Articles | Volume 21, issue 4
https://doi.org/10.5194/acp-21-2917-2021
https://doi.org/10.5194/acp-21-2917-2021
Research article
 | 
26 Feb 2021
Research article |  | 26 Feb 2021

Large-eddy simulation of traffic-related air pollution at a very high resolution in a mega-city: evaluation against mobile sensors and insights for influencing factors

Yanxu Zhang, Xingpei Ye, Shibao Wang, Xiaojing He, Lingyao Dong, Ning Zhang, Haikun Wang, Zhongrui Wang, Yun Ma, Lei Wang, Xuguang Chi, Aijun Ding, Mingzhi Yao, Yunpeng Li, Qilin Li, Ling Zhang, and Yongle Xiao

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Cited articles

Abou-Senna, H., Radwan, E., Westerlund, K., and Cooper, C. D.: Using a traffic simulation model (VISSIM) with an emissions model (MOVES) to predict emissions from vehicles on a limited-access highway, J. Air Waste Manag. Assoc., 63, 819–831, https://doi.org/10.1080/10962247.2013.795918, 2013. 
Apte, J. S., Messier, K. P., Gani, S., Brauer, M., Kirchstetter, T. W., Lunden, M. M., Marshall, J. D., Portier, C. J., Vermeulen, R. C. H., and Hamburg, S. P.: High-Resolution Air Pollution Mapping with Google Street View Cars: Exploiting Big Data, Environ. Sci. Technol., 51, 6999–7008, https://doi.org/10.1021/acs.est.7b00891, 2017. 
Biggart, M., Stocker, J., Doherty, R. M., Wild, O., Hollaway, M., Carruthers, D., Li, J., Zhang, Q., Wu, R., Kotthaus, S., Grimmond, S., Squires, F. A., Lee, J., and Shi, Z.: Street-scale air quality modelling for Beijing during a winter 2016 measurement campaign, Atmos. Chem. Phys., 20, 2755–2780, https://doi.org/10.5194/acp-20-2755-2020, 2020. 
Cécé, R., Bernard, D., Brioude, J., and Zahibo, N.: Microscale anthropogenic pollution modelling in a small tropical island during weak trade winds: Lagrangian particle dispersion simulations using real nested LES meteorological fields, Atmos. Environ., 139, 98–112, https://doi.org/10.1016/j.atmosenv.2016.05.028, 2016. 
Chen, C., Meng, D., and Sun, P.: Research on Change Characteristics of wind speed at mid-low altitude layer over China based on radiosonde wind speed data, J. Arid Meteorol., 36, 82–89, 2018. 
Short summary
Urban air quality varies drastically at street scale, but traditional methods are too coarse to resolve it. We develop a 10 m resolution air quality model and apply it for traffic-related carbon monoxide air quality in Nanjing megacity. The model reveals a detailed geographical dispersion pattern of air pollution in and out of the road network and agrees well with a validation dataset. The model can be a vigorous part of the smart city system and inform urban planning and air quality management.
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