Source Apportionment of PM2.5 in New York City: Chemical Speciated Mass Concentration vs. Particle Number Concentration

Epidemiologic studies have amply demonstrated that exposure to elevated mass concentrations of airborne particulate matter pollution is associated with many adverse health effects. In U.S., air quality standards are regulated under the National Ambient Air Quality Standards (NAAQS), which set the limit values to be fulfilled across the U.S. for mass concentrations of both PM10 and PM2.5. However, recent population-based studies have reported that even exposure to low mass concentrations may increase acute and chronic effects and mortality. It is estimated that current (2009-2011) levels of PM2.5 still cause annually more than 2,000 deaths, 4,800 emergency department visits for asthma, and 1,500 hospitalizations for respiratory and cardiovascular disease in NYC. This study investigates the main sources of PM2.5 in NYC through the application of receptor models for two particulate metrics: mass concentration and particle number concentration (PNC). The most probable sources of PM2.5 mass concentration were identified and apportioned using the positive matrix factorization (PMF) model on chemically speciated samples analyzed for major inorganic ions, organic (OC) and elemental (EC) carbon and elements. The sources of PNC were investigated by applying PMF to hourly measurements of multiple variables including number concentrations resolved over six bins (20-30 nm, 30-50 nm, 50-70 nm, 70-100 nm, 100-200 nm, 200 nm to 2.5 μm), gaseous air pollutants and mass concentrations of PM2.5 and particulate sulfate, OC, and EC. Subsequently, post-processing methods were applied to help interpret the results including: (i) the comparison of sources identified with composition and particle number concentrations; (ii) relationships with weather parameters; (iii) the use of wind data through the polar analysis to detect the location of the most probable local sources, and (iv) the use of meteorology-based hybrid methods for extracting further information on the strength of potential external sources