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<p>Quantifying the interplay between economic growth and atmospheric environment (EG-AE) is crucial for the transition of green economy in China. The Aerosol Optical Depth (AOD) variation under GDP growth index (AVGGI) is suggested to measure the air pollutant emissions per unit of economic growth, which a high AVGGI indicates a significant impact on atmospheric pollution during the process of economic growth, and vice versa. Geographically weighted regression (GWR) model is used to analyze the spatio-temporal patterns of EG-AE. The results show that: (1) Taking the <i>Hu line</i> as the boundary, AVGGI values present obvious spatio-temporal differences. High AVGGI values are mainly distributed in the Beijing-Tianjin-Hebei urban agglomeration and the Central Plains urban agglomeration. (2) The local R<sup>2</sup> shows a striped distribution in the east of the <i>Hu line</i>. There are two distinct symmetrical U-shapes in the region of R<sup>2</sup> &gt; 0.6. The local R<sup>2</sup> in the west is a low-value zone with poor correlation between GDP and AOD. (3) In 2007—2017, the trajectory of the barycenter shift of high-value, medium-value, and low-value zones in China’s EG-AE showed a trend of moving westward. China’s economic growth pattern has affected the dynamic change of atmospheric environment over the past decade. Therefore, policymakers should formulate urban economic growth patterns which helps reduce urban air pollution, to achieve green economy development.</p>

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Quantitation of the interplay between economic growth and atmospheric environment in China’s transition to green economy

  • 期刊论文

  • 发表日期：

    2025年6月2日

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  • Dan Zhang,
  • Ziwei Li,
  • Hao Hu,
  • Jiayuan Wu,
  • Chaohui Wu

摘要

Quantifying the interplay between economic growth and atmospheric environment (EG-AE) is crucial for the transition of green economy in China. The Aerosol Optical Depth (AOD) variation under GDP growth index (AVGGI) is suggested to measure the air pollutant emissions per unit of economic growth, which a high AVGGI indicates a significant impact on atmospheric pollution during the process of economic growth, and vice versa. Geographically weighted regression (GWR) model is used to analyze the spatio-temporal patterns of EG-AE. The results show that: (1) Taking the Hu line as the boundary, AVGGI values present obvious spatio-temporal differences. High AVGGI values are mainly distributed in the Beijing-Tianjin-Hebei urban agglomeration and the Central Plains urban agglomeration. (2) The local R2 shows a striped distribution in the east of the Hu line. There are two distinct symmetrical U-shapes in the region of R2 > 0.6. The local R2 in the west is a low-value zone with poor correlation between GDP and AOD. (3) In 2007—2017, the trajectory of the barycenter shift of high-value, medium-value, and low-value zones in China’s EG-AE showed a trend of moving westward. China’s economic growth pattern has affected the dynamic change of atmospheric environment over the past decade. Therefore, policymakers should formulate urban economic growth patterns which helps reduce urban air pollution, to achieve green economy development.