Urban cross-sector actions for carbon mitigation with local health co-benefits in China

Anu Ramaswami, Kangkang Tong, Andrew Fang, Raj M. Lal, Ajay Singh Nagpure, Yang Li, Huajun Yu, Daqian Jiang, Armistead G. Russell, Lei Shi, Marian Chertow, Yangjun Wang, Shuxiao Wang

Research output: Contribution to journalArticlepeer-review

69 Scopus citations

Abstract

Cities offer unique strategies to reduce fossil fuel use through the exchange of energy and materials across homes, businesses, infrastructure and industries co-located in urban areas. However, the large-scale impact of such strategies has not been quantified. Using new models and data sets representing 637 Chinese cities, we find that such cross-sectoral strategies - enabled by compact urban design and circular economy policies - contribute an additional 15%-36% to national CO2 mitigation, compared to conventional single-sector strategies. As a co-benefit, ∼25,500 to ∼7,500 deaths annually are avoided from air pollution reduction. The benefits are highly variable across cities, ranging from <1%-37% for CO2 emission reduction and <1%-47% for avoided premature deaths. These results, using multi-scale, multi-sector physical systems modelling, identify cities with high carbon and health co-benefit potential and show that urban-industrial symbiosis is a significant carbon mitigation strategy, achievable with a combination of existing and advanced technologies in diverse city types.

Original languageEnglish (US)
Pages (from-to)736-742
Number of pages7
JournalNature Climate Change
Volume7
Issue number10
DOIs
StatePublished - Sep 29 2017

Bibliographical note

Funding Information:
This work was supported by a NSF Partnerships in International Research and Education grant (PIRE-1243535), Tsinghua University Initiative Scientific Research Program (No. 20121088096), and National Science Foundation of China (21625701). We thank M. Ahern and P. Bourne of Evergreen Energy (Saint Paul, Minnesota) for reviewing the district energy scenarios. We thank H. Shen for reviewing the results of air pollution modelling. We also appreciate G. Chan’s comments on this paper.

Publisher Copyright:
© 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.

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