Implementing Machine Learning Algorithms to Compare the Ratio of NO2 and O3 in Suspended Particulate Matter

Abstract

The environmental concerns have been increasing with every passing. Most of industrial applications are considered as primary resources of air pollution in the developing countries like Pakistan. The Air Quality Index (AQI) is established to determine the present and future pollution in a city. DG Khan is one of the crucial cities of Punjab, Pakistan. The aim of this research was to study Suspended Particle Method present in the atmosphere using PM_2.5 to PM_2.10 index. The research revealed that in the urban areas of city the air quality is lower than its surrounding areas. The ultimate objective of this research was to measure to run analysis that can reveal the air quality in the DG Khan district. The city is located in one of the most industrial and productive provinces of Pakistan. The research focused on one aspect of the air pollution known as PM scale to measure the number of suspended particles in the given location. It was revealed that compared to rural areas the suspended particles contain high-levels of particles. The presence of this particle is owing to the fact that in the urban areas of the district there are high commercial and industrial activity leading to elevated levels of air pollution in the atmosphere. The current research collects its primary data form web-portal of Air Quality Index (AQI) of Pakistan and then runs multiple algorithms and statistical analysis to get a clear picture of actual situation in the area. The current research can be used as reference for future researches by extending its geographical area.