Research on the Influencing Factors of Carbon Emission in Shaanxi Province Based on the STIRPAT Model

Abstract To proactively address the growing environmental challenge of global warming, China has set an ambitious goal of achieving a carbon peak by 2030. As a significant contributor to China’s energy output, the carbon emissions produced in Shaanxi Province are of paramount importance in achieving the country’s overarching objective. By examining the factors that contribute to carbon emissions in Shaanxi Province, providing a scientific foundation for the development of low-carbon economic growth strategies is provided in this paper. Previously, hypothesis analysis based on linear relationships was employed in environmental impact assessment, which has been identified as having shortcomings, including issues with multiple covariance and insufficient model interpretation. A comparison is made between the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model and existing methods. The STIRPAT model offers greater flexibility, scalability, and the capacity to handle nonlinear relationships. When combined with ridge regression, it can also address the issue of multicollinearity and enhance the stability and reliability of the model. The STIRPAT model is particularly well-suited to the study of carbon emission influencing factors in Shaanxi Province, as it allows for the incorporation of several key factors, including population, affluence, and technology. The results of the empirical analysis show that GDP (Gross Domestic Product), urbanization level, population size, industrial structure and technological progress are the main factors affecting carbon emissions in Shaanxi Province, and it is also proved that the model has a very high accuracy, with an R 2 value of 0.961, and can accurately fit the carbon emissions in Shaanxi Province. Among them, technological progress is the most crucial factor affecting carbon emissions in Shaanxi Province, and every one percent increase in the level of technological progress reduces carbon emissions by 0.268 per cent while other factors remain unchanged, so the rapid development of renewable energy technologies, such as solar energy, wind energy and hydropower, and the application of new low-carbon materials, such as bio-based materials and biodegradable polymer materials, should be actively promoted.

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Publication Details

Journal
Journal of Physics Conference Series
Published
2025-02-01
DOI
https://doi.org/10.1088/1742-6596/2962/1/012003
Citations
1
Primary Topic
Environmental Impact and Sustainability
Type
article
Field-Weighted Citation Impact
0.80
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article

Research on the Influencing Factors of Carbon Emission in Shaanxi Province Based on the STIRPAT Model

Ke Hou, Wenqing Ma, Mengying Wu
1 citations
Journal of Physics Conference Series
Environmental Impact and Sustainability
0.80
article

Research on the Influencing Factors of Carbon Emission in Shaanxi Province Based on the STIRPAT Model

Ke Hou, Wenqing Ma, Mengying Wu
article en
1 citations

Abstract

Abstract To proactively address the growing environmental challenge of global warming, China has set an ambitious goal of achieving a carbon peak by 2030. As a significant contributor to China’s energy output, the carbon emissions produced in Shaanxi Province are of paramount importance in achieving the country’s overarching objective. By examining the factors that contribute to carbon emissions in Shaanxi Province, providing a scientific foundation for the development of low-carbon economic growth strategies is provided in this paper. Previously, hypothesis analysis based on linear relationships was employed in environmental impact assessment, which has been identified as having shortcomings, including issues with multiple covariance and insufficient model interpretation. A comparison is made between the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model and existing methods. The STIRPAT model offers greater flexibility, scalability, and the capacity to handle nonlinear relationships. When combined with ridge regression, it can also address the issue of multicollinearity and enhance the stability and reliability of the model. The STIRPAT model is particularly well-suited to the study of carbon emission influencing factors in Shaanxi Province, as it allows for the incorporation of several key factors, including population, affluence, and technology. The results of the empirical analysis show that GDP (Gross Domestic Product), urbanization level, population size, industrial structure and technological progress are the main factors affecting carbon emissions in Shaanxi Province, and it is also proved that the model has a very high accuracy, with an R 2 value of 0.961, and can accurately fit the carbon emissions in Shaanxi Province. Among them, technological progress is the most crucial factor affecting carbon emissions in Shaanxi Province, and every one percent increase in the level of technological progress reduces carbon emissions by 0.268 per cent while other factors remain unchanged, so the rapid development of renewable energy technologies, such as solar energy, wind energy and hydropower, and the application of new low-carbon materials, such as bio-based materials and biodegradable polymer materials, should be actively promoted.

Journal of Physics Conference SeriesVol. 2962(1)
Xi'an Shiyou University (CN)
Openalex Percentile: Top 32%
Environmental Impact and Sustainability
0.80
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