In China, the intensive supervision mechanism (ISM) has been implemented to combat air pollution, yet its effectiveness remains under debate. This study systematically evaluated the effectiveness of the ISM using a multisource data set integrating the CHAP data set, meteorological factors, and ISM data, with the iron and steel industry as a case study. The results indicated that the number of issues identified and the number of enterprises involved from 2018 to 2024 exhibited spatiotemporal heterogeneity. The environmental issues identified by ISM data across different processes were grouped into three main categories: automatic monitoring of pollution sources and data management, pollutant emission control and compliance, and fugitive dust and particulate matter control. Linear regression model revealed that ISM contributed to air quality improvements, influenced by baseline pollutant concentrations, meteorological factors, and the implementation intensity of the ISM. Provincial-level spatial autocorrelation indicated positive clustering between ISM implementation intensity and reductions in pollutant concentrations, particularly in Hebei, Henan, Shanxi, and Shandong Provinces. Enterprise-level evaluation revealed that even in regions with overall strong performance, significant heterogeneity existed among individual enterprises, highlighting the need for refined enterprise-level assessment and differentiated management. These findings underscored ISM's tangible effectiveness and provided empirical support for its long-term optimization.
Xu et al. (Tue,) studied this question.
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