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Particulate pollution has become one of the major issues in the mega-cities of Pakistan. As with the increase in rapid urbanization, poor air quality, climate change, and health-related issues are increasing gradually in Lahore. Therefore, the implications for the variability of air pollution need to be better understood for the improvement of air quality. So, in this article, we used aerosol robotic network (AERONET) and moderate resolution imaging spectroradiometer (MODIS) datasets along with the variability of different meteorological parameters (temperature, wind speed, relative humidity, dew point, and sea level pressure) over Lahore during 2006 to 2022. Moreover, the multi-linear regression model is used to analyse the linear relation of AERONET-retrieved aerosol optical depth (AOD) and particulate matter (PM2.5) with MODIS-retrieved AOD during the time period. Both AOD and PM2.5 increase gradually throughout the time period. AERONET-retrieved AOD showed a significant variability during the time period where each meteorological parameter gives a significant value (p < 0.05) except pressure (p > 0.05). The AERONET-retrieved AOD and PM2.5 give a strong positive value (0.78 and 0.63) of the coefficient of correlation. Seasonally, the value of the coefficient of correlation is observed high during summer (0.92) followed by autumn, spring, and winter. Considering the outcomes of this study, different methods like using better quality of fuel, use of public transport, plantation of trees, etc., can be employed to reduce air pollution.
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