Vehicle emissions have become a significant contributor to urban air pollution. However, studies specific to city-level vehicle emission inventories are still scarce and tend to be outdated. This study introduces a methodology for developing high-resolution monthly vehicle emission inventories. We applied this methodology to Changzhou in 2022 to analyze emission characteristics and generate gridded emission data with a resolution of 0.01° × 0.01°. The results show that the total vehicle emissions of carbon monoxide (CO), volatile organic compounds (VOCs), nitrogen oxides (NO_x), and fine particulate matters (PM_2.5) in Changzhou are 39.69, 8.68, 18.6, and 0.56 Gg, respectively. Light-duty passenger vehicles are the main contributors to CO (74.3%) and VOCs (86.1%) emissions, while heavy-duty trucks play a significant role in NO_x (50.7%) and PM_2.5 (34.7%) emissions. Gasoline vehicles are mainly responsible for CO (78.6%) and VOCs (91.4%) emissions, while diesel vehicles are the primary source of NO_x (81.1%) and PM_2.5 (70.6%) emissions. Notably, China IV vehicles have the highest emission contribution rates (ranging from 32.5% to 44.9%). Seasonally, emissions peak in winter and are lowest in April. Spatially, emission intensity is higher in the northeast of Changzhou compared to the west and south. The methodology presented in this study offers a valuable tool for developing comprehensive city-level emission inventories, and the results provide critical insights that can inform the formulation of effective environmental policies.

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.