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Article

Mapping Building-Based Spatiotemporal Distributions of Carbon Dioxide Emission: A Case Study in England

1
Guangdong Key Laboratory for Urbanization and Geo-Simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China
2
Faculty of Architecture, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
3
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519000, China
*
Author to whom correspondence should be addressed.
Academic Editor: Paul B. Tchounwou
Int. J. Environ. Res. Public Health 2022, 19(10), 5986; https://doi.org/10.3390/ijerph19105986
Received: 7 April 2022 / Revised: 10 May 2022 / Accepted: 12 May 2022 / Published: 14 May 2022
(This article belongs to the Special Issue Advances in Urban Spatial Planning and Carbon Emission)
The spatiotemporal inventory of carbon dioxide (CO2) emissions from the building sector is significant for formulating regional and global warming mitigation policies. Previous studies have attempted to use energy consumption models associated with field investigations to estimate CO2 emissions from buildings at local scales, or they used spatial proxies to downscale emission sources from large geographic units to grid cells for larger scales. However, mapping the spatiotemporal distributions of CO2 emissions on a large scale based on buildings remains challenging. Hence, we conducted a case study in England in 2015, wherein we developed linear regression models to analyze monthly CO2 emissions at the building scale by integrating the Emissions Database for Global Atmospheric Research, building data, and Visible Infrared Imaging Radiometer Suite night-time lights images. The results showed that the proposed model that considered building data and night-time light imagery achieved the best fit. Fine-scale spatial heterogeneity was observed in the distributions of building-based CO2 emissions compared to grid-based emission maps. In addition, we observed seasonal differences in CO2 emissions. Specifically, buildings emitted significantly more CO2 in winter than in summer in England. We believe our results have great potential for use in carbon neutrality policy making and climate monitoring. View Full-Text
Keywords: CO2 emissions; linear regression analysis; radiance-calibrated nightlight; building-based CO2 emissions; linear regression analysis; radiance-calibrated nightlight; building-based
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MDPI and ACS Style

Zheng, Y.; Ou, J.; Chen, G.; Wu, X.; Liu, X. Mapping Building-Based Spatiotemporal Distributions of Carbon Dioxide Emission: A Case Study in England. Int. J. Environ. Res. Public Health 2022, 19, 5986. https://doi.org/10.3390/ijerph19105986

AMA Style

Zheng Y, Ou J, Chen G, Wu X, Liu X. Mapping Building-Based Spatiotemporal Distributions of Carbon Dioxide Emission: A Case Study in England. International Journal of Environmental Research and Public Health. 2022; 19(10):5986. https://doi.org/10.3390/ijerph19105986

Chicago/Turabian Style

Zheng, Yue, Jinpei Ou, Guangzhao Chen, Xinxin Wu, and Xiaoping Liu. 2022. "Mapping Building-Based Spatiotemporal Distributions of Carbon Dioxide Emission: A Case Study in England" International Journal of Environmental Research and Public Health 19, no. 10: 5986. https://doi.org/10.3390/ijerph19105986

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