A New Tool for Risk Assessment of Air Pollution: Fuzzy Process Capability Indices

Abstract

Air pollution has become a high risk priority since the World Health Organization estimates that 4.6 million people die each year from causes directly attributable to air pollution, which damages people, environments, animals, and other components of natural life. There are many proposals in the literature to measure and control the destructive effects of air pollution. In this article, a methodology based on process capability indices (PCIs), which are very effective statistics that show the process dispersion and skewness to summarize process performance, has been presented for the risk assessment of air pollution. The fuzzy set theory, which provides an advantage for more flexible interpretation of the results of Process Capability Analysis (PCA), is used to obtain more detailed analyses of air pollution. In this article the main air pollution indicators are analyzed and their means and variances are obtained as fuzzy numbers. The specification limit values are considered as fuzzy numbers and then nonconforming percentages are obtained for air pollution indicators. In the application, fuzzy percentages of conforming and nonconforming items for air pollution indicators are calculated for Istanbul.