[Vehicle Air Pollutant Emission Inventory and Characterization in Henan Province from 2016 to 2019]

Based on the collected urban motor vehicle activity ownership and traffic flow of highways, combined with the mileage and source profiles of VOCs, using the emission factor method, we established high-resolution emission inventories from 2016 to 2019 for urban and 2016-based highway motor vehicles, respectively, in Henan Province, China. The results showed that gasoline vehicles, particularly minibuses and ordinary motorcycles, were the main contributors of CO, VOCs, and NH₃, whereas heavy-duty and light-duty diesel trucks emitted SO₂, NO, and PM. Vehicles with China 1, China 3, and China 4 emission standards contributed significantly to pollutant emissions in the fleet. The temporal variation in traffic flow was consistent with the changes in freight and passenger traffic, with higher coefficients of variation for highways from August to October and the lowest in November. The weekly and daily changes in urban trunk roads showed distinct weekend effects and clear double-peak features, respectively. High-value emission areas were concentrated in urban centers with dense transport networks and high traffic volumes and on roads radiating outward from urban areas. The Lianhuo Expressway and the Beijing-Hong Kong-Macau Expressway were high-emission roads. Light-duty gasoline vehicles made the largest contribution to the ozone formation potential (OFP) of VOCs from motor vehicles. Five species, such as ethylene and propylene, contributed significantly to VOC emissions and OFP. The average annual growth rate of vehicle ownership from 2016 to 2019 was 5.7%. Compared with 2016, VOC emissions increased by 2.8% in 2019, whereas emissions of other pollutants showed decreasing trends of different degrees, with decreases of 76.3%, 51.7%, 50.3%, 43.1%, 16.7%, and 5.9% for SO₂, PM_2.5, PM₁₀, NH₃, CO, and NO, respectively. The emission reduction percentage of each pollutant in 2019 under the control policies relative to the baseline scenario ranged from 15.6% to 82.4%.