气候变化领域集成服务门户(CCPortal): Investigating the impacts of driving restriction on NO2 concentration by integrating citywide scale cellular data and traffic simulation

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DOI	10.1016/j.atmosenv.2021.118721
	Investigating the impacts of driving restriction on NO2 concentration by integrating citywide scale cellular data and traffic simulation
	Tu Y.; Xu C.; Wang W.; Wang Y.; Jin K.
发表日期	2021
ISSN	1352-2310
卷号	265
英文摘要	Urban traffic is one of the main sources of NO2, and driving restriction (DR) has been widely used to alleviate air pollution in China, which means that private vehicles are not allowed to enter or pass a specific area according to their last digit of license plate numbers. This study investigates the impacts of DR on NO2 concentration at the traffic analysis zone (TAZ) level, which is particularly defined for traffic-related spatial data analysis. Measured NO2 data, citywide scale cellular data, and traffic-related data were collected for analysis. Inverse distance weighting (IDW) model was used to obtain NO2 at each TAZ. The traffic model of Nanjing was built in TranStar, a mesoscopic traffic simulation platform. Based on TAZ level NO2, traffic demand, and traffic status data, a geographically weighted regression (GWR) model was developed. DR with different proportions and spatial scales were simulated in TranStar and evaluated based on the predictions of the GWR model. Results suggest that morning rush hour is the only time in the day when urban traffic is the main cause of NO2's rise. Larger traffic volume and severer congestion with lower speed lead to the higher rise of NO2. The main factors influencing the rise of NO2 could be different at distinct locations. DR strategies can decrease the rise of NO2 significantly for most TAZs. Restriction proportion has significantly higher impacts than spatial scale, and the effects of scale enlarge with the rise of proportion. A side effect of DR is that the rise of NO2 would be higher in certain regions due to travelers' mode shift and detour, which is a key point for policymakers to weigh the pros and cons. © 2021 Elsevier Ltd
关键词	Cellular data Driving restriction NO2 concentration Traffic simulation
语种	英语
scopus关键词	License plates (automobile); Nitrogen oxides; Traffic congestion; Cellular data; Cellulars; Driving restrictions; Geographically Weighted Regression modelling; NO2 concentration; Spatial scale; Traffic analysis zones; Traffic simulations; Traffic-related; Urban traffic; Simulation platform; nitrogen dioxide; atmospheric pollution; concentration (composition); nitrogen oxides; pollution effect; simulation; spatial data; traffic emission; air pollutant; air quality; Article; boundary layer; car driving; concentration (parameter); controlled study; data analysis; driver licence; explanatory variable; geographically weighted regression; linear regression analysis; motor vehicle; simulation; solar radiation; traffic; velocity; China; Jiangsu; Nanjing [Jiangsu]
来源期刊	ATMOSPHERIC ENVIRONMENT
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/248219
作者单位	Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Southeast University, Si Pai Lou #2, Nanjing, 210096, China; Jiangsu Key Laboratory of Urban ITS Southeast University, Si Pai Lou #2, Nanjing, 210096, China; School of Transportation Southeast University, Si Pai Lou #2, Nanjing, 210096, China
推荐引用方式 GB/T 7714	Tu Y.,Xu C.,Wang W.,et al. Investigating the impacts of driving restriction on NO2 concentration by integrating citywide scale cellular data and traffic simulation[J],2021,265.
APA	Tu Y.,Xu C.,Wang W.,Wang Y.,&Jin K..(2021).Investigating the impacts of driving restriction on NO2 concentration by integrating citywide scale cellular data and traffic simulation.ATMOSPHERIC ENVIRONMENT,265.
MLA	Tu Y.,et al."Investigating the impacts of driving restriction on NO2 concentration by integrating citywide scale cellular data and traffic simulation".ATMOSPHERIC ENVIRONMENT 265(2021).