Next Article in Journal
Assessment of Foetal Exposure to the Homogeneous Magnetic Field Harmonic Spectrum Generated by Electricity Transmission and Distribution Networks
Next Article in Special Issue
Examining the Link Between Public Transit Use and Active Commuting
Previous Article in Journal
Carbamate Pesticide-Induced Apoptosis in Human T Lymphocytes
Article Menu

Export Article

Open AccessArticle
Int. J. Environ. Res. Public Health 2015, 12(4), 3646-3666; doi:10.3390/ijerph120403646

High Resolution Spatial and Temporal Mapping of Traffic-Related Air Pollutants

1
Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
2
Department of Civil Engineering, Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh 173234, India
3
Institute for Population Health, 1400 E. Woodbridge, Detroit, MI 48207, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Brian Caulfield
Received: 12 February 2015 / Revised: 16 March 2015 / Accepted: 23 March 2015 / Published: 1 April 2015
(This article belongs to the Special Issue Transport Impacts on Public Health)
View Full-Text   |   Download PDF [9305 KB, uploaded 1 April 2015]   |  

Abstract

Vehicle traffic is one of the most significant emission sources of air pollutants in urban areas. While the influence of mobile source emissions is felt throughout an urban area, concentrations from mobile emissions can be highest near major roadways. At present, information regarding the spatial and temporal patterns and the share of pollution attributable to traffic-related air pollutants is limited, in part due to concentrations that fall sharply with distance from roadways, as well as the few monitoring sites available in cities. This study uses a newly developed dispersion model (RLINE) and a spatially and temporally resolved emissions inventory to predict hourly PM2.5 and NOx concentrations across Detroit (MI, USA) at very high spatial resolution. Results for annual averages and high pollution days show contrasting patterns, the need for spatially resolved analyses, and the limitations of surrogate metrics like proximity or distance to roads. Data requirements, computational and modeling issues are discussed. High resolution pollutant data enable the identification of pollutant “hotspots”, “project-level” analyses of transportation options, development of exposure measures for epidemiology studies, delineation of vulnerable and susceptible populations, policy analyses examining risks and benefits of mitigation options, and the development of sustainability indicators integrating environmental, social, economic and health information. View Full-Text
Keywords: air pollution; dispersion models; human exposure; PM2.5; traffic air pollution; dispersion models; human exposure; PM2.5; traffic
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Batterman, S.; Ganguly, R.; Harbin, P. High Resolution Spatial and Temporal Mapping of Traffic-Related Air Pollutants. Int. J. Environ. Res. Public Health 2015, 12, 3646-3666.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Int. J. Environ. Res. Public Health EISSN 1660-4601 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top