Optimal Air Quality Monitoring Network for Green Cities

Continuous efforts are being made by cities around the world to identify methods to make their environment healthier and more livable through the improvement of water, land and air. Air pollution is of high importance since it often causes severe and irreversible damage to human health and environment and remediation is extremely difficult. The potential sources of air pollution, such as large industries, automobiles and power plants, are essential part of cities. Transforming these cities into “green cities” necessitates control of these emissions. Continuous monitoring of air pollution with a well-designed air quality monitoring network (AQMN) is usually the first step in addressing and tackling the emissions. Environmental protection agencies are looking for an optimal designed AQMN with an obvious focus on minimizing costs, along with other objectives. This article proposes a simple method of optimizing the AQMN using geographical information system (GIS), interpolation techniques and historical data. Existing air quality stations are systematically eliminated, and the missing data is filled in with data generated from the most appropriate interpolation technique. The interpolated data is then compared with the observed data. Pre-defined performance measures were used to check the accuracy of the interpolated data. An algorithm was developed in a GIS environment and the process was simulated for several sets of measurements. This methodology proved to be useful to decision makers to find optimal numbers of stations that are needed without compromising the coverage of the concentrations across the city.