2022
DOI: 10.1016/j.scitotenv.2022.156403
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Using wildland fire smoke modeling data in gerontological health research (California, 2007–2018)

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Cited by 5 publications
(3 citation statements)
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“…While the full model simulated the total PM 2.5 concentrations using all emission sources, the nonfire model toggled off wildland fire emissions to predict the nonfire PM 2.5 concentrations. Detailed descriptions of the CMAQ model are published elsewhere. , The model versions, emissions, and model configuration information on each model year in our study are presented in Table S1. In terms of the fire emission inventories, the models incorporated the BlueSky framework (v3.5.1) to represent both wildland and prescribed burning.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…While the full model simulated the total PM 2.5 concentrations using all emission sources, the nonfire model toggled off wildland fire emissions to predict the nonfire PM 2.5 concentrations. Detailed descriptions of the CMAQ model are published elsewhere. , The model versions, emissions, and model configuration information on each model year in our study are presented in Table S1. In terms of the fire emission inventories, the models incorporated the BlueSky framework (v3.5.1) to represent both wildland and prescribed burning.…”
Section: Methodsmentioning
confidence: 99%
“…Detailed descriptions of the CMAQ model are published elsewhere. 33,34 The model versions, emissions, and model configuration information on each model year in our study are presented in Table S1. In terms of the fire emission inventories, the models incorporated the BlueSky framework (v3.5.1) to represent both wildland and prescribed burning.…”
Section: ■ Introductionmentioning
confidence: 99%
“…A study within the Medicare population showed that PM 2.5 from smoke days was associated with asthma exacerbation and wheezing, and while both smoke and non-smoke PM 2.5 exposure was associated with increased hospitalization, asthma hospitalization was higher on smoke days [65]. In a model of wildfire exposures in California from 2007 to 2018, 56% (or 2.7 million) of California residents over 65 years old lived in counties representing the top three quartiles of wildfire PM 2.5 emissions [102]. Older adults are thus highly exposed, more susceptible to health effects, and may also be limited in their ability to evacuate wildfire-affected areas [103].…”
Section: Vulnerable Populationsmentioning
confidence: 99%