Kenya is a country in East Africa region located between the longitudes 32˚ East and 42˚ East and latitudes 5˚ South and 5˚ North. It is bordered by Ethiopia to the north, Tanzania to the south, South Sudan to the Northwest, Uganda to the west and Somalia to the east.

The country is populous with a population of 47,564,296 (Kenya 2019 census). Kenya has a land area of about 569,374 km² with varying topography and which includes glaciated mountain peaks with permanent snow cover, plateaus and coastal plain [12] . The long-term annual average values of temperature over the Kenyan territory are 25^˚C to 34^˚C while the relative humidity ranges between 24.0% and 69.0% respectively [17] . Climatologically, the seasons are, MAM, JJA, SON and DJF. MAM and SON are the local wet sessions whereas DJF and JJA are local dry seasons.

To ascertain the impact of lockdown on air quality, selected aerosol properties and pollutant concentrations were studied in three phases as designed by [18] .

First was the Pre-lockdown period. This period ran from April 1^st to June 30^th 2018. The second period during the study was during the lockdown period over the study domain from April 1^st to June 30^th 2019 while the last period of study was the Post Lockdown which spans from April 1^st to June 30^th 2020. These data products were sourced from http://giovanni.gsfc.nasa.gov/giovanni/.

AOD (τ) which is defined as the integrated extinction coefficient over a vertical column of unit cross-section was determined using Beer-lambert-Bouguer law in Equation (1) [25] . It describes the degree to which aerosols prevent the transmission of light from the sun by either absorption or scattering [19] [25] [26] . The Voltage (V) measured by a sun photometer is proportional to spectral irradiance (I) reaching the instrument at surface. The estimated top of the atmosphere spectral irradiance (I_o) in terms of voltage (V_o) is obtained by sun photometer measurements from sensors on board satellites. The Beer-lambert-Bouguer law has been used by a number of researchers [24] [26] [28] ;

V ( λ ) = V o ( λ ) d 2 exp [ − τ ( λ ) t o t ∗ m ] (1)

where V is the digital voltage measured at wavelength λ, V o is the extraterrestrial voltage, d is the ratio of the average to the actual Earth-Sun distance, ( τ t o t ) is the total optical depth and m is the optical air mass [23] [25] .

The size of aerosols can be estimated from spectral aerosol optical depth from 440 nm to 870 nm. The negative slope (first derivative) of AOD with wavelength in logarithmic scale is known as the angstrom exponent ( α ).

α = − d ln τ a d ln λ = log ( τ λ 1 τ λ 2 ) log ( λ 1 λ 2 ) (2)

where α is the Angstrom exponent, τ a is the aerosol optical depth, and λ is the wavelength.

Further, the SSA, which is the ratio of the scattering efficiency to total extinction efficiency can be approximated by power law relation [27] .

ω 0 = τ s p τ e x t = τ s p τ s p + τ a p (3)

where τ s p is the scattering optical depth, τ a p is the absorption optical depth and τ e x t the total extinction optical depth. The single scattering albedo (SSA) represents a key parameter in describing the aerosol optical properties. The SSA describes the portion of solar energy radiation scattered from the main beam passing through the atmosphere. The SSA influences the diffuse radiation, while its effect on direct radiation can be considered negligible.

Figure 2 shows the Time series area averaged AOD results during the study period over Kenya. It is noted that MAM and SON have decreased AOD because of increased rainfall washout [17] [20] . These seasons are also characterized by minimum dust loading since the ground is wet. Further, minimum AOD is recorded during April while maximum AOD values are recorded in June. From the start of April, it is noted that AOD increased for all the years 2019, 2020 and 2021. However there is no notable change in AOD variation in 2020 that may be associated with prevailing COVID-19 lockdown over the country. This fact is attributed to negative variation in AOD for all seasons during the year which is a result of the transported pollution inlands since the region experiences dominant South Easterlies and North Easterlies during greater period of the year [12] .

Figure 3 depicts the spatial maps for variation in AOD over Kenya during the study period. The first, second and third columns represent April, May and June while the first, second and third rows represent the years 2019, 2020 and 2021 respectively. In the investigation of the spatial variation in AOD for the months of April, May and June in 2019, 2020 and 2021 for the pre-lockdown (2019), lockdown (2020) and post lockdown (2021), it was noted that for April 2020, AOD values over the entire country were lower in MAM as compared to JJA in 2019 to 2021. These results are consistent with the findings of [28] . The lower AOD in MAM is attributed to the prevailing local wet season which enhances the wet scavenging of aerosols while the higher AOD in the local dry month of June is associated with reduced wet scavenging and increased anthropogenic activities such as biomass burning and dust generation [12] [19] [28] .

The government instituted lockdown protocols in April 2020 to curtail normal operations had insignificant variations on AOD spatial distributions as indicated by Figure 3. It is noted that COVID-19 lockdowns instituted by the government in April had no significant influence on AOD spatial-temporal variation over Kenya. The AOD variability is influenced by long-distance transport as justified by the results from the HYSPLIT model as reported by [28] . The central and southeastern Kenya had slightly lower mean AOD as compared to the north and northeastern regions of the country during the study period. This is as a result of the higher dust levels in the northeastern and northern parts of the country as compared to the wet central and southwestern parts of the country. These facts agree with the findings of [12] which postulated that aerosol optical properties over East Africa region are controlled by monsoon precipitation that enhance long distance transport [28] . The relatively higher AOD over the coast region is as a result of sea salt aerosols that are domicile there because of the marine environment. Cumulatively during the entire lockdown period in Kenya, (22^nd March 2020 to 30^th June 2020), no observable change in spatial variability of AOD was noted as compared to the mean AOD in 2019 and 2021 for the same time period.

The average annual seasonal pattern of AE is shown in Figure 4. It is clear that AE values over Kenya peaked in May and November during the study period. This is associated with high concentration of aerosols of the fine mode species from burning of biofuels and biomass burning which are least washed down by rainfall as a result of reduced precipitation.

Lower values closer to 1 i.e. 1.1, 1.2 and 1.2 for 2019, 2020 and 2021 are observed during the months of June respectively. These values depicted more contribution of course-mode dust particles relative to fine-mode particles since June is considered a dry month [28] . The average spatial patterns of AE_{470 -870} over Kenya observed during the study period is illustrated in Figure 5. The first, second and third columns represent April, May and June while the first, second and third rows represent the years 2019,2020 and 2021 respectively. The values of AE₄₇₀ are observed to vary between 0.6 to 1.15 with lower values AE₄₇₀ < 1 dominating most parts of the study domain. This is attributed to dominance of course mode aerosols resulting from desert dust produced locally [29] as well as transported from the Saharan and Arabian Peninsula [30] . The coastal region had moderately low AE₄₇₀ associated with course mode aerosols such as sea salt [25] [26] [28] . The arid areas of northwest Kenya around Lake Turkana posted low values of AE₄₇₀, resulting from local production of dust aerosols from the Chalbi desert along with carbonaceous aerosols from the alkaline Lake Turkana [31] .

From Figure 5, it was also noted that there is no significant relation between AE trends to the national wide COVID-19 lockdown. The COVID-19 lockdowns instituted by the Kenya and regional governments did not result in any change in total AE over Kenya during the period of study. This points to the fact that there was marginal change if any in the size of aerosols in the atmosphere over Kenya during this period. The inter-seasonal disparity in the meteorological conditions at the coastal strip and dust generation in the north-eastern drought prone area is the strongest contributing factor to the lower values of AE along the coastal line and in the north and northeastern part of the country.

A lower SSA indicates an enviromental episode dominated by either desert dust or biomass burning while a Single Scattering Albedo at 440 nm between 0.9 - 0.98 indicate urban/industrial aerosols, 0.92 - 0.93 indicate desert dust and 0.89 - 0.95 indicates biomass burning [32] .

The SSA over Kenya ranges between 0.156 to 0.160 from January to mid-June during the study period indication that the urban/industrial aerosols dominated the atmosphere during this period (as depicted in Figure 6). Coincidently this period corresponds to the lockdown period declared by the government of Kenya. However past this period, the SSA is erratic hitting as low as slightly over 0.166 in July and as high as 0.168 during the month of September.

In Figure 7, the first, second and third columns represent April, May and June while the first, second and third rows represent the years 2019, 2020 and 2021 respectively. The values of SSA over northeastern Kenya as indicated by Figure 7 are associated with desert dust.

It is apparent from the time series of the SSA over Kenya that the COVID-19 lockdown is seen to create no disruption of the normal distribution and concentration of main pollutants and aerosols over the Kenyan territory however, there is no significant impact of the lockdown on SSA values over Kenya.