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    Dust Emissions Management Model for Construction Sites

    Source: Journal of Construction Engineering and Management:;2021:;Volume ( 147 ):;issue: 008::page 04021092-1
    Author:
    Denis Clement
    ,
    Amir A. Aliabadi
    ,
    Jennifer Mackey
    ,
    Jesse Thé
    ,
    Bahram Gharabaghi
    DOI: 10.1061/(ASCE)CO.1943-7862.0002121
    Publisher: ASCE
    Abstract: Fugitive dust emissions from active construction sites, without wind erosion and dust suppression controls, can be orders of magnitude higher than predevelopment background values. As the exact location, size, and timing of construction activities within a region are difficult to forecast, a new probabilistic dust emission management tool is proposed to understand better and control the factors influencing dust emissions on construction sites. The proposed construction-induced dust emission management (CIDEM) probabilistic model incorporates both the spatial and temporal variation of construction activities. A characterization of the construction phases provides the basis for more accurate dust emission calculations allowing cost-savings in the selection/sizing of the wind erosion and dust suppression control measures commonly used on construction sites, including watering, mulching, chemical dust suppressants, and revegetation. A best management practices (BMPs) cost-optimization is performed using a genetic algorithm to consider multiple nonlinear influencing factors. The benefits of this new CIDEM methodology were demonstrated on its application on the Lake Simcoe region, in Canada, including generating possible management policy statements based on dust emission risk assessment for issuing building permits for different site conditions.
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      Dust Emissions Management Model for Construction Sites

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4271967
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    contributor authorDenis Clement
    contributor authorAmir A. Aliabadi
    contributor authorJennifer Mackey
    contributor authorJesse Thé
    contributor authorBahram Gharabaghi
    date accessioned2022-02-01T21:45:15Z
    date available2022-02-01T21:45:15Z
    date issued8/1/2021
    identifier other%28ASCE%29CO.1943-7862.0002121.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4271967
    description abstractFugitive dust emissions from active construction sites, without wind erosion and dust suppression controls, can be orders of magnitude higher than predevelopment background values. As the exact location, size, and timing of construction activities within a region are difficult to forecast, a new probabilistic dust emission management tool is proposed to understand better and control the factors influencing dust emissions on construction sites. The proposed construction-induced dust emission management (CIDEM) probabilistic model incorporates both the spatial and temporal variation of construction activities. A characterization of the construction phases provides the basis for more accurate dust emission calculations allowing cost-savings in the selection/sizing of the wind erosion and dust suppression control measures commonly used on construction sites, including watering, mulching, chemical dust suppressants, and revegetation. A best management practices (BMPs) cost-optimization is performed using a genetic algorithm to consider multiple nonlinear influencing factors. The benefits of this new CIDEM methodology were demonstrated on its application on the Lake Simcoe region, in Canada, including generating possible management policy statements based on dust emission risk assessment for issuing building permits for different site conditions.
    publisherASCE
    titleDust Emissions Management Model for Construction Sites
    typeJournal Paper
    journal volume147
    journal issue8
    journal titleJournal of Construction Engineering and Management
    identifier doi10.1061/(ASCE)CO.1943-7862.0002121
    journal fristpage04021092-1
    journal lastpage04021092-8
    page8
    treeJournal of Construction Engineering and Management:;2021:;Volume ( 147 ):;issue: 008
    contenttypeFulltext
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