A land use regression model for ambient ultrafine particles in Montreal, Canada: A comparison of linear regression and a machine learning approach

Environmental Research

Volumn 146, Issue , 2016, Pages 65-72

  Weichenthal, Scott ^a,b   Ryswyk, Keith Van ^a   Goldstein, Alon ^b   Bagg, Scott ^b   Shekkarizfard, Maryam ^b   Hatzopoulou, Marianne ^c  

^a HEALTH CANADA   (Canada)

^b MCGILL UNIVERSITY   (Canada)

^c UNIVERSITY OF TORONTO   (Canada)

Author keywords

Built environment; Land use regression; Traffic; Ultrafine particles

Indexed keywords

CARDIOLOGY; HEALTH IMPACT; LAND USE; MACHINE LEARNING; MORBIDITY; NITRIC OXIDE; NUMERICAL MODEL; POPULATION DENSITY; RAILWAY TRANSPORT; REGRESSION; REGRESSION ANALYSIS; ROAD TRAFFIC; SEASONAL VARIATION; SPATIAL VARIATION; TRAFFIC EMISSION; WIND VELOCITY;

AMBIENT AIR; AMBIENT ULTRAFINE PARTICLE; ARTICLE; CANADA; COMPARATIVE STUDY; ENVIRONMENTAL ASPECTS AND RELATED PHENOMENA; ENVIRONMENTAL MONITORING; ENVIRONMENTAL TEMPERATURE; HUMIDITY; LAND USE; LINEAR REGRESSION ANALYSIS; MACHINE LEARNING; POPULATION DENSITY; PRIORITY JOURNAL; SUMMER; WIND; WINTER; AIR POLLUTANT; ANALYSIS; PARTICLE SIZE; PARTICULATE MATTER; PROCEDURES; QUEBEC; REGRESSION ANALYSIS; SEASON; STATISTICAL MODEL;

CANADA; MONTREAL; QUEBEC [CANADA];

AIR POLLUTANT; PARTICULATE MATTER;

AIR POLLUTANTS; ENVIRONMENTAL MONITORING; LEAST-SQUARES ANALYSIS; LINEAR MODELS; MACHINE LEARNING; PARTICLE SIZE; PARTICULATE MATTER; QUEBEC; SEASONS;

EID: 84951084893     PISSN: 00139351     EISSN: 10960953     Source Type: Journal    
DOI: 10.1016/j.envres.2015.12.016     Document Type: Article

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