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• W4384938749 endingPage "122223" @default.
• W4384938749 startingPage "122223" @default.
• W4384938749 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 ∼5.74 and ∼6.3 for Milby Park and Lynchburg, respectively) and humidity (∼4.87 and ∼4.71, respectively) were the most important variables for both sites. For the urban station, the most important emissions sources were n_decane (∼2.96), industrial emissions/evaporation (∼1.89), and ethylene/propylene/aromatics (∼1.57), while for the industrial site, they were oil and gas flaring/production (∼1.38), ethylene/propylene (∼1.26), and industrial emissions/evaporation (∼0.95). NOx had a negative impact on ozone production at the urban station due to the NOx-rich chemical regime, whereas NOx 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." @default.
• W4384938749 created "2023-07-22" @default.
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• W4384938749 date "2023-10-01" @default.
• W4384938749 modified "2023-09-27" @default.
• W4384938749 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" @default.
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• W4384938749 doi "https://doi.org/10.1016/j.envpol.2023.122223" @default.
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• W4384938749 hasPublicationYear "2023" @default.
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