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Carbon Emission Inversion Model from Provincial to Municipal Scale Based on Nighttime Light Remote Sensing and Improved STIRPAT

Author

Listed:
  • Qi Wang

    (School of Resource and Environmental Engineering, Wuhan University of Technology, Wuhan 430062, China)

  • Jiejun Huang

    (School of Resource and Environmental Engineering, Wuhan University of Technology, Wuhan 430062, China)

  • Han Zhou

    (School of Resource and Environmental Engineering, Wuhan University of Technology, Wuhan 430062, China)

  • Jiaqi Sun

    (School of Resource and Environmental Engineering, Wuhan University of Technology, Wuhan 430062, China)

  • Mingkun Yao

    (School of Resource and Environmental Engineering, Wuhan University of Technology, Wuhan 430062, China)

Abstract

Carbon emissions and consequent climate change directly affect the sustainable development of ecological environment systems and human society, which is a pertinent issue of concern for all countries globally. The construction of a carbon emission inversion model has significant theoretical importance and practical significance for carbon emission accounting and control. Established carbon emission models usually adopt socio-economic parameters or energy statistics to calculate carbon emissions. However, high-precision estimates of carbon emissions in administrative regions lacking energy statistics are difficult. This problem is especially prominent in small-scale regions. Methods to accurately estimate carbon emissions in small-scale regions are needed. Based on nighttime light remote-sensing data and the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model, combined with the environmental Kuznets curve, this paper proposes an ISTIRPAT (Improved Stochastic Impacts by Regression on Population, Affluence, and Technology) model. Through the improved STIRPAT model (ISTIRPAT) and panel data regression, provincial carbon emission inventory data were downscaled to the municipal level, and municipal scale carbon emission inventories were obtained. This study took the 17 cities and prefectures of Hubei Province, China, as an example to verify the accuracy of the model. Carbon emissions for 17 cities and prefectures from 2012 to 2018 calculated from the original STIRPAT model and the ISTIRPAT model were compared with real values. The results show that using the ISTIRPAT model to downscale the provincial carbon emission inventory to the municipal level, the inversion accuracy reached 0.9, which was higher than that of the original model. Overall, carbon emissions in Hubei Province showed an upward trend. Regarding the spatial distribution, the main carbon emission area was formed in the central part of Hubei Province as a ring-shaped mountain peak. The lowest carbon emissions in the central area expanded outward, increased, and gradually decreased to the edge of the province. The overall composition of carbon emissions in eastern Hubei was higher than those in western Hubei.

Suggested Citation

  • Qi Wang & Jiejun Huang & Han Zhou & Jiaqi Sun & Mingkun Yao, 2022. "Carbon Emission Inversion Model from Provincial to Municipal Scale Based on Nighttime Light Remote Sensing and Improved STIRPAT," Sustainability, MDPI, vol. 14(11), pages 1-17, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:11:p:6813-:d:830496
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    References listed on IDEAS

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    Cited by:

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    2. Zheng Jiang & Shuohua Zhang & Wei Li, 2022. "Exploration of Urban Emission Mitigation Pathway under the Carbon Neutrality Target: A Case Study of Beijing, China," Sustainability, MDPI, vol. 14(21), pages 1-18, October.
    3. Bin Liu & Jiehua Lv, 2024. "Spatiotemporal Evolution and Tapio Decoupling Analysis of Energy-Related Carbon Emissions Using Nighttime Light Data: A Quantitative Case Study at the City Scale in Northeast China," Energies, MDPI, vol. 17(19), pages 1-26, September.
    4. Gulmira Abbas & Alimujiang Kasimu, 2023. "Characteristics of Land-Use Carbon Emissions and Carbon Balance Zoning in the Economic Belt on the Northern Slope of Tianshan," Sustainability, MDPI, vol. 15(15), pages 1-27, July.
    5. Weijia Li & Yuejiao Wang, 2023. "Optimization of Urban Road Green Belts under the Background of Carbon Peak Policy," Sustainability, MDPI, vol. 15(17), pages 1-17, August.

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