Modelling the correlation of PM10 concentration and location of air quality monitoring stations in Malaysia using network method

Abstract

This study highlights the advantage of network analysis in assessing an air pollutant called particulate matters of size less the 10 micrometer, PM10. Aim of the study is to develop a network model based on the concentration data of PM10 and the location of the air quality stations. Then, the behavior of the model was studied using certain network measurements. The network model, G = (V, E) consists of a set of nodes, V representing air quality monitoring stations and a set of edges, E representing the correlation value of the combined data. Threshold and simulation methods have been implemented to determine the appropriate interval correlation on the network. In this study, five network measurements were considered to analyze the network, which are degree centrality, closeness centrality, betweenness centrality, local clustering coefficient and local assortativity. Network analysis was performed to identify the important nodes (hubs) in the network. The network model of air quality based on the concentration of PM10 and the exact location of air quality monitoring stations were developed using the threshold value of 0.664. The results show that the number of air quality monitoring stations in Malaysia successfully optimized.