Articles | Volume 22, issue 24
https://doi.org/10.5194/acp-22-15685-2022
https://doi.org/10.5194/acp-22-15685-2022
Research article
 | 
15 Dec 2022
Research article |  | 15 Dec 2022

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

Zhaofeng Lv, Zhenyu Luo, Fanyuan Deng, Xiaotong Wang, Junchao Zhao, Lucheng Xu, Tingkun He, Yingzhi Zhang, Huan Liu, and Kebin He

Viewed

Total article views: 3,312 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,545 705 62 3,312 165 45 52
  • HTML: 2,545
  • PDF: 705
  • XML: 62
  • Total: 3,312
  • Supplement: 165
  • BibTeX: 45
  • EndNote: 52
Views and downloads (calculated since 15 Jun 2022)
Cumulative views and downloads (calculated since 15 Jun 2022)

Viewed (geographical distribution)

Total article views: 3,312 (including HTML, PDF, and XML) Thereof 3,390 with geography defined and -78 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 23 Dec 2024
Download

The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.

Short summary
This study developed a hybrid model, CMAQ-RLINE_URBAN, to predict the urban NO2 concentrations at a high spatial resolution. To estimate the influence of various street canyons on the dispersion of air pollutants, a new parameterization scheme was established based on computational fluid dynamics and machine learning methods. This work created a new method to identify the characteristics of vehicle-related air pollution at both city and street scales simultaneously and accurately.
Altmetrics
Final-revised paper
Preprint