Accurately identifying the sources of fine particulate matter (PM_2.5) pollution is crucial for pollution control and public health protection. Taking the PM_2.5 pollution event that occurred in Suzhou in June 2023 as a typical case, this study analyzed the characteristics and components of PM_2.5, and quantified the contributions of meteorological conditions, regional transport, and local emissions to the summertime PM_2.5 surge in a typical Yangtze River Delta (YRD) city. Chemical composition analysis highlighted a sharp increase in nitrate ions (NO₃⁻, contributing up to 49% during peak pollution), with calcium ion (Ca²⁺) and sulfate ion (SO₄²⁻) concentrations rising to 2 times and 7.5 times those of clean periods, respectively. Results from the random forest model demonstrated that emission sources (74%) dominated this pollution episode, significantly surpassing the meteorological contribution (26%). The Weather Research and Forecasting model combined with the Community Multiscale Air Quality model (WRF–CMAQ) further revealed that local emissions contributed the most to PM_2.5 concentrations in Suzhou (46.3%), while external transport primarily originated from upwind cities such as Shanghai and Jiaxing. The findings indicate synergistic effects from dust sources, industrial emissions, and mobile sources. Validation using electricity consumption and key enterprise emission data confirmed that intensive local industrial activities exacerbated PM_2.5 accumulation. Recommendations include strengthening regulations on local industrial and mobile source emissions, and enhancing regional joint prevention and control mechanisms to mitigate cross-boundary transport impacts.

Ozone pollution in densely populated urban regions poses a great threat to public health, due to the intensive anthropogenic emissions of ozone precursors and is further aggravated by global warming and the urban heat island phenomenon. Air quality models have been utilized to formulate and evaluate air pollution control strategies. This study presents a comprehensive modeling assessment of ozone mitigation strategies during an ozone pollution episode in Changzhou, an industrial city in the Yangtze River Delta region. Utilizing the Community Multiscale Air Quality Modeling System (CMAQ), we quantified the contribution of ozone from different emission sectors and counties within Changzhou using the integrated source apportionment method (ISAM). During the pollution period, local emissions within Changzhou account for an average of 41.5% of MDA8 ozone, with particularly notable contributions from Jingkai (11.2%), Wujin (9.5%), and Liyang (7.8%). Upon these findings, we evaluated three sets of emission reduction scenarios: uniform, sector-specific, and county-specific reductions. Results show that industry and transportation are responsible for over 20% of ozone concentrations, and targeted reductions in these sources yielded the most significant decreases in ozone levels. Notably, reducing industrial emissions alone decreased ozone concentrations by 3.2 μg m⁻³ during the pollution episode. County-specific reductions revealed the importance of targeted strategies, with certain counties showing more pronounced responses to emission controls. On a daily basis, emission reductions in Xinbei contributed to a maximum ozone decrease of 4.4 μg m⁻³. This study provides valuable insights into the efficacy of different mitigation measures in Changzhou and offers a practical and useful framework for policymakers to implement strategies while addressing the complexities of urban air quality management.