Spatial variation in inversion-focused vs 24-h integrated samples of PM2.5 and black carbon across Pittsburgh, PA

Autor: Courtney Roper, Leah Cambal, Ellen Kinnee, Jessie L.C. Shmool, Sheila Tripathy, Lauren Chubb, Jane E. Clougherty, Drew R. Michanowicz, Sara Gillooly, Brett Tunno
Rok vydání: 2015
Předmět:
Pollution
Geographic information system
Meteorology
Epidemiology
media_common.quotation_subject
Air pollution
Terrain
010501 environmental sciences
030501 epidemiology
Toxicology
medicine.disease_cause
01 natural sciences
Time
03 medical and health sciences
Soot
Air Pollution
Environmental monitoring
medicine
black carbon (BC)
Humans
Cities
Particle Size
inversion-focused sampling
Weather
24-h integrated sampling
0105 earth and related environmental sciences
media_common
land use regression (LUR)
Air Pollutants
Spatial Analysis
business.industry
Public Health
Environmental and Occupational Health
Sampling (statistics)
Inversion (meteorology)
fine particulate matter (PM2.5)
Models
Theoretical
Pennsylvania
Geographic Information Systems
Environmental science
Original Article
Particulate Matter
Spatial variability
Physical geography
0305 other medical science
business
Environmental Monitoring
Zdroj: Journal of Exposure Science & Environmental Epidemiology
ISSN: 1559-064X
1559-0631
Popis: A growing literature explores intra-urban variation in pollution concentrations. Few studies, however, have examined spatial variation during "peak" hours of the day (e.g., rush hours, inversion conditions), which may have strong bearing for source identification and epidemiological analyses. We aimed to capture "peak" spatial variation across a region of complex terrain, legacy industry, and frequent atmospheric inversions. We hypothesized stronger spatial contrast in concentrations during hours prone to atmospheric inversions and heavy traffic, and designed a 2-year monitoring campaign to capture spatial variation in fine particles (PM2.5) and black carbon (BC). Inversion-focused integrated monitoring (0600-1100 hours) was performed during year 1 (2011-2012) and compared with 1-week 24-h integrated results from year 2 (2012-2013). To allocate sampling sites, we explored spatial distributions in key sources (i.e., traffic, industry) and potential modifiers (i.e., elevation) in geographic information systems (GIS), and allocated 37 sites for spatial and source variability across the metropolitan domain (~388 km(2)). Land use regression (LUR) models were developed and compared by pollutant, season, and sampling method. As expected, we found stronger spatial contrasts in PM2.5 and BC using inversion-focused sampling, suggesting greater differences in peak exposures across urban areas than is captured by most integrated saturation campaigns. Temporal variability, commercial and industrial land use, PM2.5 emissions, and elevation were significant predictors, but did not more strongly predict concentrations during peak hours.
Databáze: OpenAIRE
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