Environmental Pollutants Resulting from Gas Concentrations in Babil Governorate: A Statistical–Analytical Study

Abstract

Air pollution is considered one of the most prominent contemporary environmental challenges due to its serious health and environmental impacts. It is manifested by the presence of gaseous or particulate pollutants at concentrations exceeding permissible limits, adversely affecting human health and ecosystem integrity. This study aims to analyze the spatial and temporal variability of air pollutants in Babil Governorate using official environmental data for the year 2020. The data were collected from three monitoring stations (Abu Khashtawi, University of Babylon, and Hayy Nader) and included the main pollutants under investigation: sulfur dioxide (SO₂), nitric oxide (NO), nitrogen dioxide (NO₂), and particulate matter. The study adopted a statistical–analytical approach, employing one-way analysis of variance (One-Way ANOVA) and the Tukey HSD post hoc test to identify statistically significant differences among the monitoring stations. The results revealed clear spatial and temporal variability in the concentrations of certain gases. Hayy Nader station recorded the highest concentration of sulfur dioxide, while the University of Babylon station showed the highest concentrations of NO and NO₂. In addition, Hayy Nader station was characterized by notably elevated levels of particulate matter. Statistical tests confirmed the presence of significant differences among some stations, reflecting the influence of human activities (industrial, traffic-related, and residential) in addition to natural and climatic conditions. The study concludes that air pollution in Babil Governorate represents a growing environmental and public health problem, necessitating the strengthening of environmental monitoring programs and the implementation of effective policies to reduce emission sources. It also highlights the importance of expanding statistical environmental studies to enable early detection of pollution patterns.