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<p>The emissions of exhaust gas and wastewater from non-ferrous metal enterprises (NMEs) pose a significant threat to surrounding agricultural land. Accurately assessing the long-term pollutant emissions from these enterprises and the associated relative risks to nearby agricultural areas present a substantial challenge. This study, based on multi-source data, focuses on the spatial distribution of NMEs in Gejiu City, China, from 1990 to 2020. It systematically analyzes the evolution patterns, pollutant emissions, and pollution extent over three decades, innovatively developing a grid-scale long-term risk assessment framework for agricultural land surrounding these enterprises. Key findings reveal that: (1) Multi-scale geographically weighted regression (MGWR) uncovered scale-dependent effects of driving factors, with metal mineral resource density being the dominant factor (mean coefficient: 0.5766), operating at a much broader spatial scale than secondary factors like topography and traffic. (2) Non-ferrous metal smelting enterprises, particularly Pb–Zn smelters, were the predominant emission sources, contributing to over 90% of the total heavy metal (HM) load. (3) The relative risk assessment identified intensely localized high-risk hotspots in townships with dense NMEs clusters, such as Shadian, Jijie, and Datun. The integrated relative risk from both pathways identified Jijie and Shadian as extreme-risk zones. Notably, atmospheric deposition contributed to a larger area of multi-HM relative risk than wastewater discharge, highlighting it as a priority control pathway. The methodological innovation of this study lies in the integration of dynamic enterprise emissions with grid-scale receptor vulnerability, providing a precise and actionable scientific basis for targeted environmental management and risk mitigation in industrial regions.</p>

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From emission to impact: a 30-year grid-scale tracing of heavy metal risk from non-ferrous metal enterprises to agricultural soil

  • 期刊论文

  • 发表日期：

    2026年5月12日

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  • Guanghui Guo,
  • Tienan Ju,
  • Mei Lei

摘要

The emissions of exhaust gas and wastewater from non-ferrous metal enterprises (NMEs) pose a significant threat to surrounding agricultural land. Accurately assessing the long-term pollutant emissions from these enterprises and the associated relative risks to nearby agricultural areas present a substantial challenge. This study, based on multi-source data, focuses on the spatial distribution of NMEs in Gejiu City, China, from 1990 to 2020. It systematically analyzes the evolution patterns, pollutant emissions, and pollution extent over three decades, innovatively developing a grid-scale long-term risk assessment framework for agricultural land surrounding these enterprises. Key findings reveal that: (1) Multi-scale geographically weighted regression (MGWR) uncovered scale-dependent effects of driving factors, with metal mineral resource density being the dominant factor (mean coefficient: 0.5766), operating at a much broader spatial scale than secondary factors like topography and traffic. (2) Non-ferrous metal smelting enterprises, particularly Pb–Zn smelters, were the predominant emission sources, contributing to over 90% of the total heavy metal (HM) load. (3) The relative risk assessment identified intensely localized high-risk hotspots in townships with dense NMEs clusters, such as Shadian, Jijie, and Datun. The integrated relative risk from both pathways identified Jijie and Shadian as extreme-risk zones. Notably, atmospheric deposition contributed to a larger area of multi-HM relative risk than wastewater discharge, highlighting it as a priority control pathway. The methodological innovation of this study lies in the integration of dynamic enterprise emissions with grid-scale receptor vulnerability, providing a precise and actionable scientific basis for targeted environmental management and risk mitigation in industrial regions.