<p>Analyzing the spatial patterns of pollution sources, referring to the activities or sectors that release pollutants into the environment, is key to recognizing how environmental pressures develop and improving their management. Using hierarchical clustering analysis, we found that pollution sources in China’s Yangtze River Delta are mostly grouped within counties but vary significantly between them. In 2010, rapid urbanization and industrialization led to urban living activities causing major water pollution in 55.4% of counties, while industrial emissions were the primary contributors to air pollution in 59.3% of counties. By applying an enhanced emission factor method, we more accurately identified pollution patterns at a detailed grid level. We categorized the region into high, low, and zero pollution zones, covering 14.64%, 51.53%, and 33.82% of the area, with corresponding stress indices of 1.41, 0.24, and 0 in 2020. Under high-quality development scenarios in 2035, multiple linear programming model recommends allocating 47,600 km<sup>2</sup> for urban use, 145,800 km<sup>2</sup> for agriculture, and 165,700 km<sup>2</sup> for ecological conservation to meet environmental standards. To improve pollution management, we suggest a multi-level environmental governance framework that adjusts regulations based on pollution sources and specific control targets. Our findings are particularly significant for achieving simultaneous pollution reduction and carbon neutrality in urban agglomerations worldwide, especially in delta regions.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

How environmental stress will be spatially reconfigured under artificial sources and scale mismatch? A case in Yangtze River Delta, China

  • Yufan Chen,
  • Kan Zhou,
  • Yong Xu

摘要

Analyzing the spatial patterns of pollution sources, referring to the activities or sectors that release pollutants into the environment, is key to recognizing how environmental pressures develop and improving their management. Using hierarchical clustering analysis, we found that pollution sources in China’s Yangtze River Delta are mostly grouped within counties but vary significantly between them. In 2010, rapid urbanization and industrialization led to urban living activities causing major water pollution in 55.4% of counties, while industrial emissions were the primary contributors to air pollution in 59.3% of counties. By applying an enhanced emission factor method, we more accurately identified pollution patterns at a detailed grid level. We categorized the region into high, low, and zero pollution zones, covering 14.64%, 51.53%, and 33.82% of the area, with corresponding stress indices of 1.41, 0.24, and 0 in 2020. Under high-quality development scenarios in 2035, multiple linear programming model recommends allocating 47,600 km2 for urban use, 145,800 km2 for agriculture, and 165,700 km2 for ecological conservation to meet environmental standards. To improve pollution management, we suggest a multi-level environmental governance framework that adjusts regulations based on pollution sources and specific control targets. Our findings are particularly significant for achieving simultaneous pollution reduction and carbon neutrality in urban agglomerations worldwide, especially in delta regions.