Spatiotemporal Variations in Traffic Activity and Their Influence on Air Pollution Levels in Communities Near Highways

Details

• Personal Author:
  Adar SD ; Batterman S ; Filigrana P ; Levy JI ; Milando C ; Mukherjee B
• Description:
  Localized variations in traffic volume and speed can influence air pollutant emissions and corresponding concentrations in nearby communities, but most studies have utilized only aggregated traffic activity data. In this study, we compared the estimated influence of highway traffic activity on concentrations of primary oxides of nitrogen (NOx) and fine particulate matter (PM2.5) in communities near highways using a dispersion model informed by highly spatiotemporally-resolved variations of traffic volume and flow compared to the use of Annual Average Daily Traffic (AADT) data at a few locations. We used two sources of traffic activity data on 500 half-mile roadway segments on the five major highways in the Washington State Puget Sound during 2013. The first consisted of vehicle counts available every half-mile and 5 min; the second was traffic information (e.g., AADT) aggregated across the year and roadway network. Using the Motor Vehicle Emissions Simulator (MOVES) and the Research Line source dispersion model (RLINE), we modeled hourly concentrations of primary NOx and PM2.5 generated by highway traffic at nearly 4000 residences within 1 km of major highways. These concentrations were aggregated to daily and annual average concentrations, which were compared by input data source. At most locations, concentrations of primary NOx and PM2.5 modeled using the resolved traffic data had similar spatial and temporal distributions to concentrations predicted using the AADT data. However, several areas showed large differences. For example, 25% of residences within 150 m of a highway had concentrations that differed by more than 19% (8 ppb) for NOx and 32% (0.7 µg/m3) for PM2.5, and the AADT data consistently predicted lower concentrations than the resolved traffic data. Our findings indicate that temporal and spatial variation in traffic patterns can result in complex spatiotemporal variations of air pollutant concentrations that can be captured with the use of dispersion modeling with the appropriate inputs. The use of spatiotemporally resolved traffic activity data can improve exposure estimates and help reduce exposure measurement error in epidemiological studies, especially in communities near highly congested highways. [Description provided by NIOSH]
• Subjects:
  Air Pollution Automobiles Community Health Services Occupational Health Particulate Matter Safety
• Keywords:
  Air Pollution Author Keywords: Traffic-generated Air Pollution Community Health Dispersion Model Emission Sources Environmental Health Exposure Assessment Motor Vehicles Nitrogen Oxides Particle Aerodynamics Particulates RLINE Vehicle Emissions

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• ISSN:
  1352-2310
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  Massachusetts ; Michigan ; OSHA Region 1 ; OSHA Region 5
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  242
• NIOSHTIC Number:
  nn:20070892
• Citation:
  Atmos Environ 2020 Dec; 242:117758
• Contact Point Address:
  Paola Filigrana, Department of Epidemiology, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109-2029, USA
• Email:
  filigranapaola@gmail.com
• Federal Fiscal Year:
  2021
• Performing Organization:
  University of Michigan, Ann Arbor
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  Atmospheric Environment
• End Date:
  20280630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:20cd140afb59cbe4f2f07c958ef2e0147bceba7cc846ee7c3963d82e893e0780c01fb35c2fe207113bced0b09a7b39916add9e980ef18b22606d6ff76350cafd
• Download URL:
  https://stacks.cdc.gov/view/cdc/209016/cdc_209016_DS1.pdf
• File Type:
  [PDF - 10.15 MB ]