2000 至 2020 年中国 281 个城市的城市级能量代谢账户。

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Miaohan Tang, Gengyuan Liu, Jingke Hong, Weier Liu, Chao Zhong, Dan Wang, Yuli Shan
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引用次数: 0

摘要

城市在自然环境、产业构成、能源和物质消费等方面表现出多样化的城市代谢模式。城市水平的能量代谢流随时间的量化记录可以显著增强对时间动态和城市代谢模式的理解,这为向可持续性过渡提供了重要的见解。然而,中国目前还没有能够支持详细时空分析的城市能量代谢数据集。在这项研究中,我们提出了2000年至2020年中国281个城市的城市能量代谢数据集。该数据集详细描述了21年来中国281个城市维持代谢活动的41种资源类型的生产和进口。该数据库首次通过详细描述包括资源生产、消费和进口在内的能源流动,提供了对中国城市历史代谢变化的洞察。此外,这些能流清单为研究中国城市代谢特征、评估政策影响和制定可持续发展战略提供了宝贵的资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

City-level emergy metabolism accounts for China's 281 cities from 2000 to 2020.

City-level emergy metabolism accounts for China's 281 cities from 2000 to 2020.

City-level emergy metabolism accounts for China's 281 cities from 2000 to 2020.

Cities exhibit diverse urban metabolism patterns in terms of the natural environment, industrial composition, energy, and material consumption. A chronicled city-level quantification of emergy metabolic flows over time can significantly enhance the understanding of the temporal dynamics and urban metabolism patterns, which provides critical insights for the transitions to sustainability. However, there exists no city-level urban emergy metabolism dataset in China that can support detailed spatial-temporal analysis. In this study, we present a city-level urban emergy metabolism dataset of China's 281 cities between 2000 and 2020. This dataset meticulously describes the production and import of 41 resource types that sustain metabolic activities in 281 Chinese cities over a span of 21 years. This database, for the first time, provides insights into the historical metabolic changes of China's cities by detailing emergy flows including production, consumption, and import of resources. Furthermore, these emergy flow inventories serve as valuable resources for studying urban metabolic characteristics, evaluating policy impacts, and formulating sustainable development strategies for China's cities.

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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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