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Health Promot Perspect. 2015;5(4): 269-279.
doi: 10.15171/hpp.2015.032
PMID: 26933646
PMCID: PMC4772797
  Abstract View: 1236
  PDF Download: 898

Original Research

Optimal Design of Air Quality Monitoring Network and its Application in an Oil Refinery Plant: An Approach to Keep Health Satus of Workers

Khaled ZoroufchiBenis 1, Esmaeil Fatehifar 1*, Javad Ahmadi 1, Alireza Rouhi 1

1 Environmental Engineering Research Center, Faculty of Chemical Engineering, Sahand University of Technology, Tabriz, Iran

Abstract

Background: Industrial air pollution is a growing challenge to humane health, especially in developing countries, where there is no systematic monitoring of air pollution. Given the importance of the availabil­ity of valid information on population exposure to air pollutants, it is important to design an optimal Air Quality Monitoring Network (AQMN) for assessing population exposure to air pollution and predicting the magnitude of the health risks to the population. 
Methods: A multi-pollutant method (implemented as a MATLAB program) was explored for configur­ing an AQMN to detect the highest level of pollution around an oil refinery plant. The method ranks potential monitoring sites (grids) according to their ability to represent the ambient concentra­tion. The term of cluster of contiguous grids that exceed a threshold value was used to calculate the Station Dosage. Selection of the best configuration of AQMN was done based on the ratio of a sta­tion’s dosage to the total dosage in the network. 
Results: Six monitoring stations were needed to detect the pollutants concentrations around the study area for estimating the level and distribution of exposure in the population with total network effi­ciency of about 99%. An analysis of the design procedure showed that wind regimes have greatest effect on the location of monitoring stations. 
Conclusion: The optimal AQMN enables authorities to implement an effective program of air quality management for protecting human health.
Keywords: Air Quality Monitoring Network, ISCST3 model, Multi-pollutant, Oil Refinery Plant
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Submitted: 18 Dec 2014
Accepted: 10 Nov 2015
ePublished: 30 Jan 2016
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