The outbreak of the coronavirus disease (COVID-19) has had a significant impact on the global community, affecting various aspects of life. One of the unintended consequences of the pandemic is its effect on air quality. This study uses the state of Kuwait as a case study to investigate the impact of the COVID-19 pandemic on levels of gaseous pollutants (NO2, O3, SO2, H2S, CO) and particulate matter 2.5 and 10 mu m (PM2.5 and PM10) in a hot arid region. Hourly data for COVID-19 infected cases and gaseous pollutants and particulate matter were collected from January to December 2020. The Openair model with the R package was used to analyze gaseous pollutants and particulate matter data with an applied air quality index (AQI). Stochastic models with time series analysis - Kernel density were employed to investigate how COVID-19 infection can affect the changes of gaseous pollutants and particulate matter. In addition, the spatial interpolation approach was estimated using the inverse distance weighted (IDW). The Generalized Additive Model (GAM) was used to analyze the daily data of the gasses and particle occurrences in a hot, dry climate. The results showed a significant decrease in levels of gaseous pollutants and particulate matter after implementing preventive measures to control the spread of the virus. This reduction benefits public health and the environment in the region, indicating that the preventive measures taken to address the COVID-19 pandemic have contributed to reducing environmental pollution and mitigating its adverse effects.