Learning about urban climate solutions from case studies
Climate mitigation research puts increasing emphasis on cities, but much more could be learned from urban case studies. The overall size, geographic scope and topic content of cases remains unknown, resulting in few attempts to synthesise the bottom-up evidence. Here, we use scientometric and machin...
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Published in: | Nature climate change 2019-04, Vol.9 (4), p.279-287 |
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Learning about urban climate solutions from case studies |
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Lamb, William F. Creutzig, Felix Callaghan, Max W. Minx, Jan C. |
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Case studies Climate Climate change Learning algorithms Machine learning Mitigation Production methods Scientometrics Urban areas Urban research |
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Nature climate change, 2019-04, Vol.9 (4), p.279-287 |
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Climate mitigation research puts increasing emphasis on cities, but much more could be learned from urban case studies. The overall size, geographic scope and topic content of cases remains unknown, resulting in few attempts to synthesise the bottom-up evidence. Here, we use scientometric and machine-learning methods to produce a comprehensive map of the literature. Our database of approximately 4,000 case studies provides a wealth of evidence to search, compare and review. We find that cities in world regions with the highest future mitigation relevance are systematically underrepresented. A map of the evidence allows case studies to be matched with urban typologies in new and more ambitious forms of synthesis, bringing together traditionally separate strands of qualitative and quantitative urban research. Cities around the world are at the forefront of enacting climate mitigation policies, but effective action requires a better understanding of potential solutions. This Review offers a systematic exploration of the urban case study literature and discusses ways to best make use of the growing body of cases. |
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