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Variation of spatio-temporal distribution of on-road vehicle emissions based on real-time RFID data

Journal of Environmental Sciences 2022年第6期34卷 151-162页

作者： Yonghong Liu Wenfeng Huang Xiaofang Lin Rui Xu Li Li Hui Ding School of Intelligent Systems Engineering Sun Yat-sen UniversityGuangzhou 510006China Guangdong Provincial Key Laboratory of Intelligent transportation System Guangzhou 510006China Guangdong Provincial Engineering Research Center for Traffic Environmental Monitoring and Control Guangzhou 510006China shantou municipal urban public transportation management office Shantou 515000China

High-resolution vehicular emissions inventories are important for managing vehicular pollution and improving urban air quality. This study developed a vehicular emission inventory with high spatio-temporal resolution in the main urban area of Chongqing, based on realtime traffic data from 820 RFID detectors covering 454 roads, and the differences in spatiotemporal emission characteristics between inner and outer districts were analysed. The result showed that the daily vehicular emission intensities of CO, hydrocarbons, PM2.5, PM10,and NO_(x) were 30.24, 3.83, 0.18, 0.20, and 8.65 kg/km per day, respectively, in the study area during 2018. The pollutants emission intensities in inner district were higher than those in outer district. Light passenger cars(LPCs) were the main contributors of all-day CO emissions in the inner and outer districts, from which the contributors of NO_(x) emissions were different. Diesel and natural gas buses were major contributors of daytime NO_(x) emissions in inner districts, accounting for 40.40%, but buses and heavy duty trucks(HDTs) were major contributors in outer districts. At nighttime, due to the lifting of truck restrictions and suspension of buses, HDTs become the main NO_(x) contributor in both inner and outer districts,and its three NO_(x) emission peak hours were found, which are different to the peak hours of total NO_(x) emission by all vehicles. Unlike most other cities, bridges and connecting channels are always emission hotspots due to long-time traffic congestion. This knowledge will help fully understand vehicular emissions characteristics and is useful for policymakers to design precise prevention and control measures.

关键词： Spatio-temporal distribution Link-level vehicular emission inventory Real-time RFID data HDTs Chongqing

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