Assessing the Suitability of Multiple Dispersion and Land Use Regression Models for Urban Traffic-Related Ultrafine Particles

Details

• Alternative Title:
  Environ Sci Technol
• Personal Author:
  Patton, Allison P ; Milando, Chad ; Durant, John L ; Kumar, Prashant
• Description:
  Comparative evaluations are needed to assess the suitability of near-road air pollution models for traffic-related ultrafine particle number concentration (PNC). Our goal was to evaluate the ability of dispersion (CALINE4, AERMOD, R-LINE, and QUIC) and regression models to predict PNC in a residential neighborhood (Somerville) and an urban center (Chinatown) near highways in and near Boston, Massachusetts. PNC was measured in each area, and models were compared to each other and measurements for hot (>18 °C) and cold (<10 °C) hours with wind directions parallel to and perpendicular downwind from highways. In Somerville, correlation and error statistics were typically acceptable, and all models predicted concentration gradients extending ∼100 m from the highway. In contrast, in Chinatown, PNC trends differed among models, and predictions were poorly correlated with measurements likely due to effects of street canyons and nonhighway particle sources. Our results demonstrate the importance of selecting PNC models that align with study area characteristics (e.g., dominant sources and building geometry). We applied widely available models to typical urban study areas; therefore, our results should be generalizable to models of hourly averaged PNC in similar urban areas.
• Subjects:
  Air Pollutants Air Pollution Environmental Monitoring Models, Theoretical Particulate Matter Vehicle Emissions
• Source:
  Environ Sci Technol. 51(1):384-392
• Pubmed ID:
  27966909
• Pubmed Central ID:
  PMC5209293
• Document Type:
  Journal Article
• Funding:
  T42 OH008455/OH/NIOSH CDC HHSUnited States/ ; T32 ES019854/ES/NIEHS NIH HHSUnited States/ ; P30 ES005022/ES/NIEHS NIH HHSUnited States/ ; P30 ES017885/ES/NIEHS NIH HHSUnited States/ ; R01 ES015462/ES/NIEHS NIH HHSUnited States/
• Volume:
  51
• Issue:
  1
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:85c06c1ef32e06a5b921744be7266721e567bc97d788b05ab75398dac0503fd8
• Download URL:
  https://stacks.cdc.gov/view/cdc/43698/cdc_43698_DS1.pdf
• File Type:
  [PDF - 708.58 KB ]