Analysis of the Impact of External Factors on the Air Quality Index: a Machine Learning Approach

Abstract

In today's world, we often see governments introduce green laws that are actively advertised and promoted to the public. There is active promotion of the green agenda: They create comfortable conditions for electric car manufacturers, provide benefits for the purchase and use of electric cars to citizens, create and develop alternative ways of generating electricity instead of rough heating at thermal power plants, introduce standards for car exhaust emissions that limit manufacturers in production, try to get rid of factories that emit significant amounts of harmful substances into the air by moving them to other countries (Asian countries), leaving only collection workshops or enterprises whose impact is not significant within their country. All of this is done in order to improve air quality in their own country. Although all these changes often seem unnecessary or even harmful to the population and economy, what is the actual result of such actions? This paper presents an analysis of the air composition over the past 50 years, which proves the correctness of the decisions made. It also discusses possible trends in the growth of harmful substances in the air and why they did not materialize.