Michelle Snyder
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Michelle Snyder has a total of 12 co-authors. Here are the top co-authors by number of shared publications:
- Vlad Isakov
Atmospheric & Environmental Systems Modeling Division, Center for Environmental Measurement and Modeling, US. Environmental Protection Agency, Durham, NC, USA
3 shared publications - Brian Naess
Institute for the Environment, University of North Carolina at Chapel Hill, 123 W. Franklin St., Suite 330B, CB 1105, Chapel Hill, NC 27516, USA
2 shared publications - Kevin Talgo
Institute for the Environment, University of North Carolina at Chapel Hill, 100 Europa Drive, Suite 490, Chapel Hill, NC 27517, USA
2 shared publications - Mohammad Omary
Institute for the Environment, University of North Carolina at Chapel Hill, 100 Europa Drive, Suite 490, Chapel Hill, NC 27517, USA
2 shared publications - Neil Davis
Wind Energy Department, Technical University of Denmark, Roskilde, Denmark
2 shared publications - Rich Cook
U.S. Environmental Protection Agency, Office of Transportation and Air Quality, Assessment and Standards Division, Ann Arbor, Michigan, USA
2 shared publications
Latest Publications
- Open Access
- 9 December 2014
- Published by MDPI AG in International Journal of Environmental Research and Public Health
- Vol. 11 (12) , 12739-12766
Creating Locally-Resolved Mobile-Source Emissions Inputs for Air Quality Modeling in Support of an Exposure Study in Detroit, Michigan, USA
This work describes a methodology for modeling the impact of traffic-generated air pollutants in an urban area. This methodology presented here utilizes road network geometry, traffic volume, temporal allocation factors, fleet mixes, and emission factors to provide critical modeling inputs. These inputs, assembled from a variety of sources, are combined with meteorological inputs to generate link-based emissions for use in dispersion modeling to estimate pollutant concentration levels due to traffic. A case study implementing this methodology for a large health study is presented, including a sensitivity analysis of the modeling results reinforcing the importance of model inputs and identify those having greater relative impact, such as fleet mix. In addition, an example use of local measurements of fleet activity to supplement model inputs is described, and its impacts to the model outputs are discussed. We conclude that with detailed model inputs supported by local traffic measurements and meteorology, it is possible to capture the spatial and temporal patterns needed to accurately estimate exposure from traffic-related pollutants.
- 9 December 2014
- Published by MDPI AG in International Journal of Environmental Research and Public Health
- Vol. 11 (12) , 12739-12766
Open AccessCreating Locally-Resolved Mobile-Source Emissions Inputs for Air Quality Modeling in Support of an Exposure Study in Detroit, Michigan, USA
This work describes a methodology for modeling the impact of traffic-generated air pollutants in an urban area. This methodology presented here utilizes road network geometry, traffic volume, temporal allocation factors, fleet mixes, and emission factors to provide critical modeling inputs. These inputs, assembled from a variety of sources, are combined with meteorological inputs to generate link-based emissions for use in dispersion modeling to estimate pollutant concentration levels due to traffic. A case study implementing this methodology for a large health study is presented, including a sensitivity analysis of the modeling results reinforcing the importance of model inputs and identify those having greater relative impact, such as fleet mix. In addition, an example use of local measurements of fleet activity to supplement model inputs is described, and its impacts to the model outputs are discussed. We conclude that with detailed model inputs supported by local traffic measurements and meteorology, it is possible to capture the spatial and temporal patterns needed to accurately estimate exposure from traffic-related pollutants.
- 31 October 2013
- Published by Elsevier in Transportation Research Part D: Transport and Environment
- Vol. 24, 110-119
Modeling the impact of roadway emissions in light wind, stable and transition conditions
- 31 October 2013
- Published by Elsevier in Transportation Research Part D: Transport and Environment
- Vol. 24, 110-119
Modeling the impact of roadway emissions in light wind, stable and transition conditions