Source identification of coarse particles in the Desert Southwest, USA using Positive Matrix Factorization

Abstract

The Desert Southwest Coarse Particulate Matter Study was undertaken to further our understanding of the spatial and temporal variability and sources of fine and coarse particulate matter (PM) in rural, arid, desert environments. Sampling was conducted between February 2009 and February 2010 in Pinal County, AZ near the town of Casa Grande where PM concentrations routinely exceed the U.S. National Ambient Air Quality Standards (NAAQS) for both PM 10 and PM 2.5. In this desert region, exceedances of the PM 10 NAAQS are dominated by high coarse particle concentrations, a common occurrence in this region of the United States. This work expands on previously published measurements of PM mass and chemistry by examining the sources of fine and coarse particles and the relative contribution of each to ambient PM mass concentrations using the positive matrix factorization receptor model (Clements et al., 2014). Coarse particles within the region were apportioned to nine sources including primary biological aerosol particles (PBAPs-25%), crustal material (20%), re-entrained road dust (11%), feedlot (11% at the site closest to a cattle feedlot), secondary particles (10%), boron-rich crustal material (9%), and transported soil (6%), with minor contributions from ammonium nitrate, and salt (considered to be NaCl). Fine particles within the region were apportioned to six sources including motor vehicles (37%), road dust (29%), lead-rich (10%), with minor contributions from brake wear, crustal material, and salt. These results can help guide local air pollution improvement strategies designed to reduce levels of PM to below the NAAQS.

Ambient bioaerosol distribution and associated health risks at a high traffic density junction at Dehradun city, India

“…Moreover, the coarse fraction (> 2.1 μm) dominated the bioaerosol size distribution (83.36% for fungi and 82.85% for bacteria). The abundance of coarse particles in the roadside soil dust have been reported by Ny and Lee (2010) and Clements et al (2017) which can also be attributed for the elevated concentration of coarse size bioaerosol in our study site. At Mussoorie,~30 km from Dehradun city, vehicular movement was reported as the major factor influencing the PM levels in the ambient air (Sundriyal et al 2018).…”

Probabilistic predictive principal component analysis for spatially misaligned and high‐dimensional air pollution data with missing observations

“…Highly positive scores are observed in the east and part of the Midwest, probably due to sulfur emissions from coal combustion (Hand, Schichtel, Pitchford, Malm, & Frank, ; Thurston, Ito, & Lall, ). Negative scores are observed in the west and southwest and have a classic resuspended soil profile (Clements et al, ; Thurston et al, ; Tong, Dan, Wang, & Lee, ). While the spatial distribution of PCA scores looks similar to other methods, loadings obtained by PCA applied to the complete set are fundamentally different than the rest, with much weaker positive weights on SO and S, and strongly negative weights on many additional elements, including Cr, Cu, Fe, Mn, Ni, and Zn.…”

Increase in domestic electricity consumption from particulate air pollution

“…The notable hourly variation in local PM pollution (such as in morning hours and late afternoon hours) in Arizona mostly comes from other sources such as motor vehicles and road dust, instead of from power plants, based on the study by Clements et al (ref. 52 ). As a result, the hourly change in building energy consumption will not alter local PM pollution in the Phoenix metropolitan area immediately.…”