Spatiotemporal Characterization of Atmospheric Emissions from Heavy-Duty Diesel Trucks on Port-Connected Expressways in Shanghai

Heavy-duty diesel trucks (HDDTs) are recognized as significant sources of air pollutants and greenhouse gases (GHGs) along freight corridors in port cities. Despite their impact, few studies have provided detailed spatiotemporal insights into their emissions within port-adjacent highway systems. This study presents a high-resolution, hourly emission inventory at the road-segment level for six major expressways in Shanghai, one of China’s leading port cities. The emission estimates are derived using a locally adapted COPERT V model, calibrated with HDDT GPS trajectory data and detailed road network information from OpenStreetMap. The inventory quantifies emissions of CO2, NOx, CO, PM, and VOCs, highlighting distinct temporal and spatial variation patterns. Weekday emissions consistently exceed those of weekends, with three prominent traffic-related peaks occurring between 5:00–7:00, 10:00–12:00, and 14:00–16:00. Spatial analysis identifies the G1503 and S20 expressways as major emission corridors, with S20 exhibiting particularly high emission intensity relative to its length. Combined spatiotemporal patterns reveal that weekday emission hotspots are more concentrated, reflecting typical freight activity cycles such as morning dispatch and afternoon return. The findings provide a scientific basis for formulating more precise emission control measures targeting HDDT operations in urban port environments.

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Publication Details

Journal
Atmosphere
Published
2025-10-14
DOI
https://doi.org/10.3390/atmos16101183
Citations
1
Primary Topic
Vehicle emissions and performance
Type
article
Field-Weighted Citation Impact
0.68
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article

Spatiotemporal Characterization of Atmospheric Emissions from Heavy-Duty Diesel Trucks on Port-Connected Expressways in Shanghai

Siyu Pan, Qifeng Yu, Mingqiang Chen, Lingguang Wang et al.
1 citations
Atmosphere
Vehicle emissions and performance
0.68
article

Spatiotemporal Characterization of Atmospheric Emissions from Heavy-Duty Diesel Trucks on Port-Connected Expressways in Shanghai

Siyu Pan, Qifeng Yu, Mingqiang Chen, Lingguang Wang, Xiaohua Huang, Kun Qiu
article en
1 citations

Abstract

Heavy-duty diesel trucks (HDDTs) are recognized as significant sources of air pollutants and greenhouse gases (GHGs) along freight corridors in port cities. Despite their impact, few studies have provided detailed spatiotemporal insights into their emissions within port-adjacent highway systems. This study presents a high-resolution, hourly emission inventory at the road-segment level for six major expressways in Shanghai, one of China’s leading port cities. The emission estimates are derived using a locally adapted COPERT V model, calibrated with HDDT GPS trajectory data and detailed road network information from OpenStreetMap. The inventory quantifies emissions of CO2, NOx, CO, PM, and VOCs, highlighting distinct temporal and spatial variation patterns. Weekday emissions consistently exceed those of weekends, with three prominent traffic-related peaks occurring between 5:00–7:00, 10:00–12:00, and 14:00–16:00. Spatial analysis identifies the G1503 and S20 expressways as major emission corridors, with S20 exhibiting particularly high emission intensity relative to its length. Combined spatiotemporal patterns reveal that weekday emission hotspots are more concentrated, reflecting typical freight activity cycles such as morning dispatch and afternoon return. The findings provide a scientific basis for formulating more precise emission control measures targeting HDDT operations in urban port environments.

AtmosphereVol. 16(10)
Shanghai Maritime University (CN)
Openalex Percentile: Top 24%
Vehicle emissions and performance
0.68
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Spatiotemporal Characterization of Atmospheric Emissions from Heavy-Duty Diesel Trucks on Port-Connected Expressways in Shanghai — Siyu Pan, Qifeng Yu, et al. · Atmosphere (2025) | TGRS Research Map | TGRS