Hourly land-use regression models based on low-cost PM monitor data

Environmental Research

Volumn 167, Issue , 2018, Pages 7-14

  Masiol, Mauro ^a,b   Zíková, Naděžda ^b,c   Chalupa, David C ^a   Rich, David Q ^a   Ferro, Andrea R ^d   Hopke, Philip K ^a,b  

^a UNIVERSITY OF ROCHESTER MEDICAL CENTER   (United States)

^b CLARKSON UNIVERSITY   (United States)

^c Environmental Centre   (Czech Republic)

^d Clarkson University   (United States)

Author keywords

Exposure assessment; Land use regression; Low cost monitors; PM2.5

Indexed keywords

AIR QUALITY; ALGORITHM; ATMOSPHERIC POLLUTION; CALIBRATION; CONCENTRATION (COMPOSITION); COST; HEALTH IMPACT; INSTRUMENTATION; LAND USE; METROPOLITAN AREA; MONITORING; PARTICULATE MATTER; POLLUTION EXPOSURE; POLLUTION MONITORING; REGRESSION ANALYSIS;

AIR MONITORING; AIR POLLUTION; AIR QUALITY; AMBIENT AIR; ARTICLE; ENVIRONMENTAL EXPOSURE; HIGHWAY; HOUSING; LAND USE; LAND USE REGRESSION; METEOROLOGY; NEW YORK; PARTICULATE MATTER; PREDICTOR VARIABLE; PRIORITY JOURNAL; RAILWAY; TRAFFIC; AIR POLLUTANT; DEVICES; ENVIRONMENTAL MONITORING; PROCEDURES; SEASON; THEORETICAL MODEL;

AIR POLLUTANTS; AIR POLLUTION; ENVIRONMENTAL MONITORING; MODELS, THEORETICAL; PARTICULATE MATTER; SEASONS;

EID: 85049506830     PISSN: 00139351     EISSN: 10960953     Source Type: Journal    
DOI: 10.1016/j.envres.2018.06.052     Document Type: Article

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