Statistical Trends and Characterization of Atmospheric Pollutants Levels Using Low-Cost and Satellite Total Column Data in the Greater Accra Metropolitan Assembly (GAMA), Ghana

High concentration of pollutants is known to have adverse implication on climate and public health. Every year, poor air quality is responsible for about 7 million deaths globally as it is estimated by the WHO. In sub- Saharan Africa with increasing population growth and urban emissions, the situation is no different since poor air quality is increasing at an alarming rate. Therefore, regular monitoring is required to assess the levels of pollutant in both local and regional scale. However, this is scarce in sub-Saharan Africa as it is expensive to acquire, install and maintain large number of high-grade air quality monitoring sensors. And thus, has limited studies to investigate associations between particulates with aerodynamic diameter less than 2.5 microns (PM_2.5) and gas pollutants like nitrogen dioxide (NO₂) and ozone (O₃) for a long time in sub-Saharan African cities. Hence, this study sort to bridge this gap by utilizing 5 Clarity Node-S sensors PM_2.5 data, total column particulates or Aerosol Optical Depth (AOD), NO₂ and O₃ data from satellites over 5 different Ghana Environmental Protection Agency (GEPA) air quality  traffic stations in the Greater Accra Metropolitan Assembly (GAMA). AOD, NO₂ and O₃ were retrieved from NASA Moderate Resolution Imaging Spectro-Radiometer (MODIS) Terra and Ozone Monitoring Instrument (OMI). Long-term trends over the 5 stations on (25 x 25) km resolution for OMI and (50 x 50) km resolution for MODIS Terra AOD from 2012 to 2021 were assessed using Mann-Kendall test to ascertain the impact of population growth coupled with increasing traffic, biomass burning and climate change on air quality for the past decade in the GAMA. Further, characterization of PM_2.5, AOD, NO_2, and O₃ levels in the GAMA was also assessed while the Pearson correlation coefficient was used to find correlations between the pollutants. Overall, there was an increasing trend in NO₂ (p < 0.05), no trend in O₃ (p > 0.05) and a decreasing trend in AOD (p < 0.01). Pearson correlation coefficients between PM_2.5 data and MODIS Terra AOD on (50 x 50) km resolution across the stations were (R² = 0.72, 0.72, 0.67, 0.58 and 0.57) respectively. Correlation coefficient between column NO₂ and O₃ was (R² = -0.83 ± 0.030, p < 0.01), AODand O₃ (R² = -0.43 ± 0.003, p < 0.01) and NO₂ and AOD(R² = 0.21 ± 0.010, p > 0.01). PM_2.5, AOD and NO₂ levels were generally high during the dry season while high concentrations of O₃ were observed in the wet season across the stations. Also, PM_2.5 daily mean level of 32.8 μgm^-3 for 25 months between 2018 and 2021 was more than twice WHO recommended daily mean level of 15 μgm^-3. Again, an increasing and decreasing trends in NO₂ and AOD levels shows that sources of poor air quality may be shifting from the usual biomass burning to traffic emissions. High population growth with increasing traffic and climate change in growing sub-Saharan African cities requires urgent policy measures and regulations as ground air quality monitoring sensors are limited.