Paper Title
Effect of Weather Variable and Pollutant Variables on PM10 using Statistical and Machine Learning Techniques

Abstract
Economic development drives rapid industrialization and urbanization, which are significant sources of air pollution in developing countries, particularly in large or megacities. Kuwait's quick urbanisation and rise in vehicular traffic have significantly contaminated the environment. The nation also frequently experiences dust storms, which add to the emissions of dangerous gases and particles. As a result, the nation's numerous sources of pollution make it a prime location for research into environmental pollution. Thus in the present study an attempt was made to examine the effect of weather variables(temperature, relative humidity, wind speed and wind direction) and pollutant variables (PM2.5, SO2, NO2, NOX, CO, and O3) on PM10 using statistical and machine learning techniques. The results show that both stations experienced severe air quality issues and where particulate matter concentrations (PM10) are strongly influenced by the different meteorological and pollutant variables. Keywords - Air Pollution, Weather, LASSO, k-NN, ANN, Kuwait