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Source Apportionment Using Positive Matrix Factorization (PMF) and PMF-trained Chemical Mass Balance with Gas Constraints (CMB-GC): A Case Study of 12 CSN Sites

Ola, Deepshikha
http://orcid.org/0000-0001-8447-2029
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1692273315072849

Abstract Details

2023, MS, University of Cincinnati, Engineering and Applied Science: Environmental Engineering.
Two commonly used receptor models, Positive Matrix Factorization (PMF) and Chemical Mass Balance with Gas Constraint (CMB-GC), are applied to PM2.5 speciation data at 12 Chemical Speciation Network (CSN) sites. Source apportionment results using the two receptor models are analyzed and compared. The PMF-generated factor profiles and contributions vary from site to site apportioning the local source variability. The major factors resolved include Biomass Burning, Secondary Nitrate, Secondary Sulfate, Industrial Mixture, and Dust. The CMB-GC source apportionment was carried out using nine source categories: Diesel Vehicles (DV), Gasoline Vehicles (GV), Dust (DUST), Biomass Burning (BURN), Coal Combustion (COAL), and Ammonium Sulfate, Ammonium Bisulfate, Ammonium Nitrate, and Secondary Organic Carbon (SOC). In comparison to PMF, the CMB-generated profiles obtained may not be locally representative. CMB-GC was conducted using measurement-based source profiles (MBSPs). To account for regional-specific emissions of biomass burning, PMF-based Biomass Burning factor as a proxy for regionally specific emissions. Both models are able to identify major sources at all sites, though the degree of agreements and correlations between source impacts estimated by PMF and CMB-GC varies depending on sources and receptor sites.
Simone Balachandran, Ph.D. (Committee Chair)
Jun Wang, Ph.D. (Committee Member)
Mingming Lu, Ph.D. (Committee Member)
116 p.
Environmental Engineering
Source Apportionment; Positive Matrix Factorization; Chemical Mass Balance with Gas Constraint; Biomass Burning; Factors

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Citations

  • Ola, D. (2023). Source Apportionment Using Positive Matrix Factorization (PMF) and PMF-trained Chemical Mass Balance with Gas Constraints (CMB-GC): A Case Study of 12 CSN Sites [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1692273315072849

    APA Style (7th edition)

  • Ola, Deepshikha. Source Apportionment Using Positive Matrix Factorization (PMF) and PMF-trained Chemical Mass Balance with Gas Constraints (CMB-GC): A Case Study of 12 CSN Sites. 2023. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1692273315072849.

    MLA Style (8th edition)

  • Ola, Deepshikha. "Source Apportionment Using Positive Matrix Factorization (PMF) and PMF-trained Chemical Mass Balance with Gas Constraints (CMB-GC): A Case Study of 12 CSN Sites." Master's thesis, University of Cincinnati, 2023. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1692273315072849

    Chicago Manual of Style (17th edition)

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This open access ETD is published by University of Cincinnati and OhioLINK.
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