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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/acp-2020-1168
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2020-1168
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  17 Nov 2020

17 Nov 2020

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This preprint is currently under review for the journal ACP.

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 Zhang1, Xingpei Ye1, Shibao Wang1, Xiaojing He2, Lingyao Dong1, Ning Zhang1, Haikun Wang1, Zhongrui Wang1, Yun Ma1, Lei Wang1, Xuguang Chi1, Aijun Ding1, Mingzhi Yao3, Yunpeng Li3, Qilin Li3, Ling Zhang4, and Yongle Xiao4 Yanxu Zhang et al.
  • 1School of Atmospheric Sciences, Nanjing University, Nanjing, China
  • 2School of Environment, Nanjing University, Nanjing, China
  • 3Beijing SPC Environment Protection Tech Company Ltd., Beijing, China
  • 4Hebei Saihero Environmental Protection Hi-tech. Company Ltd., Shijiazhuang, Hebei, China

Abstract. Urban air pollution has tremendous spatial variability at scales ranged from kilometer to meters due to unevenly distributed emission sources, complex flow patterns, and photochemical reactions. However, high-resolution air quality information is not available through traditional approaches such as ground-based measurements and regional air quality models (with typical resolution >1 km). Here we develop a ten-meter resolution air quality model for traffic-related CO pollution based on the parallelized large-eddy simulation model (PALM). The model performance is evaluated with measurements obtained from sensors deployed on a taxi platform, which collects data with a comparable spatial resolution to our model. The very high resolution of the model reveals a detailed geographical dispersion pattern of air pollution in and out of the road network. The model results (0.92 ± 0.40 mg/m3) agree well with the measurements (0.90 ± 0.58 mg/m3, n = 114,502). The model has similar spatial patterns with that of the measurements, and the r2 value of a linear regression between model and measurement data is 0.50 ± 0.07 during non-rush hours with middle and low wind speeds. A non-linear relationship is found between average modeled concentrations and wind speed with higher concentrations under calm wind speeds. The modeled concentrations are also 20–30 % higher in streets that align with the wind direction within ~20°. We find that streets with higher buildings in the downwind have lower modeled concentrations at the pedestrian level, and similar effects are found for the variability in building heights (including gaps between buildings). The modeled concentrations also decay fast in the first ~50 m from the nearest highway and arterial road but change slower further away. This study demonstrates the potential of large eddy simulation in urban air quality modeling, which is a vigorous part of the smart city system and could inform urban planning and air quality management.

Yanxu Zhang et al.

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Yanxu Zhang et al.

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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 a megacity, Nanjing. The model reveals a detailed geographical dispersion pattern of air pollution in and out of the road network and agrees well with validation dataset. The model can be a vigorous part of the smart city system and inform urban planning and air quality management.
Urban air quality varies drastically at street scale but traditional methods are too coarse to...
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