A Taguchi-STIRPAT input–output model for unveiling the pathways of reducing household carbon emissions under dual-carbon target—A case study of Fujian province

Analysis of Influencing Factors and Prediction of the Peak Value of Industrial Carbon Emission in the Sichuan-Chongqing Region

“…Tang et al used the extended STIRPAT model to analyze countermeasures and suggestions for carbon emissions in China's metal smelting industry, identifying population, coal consumption, urbanization rate, total metal output, carbon intensity, proportion of secondary industries, and per capita GDP as important factors affecting carbon emissions [10]. Cai et al adopted the novel STIRPAT model to explore ways to reduce carbon emissions from the perspective of household consumption and assessed the impact of major factors such as carbon emission intensity, consumption structure, per capita consumption, and population on indirect household carbon emissions, finding that the energy intensity of economic industries is an important factor affecting carbon emission intensity [11]. Wei et al employed a combination of the Tapio decoupling and STIRPAT models to conduct an analysis, leading to the conclusion that there exists a strong decoupling and weak decoupling relationship between agricultural and animal husbandry economic development and carbon emissions [12].…”