Impacts of different vehicle emissions on ozone levels in Beijing: Insights into source contributions and formation...

Beijing, with the highest number of motor vehicles in China, significantly contributes to O₃ pollution through substantial NO_x and VOC emissions in the on-road transportation sector. Understanding the unique impact of emissions from different vehicle types on O₃ levels is crucial for developing targeted strategies for O₃ pollution. This study applied the Community Multiscale Air Quality Modeling System (CMAQ) to comprehensively investigate the impacts of emissions from different vehicle types on O₃ levels in various regions of Beijing and to provide valuable insights into source contributions and formation processes. The results revealed that various vehicle types exhibited different spatial-temporal emission patterns, with medium-heavy duty trucks (HDT) and mini-light passenger vehicles (LDPV) identified as the primary contributors to NO_x (36.1 %) and VOC (57.6 %) emissions. Using the Integrated Source Apportionment Method (ISAM) coupled in CMAQ, we found the total vehicle emissions contributed to over 20 % of daily maximum 8-h average O₃ (MDA8 O₃) concentration, ranked as the second largest contributor after regional transport. Contributions to O₃ formation from LDPV and medium-large passenger vehicles (MDPV) were 2.6-4.0 and 4.2-6.8 ppb and mainly concentrated in urban areas, while the contributions from mini-light duty trucks (LDT) and HDT were 3.5-4.8 and 3.7-6.2 ppb and mainly concentrated in suburban areas. Through scenario analysis that removed emissions from specific types of vehicles, we found removing LDPV emissions led to decreases in daytime O₃ concentration by 0.3-3.8 ppb. In contrast, removing MDPV emissions led to notable O₃ increases by 4.0-11.8 ppb at rush hours. Removing LDT and HDT emissions resulted in 0.6-8.0 ppb increases in nocturnal O₃ concentrations while 0.8-2.0 ppb decreases during the afternoon. This research highlights the necessity of tailoring control strategies for different vehicle types to effectively reduce O₃ levels in Beijing and provides useful information for decision-makers to formulate effective measures of vehicle management in the future.