Emissions Lock-in, Capacity, and Public Opinion: How Insights From Political Science Can Inform Climate Modeling Efforts

被引:16
|
作者
Pianta, Silvia [1 ,2 ]
Brutschin, Elina [3 ]
机构
[1] Ctr Euro Mediterraneo Cambiamenti Climat, RFF CMCC European Inst Econ & Environm, Lecce, Italy
[2] European Univ Inst, Florence, Italy
[3] Int Inst Appl Syst Anal, Laxenburg, Austria
来源
POLITICS AND GOVERNANCE | 2022年 / 10卷 / 03期
关键词
climate policy ambition; climate modeling; climate policymaking; climate politics; emissions lock-in; integrated assessment models; Paris Agreement; public opinion; public support; state capacity; ENVIRONMENTAL POLITICS; POLICY; ENERGY; TRANSITIONS; GOVERNANCE; ECONOMY; DETERMINANTS; INSTITUTIONS; PERSPECTIVES; FEASIBILITY;
D O I
10.17645/pag.v10i3.5462
中图分类号
D0 [政治学、政治理论];
学科分类号
0302 ; 030201 ;
摘要
The implementation of ambitious climate policies consistent with the goals of the Paris Agreement is fundamentally influ-enced by political dynamics. Yet, thus far, climate mitigation pathways developed by integrated assessment models (IAMs) have devoted limited attention to the political drivers of climate policymaking. Bringing together insights from the political science and socio-technical transitions literature, we summarize evidence on how emissions lock-in, capacity, and public opinion can shape climate policy ambition. We employ a set of indicators to describe how these three factors vary across countries and regions, highlighting context-specific challenges and enablers of climate policy ambition. We outline exist-ing studies that incorporate political factors in IAMs and propose a framework to employ empirical data to build climate mitigation scenarios that incorporate political dynamics. Our findings show that there is substantial heterogeneity in key political drivers of climate policy ambition within IAM regions, calling for a more disaggregated regional grouping within models. Importantly, we highlight that the political challenges and enablers of climate policy ambition considerably vary across regions, suggesting that future modeling efforts incorporating political dynamics can significantly increase the real-ism of IAM scenarios.
引用
收藏
页码:186 / 199
页数:14
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