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Volume 16
Issue 7
10.3390/atmos16070883
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Unveiling PM2.5 Transport Pathways: A Trajectory-Channel Model Framework for Spatiotemporally Quantitative Source Apportionment

by
Yong Pan
1,2,3,4,
Jie Zheng
1,3,4,5,*,
Fangxin Fang
5,
Fanghui Liang
6,
Mengrong Yang
7,
Lei Tong
1,3,4 and
Hang Xiao
1,3,4,*
1
State Key Laboratory of Regional and Urban Ecology, Ningbo Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
2
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
3
Zhejiang Key Laboratory of Pollution Control for Port-Petrochemical Industry, Ningbo 315830, China
4
Ningbo Key Laboratory of Urban Environmental Pollution Control, CAS Haixi Industrial Technology Innovation Centre in Beilun, Ningbo 315830, China
5
Applied Modelling and Computation Group, Department of Earth Science and Engineering, Imperial College London, Prince Consort Road, London SW7 2AZ, UK
6
Beilun Branch of the Ningbo Municipal Bureau of Ecology and Environment, Ningbo 315800, China
7
Hunan Ecological Environment Monitoring Center, Key Laboratory of Heavy Metal Pollution Monitoring of State Environmental Protection, Changsha 410014, China
*
Authors to whom correspondence should be addressed.
Atmosphere 2025, 16(7), 883; https://doi.org/10.3390/atmos16070883
Submission received: 28 May 2025 / Revised: 9 July 2025 / Accepted: 17 July 2025 / Published: 18 July 2025
(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)
Review Reports Versions Notes

Abstract

In this study, we introduced a novel Trajectory-Channel Transport Model (TCTM) to unravel spatiotemporal dynamics of PM2.5 pollution. By integrating high-resolution simulations from the Weather Research and Forecasting (WRF) model with the Nested Air-Quality Prediction Modeling System (WRF-NAQPMS) and 72 h backward-trajectory analysis, TCTM enables the precise identification of source regions, the delineation of key transport corridors, and a quantitative assessment of regional contributions to receptor sites. Focusing on four Yangtze River Delta cities (Hangzhou, Shanghai, Nanjing, Hefei) during a January 2020 pollution event, the results demonstrate that TCTM’s Weighted Concentration Source (WCS) and Source Pollution Characteristic Index (SPCI) outperform traditional PSCF and CWT methods in source-attribution accuracy and resolution. Unlike receptor-based statistical approaches, TCTM reconstructs pollutant transport processes, quantifies spatial decay, and assigns contributions via physically interpretable metrics. This innovative framework offers actionable insights for targeted air-quality management strategies, highlighting its potential as a robust tool for pollution mitigation planning.
Keywords: WRF-NAQPMS; trajectory-channel transport model; TCTM; CWT; PSCF; air pollution WRF-NAQPMS; trajectory-channel transport model; TCTM; CWT; PSCF; air pollution

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MDPI and ACS Style

Pan, Y.; Zheng, J.; Fang, F.; Liang, F.; Yang, M.; Tong, L.; Xiao, H. Unveiling PM2.5 Transport Pathways: A Trajectory-Channel Model Framework for Spatiotemporally Quantitative Source Apportionment. Atmosphere 2025, 16, 883. https://doi.org/10.3390/atmos16070883

AMA Style

Pan Y, Zheng J, Fang F, Liang F, Yang M, Tong L, Xiao H. Unveiling PM2.5 Transport Pathways: A Trajectory-Channel Model Framework for Spatiotemporally Quantitative Source Apportionment. Atmosphere. 2025; 16(7):883. https://doi.org/10.3390/atmos16070883

Chicago/Turabian Style

Pan, Yong, Jie Zheng, Fangxin Fang, Fanghui Liang, Mengrong Yang, Lei Tong, and Hang Xiao. 2025. "Unveiling PM2.5 Transport Pathways: A Trajectory-Channel Model Framework for Spatiotemporally Quantitative Source Apportionment" Atmosphere 16, no. 7: 883. https://doi.org/10.3390/atmos16070883

APA Style

Pan, Y., Zheng, J., Fang, F., Liang, F., Yang, M., Tong, L., & Xiao, H. (2025). Unveiling PM2.5 Transport Pathways: A Trajectory-Channel Model Framework for Spatiotemporally Quantitative Source Apportionment. Atmosphere, 16(7), 883. https://doi.org/10.3390/atmos16070883

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