Mathematical Model to Quantify Air Quality: Indirect Measurement Approach

The air is a basic need of all life on planet earth. Unfortunately, the quality of air has fallen down and the main impact of polluted air on human is related to severe health hazards. This is a burning problem to the developing economy of countries like Sri Lanka. Urbanization and rapid development in these countries are the main reasons for air pollution. Therefore, it is important to identify the levels of the air pollution in cities in order to predetermine actions to improve the quality of air. There are lot of methods already available to measure the air quality, but these methods are based on direct measures of concentration of pollutants. The concentration cannot be measured continuously in countries like Sri Lanka by using direct measures due to lack of resources and financial support. Therefore, quantifying the levels of air pollution in cities using indirect technique is found practical.
The objective of this study is to develop a mathematical model to quantify air pollution using indirect measurements. Five most significant factors such as industries, population density, traffic intensity, green coverage and weather conditions are considered. The boundaries of the factors cannot be well defined. Therefore, fuzzy set theory is applied. Membership functions are defined for all the factors and those factors are combined using fuzzy operators. MATLAB program is used for the simulations. In order to construct and to validate the mathematical model, twenty three major cities in the world are considered. Then, the ranks of cities are compared with the PM2:5 concentration levels. Finally, a case study is carried out by selecting Colombo Municipal Council region in Sri Lanka.