Land Use Regression Models of On-Road Particulate Air Pollution (Particle Number, Black Carbon, PM2.5, Particle Size) Using Mobile Monitoring

Environmental Science and Technology

Volumn 49, Issue 15, 2015, Pages 9194-9202

  Hankey, Steve ^a   Marshall, Julian D ^b  

^a VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY   (United States)

^b University of Minnesota   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COST EFFECTIVENESS; LAND USE; MOTOR TRANSPORTATION; PARTICLES (PARTICULATE MATTER); POLLUTION; REGRESSION ANALYSIS; ROADS AND STREETS; TRAFFIC CONGESTION;

FINE PARTICULATE MATTER; LAND-USE REGRESSION MODELS; MOBILE MEASUREMENTS; PARTICLE CONCENTRATIONS; PARTICULATE AIR POLLUTION; SPATIAL AND TEMPORAL SMOOTHING; SPATIAL AUTOCORRELATIONS; SPATIO-TEMPORAL RESOLUTION;

PARTICLE SIZE;

BLACK CARBON; PARTICULATE MATTER; SOOT;

ATMOSPHERIC MODELING; ATMOSPHERIC POLLUTION; BLACK CARBON; CONCENTRATION (COMPOSITION); COST-BENEFIT ANALYSIS; DATA SET; ENVIRONMENTAL MONITORING; LAND USE CHANGE; PARTICLE SIZE; PARTICULATE MATTER; POLLUTANT SOURCE; SPATIOTEMPORAL ANALYSIS; TIME SERIES ANALYSIS;

AIR MONITORING; AIR POLLUTION; ARTICLE; BICYCLE; COST EFFECTIVENESS ANALYSIS; DENSITY GRADIENT; ENVIRONMENTAL PARAMETERS; EXHAUST GAS; HUMAN; LAND USE REGRESSION MODEL; MEASUREMENT ACCURACY; PARTICLE SIZE; PARTICULATE MATTER; POPULATION DYNAMICS; PREDICTOR VARIABLE; RAILWAY; REGRESSION ANALYSIS; SPATIOTEMPORAL ANALYSIS; TIME SERIES ANALYSIS; ANALYSIS; ENVIRONMENTAL MONITORING; MINNESOTA; MOTION; PROCEDURES; REPRODUCIBILITY; SOOT; THEORETICAL MODEL; TIME FACTOR;

MINNEAPOLIS; MINNESOTA; UNITED STATES;

AIR POLLUTION; ENVIRONMENTAL MONITORING; MINNESOTA; MODELS, THEORETICAL; MOTION; PARTICLE SIZE; PARTICULATE MATTER; REGRESSION ANALYSIS; REPRODUCIBILITY OF RESULTS; SOOT; TIME FACTORS;

EID: 84938563901     PISSN: 0013936X     EISSN: 15205851     Source Type: Journal    
DOI: 10.1021/acs.est.5b01209     Document Type: Article

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