A new global anthropogenic heat estimation based on high-resolution nighttime light data

Wangming Yang, Yibo Luan, Xiaolei Liu, Xiaoyong Yu, Lijuan Miao and Xuefeng Cui

EconStor Open Access Articles and Book Chapters, 2017, vol. 4, 1-11

Abstract: Consumption of fossil fuel resources leads to global warming and climate change. Apart from the negative impact of greenhouse gases on the climate, the increasing emission of anthropogenic heat from energy consumption also brings significant impacts on urban ecosystems and the surface energy balance. The objective of this work is to develop a new method of estimating the global anthropogenic heat budget and validate it on the global scale with a high precision and resolution dataset. A statistical algorithm was applied to estimate the annual mean anthropogenic heat (AH-DMSP) from 1992 to 2010 at 1×1 km2 spatial resolution for the entire planet. AH-DMSP was validated for both provincial and city scales, and results indicate that our dataset performs well at both scales. Compared with other global anthropogenic heat datasets, the AH-DMSP has a higher precision and finer spatial distribution. Although there are some limitations, the AH-DMSP could provide reliable, multi-scale anthropogenic heat information, which could be used for further research on regional or global climate change and urban ecosystems.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:espost:170751

DOI: 10.1038/sdata.2017.116

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