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Environ Pollut

Title:		"A comprehensive approach combining positive matrix factorization modeling, meteorology, and machine learning for source apportionment of surface ozone precursors: Underlying factors contributing to ozone formation in Houston, Texas"
Author(s):		Nelson D; Choi Y; Sadeghi B; Yeganeh AK; Ghahremanloo M; Park J;
Address:		"Department of Earth and Atmospheric Science, University of Houston, Texas, USA. Department of Earth and Atmospheric Science, University of Houston, Texas, USA. Electronic address: ychoi6@uh.edu. Air Resources Laboratory, National Oceanic and Atmospheric Administration, College Park, MD, 20740, USA; Cooperative Institute for Satellite Earth System Studies, University of Maryland, College Park, MD, 20740, USA"
Journal Title:		Environ Pollut
Year:		2023
Volume:		20230720
Issue:
Page Number:		122223 -
DOI:		10.1016/j.envpol.2023.122223
ISSN/ISBN:		1873-6424 (Electronic) 0269-7491 (Linking)
Abstract:		"Ozone concentrations in Houston, Texas, are among the highest in the United States, posing significant risks to human health. This study aimed to evaluate the impact of various emissions sources and meteorological factors on ozone formation in Houston from 2017 to 2021 using a comprehensive PMF-SHAP approach. First, we distinguished the unique sources of VOCs in each area and identified differences in the local chemistry that affect ozone production. At the urban station, the primary sources were n_decane, biogenic/industrial/fuel evaporation, oil and gas flaring/production, industrial emissions/evaporation, and ethylene/propylene/aromatics. At the industrial site, the main sources were industrial emissions/evaporation, fuel evaporation, vehicle-related sources, oil and gas flaring/production, biogenic, aromatic, and ethylene and propylene. And then, we performed SHAP analysis to determine the importance and impact of each emissions factor and meteorological variables. Shortwave radiation (SHAP values are approximately 5.74 and approximately 6.3 for Milby Park and Lynchburg, respectively) and humidity ( approximately 4.87 and approximately 4.71, respectively) were the most important variables for both sites. For the urban station, the most important emissions sources were n_decane ( approximately 2.96), industrial emissions/evaporation ( approximately 1.89), and ethylene/propylene/aromatics ( approximately 1.57), while for the industrial site, they were oil and gas flaring/production ( approximately 1.38), ethylene/propylene ( approximately 1.26), and industrial emissions/evaporation ( approximately 0.95). NO(x) had a negative impact on ozone production at the urban station due to the NO(x)-rich chemical regime, whereas NO(x) had positive impacts at the industrial site. The study's findings suggest that the PMF-SHAP approach is efficient, inexpensive, and can be applied to other similar applications to identify factors contributing to ozone-exceedance events. The study's results can be used to develop more effective air quality management strategies for Houston and other cities with high levels of ozone"
Keywords:		Humans *Ozone/analysis *Air Pollutants/analysis Texas Meteorology Ethylenes/analysis Machine Learning Environmental Monitoring/methods *Volatile Organic Compounds/analysis China Vehicle Emissions/analysis Industrial Ozone Pmf Shap Source apportionment Urb;
Notes:		"MedlineNelson, Delaney Choi, Yunsoo Sadeghi, Bavand Yeganeh, Arash Kashfi Ghahremanloo, Masoud Park, Jincheol eng England 2023/07/23 Environ Pollut. 2023 Oct 1; 334:122223. doi: 10.1016/j.envpol.2023.122223. Epub 2023 Jul 20"