This research investigates the differences in AERMOD-predicted pollutant concentrations across input source types (AREAPOLY, VOLUME, LINE, RLINE, and RLINEXT without barriers). AERMOD (version 19191) microscale dispersion modeling is performed for the Atlanta I-75/I-575 Northwest Corridor (NWC) subarea in the U.S., including freeway corridors, managed lanes, connecting arterials, and intersections serving the NWC system. Modeling is performed for all link-receptor pairs, for each hour of the year, using the approved AERMET meteorological files (24 h × 365 days in 2019) from Georgia Environmental Protection Division (GA EPD), and emissions rates are estimated using MOVES-Matrix, based on predicted speed and volume by hour (output from ARC’s ABM2020 travel demand model). The AERMOD comparative analyses are performed for the same receptor sets, link-level volumes and speeds, and fleet compositions, across the five source types to generate comparative model results by input source type for the subarea. Results indicate concentrations from RLINEXT and RLINE were similar, with differences smaller than 0.05%, and their results were significantly higher than other source types. The results from AREAPOLY were similar to those from LINE (both smaller than RLINE and RLINEXT results). It is indicated that the results from VOLUME are systematically different from AREAPOLY and LINE for both downwind (much lower than AREAPOLY and LINE) and upwind (much higher than AREAPOLY and LINE) of the sources, and the sensitivity analysis indicates these predictions occur when wind speeds are low (less than approximately 2.5 m/s), which is because the enhanced wind meander approach employed with VOLUME is different from other source types.


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    Titel :

    Comparative Analysis of AERMOD-Predicted Pollutant Concentrations by Input Source Type in Atlanta, GA


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:
    Lu, Hongyu (Autor:in) / Liu, Haobing (Autor:in) / Kim, Daejin (Autor:in) / Xia, Tian (Autor:in) / Dai, Ziyi (Autor:in) / Reichard, William (Autor:in) / Zhao, Yingping (Autor:in) / Guin, Angshuman (Autor:in) / Rodgers, Michael O. (Autor:in) / Guensler, Randall (Autor:in)


    Erscheinungsdatum :

    2022-10-10




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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