bottom-up;
energy modelling;
mitigation scenarios;
ENERGY;
POLICY;
D O I:
10.1080/14693062.2014.912980
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
Most studies that explore deep GHG emission reduction scenarios assume that climate goals are reached by implementing least-cost emission mitigation options, typically by implementing a global carbon tax. Although such a method provides insight into total mitigation costs, it does not provide much information about how to achieve a transition towards a low-carbon energy system, which is of critical importance to achieving ambitious climate targets. To enable sensible deep emission reduction strategies, this study analysed the effectiveness of 16 specific mitigation measures on a global level up to 2050, by using an energy-system simulation model called TIMER. The measures range from specific energy efficiency measures, like banning traditional light bulbs and subsidizing electric vehicles, to broader policies like introducing a carbon tax in the electricity sector. All measures combined lead to global CO2 emission reductions ranging between 39% and 73% compared to baseline by 2050, depending on the inclusion of sectoral carbon taxes and the availability of carbon capture and storage (CCS) and nuclear power. Although the effectiveness of the measures differs largely across regions, this study indicates that measures aimed at stimulating low-carbon electricity production result in the highest reductions in all regions.Policy relevanceThe results of the calculations can be used to evaluate the effects of individual climate change mitigation measures and identify priorities in discussions on global and regional policies. The type of fragmented policy scenarios presented here could provide a relevant bottom-up alternative to cost-optimal implementation of policies driven by a carbon tax. We identify overlapping and even counter-productive climate policy measures through an analysis that presents the policy effectiveness by region, and by sector. The set of 16 policy measures addresses the largest emitting sectors and represents options that are often discussed as part of planned policies.
机构:
Univ Queensland, Sch ITEE, Power & Energy Syst Grp, Brisbane, Qld, AustraliaUniv Queensland, Sch ITEE, Power & Energy Syst Grp, Brisbane, Qld, Australia
Mahmoudi, Nadali
Heydarian-Forushani, Ehsan
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机构:
Isfahan Univ Technol, Dept Elect & Comp Engn, Esfahan, IranUniv Queensland, Sch ITEE, Power & Energy Syst Grp, Brisbane, Qld, Australia
Heydarian-Forushani, Ehsan
Shafie-khah, Miadreza
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机构:
Univ Salerno, Via Giovanni Paolo 2 132, I-84084 Salerno, ItalyUniv Queensland, Sch ITEE, Power & Energy Syst Grp, Brisbane, Qld, Australia
Shafie-khah, Miadreza
Saha, Tapan K.
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机构:
Univ Queensland, Sch ITEE, Power & Energy Syst Grp, Brisbane, Qld, AustraliaUniv Queensland, Sch ITEE, Power & Energy Syst Grp, Brisbane, Qld, Australia
Saha, Tapan K.
Golshan, M. E. H.
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机构:
Isfahan Univ Technol, Dept Elect & Comp Engn, Esfahan, IranUniv Queensland, Sch ITEE, Power & Energy Syst Grp, Brisbane, Qld, Australia
Golshan, M. E. H.
Siano, Pierluigi
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机构:
Univ Salerno, Via Giovanni Paolo 2 132, I-84084 Salerno, ItalyUniv Queensland, Sch ITEE, Power & Energy Syst Grp, Brisbane, Qld, Australia
机构:
Univ Tokyo, Sch Engn, Dept Syst Innovat, Tokyo, JapanUniv Tokyo, Sch Engn, Dept Syst Innovat, Tokyo, Japan
Matsuyama, Ryutaro
Sugimura, Yoshihisa
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机构:
Kobe Univ, Grad Sch Maritime Sci, Global Transportat Sci, Kobe, Japan
5-1-1 Fukae Minami, Kobe 6580022, JapanUniv Tokyo, Sch Engn, Dept Syst Innovat, Tokyo, Japan
Sugimura, Yoshihisa
Shibasaki, Ryuichi
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Univ Tokyo, Sch Engn, Dept Syst Innovat, Tokyo, JapanUniv Tokyo, Sch Engn, Dept Syst Innovat, Tokyo, Japan
Shibasaki, Ryuichi
Tran, Trang Thi Thu
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机构:
Univ Tokyo, Sch Engn, Dept Syst Innovat, Tokyo, JapanUniv Tokyo, Sch Engn, Dept Syst Innovat, Tokyo, Japan