Spatiotemporal Analysis of Complex Emission Dynamics in Port Areas Using High-Density Air Sensor Network.

Area of Science:

• Environmental Science
• Atmospheric Chemistry
• Urban Air Quality

Background:

• Cargo terminals are critical infrastructure but major sources of air pollution.
• Emissions from terminals exhibit complex spatial and temporal variations.
• Nitrogen oxides (NO and NO2) are key pollutants impacting air quality.

Purpose of the Study:

• To investigate the spatiotemporal distribution of NO and NO2 concentrations in Shanghai cargo terminals.
• To identify emission sources and quantify their contributions to total NO and NO2 levels.
• To provide data for targeted emission control strategies.

Main Methods:

• Deployment of a high-density air sensor network (17 sites) across four functional zones.
• High-resolution monitoring of NO and NO2 concentrations.
• Data validation against regulatory monitoring stations.
• Spatial analysis and baseline extraction using the lowest percentile method.

Main Results:

• NO and NO2 concentrations peaked at 06:00 h, potentially due to heavy-duty diesel truck regulations.
• Highest NO concentrations were observed in core operational areas and adjacent roads.
• Local emissions accounted for over 80% of NO and 32-70% of NO2 concentrations.

Conclusions:

• Local emissions are the dominant source of NO and a significant contributor to NO2 in cargo terminals.
• Understanding spatial heterogeneity is crucial for effective emission control.
• Findings support the development of targeted policies to mitigate air pollution from cargo terminals.