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Abstract Although cities have risen to prominence as climate actors, emissions’ data scarcity has been the primary challenge to evaluating their performance. Here we develop a scalable, replicable machine learning approach for evaluating the mitigation performance for nearly all local administrative areas in Europe from 2001-2018. By combining publicly available, spatially explicit environmental and socio-economic data with self-reported emissions data from European cities, we predict annual carbon dioxide emissions to explore trends in city-scale mitigation performance. We find that European cities participating in transnational climate initiatives have likely decreased emissions since 2001, with slightly more than half likely to have achieved their 2020 emissions reduction target. Cities who report emissions data are more likely to have achieved greater reductions than those who fail to report any data. Despite its limitations, our model provides a replicable, scalable starting point for understanding city-level climate emissions mitigation performance.
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Cities and regions tackle climate change mitigation but often focus on less effective solutions
Abstract Although the potential for cities and regions to contribute to global mitigation efforts is widely acknowledged, there is little evidence on the effectiveness of subnational mitigation strategies. Here we address this gap through a systematic review of 234 quantitative mitigation case studies. We use a meta-analytical approach to estimate expected greenhouse gas emissions reductions from 12 categories of mitigation strategies. We find that strategies related to land use and development, circular economy, and waste management are most effective and reliable for reducing emissions. The results demonstrate that cities and regions are taking widespread action to reduce emissions. However, we find misalignment between the strategies that policymakers and researchers focus on, compared to those with the highest expected impacts. The results inform climate action planning at the city and regional level and the evaluation of subnational climate targets.
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- Award ID(s):
- 2216592
- PAR ID:
- 10475616
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- Communications Earth & Environment
- Volume:
- 4
- Issue:
- 1
- ISSN:
- 2662-4435
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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