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Analysis of the Social and Economic Factors Influencing PM2.5 Emissions at the City Level in China
Respirable suspended particles (PM2.5) are one of the key components of haze, which not only causes a variety of lung, intestinal, and vascular diseases, but also affects cognitive levels. China is facing the challenge of severe PM2.5 concentrations, especially in urban areas with a high population density. Understanding the key factors that influence PM2.5 concentrations is fundamental for the adoption of targeted measures. Therefore, this study used the Logarithmic Mean Divisia Index (LMDI) method to identify the key factors influencing PM2.5 concentrations in 236 cities in northeastern, western, central, and eastern China. The findings were as follows. The emission intensity (EI) played an important suppressing role on PM2.5 concentrations in all cities from 2011–2020. The energy intensity (EnI) inhibited PM2.5 concentrations in 157 cities; the economic output (EO) stimulated PM2.5 concentrations in some less economically developed regions; and population (P) spurred PM2.5 concentrations in135 cities, mainly concentrated in developed eastern cities. This study provides a whole picture of the key factors influencing PM2.5 concentrations in Chinese cities, and the findings can act as the scientific basis and guidance for Chinese city authorities in formulating policies toward PM2.5 concentration reduction.
Analysis of the Social and Economic Factors Influencing PM2.5 Emissions at the City Level in China
Respirable suspended particles (PM2.5) are one of the key components of haze, which not only causes a variety of lung, intestinal, and vascular diseases, but also affects cognitive levels. China is facing the challenge of severe PM2.5 concentrations, especially in urban areas with a high population density. Understanding the key factors that influence PM2.5 concentrations is fundamental for the adoption of targeted measures. Therefore, this study used the Logarithmic Mean Divisia Index (LMDI) method to identify the key factors influencing PM2.5 concentrations in 236 cities in northeastern, western, central, and eastern China. The findings were as follows. The emission intensity (EI) played an important suppressing role on PM2.5 concentrations in all cities from 2011–2020. The energy intensity (EnI) inhibited PM2.5 concentrations in 157 cities; the economic output (EO) stimulated PM2.5 concentrations in some less economically developed regions; and population (P) spurred PM2.5 concentrations in135 cities, mainly concentrated in developed eastern cities. This study provides a whole picture of the key factors influencing PM2.5 concentrations in Chinese cities, and the findings can act as the scientific basis and guidance for Chinese city authorities in formulating policies toward PM2.5 concentration reduction.
Analysis of the Social and Economic Factors Influencing PM2.5 Emissions at the City Level in China
Han Huang (author) / Ping Jiang (author) / Yuanxiang Chen (author)
2023
Article (Journal)
Electronic Resource
Unknown
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