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

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.

[1]  T. Husain,et al.  Design of Urban Air Quality Monitoring Network: Fuzzy Based Multi-Criteria Decision Making Approach , 2011 .

[2]  Andreas Kerschbaumer,et al.  The development of a dense urban air pollution monitoring network , 2015 .

[3]  Sumit Sharma,et al.  Simulation of Air Quality using an ISCST3 Dispersion Model , 2008 .

[4]  A. Abdelrasoul,et al.  Oil Refineries Emissions Impact on Urban Localities Using AERMOD , 2010 .

[5]  Kh. Zoroufchi Benis,et al.  Optimal design of air quality monitoring network around an oil refinery plant: a holistic approach , 2015, International Journal of Environmental Science and Technology.

[6]  Sabah A. Abdul-Wahab,et al.  The role of meteorology on predicting SO2 concentrations around a refinery: A case study from Oman , 2006 .

[7]  A. Elkamel,et al.  Modelling of greenhouse gas emissions from the steady state and non-steady state operations of a combined cycle power plant located in Ontario, Canada , 2014 .

[8]  S. Abdul-Wahab.  Evaluation of the Industrial Source Complex Short-Term Model: Dispersion over Terrain , 2004, Journal of the Air & Waste Management Association.

[9]  A. Senatore,et al.  Project of an air quality monitoring network for industrial site in Italy , 2000 .

[10]  Paul Quincey,et al.  New Directions: The future of European urban air quality monitoring , 2014 .

[11]  Ching-Ho Chen,et al.  Development of a multiple objective planning theory and system for sustainable air quality monitoring networks. , 2006, The Science of the total environment.

[12]  M S Al-Rashidi,et al.  A heuristic optimization approach for Air Quality Monitoring Network design with the simultaneous consideration of multiple pollutants. , 2008, Journal of environmental management.

[13]  W. Rea,et al.  Adverse health effects of outdoor air pollutants. , 2006, Environment international.

[14]  J. Koenig,et al.  Health Effects of Ambient Air Pollution , 2000 .

[15]  Jehng-Jung Kao,et al.  Utilizing multiobjective analysis to determine an air quality monitoring network in an industrial district , 2006 .

[16]  Angel Hsu,et al.  Toward the Next Generation of Air Quality Monitoring Indicators , 2013 .

[17]  Tao Li,et al.  Optimization of air pollutant monitoring stations with constraints using genetic algorithm , 2015, J. High Speed Networks.

[18]  Ali Elkamel,et al.  A surrogate-based optimization methodology for the optimal design of an air quality monitoring network † , 2015 .

[19]  I. Kooter,et al.  Generation and characterization of diesel engine combustion emissions from petroleum diesel and soybean biodiesel fuels and application for inhalation exposure studies , 2015, Inhalation toxicology.

[20]  Lidia Morawska,et al.  Respiratory health effects of diesel particulate matter , 2012, Respirology.

[21]  Tahir Husain,et al.  A holistic approach for optimal design of air quality monitoring network expansion in an urban area , 2010 .

[22]  Esmaeil Fatehifar,et al.  Using ANN and EPR models to predict carbon monoxide concentrations in urban area of Tabriz , 2015 .

[23]  Kamal Hadad,et al.  The design of long-term air quality monitoring networks in urban areas using a spatiotemporal approach , 2011, Environmental monitoring and assessment.

[24]  Isabella Annesi-Maesano,et al.  Estimating the health effects of exposure to multi-pollutant mixture. , 2012, Annals of epidemiology.

[25]  Toolseeram Ramjeawon,et al.  Prediction of Ground-Level Concentration of Sulfur Dioxide Downwind of an Industrial Estate in Mauritius Using the ISCST3 Model and Selection of Air Pollution Control Systems , 2011 .

[26]  Mukesh Khare,et al.  Air quality modelling study to analyse the impact of the World Bank emission guidelines for thermal power plants in Delhi , 2011 .

[27]  Paul Quincey,et al.  Air Pollution Monitoring Strategies and Technologies for Urban Areas , 2013 .

[29]  Nicolás A Mazzeo,et al.  Design of an Air-Quality Surveillance System for Buenos Aires City Integrated by a NOx Monitoring Network and Atmospheric Dispersion Models , 2008 .

[30]  Amitava Bandyopadhyay,et al.  Prediction of ground level concentration of sulfur dioxide using ISCST3 model in Mangalore industrial region of India , 2009 .

[31]  Michaela Saisana,et al.  Multi-objective optimization of air quality monitoring , 2007, Environmental monitoring and assessment.

[32]  Juan Carlos García-Díaz,et al.  Uncertainty and sensitive analysis of environmental model for risk assessments: An industrial case study , 2012, Reliab. Eng. Syst. Saf..

[33]  Sujing Wang,et al.  Multiobjective Optimization for Air-Quality Monitoring Network Design , 2015 .