An emissions-socioeconomic inventory of Chinese cities

Shan, Yuli, Liu, Jianghua, Liu, Zhu, Shao, Shuai and Guan, Dabo (2019) An emissions-socioeconomic inventory of Chinese cities. Scientific Data, 6. ISSN 2052-4463

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Abstract

As the centre of human activity and being under the threat of climate change, cities are considered to be major components in the implementation of climate change mitigation and CO2 emission reduction strategies. Inventories of cities’ emissions serve as the foundation for the analysis of emissions characteristics and policymaking. China is the world’s top energy consumer and CO2 emitter, and it is facing great potential harm from climate change. Consequently, China is taking increasing responsibility in the fight against global climate change. Many energy/emissions control policies have been implemented in China, most of which are designed at the national level. However, cities are at different stages of industrialization and have distinct development pathways; they need specific control policies designed based on their current emissions characteristics. This study is the first to construct emissions inventories for 182 Chinese cities. The inventories are constructed using 17 fossil fuels and 47 socioeconomic sectors. These city-level emissions inventories have a scope and format consistent with China’s national/provincial inventories. Some socioeconomic data of the cities, such as GDP, population, industrial structures, are included in the datasets as well. The dataset provides transparent, accurate, complete, comparable, and verifiable data support for further city-level emissions studies and low-carbon/sustainable development policy design. The dataset also offers insights for other countries by providing an emissions accounting method with limited data.

Item Type: Article
Faculty \ School: Faculty of Social Sciences > School of International Development
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 27 Feb 2019 11:30
Last Modified: 22 Apr 2020 07:32
URI: https://ueaeprints.uea.ac.uk/id/eprint/70028
DOI: 10.1038/sdata.2019.27

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