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Meeting radiative forcing targets under delayed participation
Energy Economics 31 (2009) S152–S162
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Energy Economics j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / e n e c o
Meeting radiative forcing targets under delayed participation Jasper van Vliet ⁎, Michel G.J. den Elzen, Detlef P. van Vuuren Netherlands Environmental Assessment Agency (PBL), P.O. Box 303, 3720 AH Bilthoven, The Netherlands
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Article history: Received 7 April 2009 Received in revised form 29 May 2009 Accepted 11 June 2009 Available online 21 June 2009 Keywords: Climate Climate policy Participation regimes Integrated assessment model Overshoot scenarios
a b s t r a c t In this article we explore several scenarios that aim at meeting radiative forcing targets at 4.5, 3.7, 2.9 and 2.6 W/m2 by 2100. These scenarios are run under the assumption of participation of all countries by 2012 in climate policy and under the assumption of a significant delay in the participation of Russia and non-Annex I countries (up to 2030 and 2050). The study finds the lowest radiative forcing categories to be feasible under full participation, certainly if overshoot of targets is allowed and when bio-energy and carbon-capture-andstorage is added to the mitigation portfolio. In cases with severe delay in participation, the lowest targets become infeasible. For less strict targets (e.g. 3.7 W/m2), delayed participation leads to considerable costs increases (up to 90% for the stabilisation case). As a next step, scenarios with less delay in participation need to be explored. © 2009 Elsevier B.V. All rights reserved.
1. Introduction Limiting global mean temperature increase to only 2–3 °C with reasonable probability requires that GHG concentrations are kept below 550 ppm CO2-eq. So-far, the number of scenario studies that aim at low GHG concentration targets is still relatively scarce (for an overview see Fisher et al., 2007). Almost all of these studies analyse the implication of low concentration targets under the idealized assumption that all regions and sectors participate in full emissions trading without any restrictions (first-best worlds). This implies that there is full flexibility with respect to the question where and when emission reductions take place allowing for least costs solutions (so-called full when and where flexibility). Only a limited number of studies explored the possibility of achieving GHG concentration or radiative forcing targets in situations where not all regions contribute to mitigation (like Russ et al., 2005; Keppo and Rao, 2007; Richels et al., 2007; Edmonds et al., 2008; Russ et al., 2009). As a result, limited insight exists on the level and timing of global abatement costs for a more realistic scenario assuming limited participation (i.e. participation gradually develops in time including more countries and/or sectors). Similarly, limited insight exists on the attainability of low concentration targets under these imperfect conditions. In particular, the timing of participation of major emitting developing countries, like China and India, in a reduction regime is likely to play an important role. This paper forms part of the EMF-22 model comparison study of international transition scenarios that explores the impact of staged participation on the costs of stabilizing CO2-equivalent concentrations (Clarke et al., 2009-this issue). In the experiments, full participation ⁎ Corresponding author. Tel.: +31 30 274 3723. E-mail address: [email protected] (J. van Vliet). 0140-9883/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.eneco.2009.06.010
regimes are compared to regimes with delayed participation by Russia and the non-Annex I countries (a full definition of regions and timing of participation is given in Section 2.2). This paper describes the results of the experiments run with the IMAGE framework (i.e. IMAGE, TIMER and FAIR models) (Bouwman et al., 2006). The model ran for satisfying targets at 4.5, 3.7, 2.9 and 2.6 W/m2 by 2100 (including and excluding an overshoot) and sensitivity tests. In this paper, we first describe the model framework (Section 2), and the baseline assumptions (Section 3), and then focus on the mitigation scenarios (Section 4). We briefly discuss the impact of the assumptions made by EMF-22 on the results (Section 5) and finish with drawing general conclusions (Section 6). 2. Research design 2.1. Climate strategies and policy regimes There are many factors that determine the costs of future climate policy. As indicated in the Introduction, most long-term studies so-far looking at low stabilization targets have assumed full participation of all countries and sectors. These studies explored the costs of international climate policy as a function of factors such as 1) the overall objective of climate policy, 2) baseline developments, 3) the ability to allow for substitution across different gases (EMF-21), 4) technology development (EMF-19 and IMCP, i.e. Innovation Modelling Comparison Project), and 5) timing of reductions (and more specifically the inclusion of overshoot). A future climate regime, however, will also have to define elements like participation and the specific instruments that are used. To some degree, the influence of these factors has been studied in the context of medium term climate policy and for relatively high GHG concentration targets (EMF-14).
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No model comparison study has been performed, however, on the influence of participation rules on the attainability of low GHG concentration targets. The fact that the feasibility of climate targets and associated costs is determined by a range of factors (see above) implies that the influence of one factor alone (here participation of counties) cannot be studied in isolation. Below, we briefly discuss some factors that determine the costs of future climate policy. Regarding the objective of future climate policy, most studies on long-term climate policy have explored the costs of various stabilization goals (with a strong bias towards particular goals such as stabilization at 650 ppm CO2e). These studies show that (as expected) the costs strongly depend on the stringency of the target with costs exponentially rising for lower stabilization levels. In recent years, many more studies have explored the costs and feasibility of achieving stabilization targets that could lead to avoiding a 2 °C increase in global mean temperature compared to pre-industrial levels. These studies showed such scenarios to be feasible under certain conditions, with costs typically in the order of a few percent of GDP (in terms of GDP losses). These costs, however, are strongly influenced by other assumptions. Both van Vuuren et al. (2007) and Knopf et al. (2009) show that the availability of different technologies, including the option of Bio-Energy and carbon-Capture-and-Storage (BECS) could critically influence costs and even the feasibility of targets. den Elzen and van Vuuren (2007) show that costs also strongly depend on whether one allows a limited overshoot of concentration targets. They show that overshoot scenarios can achieve temperature targets at lower costs—and therefore recommend future studies to look into overshoot strategies rather than stabilization strategies. The issue of participation is also known to be a crucial element of future climate policy. Hof et al. (2009) have made an overview of studies that provided quantitative results for full participation versus partial participation regimes. In each case, partial participation regimes lead to considerably higher costs. The advantage of full participation regimes is that they allow for full flexibility in implementing the least expensive emission reductions throughout all countries, sources and sectors, lowering the costs for meeting the overall emission target. The disadvantage is that it is far from easy to achieve global agreement on such comprehensive regimes—and one may argue that in the short-term assuming full participation is not realistic. It should be noted, however, that in reality the difference is not clear cut. Even under a full participation regime, countries could have a limited contribution in emission reductions allowing them to become a net seller of emission credits. And under partial participation regimes, flexible instruments like the Clean Development Mechanism (CDM), may allow for some form of flexibility.
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2.2. Set up the analysis in this study On the basis of the discussion above (and as part of the model comparison study for EMF-22), this study looks into the influence of participation on the costs and feasibility of meeting radiative forcing targets at 4.5, 3.7, 2.9 and 2.6 W/m2 (or GHG concentrations at 650, 550, 480 and 450 ppm CO2-eq) by 2100. Radiative forcing targets refer to Kyoto gases only (CO2, CH4, N2O, HFCs, PFCs, and SF6) (as prescribed for model comparison). For our modelling framework (see also Section 2.3), the targets are calculated using the MAGICC 4.1 model, calibrated to forcing levels as reported in IPCC's Third Assessment Report (changes in radiative forcing levels from greenhouse gases since then are small) (Ramaswamy et al., 2001). A medium emission pathway is used as a baseline for this analysis. We specifically look into the question how the inclusion of overshoot (for 3.7, 2.9 and 2.6 W/m2) and the use of BECS (BECS is not part of the default set of mitigation options, only for 2.9 and 2.6 W/m2) influences overall costs. This leads to the following nine mitigation scenarios (Table 1), which are labelled as: 2.6 W/m2 BECS, 2.6 W/m2, 2.6 W/m2 BECS OS, 2.6 W/m2 OS, 2.9 W/m2 BECS OS, 2.9 W/m2 OS, 3.7 W/m2, 3.7 W/m2 OS and 4.5 W/m2 (note: OS stands for overshoot). The analysis assumes two main cases for each scenario with respect to participation: Full Participation and Delayed Participation (hereafter these scenarios are shortly labelled as Full and Delay, see Table 1). In the latter case, it is assumed that Annex I or developed regions (excluding Russia) (hereafter labelled as group 1 regions) begin or continue with emissions reductions in 2012; Brazil, Russia, China, and India (BRIC) regions (group 2 regions) join the global coalition in 2030 while for the remaining non-Annex I or developing regions (group 3 regions) it is assumed that they join the global coalition in 2050. For the late entrants in the coalition, it is also assumed that there is a period of 20 years before they are fully exposed to the global carbon price. In fully participating regions, carbon prices are equal. Non-participating regions have a zero carbon price. For regions in transition from no- to full-participation the carbon price grows from zero to the level of the participating regions during the transition period. A linearly growing proportion of the regions' mitigation potential is exposed to the global carbon price and the regional price is the price at which the exposed mitigation potential is fully implemented, until the global carbon price is reached. In the analysis, we found several mitigation scenarios not to be feasible in our model framework: the current framework is not able to find a solution if carbon taxes exceed 273$/tCO2 (expressed in 2005 U.S. $) (see Table 1). In a limited number of cases, the scenarios can even be regarded as physically infeasible, as they lead to extremely negative emissions for the coalition of participating regions). The 2.6 W/m2 target
Table 1 Overview of the scenarios. Scenarioa
Characteristicsb
Mitigation optionsc
Scenario 1 (full participation—Full)d
Scenario 2 (delayed participation—Delay)d
0. Baseline 1. Stabilisation 2.6 W/m2 (2.6 W/m2 BECS) 2. Stabilisation 2.6 W/m2 (2.9 W/m2 OS) 3. Overshoot 2.6 W/m2 (2.6 W/m2 BECS OS) 4. Overshoot 2.6 W/m2 (2.9 W/m2 OS) 5. Overshoot 2.9 W/m2 (2.9 W/m2 BECS OS) 6. Overshoot 2.9 W/m2 (2.9 W/m2 OS) 7. Stabilisation 3.7 W/m2 (3.7 W/m2) 8. Overshoot 3.7 W/m2 (3.7 W/m2 OS) 9. Stabilisation 4.5 W/m2 (4.5 W/m2)
No climate policy Not to exceed 2.6 W/m2 (450 ppm CO2-eq) Not to exceed 2.6 W/m2 (450 ppm CO2-eq) 2.6 W/m2 in 2100 (450 ppm CO2-eq) with overshoot allowed 2.6 W/m2 in 2100 (450 ppm CO2-eq) with overshoot allowed 2.9 W/m2 in 2100 (480 ppm CO2-eq) with overshoot allowed 2.9 W/m2 in 2100 (480 ppm CO2-eq) with overshoot allowed Not to exceed 3.7 W/m2 (550 ppm CO2-eq) 3.7 W/m2 in 2100 (550 ppm CO2-eq) with overshoot allowed Not to exceed 4.5 W/m2 (650 ppm CO2-eq)
Default + BECS Default Default + BECS Default Default + BECS Default Default Default Default
Infeasible Infeasible X Infeasible X X X X X
Infeasible⁎ Infeasible⁎ Infeasible⁎ Infeasible⁎ Infeasible Infeasible X X X
An additional indication (⁎) has been added for those scenarios, which are considered physically infeasible as they lead to extremely negative emissions for the coalition of participating regions. a Radiative forcing targets as calculated by MAGICC 4.1 based on forcing from Kyoto gases only. b “Not to exceed” targets imply standard stabilization scenarios without overshoot. c Default settings do not include BECS. d Scenarios become infeasible in our framework if required tax levels to meet the radiative forcing target exceed at any time 1000$/tC (= 273$/tCO2) (no solvable solution).
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Fig. 1. Linkage and information flows between the models IMAGE, TIMER and FAIR (note CP = Carbon plantations). Steps 1–2 are explained in the text. Source: adapted from van Vuuren et al. (2007).
was only found to be feasible with use of BECS and in overshoot scenarios. In the analysis of the results (Section 4) we concentrate mostly on the scenarios for which a solution was found. 2.3. Modeling framework IMAGE, TIMER and FAIR For the analysis of the mitigation scenarios, we use the Integrated Assessment modeling framework IMAGE 2.4 (Bouwman et al., 2006).1 The IMAGE model consists of a set of linked and integrated models that together describe important elements of the long-term dynamics of global environmental change, such as air pollution, climate change, and land-use change. The land modules of IMAGE describe the dynamics of agriculture and natural vegetation, including potentials for biofuels under resulting climate change, and the land-use related emissions of GHGs. The global energy model, TIMER, as part of the IMAGE model, describes the primary and secondary demand and production of energy and the related emissions of GHGs and regional air pollutants (van Vuuren et al., 2007). The FAIR–SiMCaP model is a combination of the abatement costs model of the FAIR model and the SiMCaP model (den Elzen and Meinshausen, 2006; den Elzen et al., 2007; den Elzen and van Vuuren, 2007). The FAIR cost model distributes the difference between baseline and global emission pathway following a least-cost approach using regional Marginal Abatement Costs (MAC) curves for the different emissions sources (den Elzen et al., 2007). More specifically, the MAC curves for energyand industry-related CO2 emissions were determined with the TIMER energy model (van Vuuren et al., 2007) by imposing a carbon tax and recording the induced reduction of CO2 emissions. This has been further improved compared to earlier work by now including four instead of two different tax profiles. We now capture the full range of possible tax paths that represent early action and highly delayed action. The MAC curves for carbon plantations were derived using the IMAGE model (Strengers et al., 2008). MAC curves from the EMF-21 project (Weyant et al., 2006) were used for non-CO2 GHG emissions. These curves have been made consistent with the baseline used here and made time-dependent to account for technology change and removal of implementation barriers (Lucas et al., 2007). It should be noted that while CO2 emission reductions from the energy system are
1 The model names are acronyms. IMAGE = Integrated Model to Assess the Global Environment; TIMER = The IMage Energy Regional model; FAIR = Framework to Assess International Regimes for the differentiation of commitments.
described accounting for dynamic processes such as induced learning and limited capital turn-over rates, reductions for non-CO2 gases are based on simple MAC curves (that change over time, but do not limit reduction potential based on a vintage structure). The SiMCaP pathfinder module makes use of an optimisation procedure to find least-cost, multi-gas emission pathways over the 2005–2100 time period that correspond to a predefined climate target. The recently added intertemporal optimisation was set to minimize the cumulative discounted abatement costs. The discount rate applied here is 5%. Furthermore a maximum reduction rate of 3% was assumed (for the BECS scenarios 4%), reflecting the technical (and political) inertia that limits emission reductions, avoiding premature replacement of existing fossil fuel-based capital stock. As reduction rates in existing scenarios hardly exceed 2.5% per year (Swart et al., 2002). Global climate and GHG concentration calculations make use of the simple ‘climate’ model, MAGICC 4.1 (Wigley and Raper, 2001, 2002; Wigley, 2003). The climate model of MAGICC is a simple upwelling-diffusion energy balance model. The carbon cycle model describes fluxes between six global reservoirs (oceans, atmosphere, and four terrestrial carbon stores). For radiative forcing levels, MAGICC 4.1 is calibrated on the information of the Third Assessment Report (Ramaswamy et al., 2001). The model framework calculates emissions of all greenhouse gases (GHGs), ozone precursors (volatile organic compounds, CO, and NOx), and sulfur aerosols (SO2) from energy and land-use related sources, atmospheric concentrations, radiative forcing, and resulting climate change. The analysis consists of the following steps (Fig. 1): 1. The baseline emission scenario is constructed using the models TIMER (energy) and IMAGE (land). These models also provide information on the potentials and abatement costs of reducing emissions from the energy and land-use systems. 2. The FAIR–SiMCaP model is used to develop global emission pathways that lead to a long-term target of the atmospheric GHG concentration. The FAIR model distributes the global emission reduction from baseline to meet the global emission pathway, assuming a costoptimal implementation of available reduction options over time, different regions, gases and sources, based on the information in step 1. 3. The scenarios are implemented in the TIMER model to identify changes in the energy system. Abatement costs of each scenario are calculated on the basis of the marginal permit prices and the actual reductions. They represent the
J. van Vliet et al. / Energy Economics 31 (2009) S152–S162 Table 2 Baseline scenario (Group 1: Annex I regions excl. Russia; Group 2: Brazil, Russia, China, and India (BRIC) regions; Group 3: remaining non-Annex I or developing regions). 2000 2050 Population
Billions
World 6.1 Group 1 1.1 Group 2 2.7 Group 3 2.3 GDP Trillion 2005US$ World 38.6 Group 1 30.1 Group 2 3.7 Group 3 4.8 GHG emissions (excl. LULUCF CO2) GtCO2e World 30.1 Group 1 15.9 Group 2 8.5 Group 3 5.7
2100
9.0 9.1 1.2 1.1 3.3 3.0 4.5 5.0 156.3 396.6 75.7 125.8 48.2 137.9 32.5 132.9 57.2 74.6 19.4 19.3 21.3 23.9 16.5 31.4
direct additional costs due to climate policy, but do not capture the macro-economic implications of these costs. We also do not account for (avoided) damages and adaptation costs of climate change. 3. Baseline 3.1. General assumptions The B2 baseline scenario used here is based on the original set of SRES scenarios (Nakicenovic et al., 2000) as described in van Vuuren et al. (2007). The SRES B2 scenario focuses on exploring possible developments under medium assumptions for the most important drivers (population, economy, technology development and lifestyle). For population, the long-term UN medium population projection is used. In 2000, about 20% of the world population lives in the group 1 region, 45% in the group 2 region and 35% in the group 3 region. In 2100, the share of the group 3 region has become 55%, while the share of the group 1 and group 2 regions has declined to about 10 and 35%, respectively. In the period 2000–2030, the economic growth and energy trends of the IMAGE B2 scenario are based on the reference scenario of the World Energy Outlook 2004. After 2030, economic growth converges to the IPCC B2 trajectory. While in 2000, group 1 still represents three-quarters of the world GDP (Market Exchange Rates), by 2100, the three regions each represent about a third of world GDP (Table 2).
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3.2. Energy and land-use change in the baseline In the baseline, worldwide primary energy use increases by 70% between 2000 and 2030 and by another 70% between 2030 and 2100. Most of this growth occurs in the group 2 and group 3 regions (about 80%). The global energy system continues to be dominated by fossil fuels. While early on, natural gas and oil continue to have a high share, by the end of the century both fuels lose market share to coal (natural gas in the power sector), biofuels and hydrogen mostly produced from coal. As a result, energy-sector CO2 emissions continue to rise for most of the century, by 2100 reaching some 75 GtCO2. By 2100, the shift to coal use (for both electricity and hydrogen production) contributes to a further increase in emissions, despite a stabilising population and a slowing-down of growth in energy use. The scenario is rather optimistic about agricultural technology (“adaptive mosaic” scenario, (Alcamo et al., 2006)), and as a result the agricultural area stabilises after 2030. The total anthropogenic landuse related CO2 emissions (5.5 GtCO2 in 2000) stay above 3.5 GtCO2 throughout the century. However, as uptake by regrowing vegetation is increasing, the net land-use emissions decrease over time, to nearly zero emissions after 2050 (Fig. 2). Agriculture related emissions for the non-CO2 GHGs grow over time—but at a much slower rate than CO2 emissions from energy. Around 2050, the increase is in the order of 40% for CH4 (reaching a level of about 7 GtCO2-e) and 15% for N2O (reaching a level of 2.5 GtCO2-e) compared to 2000 levels. 3.3. GHG concentration and climate in the baseline Total GHG emissions increase significantly in the B2 scenario, i.e. from about 41 GtCO2e/yr in 2000 to 81 GtCO2e/yr in 2100. This characterizes our baseline as a medium emission baseline compared to literature. Radiative forcing, using Kyoto GHGs only, reaches 7.0 W/ m2 in 2100. The global mean temperature rises nearly 4 °C above preindustrial levels in 2100, assuming a climate sensitivity of 3.0 °C. 4. Analysis of mitigation scenarios This section discusses the full and delayed participation mitigation scenarios. The results focus on the implications for emissions, radiative forcing, abatement costs and the energy system.
Fig. 2. Emissions (sum of CO2, CH4, N2O, HFC, PFCs and SF6 from energy, industry and land-use) for the three regions and the global land-use, land-use change and forestry (LULUCF) CO2 emissions. For comparison the emissions pathway for the 2.6 W/m2 overshoot scenario is also shown here.
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Fig. 3. GHG emissions (upper) and radiative forcing (only Kyoto gases) (lower) in the scenarios for 4.5 W/m2(left), 3.7 W/m2 (center), and 2.6 and 2.9 W/m2 (right).
4.1. Full participation 4.1.1. Emission pathways and concentration profiles Fig. 3 shows the outcomes for emissions and radiative forcing based on the cost-optimal pathways.2 There are considerable differences between the emission pathways of the different full participation scenarios mostly resulting from the differences in target level. For the scenario that aims at stabilisation at 4.5 W/m2, emissions reach a level of about 27.5 GtCO2e/yr by 2100, i.e. about a third of baseline emissions. For the scenarios aimed at 3.7 W/m2, emissions need to be reduced further, to roughly a quarter of global emissions in 2100 (about 18 GtCO2e/yr). Finally, there is a group of scenarios aimed
2 There is a wide set of pathways differing in the timing of reductions that can lead to the same forcing target, as analysed by den Elzen et al. (2007).
at reaching a 2.9 and 2.6 W/m2 radiative forcing. These scenarios have emissions of 7–15 GtCO2e/yr by 2100. The remaining GHG emissions include little (in the case of 2.9 W/m2) to no (in the case of 2.6) CO2 emissions. A second factor that influences emission trajectories is the role of overshoot vs. stabilisation. This can be seen clearly for the 3.7 W/m2 scenarios. The overshoot 3.7 W/m2 scenario reduces emissions less in the short-term and compensates this by stronger reductions in the second half of the century. In 2050, this implies more than 40% reduction of global emissions for the stabilisation case, and only 30% for the overshoot case. The lowest targets (2.9 and 2.6 W/m2) are only feasible for the overshoot cases. Clearly, the timing of peaking in global emissions is also a function of the stabilisation level and the allowance of overshoot. For the 4.5 W/m2 scenario global emissions peak by 2050, whereas for 2.6 and 2.9 W/m2 this peaking is even before 2020. Allowing an overshoot for 3.7 W/m2 clearly delays the peaking till 2040.
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For the lowest category, the effect of including BECS as a mitigation technology is significant. The introduction of this technology provides considerable additional mitigation potential, which is attractive to deploy mainly at the end of the simulation period. Introduction of BECS to the mitigation portfolio leads to a delay in emission reduction for the 2.9 W/m2 overshoot scenario. The technology also makes a 2.6 W/m2 target a feasible scenario. Because of the considerable lifetime of different gases, the scenarios show somewhat less divergence for radiative forcing than for emissions. For the 3.7 W/m2 scenario, the stabilisation case stays below the target level, but the overshoot scenario reaches a maximum of 4 W/m2 before returning to the target level. A similar behaviour is noted for the 2.6 and 2.9 W/m2 overshoot case (here no stabilisation scenario exists). The emission pathway for 2.6 W/m2 overshoot reaches a level of 3.2 W/m2. For the 2.9 W/m2 overshoot pathway, the overshoot depends on the availability of BECS (3.2 versus 3.5 W/m2). 4.1.2. Energy use Fig. 4 (upper row) shows the impacts of climate policy on the world energy use as a function of the different targets. The increasingly tight concentration targets lead to a decrease in fossil fuel use without
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carbon-capture and storage (CCS), and an increase in efficiency, renewable energy use, nuclear power and fossil fuel consumption with CCS. Large-scale use of the latter type of technology in fact means that even by 2100 coal use under the mitigation cases is larger than today (although less than in the baseline). The same holds for natural gas. In contrast, oil use is substantially reduced, partly as a result of depletion. In the 2.6 W/m2 case, early mitigation action leads to a stronger competitive position of oil and therefore a longer time period in which oil remains to be used. The implementation of 2.9 W/m2 target was investigated including and excluding the BECS technology option (Fig. 4, lower row). This has a significant effect on timing of emission reductions (see Fig. 3), but also the energy system response. As can be expected the BECS introduction, implies a strong incentive to use bio-energy for this purpose—increasing total bio-energy consumption. At the same time, the contribution of other mitigation options decreases (e.g. the shortterm reliance on energy efficiency improvement). 4.1.3. Abatement costs Fig. 5 (upper) shows the abatement costs over time. The delay scenarios lead to higher costs, in particular on the medium term. The
Fig. 4. Total primary energy supply in the three scenarios for meeting radiative forcing targets at 4.5 W/m2(left), 3.7 W/m2 (middle) and 2.6 W/m2 (right) without overshoot (upper), or at 2.9 W/m2 target (lower) allowing an overshoot excluding and including BECS technology option.
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Fig. 5. The abatement costs in time (upper) and cumulative discounted abatement costs (lower) in the scenarios for CO2-equivalent concentration at 4.5 W/m2 (left), 3.7 W/m2 (middle) and 2.6 and 2.9 W/m2 (right).
3.7 W/m2 scenario shows higher mitigation costs for the whole century. This is related to the fact that this is a case without overshoot. As a result, there is little room in postponing emissions (also in relation to our assumed maximum reduction rate). Reducing participation implies that emission reductions need to take place in a smaller number of countries and thus result in higher marginal costs. The limited postponement does not compensate this effect. In scenarios were overshoot is allowed, there is more flexibility (and as a result costs stay lower). Fig. 5 (lower) shows the cumulative discounted abatement costs over time. As costs metric to compare the scenarios, we only use the 2100 value of this indicator. The figure shows also the time dependence to better understand the results. As for emissions, the costs of the policies depend first of all on the overall target, going from 4.5 to 2.6 W/m2. The cumulative discounted abatement costs in 2100 increase from 1 × 1012 US$ (4.5 W/m2) to around 4 × 1012 (3.7 W/m2), nearly 13 × 1012 (2.9 W/m2) and 13 × 1012
(2.6 W/m2 w/ BECS) in 2100. But also other factors are found to be relevant for costs. In case of the 3.7 W/m2 scenario, the overshoot scenario saves nearly 30% of overall costs. This is caused mainly by discounting, as this implies that long-term costs weigh less compared to costs made earlier in time in the stabilisation scenario. Postponement of action also allows to profit more from autonomous technology change (but at the same time forfeits some of the induced learning). Also the availability of BECS has significant effects. The technology not only provides more mitigation potential but also allows to postpone action providing benefits both from technology development and discounting effects. The availability of BECS halves the cumulative discounted abatement costs for the 2.9 W/m2 target.3
3 The similarity of expenses needed to attain a 2.6 and 2.9 without BECS W/m2 overshoot target is coincidental.
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4.2. Delayed participation 4.2.1. Emission pathways and concentration profiles The effect of delayed participation on the mitigation scenarios depends on the stringency of the forcing targets. • As a result of the considerable delay in participation of groups 2 and 3 that is assumed (30–50 years), the most stringent radiative forcing targets (2.6 and 2.9 W/m2) become unattainable in our framework. One may argue that the stabilisation cases become “physically unattainable”, as they require significant negative emissions for the group 1 region in the short-term. The stringent overshoot scenarios are constrained by our maximum marginal costs level of 273 US$/ tCO2. The introduction of overshoot scenarios and the addition of BECS to the mitigation portfolio are insufficient to reach the targets under the stringent delay conditions. • In the 4.5 W/m2 scenario the effect of delayed participation is more limited (Fig. 3, top-left), given there are little reductions during periods of limited participation. • For the intermediate radiative target (3.7 W/m2), a delayed participation scenario leads to moderate postponement of abatement of global emission reductions for both the overshoot and stabilisation case compared to the full participation case (Fig. 3, top-middle) (in other words, the reduced-participation partly leads to more reduction in participating regions, and partly to postponement). Apart from this delay in global emission reductions for the 3.7 W/m2 target, there are in particular large differences in the timing and amount of abatements in the three regions. Below we will discus these regional reduction differences in more detail for the overshoot case, and only briefly for the stabilisation case. The delay in participation of group 2 and 3 regions implies that the reduction effort in group 1 region is increased compared to the full participation case (Fig. 6, left). In 2050, this implies about a 40% emission reduction compared to baseline instead of a 30% reduction. For the group 2 region, the delay in action until 2030 is compensated
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by steep reductions after 2030. The total emissions across the century are in fact lower compared to the full participation scenario. Group 3 delays (by design) its emission reductions until 2050. After 2050 their emissions remain above the levels under full participation—as a result of the graduation rule, the inertia in emission reduction and reduced technology learning. Reductions in groups 1 and 2 thus compensate the higher emissions of group 3, leading to higher reductions in both regions. The changes in emission reduction rates are also reflected in the carbon price. As a result the carbon prices in the group 1 and 2 regions exceed the global permit price under full participation assumptions soon after 2010 and 2030, resp., and remain well above these levels (Fig. 7, left). Because of little demand in the period 2030–2040 the carbon price in the group 2 region grows to the price in the group 1 region within the 20 year transition period. Even the carbon price in group 3 exceeds the global permit price level by 2060 (as a result of the inertia and delayed learning). Together this leads to higher abatement costs for the delayed participation case globally (Fig. 5, middle). For a stabilisation 3.7 W/m2 scenario the carbon price developments in the three regions are even more extreme (Fig. 7, right). The stabilisation scenario requires early action: as overshoot is not allowed, the flexibility in the emission reductions is limited. This leads to high prices in the group 1 region until 2030 in order to reduce emissions fast enough. After 2030, the group 2 region gradually enters the carbon trading market, and this initially lowers the price, but by 2050 it reaches maximum levels again. These high prices are needed to achieve sufficient action in both group 1 and 2 regions. After 2050, the price decreases to lower levels due to the participation of group 3. Under the overshoot 3.7 W/m2 scenario the reduction action in the group 1 and 2 regions are postponed after 2050 to avoid these high price peaks before 2050. It also leads to a consistently increasing carbon price in the overshoot scenario, which differs from the double peaking price pathway under the 3.7 /m2 stabilisation scenario.
Fig. 6. Emissions in the three region groups under the baseline scenario and the full and delayed participation mitigation scenarios for meeting the 3.7 W/m2 overshoot target.
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Fig. 7. Global and regional carbon price under the full and delayed participation mitigation scenarios for meeting the 3.7 W/m2 overshoot (left) and 3.7 W/m2 stabilisation (right).
4.2.2. Energy use There are little changes in the energy system from a global perspective. Global total primary energy use remains almost unchanged compared to the full participation case. Regions that participate in reductions generally show an increase in biofuel use with a marginally reduced preference for coal. 4.2.3. Abatement costs The delayed participation highly influences the total abatement costs, and the resulting total cumulative discounted abatement costs, in particular for the 3.7 W/m2 scenarios (Fig. 5, middle). In case of the 3.7 W/m2 overshoot scenario the total cumulative discounted costs by 2100 increase by about 25% compared to the costs under the full participation scenario. The costs increase is relatively modest as a result of the flexibility in emission reduction: the delayed participation also leads to a delay in emission reduction. However, for the stabilisation 3.7 W/m2 scenario costs increase significantly by some 90%. Avoiding an overshoot in the radiative forcing requires early action and as there is little flexibility in the
timing of reduction action, this leads to a steeper increase in the regional permit prices, as was explained before. For the more stringent radiative forcing targets, costs increases cannot be assessed—as the mitigation target becomes infeasible if run under the delayed response assumption in this study. For the 4.5 W/m2 scenarios, the differences are relatively small (less than 5%). Again, this is a consequence of the fact that emission reductions under this scenario are clearly delayed anyway. 5. Discussion The main findings of this study with respect to participation are that: 1) delayed participation of developing countries leads to significant costs increases and 2) delayed participation of developing countries makes it impossible to achieve targets at or below 2.9 W/m2 in the current modelling framework. Below, we discuss the implications of the experimental set-up for these findings. In that context, it should be noted that most scenario runs in this study have been prescribed by the EMF-22 study.
Fig. 8. Effect of choice of the definition of radiative forcing (only Kyoto gases vs. all forcings).
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Fig. 9. Resulting temperature increase above pre-industrial levels, under different scenarios.
5.1. Formulation of the overall target In the EMF-22 study and thus in this article, the radiative forcing targets include all Kyoto gases, but not the Montreal gases or other substances such as aerosols. In many other studies (e.g. the Representative Concentration Pathways of IPCC) but also our earlier work (den Elzen et al., 2007; den Elzen and van Vuuren, 2007; van Vuuren et al., 2007) the definition for radiative forcing includes all GHGs, including the CFCs, HCFCs, tropospheric ozone and aerosols. As climate change depends on the total forcing (and not on the Kyotogas only forcing), the focus on the Kyoto-gas only forcing is arguably artificial. The effect of both definitions is illustrated in Fig. 8 for the full participation 3.7 W/m2 overshoot and 2.6 W/m2 BECS overshoot scenario. By excluding the non-Kyoto forcing agents, current radiative forcing is higher (mainly by not including the cooling effect of sulphur aerosols). This “Kyoto gas” radiative forcing remains above the total radiative forcing for the whole period until 2070– 2080. By 2100, the difference between the two definitions falls away due to reduced aerosol forcing. Emissions of these substances fall significantly due to air pollution control policies included in baseline assumptions, but also indirectly as a synergetic effect of climate policies. 5.2. Overshoot versus stabilization The scenarios as defined in this EMF study were defined using radiative forcing targets, however it is the resulting temperature change that is most relevant for climate impacts. This may have important implications. Fig. 9 shows the resulting transient temperature increase for the pathways of overshoot 2.6 and 2.9 W/m2 and compares these with the equilibrium temperature increase for a stabilisation profile at 2.6 W/m2. Given the inertia in the climate system, a stabilisation 2.6 W/ m2 profile leads to ongoing warming beyond 2100 until temperature reaches equilibrium. For the overshoot scenarios, the post-2100 warming depends on assumptions on post-2100 forcing. Given the decreasing forcing and temperature levels in 2100, one logical extension would be to assume that in these scenarios forcings continue to decrease, effectively preventing some of the temperature increase (“committed warming”) that would still occur after this concentration peak. In this way, in terms of temperature increase effects, overshoot profiles can be more effective than stabilisation profiles (for details see den Elzen and van Vuuren (2007)). This implies that while the EMF study focused on the 2.6 W/m2 scenario—from an environmental perspective the study could just as well have focused on an overshoot 2.9 W/m2 scenario. And while a
stabilisation target is considerably more stringent (and thus more expensive), the resulting gains in reducing temperature increase might be relatively small. 5.3. Participation rules The participation rules as formulated for this study should be considered as rather pessimistic both in timing as in definition of groups. First of all, developing country participation is considerably delayed (until 2030 for group 2; until 2050 for other developing countries). While full participation by 2012 is arguably not a realistic result of current international negotiations, more intermediate scenarios might also be achievable. Secondly, several regions now included in group 3 could be eligible for participation at an earlier time. There are several advanced developing countries or regions identifiable in this group that have per capita income levels above the average per capita income level in group 2, for example Mexico and the rest of Central America, Argentina, Middle East and South-Korea. Thirdly, the current model set-up does not explore new types of contributions from the non-Annex I countries in-between a voluntary non-binding approach under the Kyoto Protocol and the binding absolute reduction targets of current Annex I countries. These intermediate contributions, like sectoral targets, sectoral CDM, no lose emission targets or sustainable development policies and measures, allow for using the mitigation potential in developing countries—and still allow for low costs in developing countries. Finally, not all of the presently known mitigation options, like reducing emissions from deforestation are included in our present modelling framework. For others like forest management we use rather conservative estimates. This could have consequences for both mitigation potential and policy costs. Under such conditions, several low stabilisation targets may become feasible again even under delayed participation. 5.4. Burden-sharing This study has implemented regional carbon prices to induce emission reductions and assess the costs of mitigation policy. It does not necessarily mean that investments for regional emissions reductions are financed by the same region. By setting regional targets under a post-2012 burden-sharing regime and allowing a capand-trade mechanism financing does not necessarily originate from the same region as emission reductions are taking place. In such a case, the costs of increased mitigation action in group 2 under delayed assumptions could be distributed among participating regions.
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Conclusions on the attractiveness of scenarios discussed here for certain regions must be drawn prudently. These comments are not intended to undermine the results/setup of the present study. On the contrary, it is important to define and explore the limits of ‘the playing field’ in order to judge ambitious policy proposals. And the presented changes in the energy system are challenging indeed, both from a point of engineering and policy design. Given the arguments as described in this section this study does not imply that the more stringent targets are infeasible. Future work accounting for more optimistic assumptions like an earlier and broader participation is needed to explore the feasibility of meeting the most stringent stabilisation targets (2.6 and 2.9 W/m2). 6. Conclusions The main findings of the study are: Early participation of key developing countries is critically important for the feasibility of achieving low greenhouse gas concentration targets. The IMAGE framework is able to identify mitigation strategies for radiative forcing targets as low as 2.6 W/m2, but such targets become infeasible (i.e. no solutions with prices below 273 US$/tCO2) if there is a long delay in developing country participation. If participation of developing countries is seriously delayed as defined by the EMF-22 specifications the model was still able to achieve a 3.7 W/m2 target, but not the 2.6 or 2.9 W/m2 targets. Delayed participation leads to higher costs (25–90% in the 3.7 W/m2 cases) and delay in mitigation action. As international climate policy currently only requires emission reductions in a limited number of countries, increasing participation is a key priority if one aims to achieve low concentration targets. There are several key factors that increase the ability of achieving low greenhouse gas concentration targets, such as allowing overshoot and including technologies like bio-energy and carbon-capture-andstorage. The current analysis shows several of the EMF-22 scenarios to be infeasible under the current IMAGE framework set-up. However, the infeasibility does depend on various factors. For instance, the definition of radiative forcing targets on the basis of Kyoto gases only means that in the short-term radiative forcing levels are higher— making stabilisation scenarios more difficult to achieve. The results of the EMF-22 exercise can therefore not be directly compared to some other studies (including the new IPCC scenarios). Similarly, including overshoot profiles allows for lower targets to be feasible. Finally, the inclusion of bio-energy and carbon-capture-and-storage significantly influences the feasibility (and costs) of different targets. Both BECS and allowance for overshoot lead to a slightly delayed emission profile. For climate policy, this implies that making sure that key technologies are available is important (in particular CCS and BECS)—and that policies should consider overshoot strategies both from a perspective of reduced costs and efficiency in limiting temperature change. Further exploration of scenarios with delayed participation is needed. In this study, we run two main participation cases (full participation vs. seriously delayed participation). The experimental design, particularly the delayed participation assumptions, implies that several targets become infeasible to achieve. However, the assumed delay in participation is rather extreme. In order to support international policy-making it
is worthwhile to explore scenarios with less delay in participation for key regions (together with further regional differentiation). References Alcamo, J.A., Van Vuuren, D.P., Cramer, W., 2006. Changes in provisioning and regulating ecosystem goods and services and their drivers across the scenarios. In: Carpenter, S., Pingali, P. (Eds.), Millennium Ecosystem Assessment—Scenarios Assessment. Island Press, Washington DC. Bouwman, A.F., Kram, T., Klein_Goldewijk, K., 2006. Integrated modelling of global environmental change. An overview of IMAGE 2.4. Netherlands Environmental Assessment Agency. available at: www.mnp.nl\en, Bilthoven, The Netherlands. Clarke, L., Edmonds, J., Krey, V., Richels, R., Rose, S., Tavoni, M., 2009. International climate policy architectures: Overview of the EMF 22 International Scenarios. Energy Economics 31, S64–S81 (this issue). den Elzen, M.G.J., Meinshausen, M., 2006. Meeting the EU 2 °C climate target: global and regional emission implications. Climate Policy 6 (5), 545–564. den Elzen, M.G.J., Meinshausen, M., van Vuuren, D.P., 2007. Multi-gas emission envelopes to meet greenhouse gas concentration targets: costs versus certainty of limiting temperature increase. Global Environmental Change 17 (2), 260–280. den Elzen, M.G.J., van Vuuren, D.P., 2007. Peaking profiles for achieving long-term temperature targets with more likelihood at lower costs. Proceedings of the National Academy of Sciences USA (PNAS) 104 (46), 17931–17936. Edmonds, J., Clarke, L., Lurz, J., Wise, M., 2008. Stabilizing CO2 concentrations with incomplete international cooperation. Climate Policy 8, 355–376. Fisher, B.S., Nakicenovic, N., Alfsen, K., et al., 2007. Issues related to mitigation in the long term context. In: Metz, B., Davidson, O.R., Bosch, P.R., Dave, R., Meyer, L.A. (Eds.), Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK. Hof, A., den Elzen, M.G.J., van Vuuren, D.P., 2009. Environmental effectiveness and economic consequences of fragmented vs. universal regimes: what can we learn from model studies? International Environmental Agreements: Politics, Law and Economics 9 (1), 39–62. Keppo, I., Rao, S., 2007. International climate regimes: effects of delayed participation. Technological Forecasting and Social Change 74 (7), 962–979. Knopf, B., Edenhofer, O., Barker, T., et al., 2009. The economics of low stabilisation: implications for technological change and policy. In: Hulme, M., Neufeld, H. (Eds.), Making climate change work for us. Lucas, P., van Vuuren, D.P., Olivier, J.A., den Elzen, M.G.J., 2007. Long-term reduction potential of non-CO2 greenhouse gases. Environmental Science & Policy 10 (2), 85–103. Nakicenovic, N., Alcamo, J., Davis, G., et al., 2000. IPCC Special Report on Emissions Scenarios. Cambridge University Press, Cambridge. Ramaswamy, V., Boucher, O., Haigh, J., et al., 2001. Radiative forcing of climate change. In: Houghton, J.T., et al. (Ed.), IPCC Third Assessment—Climate Change 2001, The Scientific Basis. Cambridge University Press, Cambridge, UK. Richels, R.G., Rutherford, T.F., Blanford, G.J., Clarke, L., 2007. Managing the transition to climate stabilization. Climate Policy 7 (5), 409–428. Russ, P., Ciscar, J.C., Szabó, L., 2005. Analysis of Post-2012, Climate Policy Scenarios with Limited Participation. EUR 21758 EN, http://www.jrc.es, European Commission, Joint Research Centre (DG JRC), Institute for Prospective Technological Studies. Russ, P., Ciscar, J.C., Saveyn, B., et al., 2009. Economic assessment of post-2012 global climate policies: analysis of greenhouse gas emission reduction scenarios with the POLES and GEM-E3 models. Technical Report EUR 23768 EN—2009, Joint Research Centre. download at: http://ipts.jrc.ec.europa.eu. Strengers, B.J., van Minnen, J., Eickhout, B., 2008. 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Energy Economics j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / e n e c o
Meeting radiative forcing targets under delayed participation Jasper van Vliet ⁎, Michel G.J. den Elzen, Detlef P. van Vuuren Netherlands Environmental Assessment Agency (PBL), P.O. Box 303, 3720 AH Bilthoven, The Netherlands
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Article history: Received 7 April 2009 Received in revised form 29 May 2009 Accepted 11 June 2009 Available online 21 June 2009 Keywords: Climate Climate policy Participation regimes Integrated assessment model Overshoot scenarios
a b s t r a c t In this article we explore several scenarios that aim at meeting radiative forcing targets at 4.5, 3.7, 2.9 and 2.6 W/m2 by 2100. These scenarios are run under the assumption of participation of all countries by 2012 in climate policy and under the assumption of a significant delay in the participation of Russia and non-Annex I countries (up to 2030 and 2050). The study finds the lowest radiative forcing categories to be feasible under full participation, certainly if overshoot of targets is allowed and when bio-energy and carbon-capture-andstorage is added to the mitigation portfolio. In cases with severe delay in participation, the lowest targets become infeasible. For less strict targets (e.g. 3.7 W/m2), delayed participation leads to considerable costs increases (up to 90% for the stabilisation case). As a next step, scenarios with less delay in participation need to be explored. © 2009 Elsevier B.V. All rights reserved.
1. Introduction Limiting global mean temperature increase to only 2–3 °C with reasonable probability requires that GHG concentrations are kept below 550 ppm CO2-eq. So-far, the number of scenario studies that aim at low GHG concentration targets is still relatively scarce (for an overview see Fisher et al., 2007). Almost all of these studies analyse the implication of low concentration targets under the idealized assumption that all regions and sectors participate in full emissions trading without any restrictions (first-best worlds). This implies that there is full flexibility with respect to the question where and when emission reductions take place allowing for least costs solutions (so-called full when and where flexibility). Only a limited number of studies explored the possibility of achieving GHG concentration or radiative forcing targets in situations where not all regions contribute to mitigation (like Russ et al., 2005; Keppo and Rao, 2007; Richels et al., 2007; Edmonds et al., 2008; Russ et al., 2009). As a result, limited insight exists on the level and timing of global abatement costs for a more realistic scenario assuming limited participation (i.e. participation gradually develops in time including more countries and/or sectors). Similarly, limited insight exists on the attainability of low concentration targets under these imperfect conditions. In particular, the timing of participation of major emitting developing countries, like China and India, in a reduction regime is likely to play an important role. This paper forms part of the EMF-22 model comparison study of international transition scenarios that explores the impact of staged participation on the costs of stabilizing CO2-equivalent concentrations (Clarke et al., 2009-this issue). In the experiments, full participation ⁎ Corresponding author. Tel.: +31 30 274 3723. E-mail address: [email protected] (J. van Vliet). 0140-9883/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.eneco.2009.06.010
regimes are compared to regimes with delayed participation by Russia and the non-Annex I countries (a full definition of regions and timing of participation is given in Section 2.2). This paper describes the results of the experiments run with the IMAGE framework (i.e. IMAGE, TIMER and FAIR models) (Bouwman et al., 2006). The model ran for satisfying targets at 4.5, 3.7, 2.9 and 2.6 W/m2 by 2100 (including and excluding an overshoot) and sensitivity tests. In this paper, we first describe the model framework (Section 2), and the baseline assumptions (Section 3), and then focus on the mitigation scenarios (Section 4). We briefly discuss the impact of the assumptions made by EMF-22 on the results (Section 5) and finish with drawing general conclusions (Section 6). 2. Research design 2.1. Climate strategies and policy regimes There are many factors that determine the costs of future climate policy. As indicated in the Introduction, most long-term studies so-far looking at low stabilization targets have assumed full participation of all countries and sectors. These studies explored the costs of international climate policy as a function of factors such as 1) the overall objective of climate policy, 2) baseline developments, 3) the ability to allow for substitution across different gases (EMF-21), 4) technology development (EMF-19 and IMCP, i.e. Innovation Modelling Comparison Project), and 5) timing of reductions (and more specifically the inclusion of overshoot). A future climate regime, however, will also have to define elements like participation and the specific instruments that are used. To some degree, the influence of these factors has been studied in the context of medium term climate policy and for relatively high GHG concentration targets (EMF-14).
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No model comparison study has been performed, however, on the influence of participation rules on the attainability of low GHG concentration targets. The fact that the feasibility of climate targets and associated costs is determined by a range of factors (see above) implies that the influence of one factor alone (here participation of counties) cannot be studied in isolation. Below, we briefly discuss some factors that determine the costs of future climate policy. Regarding the objective of future climate policy, most studies on long-term climate policy have explored the costs of various stabilization goals (with a strong bias towards particular goals such as stabilization at 650 ppm CO2e). These studies show that (as expected) the costs strongly depend on the stringency of the target with costs exponentially rising for lower stabilization levels. In recent years, many more studies have explored the costs and feasibility of achieving stabilization targets that could lead to avoiding a 2 °C increase in global mean temperature compared to pre-industrial levels. These studies showed such scenarios to be feasible under certain conditions, with costs typically in the order of a few percent of GDP (in terms of GDP losses). These costs, however, are strongly influenced by other assumptions. Both van Vuuren et al. (2007) and Knopf et al. (2009) show that the availability of different technologies, including the option of Bio-Energy and carbon-Capture-and-Storage (BECS) could critically influence costs and even the feasibility of targets. den Elzen and van Vuuren (2007) show that costs also strongly depend on whether one allows a limited overshoot of concentration targets. They show that overshoot scenarios can achieve temperature targets at lower costs—and therefore recommend future studies to look into overshoot strategies rather than stabilization strategies. The issue of participation is also known to be a crucial element of future climate policy. Hof et al. (2009) have made an overview of studies that provided quantitative results for full participation versus partial participation regimes. In each case, partial participation regimes lead to considerably higher costs. The advantage of full participation regimes is that they allow for full flexibility in implementing the least expensive emission reductions throughout all countries, sources and sectors, lowering the costs for meeting the overall emission target. The disadvantage is that it is far from easy to achieve global agreement on such comprehensive regimes—and one may argue that in the short-term assuming full participation is not realistic. It should be noted, however, that in reality the difference is not clear cut. Even under a full participation regime, countries could have a limited contribution in emission reductions allowing them to become a net seller of emission credits. And under partial participation regimes, flexible instruments like the Clean Development Mechanism (CDM), may allow for some form of flexibility.
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2.2. Set up the analysis in this study On the basis of the discussion above (and as part of the model comparison study for EMF-22), this study looks into the influence of participation on the costs and feasibility of meeting radiative forcing targets at 4.5, 3.7, 2.9 and 2.6 W/m2 (or GHG concentrations at 650, 550, 480 and 450 ppm CO2-eq) by 2100. Radiative forcing targets refer to Kyoto gases only (CO2, CH4, N2O, HFCs, PFCs, and SF6) (as prescribed for model comparison). For our modelling framework (see also Section 2.3), the targets are calculated using the MAGICC 4.1 model, calibrated to forcing levels as reported in IPCC's Third Assessment Report (changes in radiative forcing levels from greenhouse gases since then are small) (Ramaswamy et al., 2001). A medium emission pathway is used as a baseline for this analysis. We specifically look into the question how the inclusion of overshoot (for 3.7, 2.9 and 2.6 W/m2) and the use of BECS (BECS is not part of the default set of mitigation options, only for 2.9 and 2.6 W/m2) influences overall costs. This leads to the following nine mitigation scenarios (Table 1), which are labelled as: 2.6 W/m2 BECS, 2.6 W/m2, 2.6 W/m2 BECS OS, 2.6 W/m2 OS, 2.9 W/m2 BECS OS, 2.9 W/m2 OS, 3.7 W/m2, 3.7 W/m2 OS and 4.5 W/m2 (note: OS stands for overshoot). The analysis assumes two main cases for each scenario with respect to participation: Full Participation and Delayed Participation (hereafter these scenarios are shortly labelled as Full and Delay, see Table 1). In the latter case, it is assumed that Annex I or developed regions (excluding Russia) (hereafter labelled as group 1 regions) begin or continue with emissions reductions in 2012; Brazil, Russia, China, and India (BRIC) regions (group 2 regions) join the global coalition in 2030 while for the remaining non-Annex I or developing regions (group 3 regions) it is assumed that they join the global coalition in 2050. For the late entrants in the coalition, it is also assumed that there is a period of 20 years before they are fully exposed to the global carbon price. In fully participating regions, carbon prices are equal. Non-participating regions have a zero carbon price. For regions in transition from no- to full-participation the carbon price grows from zero to the level of the participating regions during the transition period. A linearly growing proportion of the regions' mitigation potential is exposed to the global carbon price and the regional price is the price at which the exposed mitigation potential is fully implemented, until the global carbon price is reached. In the analysis, we found several mitigation scenarios not to be feasible in our model framework: the current framework is not able to find a solution if carbon taxes exceed 273$/tCO2 (expressed in 2005 U.S. $) (see Table 1). In a limited number of cases, the scenarios can even be regarded as physically infeasible, as they lead to extremely negative emissions for the coalition of participating regions). The 2.6 W/m2 target
Table 1 Overview of the scenarios. Scenarioa
Characteristicsb
Mitigation optionsc
Scenario 1 (full participation—Full)d
Scenario 2 (delayed participation—Delay)d
0. Baseline 1. Stabilisation 2.6 W/m2 (2.6 W/m2 BECS) 2. Stabilisation 2.6 W/m2 (2.9 W/m2 OS) 3. Overshoot 2.6 W/m2 (2.6 W/m2 BECS OS) 4. Overshoot 2.6 W/m2 (2.9 W/m2 OS) 5. Overshoot 2.9 W/m2 (2.9 W/m2 BECS OS) 6. Overshoot 2.9 W/m2 (2.9 W/m2 OS) 7. Stabilisation 3.7 W/m2 (3.7 W/m2) 8. Overshoot 3.7 W/m2 (3.7 W/m2 OS) 9. Stabilisation 4.5 W/m2 (4.5 W/m2)
No climate policy Not to exceed 2.6 W/m2 (450 ppm CO2-eq) Not to exceed 2.6 W/m2 (450 ppm CO2-eq) 2.6 W/m2 in 2100 (450 ppm CO2-eq) with overshoot allowed 2.6 W/m2 in 2100 (450 ppm CO2-eq) with overshoot allowed 2.9 W/m2 in 2100 (480 ppm CO2-eq) with overshoot allowed 2.9 W/m2 in 2100 (480 ppm CO2-eq) with overshoot allowed Not to exceed 3.7 W/m2 (550 ppm CO2-eq) 3.7 W/m2 in 2100 (550 ppm CO2-eq) with overshoot allowed Not to exceed 4.5 W/m2 (650 ppm CO2-eq)
Default + BECS Default Default + BECS Default Default + BECS Default Default Default Default
Infeasible Infeasible X Infeasible X X X X X
Infeasible⁎ Infeasible⁎ Infeasible⁎ Infeasible⁎ Infeasible Infeasible X X X
An additional indication (⁎) has been added for those scenarios, which are considered physically infeasible as they lead to extremely negative emissions for the coalition of participating regions. a Radiative forcing targets as calculated by MAGICC 4.1 based on forcing from Kyoto gases only. b “Not to exceed” targets imply standard stabilization scenarios without overshoot. c Default settings do not include BECS. d Scenarios become infeasible in our framework if required tax levels to meet the radiative forcing target exceed at any time 1000$/tC (= 273$/tCO2) (no solvable solution).
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Fig. 1. Linkage and information flows between the models IMAGE, TIMER and FAIR (note CP = Carbon plantations). Steps 1–2 are explained in the text. Source: adapted from van Vuuren et al. (2007).
was only found to be feasible with use of BECS and in overshoot scenarios. In the analysis of the results (Section 4) we concentrate mostly on the scenarios for which a solution was found. 2.3. Modeling framework IMAGE, TIMER and FAIR For the analysis of the mitigation scenarios, we use the Integrated Assessment modeling framework IMAGE 2.4 (Bouwman et al., 2006).1 The IMAGE model consists of a set of linked and integrated models that together describe important elements of the long-term dynamics of global environmental change, such as air pollution, climate change, and land-use change. The land modules of IMAGE describe the dynamics of agriculture and natural vegetation, including potentials for biofuels under resulting climate change, and the land-use related emissions of GHGs. The global energy model, TIMER, as part of the IMAGE model, describes the primary and secondary demand and production of energy and the related emissions of GHGs and regional air pollutants (van Vuuren et al., 2007). The FAIR–SiMCaP model is a combination of the abatement costs model of the FAIR model and the SiMCaP model (den Elzen and Meinshausen, 2006; den Elzen et al., 2007; den Elzen and van Vuuren, 2007). The FAIR cost model distributes the difference between baseline and global emission pathway following a least-cost approach using regional Marginal Abatement Costs (MAC) curves for the different emissions sources (den Elzen et al., 2007). More specifically, the MAC curves for energyand industry-related CO2 emissions were determined with the TIMER energy model (van Vuuren et al., 2007) by imposing a carbon tax and recording the induced reduction of CO2 emissions. This has been further improved compared to earlier work by now including four instead of two different tax profiles. We now capture the full range of possible tax paths that represent early action and highly delayed action. The MAC curves for carbon plantations were derived using the IMAGE model (Strengers et al., 2008). MAC curves from the EMF-21 project (Weyant et al., 2006) were used for non-CO2 GHG emissions. These curves have been made consistent with the baseline used here and made time-dependent to account for technology change and removal of implementation barriers (Lucas et al., 2007). It should be noted that while CO2 emission reductions from the energy system are
1 The model names are acronyms. IMAGE = Integrated Model to Assess the Global Environment; TIMER = The IMage Energy Regional model; FAIR = Framework to Assess International Regimes for the differentiation of commitments.
described accounting for dynamic processes such as induced learning and limited capital turn-over rates, reductions for non-CO2 gases are based on simple MAC curves (that change over time, but do not limit reduction potential based on a vintage structure). The SiMCaP pathfinder module makes use of an optimisation procedure to find least-cost, multi-gas emission pathways over the 2005–2100 time period that correspond to a predefined climate target. The recently added intertemporal optimisation was set to minimize the cumulative discounted abatement costs. The discount rate applied here is 5%. Furthermore a maximum reduction rate of 3% was assumed (for the BECS scenarios 4%), reflecting the technical (and political) inertia that limits emission reductions, avoiding premature replacement of existing fossil fuel-based capital stock. As reduction rates in existing scenarios hardly exceed 2.5% per year (Swart et al., 2002). Global climate and GHG concentration calculations make use of the simple ‘climate’ model, MAGICC 4.1 (Wigley and Raper, 2001, 2002; Wigley, 2003). The climate model of MAGICC is a simple upwelling-diffusion energy balance model. The carbon cycle model describes fluxes between six global reservoirs (oceans, atmosphere, and four terrestrial carbon stores). For radiative forcing levels, MAGICC 4.1 is calibrated on the information of the Third Assessment Report (Ramaswamy et al., 2001). The model framework calculates emissions of all greenhouse gases (GHGs), ozone precursors (volatile organic compounds, CO, and NOx), and sulfur aerosols (SO2) from energy and land-use related sources, atmospheric concentrations, radiative forcing, and resulting climate change. The analysis consists of the following steps (Fig. 1): 1. The baseline emission scenario is constructed using the models TIMER (energy) and IMAGE (land). These models also provide information on the potentials and abatement costs of reducing emissions from the energy and land-use systems. 2. The FAIR–SiMCaP model is used to develop global emission pathways that lead to a long-term target of the atmospheric GHG concentration. The FAIR model distributes the global emission reduction from baseline to meet the global emission pathway, assuming a costoptimal implementation of available reduction options over time, different regions, gases and sources, based on the information in step 1. 3. The scenarios are implemented in the TIMER model to identify changes in the energy system. Abatement costs of each scenario are calculated on the basis of the marginal permit prices and the actual reductions. They represent the
J. van Vliet et al. / Energy Economics 31 (2009) S152–S162 Table 2 Baseline scenario (Group 1: Annex I regions excl. Russia; Group 2: Brazil, Russia, China, and India (BRIC) regions; Group 3: remaining non-Annex I or developing regions). 2000 2050 Population
Billions
World 6.1 Group 1 1.1 Group 2 2.7 Group 3 2.3 GDP Trillion 2005US$ World 38.6 Group 1 30.1 Group 2 3.7 Group 3 4.8 GHG emissions (excl. LULUCF CO2) GtCO2e World 30.1 Group 1 15.9 Group 2 8.5 Group 3 5.7
2100
9.0 9.1 1.2 1.1 3.3 3.0 4.5 5.0 156.3 396.6 75.7 125.8 48.2 137.9 32.5 132.9 57.2 74.6 19.4 19.3 21.3 23.9 16.5 31.4
direct additional costs due to climate policy, but do not capture the macro-economic implications of these costs. We also do not account for (avoided) damages and adaptation costs of climate change. 3. Baseline 3.1. General assumptions The B2 baseline scenario used here is based on the original set of SRES scenarios (Nakicenovic et al., 2000) as described in van Vuuren et al. (2007). The SRES B2 scenario focuses on exploring possible developments under medium assumptions for the most important drivers (population, economy, technology development and lifestyle). For population, the long-term UN medium population projection is used. In 2000, about 20% of the world population lives in the group 1 region, 45% in the group 2 region and 35% in the group 3 region. In 2100, the share of the group 3 region has become 55%, while the share of the group 1 and group 2 regions has declined to about 10 and 35%, respectively. In the period 2000–2030, the economic growth and energy trends of the IMAGE B2 scenario are based on the reference scenario of the World Energy Outlook 2004. After 2030, economic growth converges to the IPCC B2 trajectory. While in 2000, group 1 still represents three-quarters of the world GDP (Market Exchange Rates), by 2100, the three regions each represent about a third of world GDP (Table 2).
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3.2. Energy and land-use change in the baseline In the baseline, worldwide primary energy use increases by 70% between 2000 and 2030 and by another 70% between 2030 and 2100. Most of this growth occurs in the group 2 and group 3 regions (about 80%). The global energy system continues to be dominated by fossil fuels. While early on, natural gas and oil continue to have a high share, by the end of the century both fuels lose market share to coal (natural gas in the power sector), biofuels and hydrogen mostly produced from coal. As a result, energy-sector CO2 emissions continue to rise for most of the century, by 2100 reaching some 75 GtCO2. By 2100, the shift to coal use (for both electricity and hydrogen production) contributes to a further increase in emissions, despite a stabilising population and a slowing-down of growth in energy use. The scenario is rather optimistic about agricultural technology (“adaptive mosaic” scenario, (Alcamo et al., 2006)), and as a result the agricultural area stabilises after 2030. The total anthropogenic landuse related CO2 emissions (5.5 GtCO2 in 2000) stay above 3.5 GtCO2 throughout the century. However, as uptake by regrowing vegetation is increasing, the net land-use emissions decrease over time, to nearly zero emissions after 2050 (Fig. 2). Agriculture related emissions for the non-CO2 GHGs grow over time—but at a much slower rate than CO2 emissions from energy. Around 2050, the increase is in the order of 40% for CH4 (reaching a level of about 7 GtCO2-e) and 15% for N2O (reaching a level of 2.5 GtCO2-e) compared to 2000 levels. 3.3. GHG concentration and climate in the baseline Total GHG emissions increase significantly in the B2 scenario, i.e. from about 41 GtCO2e/yr in 2000 to 81 GtCO2e/yr in 2100. This characterizes our baseline as a medium emission baseline compared to literature. Radiative forcing, using Kyoto GHGs only, reaches 7.0 W/ m2 in 2100. The global mean temperature rises nearly 4 °C above preindustrial levels in 2100, assuming a climate sensitivity of 3.0 °C. 4. Analysis of mitigation scenarios This section discusses the full and delayed participation mitigation scenarios. The results focus on the implications for emissions, radiative forcing, abatement costs and the energy system.
Fig. 2. Emissions (sum of CO2, CH4, N2O, HFC, PFCs and SF6 from energy, industry and land-use) for the three regions and the global land-use, land-use change and forestry (LULUCF) CO2 emissions. For comparison the emissions pathway for the 2.6 W/m2 overshoot scenario is also shown here.
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Fig. 3. GHG emissions (upper) and radiative forcing (only Kyoto gases) (lower) in the scenarios for 4.5 W/m2(left), 3.7 W/m2 (center), and 2.6 and 2.9 W/m2 (right).
4.1. Full participation 4.1.1. Emission pathways and concentration profiles Fig. 3 shows the outcomes for emissions and radiative forcing based on the cost-optimal pathways.2 There are considerable differences between the emission pathways of the different full participation scenarios mostly resulting from the differences in target level. For the scenario that aims at stabilisation at 4.5 W/m2, emissions reach a level of about 27.5 GtCO2e/yr by 2100, i.e. about a third of baseline emissions. For the scenarios aimed at 3.7 W/m2, emissions need to be reduced further, to roughly a quarter of global emissions in 2100 (about 18 GtCO2e/yr). Finally, there is a group of scenarios aimed
2 There is a wide set of pathways differing in the timing of reductions that can lead to the same forcing target, as analysed by den Elzen et al. (2007).
at reaching a 2.9 and 2.6 W/m2 radiative forcing. These scenarios have emissions of 7–15 GtCO2e/yr by 2100. The remaining GHG emissions include little (in the case of 2.9 W/m2) to no (in the case of 2.6) CO2 emissions. A second factor that influences emission trajectories is the role of overshoot vs. stabilisation. This can be seen clearly for the 3.7 W/m2 scenarios. The overshoot 3.7 W/m2 scenario reduces emissions less in the short-term and compensates this by stronger reductions in the second half of the century. In 2050, this implies more than 40% reduction of global emissions for the stabilisation case, and only 30% for the overshoot case. The lowest targets (2.9 and 2.6 W/m2) are only feasible for the overshoot cases. Clearly, the timing of peaking in global emissions is also a function of the stabilisation level and the allowance of overshoot. For the 4.5 W/m2 scenario global emissions peak by 2050, whereas for 2.6 and 2.9 W/m2 this peaking is even before 2020. Allowing an overshoot for 3.7 W/m2 clearly delays the peaking till 2040.
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For the lowest category, the effect of including BECS as a mitigation technology is significant. The introduction of this technology provides considerable additional mitigation potential, which is attractive to deploy mainly at the end of the simulation period. Introduction of BECS to the mitigation portfolio leads to a delay in emission reduction for the 2.9 W/m2 overshoot scenario. The technology also makes a 2.6 W/m2 target a feasible scenario. Because of the considerable lifetime of different gases, the scenarios show somewhat less divergence for radiative forcing than for emissions. For the 3.7 W/m2 scenario, the stabilisation case stays below the target level, but the overshoot scenario reaches a maximum of 4 W/m2 before returning to the target level. A similar behaviour is noted for the 2.6 and 2.9 W/m2 overshoot case (here no stabilisation scenario exists). The emission pathway for 2.6 W/m2 overshoot reaches a level of 3.2 W/m2. For the 2.9 W/m2 overshoot pathway, the overshoot depends on the availability of BECS (3.2 versus 3.5 W/m2). 4.1.2. Energy use Fig. 4 (upper row) shows the impacts of climate policy on the world energy use as a function of the different targets. The increasingly tight concentration targets lead to a decrease in fossil fuel use without
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carbon-capture and storage (CCS), and an increase in efficiency, renewable energy use, nuclear power and fossil fuel consumption with CCS. Large-scale use of the latter type of technology in fact means that even by 2100 coal use under the mitigation cases is larger than today (although less than in the baseline). The same holds for natural gas. In contrast, oil use is substantially reduced, partly as a result of depletion. In the 2.6 W/m2 case, early mitigation action leads to a stronger competitive position of oil and therefore a longer time period in which oil remains to be used. The implementation of 2.9 W/m2 target was investigated including and excluding the BECS technology option (Fig. 4, lower row). This has a significant effect on timing of emission reductions (see Fig. 3), but also the energy system response. As can be expected the BECS introduction, implies a strong incentive to use bio-energy for this purpose—increasing total bio-energy consumption. At the same time, the contribution of other mitigation options decreases (e.g. the shortterm reliance on energy efficiency improvement). 4.1.3. Abatement costs Fig. 5 (upper) shows the abatement costs over time. The delay scenarios lead to higher costs, in particular on the medium term. The
Fig. 4. Total primary energy supply in the three scenarios for meeting radiative forcing targets at 4.5 W/m2(left), 3.7 W/m2 (middle) and 2.6 W/m2 (right) without overshoot (upper), or at 2.9 W/m2 target (lower) allowing an overshoot excluding and including BECS technology option.
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Fig. 5. The abatement costs in time (upper) and cumulative discounted abatement costs (lower) in the scenarios for CO2-equivalent concentration at 4.5 W/m2 (left), 3.7 W/m2 (middle) and 2.6 and 2.9 W/m2 (right).
3.7 W/m2 scenario shows higher mitigation costs for the whole century. This is related to the fact that this is a case without overshoot. As a result, there is little room in postponing emissions (also in relation to our assumed maximum reduction rate). Reducing participation implies that emission reductions need to take place in a smaller number of countries and thus result in higher marginal costs. The limited postponement does not compensate this effect. In scenarios were overshoot is allowed, there is more flexibility (and as a result costs stay lower). Fig. 5 (lower) shows the cumulative discounted abatement costs over time. As costs metric to compare the scenarios, we only use the 2100 value of this indicator. The figure shows also the time dependence to better understand the results. As for emissions, the costs of the policies depend first of all on the overall target, going from 4.5 to 2.6 W/m2. The cumulative discounted abatement costs in 2100 increase from 1 × 1012 US$ (4.5 W/m2) to around 4 × 1012 (3.7 W/m2), nearly 13 × 1012 (2.9 W/m2) and 13 × 1012
(2.6 W/m2 w/ BECS) in 2100. But also other factors are found to be relevant for costs. In case of the 3.7 W/m2 scenario, the overshoot scenario saves nearly 30% of overall costs. This is caused mainly by discounting, as this implies that long-term costs weigh less compared to costs made earlier in time in the stabilisation scenario. Postponement of action also allows to profit more from autonomous technology change (but at the same time forfeits some of the induced learning). Also the availability of BECS has significant effects. The technology not only provides more mitigation potential but also allows to postpone action providing benefits both from technology development and discounting effects. The availability of BECS halves the cumulative discounted abatement costs for the 2.9 W/m2 target.3
3 The similarity of expenses needed to attain a 2.6 and 2.9 without BECS W/m2 overshoot target is coincidental.
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4.2. Delayed participation 4.2.1. Emission pathways and concentration profiles The effect of delayed participation on the mitigation scenarios depends on the stringency of the forcing targets. • As a result of the considerable delay in participation of groups 2 and 3 that is assumed (30–50 years), the most stringent radiative forcing targets (2.6 and 2.9 W/m2) become unattainable in our framework. One may argue that the stabilisation cases become “physically unattainable”, as they require significant negative emissions for the group 1 region in the short-term. The stringent overshoot scenarios are constrained by our maximum marginal costs level of 273 US$/ tCO2. The introduction of overshoot scenarios and the addition of BECS to the mitigation portfolio are insufficient to reach the targets under the stringent delay conditions. • In the 4.5 W/m2 scenario the effect of delayed participation is more limited (Fig. 3, top-left), given there are little reductions during periods of limited participation. • For the intermediate radiative target (3.7 W/m2), a delayed participation scenario leads to moderate postponement of abatement of global emission reductions for both the overshoot and stabilisation case compared to the full participation case (Fig. 3, top-middle) (in other words, the reduced-participation partly leads to more reduction in participating regions, and partly to postponement). Apart from this delay in global emission reductions for the 3.7 W/m2 target, there are in particular large differences in the timing and amount of abatements in the three regions. Below we will discus these regional reduction differences in more detail for the overshoot case, and only briefly for the stabilisation case. The delay in participation of group 2 and 3 regions implies that the reduction effort in group 1 region is increased compared to the full participation case (Fig. 6, left). In 2050, this implies about a 40% emission reduction compared to baseline instead of a 30% reduction. For the group 2 region, the delay in action until 2030 is compensated
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by steep reductions after 2030. The total emissions across the century are in fact lower compared to the full participation scenario. Group 3 delays (by design) its emission reductions until 2050. After 2050 their emissions remain above the levels under full participation—as a result of the graduation rule, the inertia in emission reduction and reduced technology learning. Reductions in groups 1 and 2 thus compensate the higher emissions of group 3, leading to higher reductions in both regions. The changes in emission reduction rates are also reflected in the carbon price. As a result the carbon prices in the group 1 and 2 regions exceed the global permit price under full participation assumptions soon after 2010 and 2030, resp., and remain well above these levels (Fig. 7, left). Because of little demand in the period 2030–2040 the carbon price in the group 2 region grows to the price in the group 1 region within the 20 year transition period. Even the carbon price in group 3 exceeds the global permit price level by 2060 (as a result of the inertia and delayed learning). Together this leads to higher abatement costs for the delayed participation case globally (Fig. 5, middle). For a stabilisation 3.7 W/m2 scenario the carbon price developments in the three regions are even more extreme (Fig. 7, right). The stabilisation scenario requires early action: as overshoot is not allowed, the flexibility in the emission reductions is limited. This leads to high prices in the group 1 region until 2030 in order to reduce emissions fast enough. After 2030, the group 2 region gradually enters the carbon trading market, and this initially lowers the price, but by 2050 it reaches maximum levels again. These high prices are needed to achieve sufficient action in both group 1 and 2 regions. After 2050, the price decreases to lower levels due to the participation of group 3. Under the overshoot 3.7 W/m2 scenario the reduction action in the group 1 and 2 regions are postponed after 2050 to avoid these high price peaks before 2050. It also leads to a consistently increasing carbon price in the overshoot scenario, which differs from the double peaking price pathway under the 3.7 /m2 stabilisation scenario.
Fig. 6. Emissions in the three region groups under the baseline scenario and the full and delayed participation mitigation scenarios for meeting the 3.7 W/m2 overshoot target.
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Fig. 7. Global and regional carbon price under the full and delayed participation mitigation scenarios for meeting the 3.7 W/m2 overshoot (left) and 3.7 W/m2 stabilisation (right).
4.2.2. Energy use There are little changes in the energy system from a global perspective. Global total primary energy use remains almost unchanged compared to the full participation case. Regions that participate in reductions generally show an increase in biofuel use with a marginally reduced preference for coal. 4.2.3. Abatement costs The delayed participation highly influences the total abatement costs, and the resulting total cumulative discounted abatement costs, in particular for the 3.7 W/m2 scenarios (Fig. 5, middle). In case of the 3.7 W/m2 overshoot scenario the total cumulative discounted costs by 2100 increase by about 25% compared to the costs under the full participation scenario. The costs increase is relatively modest as a result of the flexibility in emission reduction: the delayed participation also leads to a delay in emission reduction. However, for the stabilisation 3.7 W/m2 scenario costs increase significantly by some 90%. Avoiding an overshoot in the radiative forcing requires early action and as there is little flexibility in the
timing of reduction action, this leads to a steeper increase in the regional permit prices, as was explained before. For the more stringent radiative forcing targets, costs increases cannot be assessed—as the mitigation target becomes infeasible if run under the delayed response assumption in this study. For the 4.5 W/m2 scenarios, the differences are relatively small (less than 5%). Again, this is a consequence of the fact that emission reductions under this scenario are clearly delayed anyway. 5. Discussion The main findings of this study with respect to participation are that: 1) delayed participation of developing countries leads to significant costs increases and 2) delayed participation of developing countries makes it impossible to achieve targets at or below 2.9 W/m2 in the current modelling framework. Below, we discuss the implications of the experimental set-up for these findings. In that context, it should be noted that most scenario runs in this study have been prescribed by the EMF-22 study.
Fig. 8. Effect of choice of the definition of radiative forcing (only Kyoto gases vs. all forcings).
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Fig. 9. Resulting temperature increase above pre-industrial levels, under different scenarios.
5.1. Formulation of the overall target In the EMF-22 study and thus in this article, the radiative forcing targets include all Kyoto gases, but not the Montreal gases or other substances such as aerosols. In many other studies (e.g. the Representative Concentration Pathways of IPCC) but also our earlier work (den Elzen et al., 2007; den Elzen and van Vuuren, 2007; van Vuuren et al., 2007) the definition for radiative forcing includes all GHGs, including the CFCs, HCFCs, tropospheric ozone and aerosols. As climate change depends on the total forcing (and not on the Kyotogas only forcing), the focus on the Kyoto-gas only forcing is arguably artificial. The effect of both definitions is illustrated in Fig. 8 for the full participation 3.7 W/m2 overshoot and 2.6 W/m2 BECS overshoot scenario. By excluding the non-Kyoto forcing agents, current radiative forcing is higher (mainly by not including the cooling effect of sulphur aerosols). This “Kyoto gas” radiative forcing remains above the total radiative forcing for the whole period until 2070– 2080. By 2100, the difference between the two definitions falls away due to reduced aerosol forcing. Emissions of these substances fall significantly due to air pollution control policies included in baseline assumptions, but also indirectly as a synergetic effect of climate policies. 5.2. Overshoot versus stabilization The scenarios as defined in this EMF study were defined using radiative forcing targets, however it is the resulting temperature change that is most relevant for climate impacts. This may have important implications. Fig. 9 shows the resulting transient temperature increase for the pathways of overshoot 2.6 and 2.9 W/m2 and compares these with the equilibrium temperature increase for a stabilisation profile at 2.6 W/m2. Given the inertia in the climate system, a stabilisation 2.6 W/ m2 profile leads to ongoing warming beyond 2100 until temperature reaches equilibrium. For the overshoot scenarios, the post-2100 warming depends on assumptions on post-2100 forcing. Given the decreasing forcing and temperature levels in 2100, one logical extension would be to assume that in these scenarios forcings continue to decrease, effectively preventing some of the temperature increase (“committed warming”) that would still occur after this concentration peak. In this way, in terms of temperature increase effects, overshoot profiles can be more effective than stabilisation profiles (for details see den Elzen and van Vuuren (2007)). This implies that while the EMF study focused on the 2.6 W/m2 scenario—from an environmental perspective the study could just as well have focused on an overshoot 2.9 W/m2 scenario. And while a
stabilisation target is considerably more stringent (and thus more expensive), the resulting gains in reducing temperature increase might be relatively small. 5.3. Participation rules The participation rules as formulated for this study should be considered as rather pessimistic both in timing as in definition of groups. First of all, developing country participation is considerably delayed (until 2030 for group 2; until 2050 for other developing countries). While full participation by 2012 is arguably not a realistic result of current international negotiations, more intermediate scenarios might also be achievable. Secondly, several regions now included in group 3 could be eligible for participation at an earlier time. There are several advanced developing countries or regions identifiable in this group that have per capita income levels above the average per capita income level in group 2, for example Mexico and the rest of Central America, Argentina, Middle East and South-Korea. Thirdly, the current model set-up does not explore new types of contributions from the non-Annex I countries in-between a voluntary non-binding approach under the Kyoto Protocol and the binding absolute reduction targets of current Annex I countries. These intermediate contributions, like sectoral targets, sectoral CDM, no lose emission targets or sustainable development policies and measures, allow for using the mitigation potential in developing countries—and still allow for low costs in developing countries. Finally, not all of the presently known mitigation options, like reducing emissions from deforestation are included in our present modelling framework. For others like forest management we use rather conservative estimates. This could have consequences for both mitigation potential and policy costs. Under such conditions, several low stabilisation targets may become feasible again even under delayed participation. 5.4. Burden-sharing This study has implemented regional carbon prices to induce emission reductions and assess the costs of mitigation policy. It does not necessarily mean that investments for regional emissions reductions are financed by the same region. By setting regional targets under a post-2012 burden-sharing regime and allowing a capand-trade mechanism financing does not necessarily originate from the same region as emission reductions are taking place. In such a case, the costs of increased mitigation action in group 2 under delayed assumptions could be distributed among participating regions.
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Conclusions on the attractiveness of scenarios discussed here for certain regions must be drawn prudently. These comments are not intended to undermine the results/setup of the present study. On the contrary, it is important to define and explore the limits of ‘the playing field’ in order to judge ambitious policy proposals. And the presented changes in the energy system are challenging indeed, both from a point of engineering and policy design. Given the arguments as described in this section this study does not imply that the more stringent targets are infeasible. Future work accounting for more optimistic assumptions like an earlier and broader participation is needed to explore the feasibility of meeting the most stringent stabilisation targets (2.6 and 2.9 W/m2). 6. Conclusions The main findings of the study are: Early participation of key developing countries is critically important for the feasibility of achieving low greenhouse gas concentration targets. The IMAGE framework is able to identify mitigation strategies for radiative forcing targets as low as 2.6 W/m2, but such targets become infeasible (i.e. no solutions with prices below 273 US$/tCO2) if there is a long delay in developing country participation. If participation of developing countries is seriously delayed as defined by the EMF-22 specifications the model was still able to achieve a 3.7 W/m2 target, but not the 2.6 or 2.9 W/m2 targets. Delayed participation leads to higher costs (25–90% in the 3.7 W/m2 cases) and delay in mitigation action. As international climate policy currently only requires emission reductions in a limited number of countries, increasing participation is a key priority if one aims to achieve low concentration targets. There are several key factors that increase the ability of achieving low greenhouse gas concentration targets, such as allowing overshoot and including technologies like bio-energy and carbon-capture-andstorage. The current analysis shows several of the EMF-22 scenarios to be infeasible under the current IMAGE framework set-up. However, the infeasibility does depend on various factors. For instance, the definition of radiative forcing targets on the basis of Kyoto gases only means that in the short-term radiative forcing levels are higher— making stabilisation scenarios more difficult to achieve. The results of the EMF-22 exercise can therefore not be directly compared to some other studies (including the new IPCC scenarios). Similarly, including overshoot profiles allows for lower targets to be feasible. Finally, the inclusion of bio-energy and carbon-capture-and-storage significantly influences the feasibility (and costs) of different targets. Both BECS and allowance for overshoot lead to a slightly delayed emission profile. For climate policy, this implies that making sure that key technologies are available is important (in particular CCS and BECS)—and that policies should consider overshoot strategies both from a perspective of reduced costs and efficiency in limiting temperature change. Further exploration of scenarios with delayed participation is needed. In this study, we run two main participation cases (full participation vs. seriously delayed participation). The experimental design, particularly the delayed participation assumptions, implies that several targets become infeasible to achieve. However, the assumed delay in participation is rather extreme. In order to support international policy-making it
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