Application and Comparison of MLR, ANN and CART Models for Predicting PM10 Concentration Level of Guwahati City (India)

Abstract

Indian cities are increasingly becoming susceptible to PM10 induced health effects which have become a matter of concern for the policymakers of the country. Air pollution is engulfing the comparatively smaller cities as the rapid pace of urbanization, and economic development seems not to lose steam ever. A review of air pollution of 28 cities of India, which includes tier-I, II, and III cities of India, found to have grossly violated both WHO and NAAQS standards in respect of acceptable daily average PM10 concentrations by a wide margin. Predicting the city level PM10 concentrations in advance and accordingly initiate prior actions is an acceptable solution to save the city dwellers from PM10 induced health hazards. Predictive ability of three models, linear MLR, nonlinear MLP (ANN), and nonlinear CART, for one day ahead PM10 concentration forecasting of tier-II Guwahati city, were tested with 2016-2018 daily average observed climate data, PM10, and gaseous pollutants. The results show that the non-linear algorithm MLP with feedforward backpropagation network topologies of ANN class, giving the best prediction value when compared with linear MLR and nonlinear CART model. ANN (MLP) approach, therefore, may be useful to effectively derive a predictive understanding of one day ahead PM10 concentration level and thus provide a tool to the policymakers for improving decision-making associated with air pollution and public health.

Air Quality, Atmospheric Variables and Spread of COVID-19 in Delhi (India): An Analysis

“…Investigation of air quality and its relationship with COVID-19 cases is highly important where both epidemic and air pollutions are currently high (Zoran et al, 2020). The previous reports have also been showing air pollution (both ambient and household) as key risk factors in terms of disease spread for the Indian population (Cowling et al, 2014;Gargava and Rajagopalan, 2015;Dutta and Jinsart, 2020).…”