Preprints
https://doi.org/10.5194/acp-2022-371
https://doi.org/10.5194/acp-2022-371
 
15 Jun 2022
15 Jun 2022
Status: this preprint is currently under review for the journal ACP.

Development and application of a multi-scale modelling framework for urban high-resolution NO2 pollution mapping

Zhaofeng Lv1,, Zhenyu Luo1,, Fanyuan Deng1, Xiaotong Wang1, Junchao Zhao1, Lucheng Xu1, Tingkun He1, Huan Liu1, and Kebin He1 Zhaofeng Lv et al.
  • 1State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University, Beijing 100084, China
  • These authors contributed equally to this work.

Abstract. Vehicle emissions have become a major source of air pollution in urban areas, especially for near-road environments, where the pollution characteristics are difficult to be captured by a single-scale air quality model due to the complex composition of the underlying surface. Here we developed a hybrid model CMAQ-RLINE_URBAN to quantitatively analyse the effects of vehicle emissions on urban roadside NO2 concentrations at a high spatial resolution of 50 m × 50 m. To estimate the influence of various street canyons on the dispersion of air pollutants, a Machine Learning-based Street Canyon Flow (MLSCF) scheme was constructed based on Computational Fluid Dynamic and ensemble learning methods. The results indicated that compared with the CMAQ model, the hybrid model improved the underestimation of NO2 concentration at near-road sites with MB changing from -10 μg/m3 to 6.3 μg/m3. The MLSCF scheme obviously increased concentrations at upwind receptors within deep street canyons due to changes in the wind environment caused by the vortex. In summer, the relative contribution of vehicles to NO2 concentrations in Beijing urban areas was 39 % on average, similar to results from CMAQ-ISAM model, but increased significantly with the decreased distance to the road centerline, especially reaching 75 % on urban freeways.

Zhaofeng Lv et al.

Status: open (until 27 Jul 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Zhaofeng Lv et al.

Zhaofeng Lv et al.

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Short summary
This study developed a hybrid model to quantitatively analyze the effects of vehicle emissions on urban roadside NO2 concentrations at a high spatial resolution. The modelling results revealed the effects of street canyons on the inside wind environment and pollutant concentrations. In summer, the relative contribution of vehicles to NO2 concentrations in Beijing urban areas was 39 % on average, but increased significantly with the decreased distance to the road centerline (up to 75 %).
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