Hourly land-use regression models based on low-cost PM monitor data
Jazyk angličtina Země Nizozemsko Médium print-electronic
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
30005199
DOI
10.1016/j.envres.2018.06.052
PII: S0013-9351(18)30357-8
Knihovny.cz E-zdroje
- Klíčová slova
- Exposure assessment, Land-use regression, Low-cost monitors, PM(2.5),
- MeSH
- látky znečišťující vzduch * MeSH
- monitorování životního prostředí * přístrojové vybavení metody MeSH
- pevné částice MeSH
- roční období MeSH
- teoretické modely MeSH
- znečištění ovzduší * MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- látky znečišťující vzduch * MeSH
- pevné částice MeSH
Land-use regression (LUR) models provide location and time specific estimates of exposure to air pollution and thereby improve the sensitivity of health effects models. However, they require pollutant concentrations at multiple locations along with land-use variables. Often, monitoring is performed over short durations using mobile monitoring with research-grade instruments. Low-cost PM monitors provide an alternative approach that increases the spatial and temporal resolution of the air quality data. LUR models were developed to predict hourly PM concentrations across a metropolitan area using PM concentrations measured simultaneously at multiple locations with low-cost monitors. Monitors were placed at 23 sites during the 2015/16 heating season. Monitors were externally calibrated using co-located measurements including a reference instrument (GRIMM particle spectrometer). LUR models for each hour of the day and weekdays/weekend days were developed using the deletion/substitution/addition algorithm. Coefficients of determination for hourly PM predictions ranged from 0.66 and 0.76 (average 0.7). The hourly-resolved LUR model results will be used in epidemiological studies to examine if and how quickly, increases in ambient PM concentrations trigger adverse health events by reducing the exposure misclassification that arises from using less time resolved exposure estimates.
Department of Civil and Environmental Engineering Clarkson University Potsdam NY USA
Department of Environmental Medicine University of Rochester Medical Center Rochester NY USA
Department of Public Health Sciences University of Rochester Medical Center Rochester NY USA
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