MOVES-Beijing-based high spatial and temporal resolution ammonia emissions from road traffic in Beijing. (1st July 2021) - Chen, Sha
Abstract: Ammonia (NH3 ) is an important precursor of PM2.5 (particulate matter with aerodynamic diameter below 2.5 μm). In recent years, ammonia emissions from road traffic notably increased, growing pollution of PM2.5 . Therefore, addressing spatial and temporal ammonia emissions from road traffic is a keyword for controlling urban traffic pollution. However, most of current China's ammonia emissions inventories are annual emissions, lack of spatial and temporal information, which is a gap for governments to make effective and practical policies in terms of controlling road traffic pollution. In this study, based on the built MOVES-Beijing Model, the ammonia emission factors of eight types of vehicle in Beijing, including passenger car (PC), TAXI, middle-duty vehicle (MDV), heavy-duty vehicle (HDV), light-duty truck (LDT), middle-duty gasoline truck (MDGT); middle-duty diesel truck (MDDT) and heavy-duty truck (HDT), were obtained. And through the modified local speed-flow model, the traffic flow was obtained acquisitively with the average speed data of the main roads in Beijing. The road length data were obtained according to the ranging function in the Gaode map and the status of Beijing. Then the high spatial and temporal ammonia emission inventory in Beijing was achieved. The results showed the order of ammonia emission factors (EFs) for different types of vehicles was MDGT > HDV > MDDT > HDT > LDT > TAXI > MDV > PC, and ammonia EFs were the lowest when the vehicle speed was around 48 km/h. Total ammonia emissions on weekdays were slightly higher than on weekends, but were not significant, although there are restrictions during the week. And ammonia emissions from ordinary roads were the highest among the three types of roads, including highways and urban expressways. Due to heavy traffic, ammonia emissions were highest during peak 1 periods. PC's ammonia emissions were 68% due to its larger population. Graphical abstract: Image 1 Highlights: MOVES-Beijing model was built for obtaining the ammonia emission factors The traffic flow was calculated by modified local speed-flow model High spatial and temporal resolution ammonia emission inventory was analyzed