Emission mitigation potentials and costs for non-CO<sub>2</sub>greenhouse gases in Annex-I countries according to the GAINS model

Winiwarter, Wilfried; Hoeglund-Isaksson, L.; Schoepp, W.; Tohka, Antti; Wagner, Fabian; Amann, Markus

doi:10.1080/19438151003774430

Cited by 8 publications

(5 citation statements)

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“…The model used in this assessment, the Greenhouse Gas Air Pollution Interactions and Synergies (GAINS) model, has a comprehensive, multi-country and region representation of non-CO 2 GHG emissions sources, as well as the measures and costs for their mitigation [24,25]. The cost data used here is from the 2013 update of the GAINS model.…”

Section: Methodsmentioning

confidence: 99%

“…The TIAM-Grantham [28][29][30] and IIASA GAINS [24,25] models are used to derive time profiles of emissions of CO 2 , CH 4 , N 2 O and total F-Gas emissions from a given cumulative CO 2 budget for fossil fuels and industry (FFI) in order to meet a given long-term temperature goal (LTTG)-the temperature change in 2100. In order to make climate projections (verifying the CO 2 budgets) the total F-Gas emissions must be broken down into constituent species and emissions of other gases must also be estimated.…”

Section: Appendix B Deriving Temperature Goal-consistent 21st Centurmentioning

confidence: 99%

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The Contribution of Non-CO2 Greenhouse Gas Mitigation to Achieving Long-Term Temperature Goals

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This paper analyses the emissions and cost impacts of mitigation of non-CO 2 greenhouse gases (GHGs) at a global level, in scenarios aimed at meeting a range of long-term temperature goals (LTTGs). The study combines an integrated assessment model (TIAM-Grantham) representing CO 2 emissions (and their mitigation) from the fossil fuel combustion and industrial sectors, coupled with a model covering non-CO 2 emissions (GAINS), using the latest global warming potentials from the Intergovernmental Panel on Climate Change's Fifth Assessment Report. We illustrate that in general non-CO 2 mitigation measures are less costly than CO 2 mitigation measures, with the majority of their abatement potential achievable at US2005$100/tCO 2 e or less throughout the 21st century (compared to a marginal CO 2 mitigation cost which is already greater than this by 2030 in the most stringent mitigation scenario). As a result, the total cumulative discounted cost over the period 2010-2100 (at a 5% discount rate) of limiting global average temperature change to 2.5 • C by 2100 is $48 trillion (about 1.6% of cumulative discounted GDP over the period 2010-2100) if only CO 2 from the fossil fuel and industrial sectors is targeted, whereas the cost falls to $17 trillion (0.6% of GDP) by including non-CO 2 GHG mitigation in the portfolio of options-a cost reduction of about 65%. The criticality of non-CO 2 mitigation recommends further research, given its relatively less well-explored nature when compared to CO 2 mitigation.

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Section: Methodsmentioning

confidence: 99%

Section: Appendix B Deriving Temperature Goal-consistent 21st Centurmentioning

confidence: 99%

The Contribution of Non-CO2 Greenhouse Gas Mitigation to Achieving Long-Term Temperature Goals

et al. 2017

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“…Therefore, it is necessary to extract a reduced-form representation of complex sets of technological specifications and then usefully integrate them into the CGE model with minimal structural changes. One way to do this is to extract marginal cost curve information derived from model simulations of a more technology-oriented model, such as GAINS [37][38][39]. With this information, it will be possible to not only represent in a CGE model the changes in energy consumption and greenhouse gases (GHG) emission reduction, but also the changes in different categories of expenditures, i.e., investment versus operating costs (see Figure 1).…”

Section: Methodsmentioning

confidence: 99%

“…For the technology model, we use the input data and methodology of the GAINS model, which has been documented extensively elsewhere [33,[37][38][39][45][46][47][48][49]. The GAINS model is both an integrated assessment model of air pollution and a model for calculating marginal abatement costs and potentials for greenhouse gas mitigation.…”

Section: Technology Frameworkmentioning

confidence: 99%

The Deployment of Low Carbon Technologies in Energy Intensive Industries: A Macroeconomic Analysis for Europe, China and India

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Industrial processes currently contribute 40% to global CO 2 emissions and therefore substantial increases in industrial energy efficiency are required for reaching the 2 • C target. We assess the macroeconomic effects of deploying low carbon technologies in six energy intensive industrial sectors (Petroleum, Iron and Steel, Non-metallic Minerals, Paper and Pulp, Chemicals, and Electricity) in Europe, China and India in 2030. By combining the GAINS technology model with a macroeconomic computable general equilibrium model, we find that output in energy intensive industries declines in Europe by 6% in total, while output increases in China by 11% and in India by 13%. The opposite output effects emerge because low carbon technologies lead to cost savings in China and India but not in Europe. Consequently, the competitiveness of energy intensive industries is improved in China and India relative to Europe, leading to higher exports to Europe. In all regions, the decarbonization of electricity plays the dominant role for mitigation. We find a rebound effect in China and India, in the size of 42% and 34% CO 2 reduction, respectively, but not in Europe. Our results indicate that the range of considered low-carbon technology options is not competitive in the European industrial sectors. To foster breakthrough low carbon technologies and maintain industrial competitiveness, targeted technology policy is therefore needed to supplement carbon pricing.

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“…The TIAM-Grantham and IIASA GAINS [66,67] models are used to derive time profiles of emissions of CO 2 , CH 4 , N 2 O and total F-Gas emissions from a given cumulative CO 2 budget for fossil fuels and industry (FFI) in order to meet a given LTTG-the temperature change in 2100. In order to make climate projections (verifying the CO 2 budgets) the total F-Gas emissions must be broken down into constituent species and emissions of other gases must also be estimated.…”

Section: Appendix D Deriving Temperature Goal-consistent 21st Centurmentioning

confidence: 99%

Assessing the Feasibility of Global Long-Term Mitigation Scenarios

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This study explores the critical notion of how feasible it is to achieve long-term mitigation goals to limit global temperature change. It uses a model inter-comparison of three integrated assessment models (TIAM-Grantham, MESSAGE-GLOBIOM and WITCH) harmonized for socio-economic growth drivers using one of the new shared socio-economic pathways (SSP2), to analyse multiple mitigation scenarios aimed at different temperature changes in 2100, in order to assess the model outputs against a range of indicators developed so as to systematically compare the feasibility across scenarios. These indicators include mitigation costs and carbon prices, rates of emissions reductions and energy efficiency improvements, rates of deployment of key low-carbon technologies, reliance on negative emissions, and stranding of power generation assets. The results highlight how much more challenging the 2 • C goal is, when compared to the 2.5-4 • C goals, across virtually all measures of feasibility. Any delay in mitigation or limitation in technology options also renders the 2 • C goal much less feasible across the economic and technical dimensions explored. Finally, a sensitivity analysis indicates that aiming for less than 2 • C is even less plausible, with significantly higher mitigation costs and faster carbon price increases, significantly faster decarbonization and zero-carbon technology deployment rates, earlier occurrence of very significant carbon capture and earlier onset of global net negative emissions. Such a systematic analysis allows a more in-depth consideration of what realistic level of long-term temperature changes can be achieved and what adaptation strategies are therefore required.

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Emission mitigation potentials and costs for non-CO₂greenhouse gases in Annex-I countries according to the GAINS model

Cited by 8 publications

References 1 publication

The Contribution of Non-CO2 Greenhouse Gas Mitigation to Achieving Long-Term Temperature Goals

The Contribution of Non-CO2 Greenhouse Gas Mitigation to Achieving Long-Term Temperature Goals

The Deployment of Low Carbon Technologies in Energy Intensive Industries: A Macroeconomic Analysis for Europe, China and India

Assessing the Feasibility of Global Long-Term Mitigation Scenarios

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Emission mitigation potentials and costs for non-CO2greenhouse gases in Annex-I countries according to the GAINS model

Cited by 8 publications

References 1 publication

The Contribution of Non-CO2 Greenhouse Gas Mitigation to Achieving Long-Term Temperature Goals

The Contribution of Non-CO2 Greenhouse Gas Mitigation to Achieving Long-Term Temperature Goals

The Deployment of Low Carbon Technologies in Energy Intensive Industries: A Macroeconomic Analysis for Europe, China and India

Assessing the Feasibility of Global Long-Term Mitigation Scenarios

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Product

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Emission mitigation potentials and costs for non-CO₂greenhouse gases in Annex-I countries according to the GAINS model