Determine the Variables Affecting Environmental Pollution with CO and 〖SO〗_2 Gases Using the Log-Logistic Regression Model

Abstract

The problem of environmental pollution is one of the most important and dangerous problems facing humans at present because of its direct impact on human health and other living organisms. In recent years, it has been observed that there has been an increase in environmental pollution rates, which has greatly affected human health and led to the emergence of many diseases such as cancer, pneumonia, poisoning, birth defects, and others. Its impact has not only been limited to humans but has extended beyond its impact on animals and plants as well.

Given the importance of the topic, its seriousness, and its direct impact on human life, this research was conducted to determine the proportion of the amount of pollution based on two of the most important factors on air pollution, which are both gases (CO and ), based on the explanatory variables, which are the average temperature, the average dew point, and the average humidity: the average wind speed and the average amount of crude oil used in the filtering process.

In this research, the risk function was estimated using the Log-Logistic regression model using estimation methods: the Chi-square minimization method, the weighted least squares method, and the genetic algorithm method. These methods were applied to air pollution data from the Central Refineries Company in Baghdad (Al-Dora Refinery). which represents daily measurements of environmental pollution compounds, which are based on time for the period from 2018 to 2022.