Identifying optimal green plot ratio thresholds for mitigating PM_2.5 in street canyons: Integrating LiDAR, CFD, and...

Area of Science:

• Environmental Science
• Urban Planning
• Atmospheric Chemistry

Background:

• Particulate matter (PM2.5) in urban street canyons poses health risks.
• The influence of vegetation on PM2.5 dispersion is complex, involving aerodynamic and deposition processes.
• Quantifying these mechanisms at the street canyon scale is crucial for effective urban greening strategies.

Purpose of the Study:

• To investigate the interplay of vegetation aerodynamics and deposition on PM2.5 dispersion in an urban street canyon.
• To develop and validate a model for simulating PM2.5 distribution considering realistic urban geometry and traffic emissions.
• To identify optimal vegetation configurations for mitigating pedestrian-level PM2.5 concentrations.

Main Methods:

• Utilized LiDAR and YOLOv8 for 3D urban geometry and traffic flow analysis.
• Employed Computational Fluid Dynamics (CFD) to simulate PM2.5 dispersion and emissions.
• Validated the CFD model against field measurements (R² = 0.91).

Main Results:

• Dense vegetation can increase near-surface PM2.5 by reducing airflow.
• Low shrubs are more effective for near-surface deposition than trees at higher levels.
• Street canyon configurations with low hedges and optional central trees showed the best reduction in pedestrian-level PM2.5 (ARDC -2.49% to -0.34%).
• Green Plot Ratio (GPR) between 0.54-0.56 is an effective threshold for PM2.5 reduction.

Conclusions:

• Effective PM2.5 mitigation in street canyons requires balancing aerodynamic effects and deposition enhancement.
• Optimized vegetation configuration, particularly low hedges, can significantly reduce pedestrian-level PM2.5.
• Findings provide a quantitative basis for mechanism-informed urban greening design.