The Relationship between the Low-Carbon Industrial Model and Human Well-Being: A Case Study of the Electric Power Industry

Ying Zhang, Xiaobin Dong (), Xuechao Wang, Peng Zhang, Mengxue Liu, Yufang Zhang and Ruiming Xiao
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Ying Zhang: State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Xiaobin Dong: State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Xuechao Wang: State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Peng Zhang: State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Mengxue Liu: State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Yufang Zhang: Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Ruiming Xiao: State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

Energies, 2023, vol. 16, issue 3, 1-19

Abstract: The electric power industry is one of the major industries in terms of carbon dioxide (CO 2 ) emissions, and it is necessary to explore low-carbon green power generation models. In recent years, more research has focused on the difference in carbon emissions in fossil energy versus renewable energy but ignored the impact of energy on human well-being. The life cycle assessment (LCA) method is a better method for assessing the impact of the low-carbon model on human well-being. In this paper, the carbon footprints of coal power plants and photovoltaic power (PV) plants generating 1 Kilowatt hour (kWh) of electricity are compared to analyze the degree of carbon emissions at different stages of the two models, and the environmental impact potential of the two models is analyzed using the LCA method. The differences between the two models in terms of human well-being were analyzed through questionnaires and quantified using the hierarchical analysis method. The impact of the different models on human well-being was compared using LCA method. The results of the study were as follows: the total CO 2 emissions from coal-fired power generation at the 1 kWh standard were 973.38 g, while the total CO 2 emissions from PV power generation were 91.95 g, and the carbon emission intensity of coal-fired power plants was higher than that of PV power plants. The global warming potential and eutrophication potential of coal-fired power plants were higher than those of PV power plants, and the rest of the indicators were lower than those of PV power plants. The composite human well-being index of PV power plants was 0.613 higher than that of coal-fired power plants at 0.561. The per capita income–global warming potential of PV power plants was higher than that of coal-fired power plants, indicating that PV power plants were a low carbon-emission and high well-being model. In conclusion, the PV power plant model is a low-carbon and high human well-being industrial model that is worthy of application in the Qilian Mountains region. The low-carbon industrial model proposed in this study can have a positive effect on regional ecological environmental protection and human well-being enhancement.

Keywords: low-carbon model; human well-being; carbon footprint; life cycle assessment; hierarchical analysis method (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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