Leveraging satellite and reanalysis air quality data for bottom-up approach in tackling air pollution in nigeria

The failure of air pollution mitigation strategies at national levels can be attributed to the disconnect between policy makers and creators of this pollutants. This is not unconnected to lack of data at the smallest level of the society. Sparse air quality data in developing countries have hindered policy implementations for it’s reduction. There is the need to compensate for the sparse data using other sources. In this study, the performance of satellite (WashU) and reanalysis (CAMS) data was evaluated against two low cost sensors – Purple Air and Clarity devices, across several locations in Nigeria. Both models were found to perform fairly well during the wet season but poorly during the dry season. We developed correction factors to improve both satellite and reanalysis data over Nigeria. We further leverage on the corrected data to develop a bottom-up approach to tackle air pollution from the grassroots using a credit reward system. This will make every citizen part of the clean-up process while accelerating holistic and fair transitioning to a clean economy.