ABSTRACT
Nairobi
County experiences rapid industrialization and urbanization that contributes to
the deteriorating state of air quality, posing a potential health risk to its
growing population. Currently, in Nairobi County, most air quality monitoring
stations use low-cost, inaccurate monitors prone to defects. The study’s objective was to map
Nairobi County’s air
quality using freely available remotely sensed imagery. The Air Pollution Index
(API) formula was used to characterize the
air quality from cloud-free Landsat satellite images i.e., Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI from Google
Earth Engine. The API values were computed based on vegetation indices namely
NDVI, TVI, DVI, and the SWIR1 and NIR bands on the QGIS platform.
Qualitative accuracy assessment was done
using sample points drawn from residential, industrial, green spaces, and
traffic hotspot categories, based on a passive-random sampling
technique. In this study, Landsat 5 API imagery for 2010 provided a reliable
representation of local conditions but indicated significant pollution in green
spaces, with recorded values ranging from -143 to 334. The study found that
Landsat 7 API imagery in 2002 showed expected results with the range of values
being -55 to 287, while Landsat 8 indicated high pollution levels in Nairobi.
The results emphasized the importance of air quality factors in API calibration
and the unmatched spatial coverage of satellite observations over ground-based
monitoring techniques. The study recommends the recalibration of the API
formula for characteristic regions, exploring newer satellite sensors like
those onboard Landsat 9 and Sentinel 2, and involving key stakeholders in a
discourse to develop a suitable Kenyan air quality index.