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

Abstract

• Medium-heavy trucks and mini-light passenger vehicles are main NO x and VOC sources. • Passenger vehicles’ O 3 contributions are mainly concentrated in urban areas. • Trucks’ O 3 contributions are mainly concentrated in suburban areas. • Removing mini-light passenger vehicle emissions effectively reduces daytime O 3 . • Removing other vehicle emissions raises nocturnal O 3 but lowers afternoon levels. Beijing, with the highest number of motor vehicles in China, significantly contributes to O 3 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 O 3 levels is crucial for developing targeted strategies for O 3 pollution. This study applied the Community Multiscale Air Quality Modeling System (CMAQ) to comprehensively investigate the impacts of emissions from different vehicle types on O 3 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 O 3 (MDA8 O 3 ) concentration, ranked as the second largest contributor after regional transport. Contributions to O 3 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 O 3 concentration by 0.3–3.8 ppb. In contrast, removing MDPV emissions led to notable O 3 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 O 3 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 O 3 levels in Beijing and provides useful information for decision-makers to formulate effective measures of vehicle management in the future.

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