MOVES-Matrix and Distributed Computing for Microscale Line Source Dispersion Analysis

Liu, Haobing; Xu, Xiaodan; Rodgers, Michael O.; Xu, Yanzhi; Guensler, Randall; National Center for Sustainable Transportation (NCST); University of California, Davis, Institute of Transportation Studies; Georgia Institute of Technology

doi:10.1080/10962247.2017.1287788

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MOVES-Matrix and Distributed Computing for Microscale Line Source Dispersion Analysis

2017-04-17
By Liu, Haobing ; Xu, Xiaodan ; Rodgers, Michael O. ; ...

[PDF-1.03 MB]

English

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Creators:

Liu, Haobing ; Xu, Xiaodan ; Rodgers, Michael O. ; Xu, Yanzhi ; Guensler, Randall

Liu, Haobing ; Xu, Xiaodan ; Rodgers, Michael O. ; Xu, Yanzhi ; Guensler, Randall Less -
Corporate Creators:

National Center for Sustainable Transportation (NCST) ; University of California, Davis, Institute of Transportation Studies ; Georgia Institute of Technology

National Center for Sustainable Transportation (NCST) ; University of California, Davis, Institute of Transportation Studies ; Georgia Institute of Technology Less -
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology Less -
Subject/TRT Terms:

[+]

Data Analysis Data Collection Environmental Impacts Exhaust Gases Information Processing Meteorology
DOI:

https://doi.org/10.1080/10962247.2017.1287788
Resource Type:

Journal Article
Right Statement:

Open Access Select Journal:https://www.tandfonline.com/action/journalInformation?journalCode=uawm20
Geographical Coverage:

United States
Corporate Publisher:

Taylor & Francis
Abstract:

MOVES and AERMOD are the U.S. Environmental Protection Agency’s recommended models for use in project-level transportation conformity and hot-spot analysis. However, the structure and algorithms involved in running MOVES make analyses cumbersome and time-consuming. Likewise, the modeling setup process, including extensive data requirements and required input formats, in AERMOD lead to a high potential for analysis error in dispersion modeling.
Content Notes:

Open Access Select Journal. Citation: Haobing Liu, Xiaodan Xu, Michael O. Rodgers, Yanzhi “Ann” Xu & Randall L. Guensler (2017) MOVES-Matrix and distributed computing for microscale line source

dispersion analysis, Journal of the Air & Waste Management Association, 67:7, 763-775, DOI: https://doi.org/10.1080/10962247.2017.1287788
Format:

PDF
Funding:

DTRT13-G-UTC29
Collection(s):

University Transportation Centers
Main Document Checksum:

[+]

urn:sha256:c69fe7c7f7b34a67f3ccaa5863556c88eefa58d431eed79df5879d7aaace164c
Download URL:

https://rosap.ntl.bts.gov/view/dot/67087/dot_67087_DS1.pdf
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MOVES-Matrix and Distributed Computing for Microscale Line Source Dispersion Analysis

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