Comparison of Source Apportionment of PM2.5 Using PMF2 and EPA PMF Version 2

Hwang, In-Jo; Hopke, Philip K.

doi:10.5572/ajae.2011.5.2.086

Cited by 17 publications

(2 citation statements)

References 31 publications

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“…Zinc and Cu are prominent species in the combustion source factor and have been shown to be pronounced in vehicular emissions [ 64 ]. Incinerating activities located in the counties surrounding the sampling site [ 65 ] likely contributed to OC1, OC4, EC1, K, Pb, Si, and Zn [ 66 ].…”

Section: Resultsmentioning

confidence: 99%

Source Apportionment of Aerosol at a Coastal Site and Relationships with Precipitation Chemistry: A Case Study over the Southeast United States

et al. 2020

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This study focuses on the long-term aerosol and precipitation chemistry measurements from colocated monitoring sites in Southern Florida between 2013 and 2018. A positive matrix factorization (PMF) model identified six potential emission sources impacting the study area. The PMF model solution yielded the following source concentration profiles: (i) combustion; (ii) fresh sea salt; (iii) aged sea salt; (iv) secondary sulfate; (v) shipping emissions; and (vi) dust. Based on these results, concentration-weighted trajectory maps were developed to identify sources contributing to the PMF factors. Monthly mean precipitation pH values ranged from 4.98 to 5.58, being positively related to crustal species and negatively related to SO42−. Sea salt dominated wet deposition volume-weighted concentrations year-round without much variability in its mass fraction in contrast to stronger seasonal changes in PM2.5 composition where fresh sea salt was far less influential. The highest mean annual deposition fluxes were attributed to Cl−, NO3−, SO42−, and Na+ between April and October. Nitrate is strongly correlated with dust constituents (unlike sea salt) in precipitation samples, indicative of efficient partitioning to dust. Interrelationships between precipitation chemistry and aerosol species based on long-term surface data provide insight into aerosol–cloud–precipitation interactions.

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Section: Resultsmentioning

confidence: 99%

Source Apportionment of Aerosol at a Coastal Site and Relationships with Precipitation Chemistry: A Case Study over the Southeast United States

et al. 2020

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“…The FKEY matrix of integer values has the same dimension as F matrix, where F matrix is a p×m source profile matrix. The details are reported in previous studies (Hwang and Hopke, 2011;Zhao and Hopke, 2004). In this study, values of all elements in the FKEY matrix were set to zero, except for a value of 1 for OC in field burning source.…”

Section: Determination Of the Number Of Factorsmentioning

confidence: 99%

Source Identification and Estimation of Source Apportionment for Ambient PM10 in Seoul, Korea

Yi¹,

Hwang²

2014

Asian J. Atmos. Environ

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and were analyzed to provide source identification and apportionment. A total of 164 samples were collected and 21 species (15 inorganic species, 4 ionic species, OC, and EC) were analyzed by particle-induced x-ray emission, ion chromatography, and thermal optical transmittance methods. Positive matrix factorization (PMF) was used to develop source profiles and to estimate their mass contributions. The PMF modeling identified nine sources and the average mass was apportioned to secondary nitrate (9.3%), motor vehicle (16.6%), road salt (5.8%), industry (4.9%), airborne soil (17.2 %), aged sea salt (6.2%), field burning (6.0%), secondary sulfate (16.2%), and road dust (17.7%), respectively. The nonparametric regression (NPR) analysis was used to help identify local source in the vicinity of the sampling area. These results suggest the possible strategy to maintain and manage the ambient air quality of Seoul.

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