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The GIS-Based Approach for Optimal Design of Air Quality Monitoring Network for Management of Chemical Clusters

Published: 07 November 2017 Publication History

Abstract

An industrial district with chemical plants producing inside poses a great threat to the surrounding atmospheric environment and human health. Therefore, designing a proper and available air quality monitoring network (AQMN) is essential for assessing the effectiveness of deployed pollution controlling strategies and facilities in dealing with reducing pollutants in the planning stage of emergency management. Whereas monitoring facilities located at inappropriate sites would affect data validity. Thus, in this paper, a geospatial technique-Bayesian Maximum Entropy (BME) in conjunction with a multi-objective optimization model was utilized to optimize the design of an AQMN of gas sensors. Our developed atmospheric dispersion simulation system was employed to generate 'real' historical data for the above method and an experiment was implemented to illustrate the feasibility of the proposed approach. This work is expected to facilitate a decision-making process for determining an appropriate AQMN and assist the management work of environmental protection authorities.

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    cover image ACM Conferences
    EM-GIS '17: Proceedings of the 3rd ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management
    November 2017
    92 pages
    ISBN:9781450354936
    DOI:10.1145/3152465
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 07 November 2017

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    Author Tags

    1. Air quality monitoring network
    2. Atmospheric dispersion simulation system
    3. Bayesian maximum entropy
    4. Multi-objective optimization model

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