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Environ Pollut. 2019 Jun;249:923-931. doi: 10.1016/j.envpol.2019.03.113. Epub 2019 Mar 30.

Characterizing spatiotemporal dynamics of anthropogenic heat fluxes: A 20-year case study in Beijing-Tianjin-Hebei region in China.

Author information

1
Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing, 100871, China; College of Resource Environment and Tourism, Capital Normal University, Beijing, 100048, China.
2
College of Resource Environment and Tourism, Capital Normal University, Beijing, 100048, China. Electronic address: deyonghu@163.com.
3
Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong.
4
Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing, 100871, China.
5
College of Resource Environment and Tourism, Capital Normal University, Beijing, 100048, China.
6
Department of Urban Planning and Design, The Hong Kong University, Hong Kong.

Abstract

Rapid urbanization, which is closely related to economic growth, human health, and micro-climate, has resulted in a considerable amount of anthropogenic heat emissions. The lack of estimation data on long-term anthropogenic heat emissions is a great concern in climate and urban flux research. This study estimated the annual average anthropogenic heat fluxes (AHFs) in Beijing-Tianjin-Hebei region in China between 1995 and 2015 on the basis of multisource remote sensing images and ancillary data. Anthropogenic heat emissions from different sources (e.g., industries, buildings, transportation, and human metabolism) were also estimated to analyze the composition of AHFs. The spatiotemporal dynamics of long-term AHFs with high spatial resolution (500 m) were estimated by using a refined AHF model and then analyzed using trend and standard deviation ellipse analyses. Results showed that values in the region increased significantly from 0.15 W· m-2 in 1995 to 1.46 W· m-2 in 2015. Heat emissions from industries, transportation, buildings, and human metabolism accounted for 64.1%, 17.0%, 15.5%, and 3.4% of the total anthropogenic heat emissions, respectively. Industrial energy consumption was the dominant contributor to the anthropogenic heat emissions in the region. During this period, industrial heat emissions presented an unstable variation but showed a growing trend overall. Heat emissions from buildings increased steadily. Spatial distribution was extended with an increasing tendency of the difference between the maximum and the minimum and was generally dominated by the northeast-southwest directional pattern. The spatiotemporal distribution patterns and trends of AHFs could provide vital support on management decision in city planning and environmental monitoring.

KEYWORDS:

Anthropogenic heat; Human activity; Mitigation; Nighttime light data; Spatiotemporal dynamics; Thermal environment monitoring

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