emission bands. Furthermore, inaddition to these vehicle stock level estimates, TREMOVE also contains estimates of vehiclekilometres and fuel consumption. From the latter, an estimate of fuel efficiency can be derivedwhen divided by vehicle stock. This has been achieved for all vehicle categories and fuel types asdefined by GAINS.
35 | P a g eHowever, there were some methodological issues in incorporating this work into GAINS Irelandat this point, and as a result much of the GAINS model calibration of the transport sector for thisreport remains based on a European wide average of abatement potentials and costs for thevehicle fleet. Whilst this approach serves well for more aggregate analysis, an ex post resultsassessment by the IMP team suggests that some considerable further work is necessary to refinethe technical potential of this sector for Ireland. In brief, it is believed that the model analysis aspresented in this report currently underestimates the technical potential for abatement fromthis sector. There are also some further research tasks to be undertaken in order to improve thissector in the model calibration. For example, more refined work in determining the potentialshare of transport activity that may be displaced by electric vehicles, or estimating the futurebalance of vehicle fleet fuel efficiency, taxes and demand in a manner consistent with nationalenergy forecasts. A comprehensive review and recalibration of this sector in the model isplanned under further work. In the interim, the estimations draw most heavily on Europeanaverage data and are believed by the authors to underestimate potential for abatement.5. ResultsIn this section we discuss the baseline and the cost-optimal baseline45 outcomes, followed by theresults of the least cost optimisation (LCO) and maximum feasible reduction (MFR) scenario. Inregard to the baseline, the setup of the GAINS Ireland model for this analysis using the ‘withmeasures’ scenario, delivers a total of 65.10 M tonnes of CO2e in 2020 whereas the officialnational projections come in at 64.05 M tonnes46. Just under 1M tonnes of the variation isexplained by higher emissions associated with higher milk yield under the GAINS methodology,with the balance attributable to moderate variations in other sectors such as waste. The variedcategorisation of certain emission sources in GAINS also gives rise to some apparentdistributional variation in the emissions, but these are generally well understood and have littleimpact on the results presented. Figure 3 illustrates how the 65.1Mt are distributed across thesectors in GAINS Ireland.45 Technically the cost-optimal baseline is an optimisation.46 Further detail on the setup and sectoral calibration is found in section 4
36 | P a g eFigure 3: 2020 Emission break-down for the With Measures scenario in GAINS IrelandThe cost-optimal baseline (COB) is the first result presented. The COB is effectively a first stageoptimisation whereby all measures with no net annualised cost are engaged and deployed. Thusmeasures that deliver an annualised net saving are assumed to be taken under the COB. For thisreason, the model estimates the COB first as it is intended to be representative of what couldand should be done anyway from a societal perspective. The outcome of the COB analysis overthe baseline is captured in Figure 4, the result being a reduction in both ETS and NETS CO2eemissions of 3.1Mt combined, with NETS emissions coming down to a level of 46.2Mt. Thespecific measures taken (more of / less of marginal cost curve format) are presented inAppendix 1 of the report for all marginal cost levels47. The COB options are captured in the €0marginal cost row.In regard to the COB though and the general presentation of abatement costs, it is worthreiterating the approach to cost in the model and in this specific assessment as described insection 3. All costs presented here are calculated on a social interest rate of 4% on 2005 pricelevels and exclude transfer payments and transaction costs. It is principally these assumptions47 Some care is required in interpreting the marginal cost curve in the format presented in the appendix. Notes on this point areincluded within the appendix itself.0.0010.0020.0030.0040.0050.0060.00ETS NETSMtofCO2eOtherWasteDomesticTransportAgricultureIndustryPower
37 | P a g ethat give rise to the significant negative costs48. However, the observed potential in this analysisis by no means unique. Significant negative cost abatement options under comparableevaluation criteria are in line with the outcomes presented under the Fourth Assessment Reportof the IPCC (Barker et al., 2007).The next result presented is the least cost optimisation (LCO). The LCO is a cost-minimisingoptimisation whereby the scenario seeks the lowest cost package of available measures that canbe engaged to achieve a given target level of emissions. In the case of this report, the LCO targetis the NETS emission target of 37.4Mt CO2e with a marginal cost cap of less than €502005 pertonne of CO2e imposed. The outcome of the LCO analysis is a total national emissions level of55.9 Mt CO2e, with the NETS emissions reduced to a level of 42.2 Mt CO2e. Thus in this case weagain fail to meet the NETS target under the prescribed conditions.The final result presented is the outcome of the maximum feasible reduction (MFR) scenario. Inthis case the optimisation applies all available measures to determine the maximum feasiblereductions possible under the model conditions. In this assessment, the listed measures do notexceed a marginal cost of €250 per tonne of CO2e, however, in time the menu can be extended toinclude even higher cost potentials for abatement. The result of the MFR optimisation is a totalnational emission level of 51.4 Mt CO2e with NETS emissions of 41.4 Mt CO2e. Therefore evenunder the MFR conditions described, Ireland fails to meet the NETS target of 37.4 Mt CO2e. Thesummary results of all scenarios and the cumulative cost of different levels of marginalabatement cost thresholds are presented in Figures 4 and 5. Of note, Figure 4 illustrates theconnected impact of the optimisations on the ETS sector, where the COB, OPT and MFRscenarios all deliver significant over compliance for the ETS objective. Whilst Figure 5demonstrates that from a social planner’s perspective, the cumulative annualised net social costof options taken remains negative up to the €150 per tonne marginal abatement cost level.48 That said, it is a common question to ask why, where such measures exist, they have not been taken. Briefly, this can be due toother barriers and failures beyond cost. Whilst we do not discuss these other barriers in this report, we note that it may be of interestto utilise a 20% rate to present a cost outcome representative of the cost investment under a private investment interest rate. Thislatter analysis would paint a different picture of the abatement options and can be conducted under further research in this area.Specifically it would offer a perspective on the indicative scale of the financial barrier to private investment and would substantiallyreduce the cost savings relative to the social interest rate analysis presented.
38 | P a g eIn terms of specific measures, at the COB level, national GHG emissions are reduced by 3.1MtCO2e by taking measures from the zero marginal cost category. These are measures that offer netcost savings and emission reductions under the defined methodology. In terms of the mainactions at this level, the COB scenario adopts a range of measures principally associated with theincreased efficiency of commercial and residential appliances and space heating, and theadoption of advanced efficiency and hybrid diesel trucks and buses into the transport fleet.Further measures in other sectors include the deep injection of manure into soils in theagriculture sector, and further investment in leak control for gas distribution networks andcompressor stations.The LCO/OPT scenario selects measures up to a marginal cost of €50 per tonne of CO2e anddevelops from the COB. The LCO reduces total national GHG emissions by 9.2 Mt CO2e from thebaseline. At this level we see changes in the power sector, with coal fired generation beingreplaced by new gas-fired plants, and further adoption of biofuels and wind power in the sector.This further decarbonisation of the power generation sector in turn influences the penetration ofefficient appliances and heating services in the domestic and commercial sectors, specificallyslowing some of the change, as higher cost advanced stages of energy efficient appliances andheating become less significant in terms of associated CO2e reductions. At this level we also seechanges in industry, with the introduction of more industrial CHP, the use of alternativesolvents and refrigerants, and the adoption of more efficient processes in production. In theagricultural sector we see the introduction of farm scale anaerobic digestion, a mix of feedchanges and improvement of nitrogen efficiency via “precision farming”.Under the MFR scenario all measures (within the model menu of abatement options) that maybe combined to achieve emission reductions are taken, with a view to identifying the greatestreduction in emissions possible under the current model framework conditions. In the MFRsome constraints remain in place over the potential change as described in section 3 (e.g. nomore than an additional 8.75pj of wind power beyond the baseline), and the menu of measuresdraws on those summarised earlier in Box 2. Under the MFR a large number of “more of” / “lessof” changes take place in terms of abatement options, ultimately delivering a reduction innational GHG emissions of 13.7 Mt CO2e from the baseline, with NETS emissions at 40.4 MtCO2e, some 4Mt CO2e above the target level for 2020.
39 | P a g eFigure 4: ETS & NETS Emission outcomes for WM baseline and defined optimisations in 2020Figure 5: Net social cost of cumulative marginal cost band measures for WM scenario in 202047,962 46,20042,200 40,40037,40017,39315,80013,70011,000 17,690010000200003000040000500006000070000Baseline COB OPT MFR Targets000TonnesofCO2eWith Measures Scenario Run and TargetsETSNETS-500-400-300-200-10001002000 25 50 75 100 125 150 175 200 225NetAnnualCostin2020in€2005Marginal Cost Bands €2005
40 | P a g eSensitivityAs a matter of interest, the COB, LCO and MFR optimisations were also applied over thealternative ‘With Additional Measures’ (WAM) scenario, officially now known as theNEEAP/NREAP scenario. In this scenario the energy data implicitly account for a higher degreeof renewables nationally and the successful attainment of a number of policy targets,particularly in relation to energy efficiency.The WAM scenario therefore presents a more advanced (in terms of emission reductions)starting point for the analysis49. Under the WAM scenario, the baseline emissions from thecalibrated model are 59.2 Mt CO2e. The COB run delivers total national emissions of 56.8 MtCO2e with NETS emissions down to 42.9 Mt CO2e. The LCO run delivers a national emissionstotal of 51.2 Mt CO2e with a corresponding NETS emission level of 38.7 Mt CO2e – still in excessof the national NETS target. Finally however, the MFR brings national emissions to a level of47.2 Mt CO2e, with NETS sector emissions reduced to exactly 37.4 Mt CO2e – the NETS target.Caution is however required with using the WAM/NEEAP/NREAP scenario given the inherentambition of a number of the scenario assumptions, particularly the assumed success ofundefined policies to achieve challenging energy efficiency and renewable targets across thesectors. As noted at the outset, we feel the WM scenario offers a more rational basis from whichto plan and evaluate strategies and pathways to compliance.6. Note on Additional Mitigation Options and LULUCFAs a point of information related to the results presented in section 5, it is important tounderstand what these results represent in terms of potential. Simply put, they represent themenu of abatement options as defined in the modelling system used for the analysis. There are a49 Although the effect of commercial and residential efficiency measures are captured in the model setup process by way of greaterpenetration of improved efficiency stage controls.
41 | P a g enumber of considerations with respect to abatement potentials and compliance with the NETStarget therefore, that should also be discussed. Specifically we will present three briefdiscussions in relation to: Additional technical potential and the core menu of measures Non-technical and Behavioural measures The role and relevance of LULUCF and carbon sinks in the NETS processAdditional technical potential of the menu of measuresThis report presents the analytical outcomes of a first calibration of the full GAINS Irelandmodel for an assessment of GHG abatement potential. This introduces numerous additionalchallenges beyond those addressed whilst using the model to inform transboundary air pollutionpolicy as it extends the system into a new area with new information requirements. We identifyin the results that there is an apparent untapped potential from certain sectors which thecurrent setup of the model is not identifying. Specifically the transport sector should offersignificantly more emission reduction potential than identified in this first analysis, and this willbe addressed in further work where a blend of model improvements and exogenous research canbe combined to integrate the potentials and costs associated with options such as high levels ofelectric vehicle penetration, retrofitting and so forth. Similarly we have earlier acknowledgedthat the model has not included the potential for certain options such as CHP in domesticheating, solar or geothermal, and has constrained certain potentials (e.g. wind energy andbiofuels) to a degree. Of course these constraints can and will be changed in time as the systemis further developed, and as new evidence and research to inform the setup are gathered.Indeed, on this first calibration exercise a number of areas were identified where national data islacking in respect of calibration requirements. This is not exclusively an ‘Irish’ problem, and thedifficulties are quite common at an international level also. The driver of this challenge isprincipally that the decision-support demands on the models are requiring increasing levels ofdetail in calibration to enable their analysis of complex issues50. However, whilst increaseddetail may prompt concern from some quarters, there is cause for optimism in regard to this50 A major motivation for the development of the www.policymeasures.com resource was to support progress on this ‘calibrationchallenge’ in a coherent and internationally cooperative manner.
42 | P a g e‘calibration challenge’, as it is expected that a number of research and technology initiatives,unknown or untested a decade ago, will be a great support in delivering the requisite data at ahigh resolution, that will offer a more robust evidence base into the future (e.g. advanced ICT intransport, Smart metering in the home). Similarly, the higher level of funded research andmonitoring that prevails nowadays will also facilitate the availability of an evidence base forcalibration that simply did not exist a decade or more ago. For the time being however, weremain at an earlier stage in this process, and recognise that the calibration of the modelrequires additional evidence and research. Improvements in this regard will remain an iterativeprocess, and we acknowledge that calibration of certain measures in the modelling system (e.g.the cost and potential for insulation to reduce energy demands in the domestic sector) representsignificant bodies of work in their own right that will take time to address. Nonetheless, themodel framework offers a sound basis on which to integrate evidence for analysis over time.Non-technical and behavioural policy measuresThere are many behavioural measures (e.g. road pricing, carbon taxation) that are notincorporated into the GAINS methodological framework explicitly. However, in the context ofGHGs and specifically the NETS target, such measures are of particular relevance to nationalprogress on targets and stimulating the necessary investments and change. Such measures canbe evaluated exogenously and subsequently be incorporated back into the GAINS modellingframework51 (AP EnvEcon, 2010d).Analysis to deliver quantified abatement potential estimates of such exogenous measures, aswell as policy interactions have been conducted as part of parallel research under the IMPIreland project. Of particular relevance the team have conducted detailed measure analyses andwritten papers on topics such as: The factors influencing vehicle purchase decisions in Ireland (Fu et al., 2011) Carbon, vehicle registration and road tax policies for transport (Fu and Kelly, 2011a) The scope for flexible working policies to reduce emissions (Fu et al., 2011b)51 Though this process remains somewhat complex and challenges persist in regard to accounting for exogenously evaluatedmeasures appropriately in the context of optimisation analyses such as those presented in this report.