Application of an Improved Gas-constrained Source Apportionment Method Using Data Fused Fields: a Case Study in North...

Area of Science:

• Environmental Science
• Atmospheric Chemistry
• Air Quality Modeling

Background:

• Previous studies show varied links between PM2.5 components/sources and disease.
• Accurate source apportionment is crucial for understanding air pollution impacts.

Purpose of the Study:

• To develop spatiotemporal fields of PM2.5 components and source contributions.
• To quantify the impacts of ten distinct source categories on PM2.5 concentrations in North Carolina.

Main Methods:

• Fusing daily Community Multiscale Air Quality Modeling results with observational data.
• Utilizing a chemical mass balance source apportionment model (CMBGC-Iteration) with gas and particulate matter constraints.
• Generating spatiotemporal fields for gaseous pollutants, total PM2.5, and speciated PM2.5.

Main Results:

• Quantified contributions of ten source categories (e.g., vehicles, power plants, secondary components) to PM2.5.
• Observed a significant decrease in impacts from anthropogenic sources, particularly diesel vehicles and coal-fired power plants.
• Determined that secondary pollutant components constituted approximately 70% of the total PM2.5 mass.

Conclusions:

• The study successfully generated spatiotemporal fields of PM components and source impacts.
• This integrated modeling approach provides valuable data for air quality management and health studies.
• Findings highlight the significant role of secondary pollutants and the effectiveness of emission control strategies for anthropogenic sources.