Olusegun Gabriel Fawole

The increased reliance on thermal satellite images for urban climatic analysis requires robust temperature retrievals for urban surfaces. As the emissivity of any surface type determines the amount of thermal radiation received by a sensor, accurate emissivity values of reflecting surfaces are important in Land Surface Temperature (LST) computations. It is known that the commonly used Temperature Emissivity Separation (TES) algorithm is inaccurate over low-emissivity surfaces such as desert sand and metallic surfaces. However, in indigenous cities, much of the satellite ‘seen’ surface consists of metallic roofing materials like corrugated iron or aluminum. This study uses 853 ECOSTRESS images to examine the diurnal and seasonal pattern of LST for five indigenous cities in sub-Saharan Africa. Surface Urban Cool Islands (SUCIs) were observed in all five cities during both summer and winter, which were more pronounced during daytime than at night. This conflicts with air temperature data and published reports, as well as the dominant low-rise urban morphology, which would suggest the occurrence of Surface Urban Heat Islands (SUHIs). The influence of emissivity on urban LST was examined by allocating more realistic emissivity values to metallic surfaces. For a Landsat image, LST values for the urban area increased from 41 °C to 44, 46, and 49 °C when metallic surfaces were allocated emissivity values of 0.96, 0.83, 0.74, and 0.63, respectively, and SUHIs, rather than SUCIs, were observed. Similar results were obtained for an ECOSTRESS image. As increasing summer temperatures cause significant morbidity and mortality in the populations of these cities, accurate urban climatic data are essential.

Compared to carbon dioxide (CO2), methane (CH2 ) is a more potent greenhouse gas, trapping more heat than CO2 on a per molecule basis. With increasing levels of activities in prominent sources of methane such as 2 livestock farming, rice farming and waste management, especially in developing economies like Nigeria, the need for a comprehensive and reliable CH4 inventory cannot be over- emphasized. Using a bespoke low-cost 4 measuring unit, this study investigated the vertical profile and variability of methane around rice farms and waste dumpsites. Findings show that ambient levels of methane around the rice farms ranged between 26 ppm and 698 ppm and were highest at temperatures >30°C while lower concentrations were measured at lower temperatures. High methane concentrations were observed at a height of around 15 m and gradually decreased with increasing altitude. For waste dumpsites, methane levels measured ranged between 45 ppm and 1220 ppm aligning with variation in the amount of waste. These higher concentrations are, however, often found at low altitudes below 20 m over both dump sites. At temperatures above 30 °C, methane concentrations are found at its highest across both dumpsites. Also, while waste dumpsites seem to emit more methane than rice farms, all study sites emitted appreciable amounts of methane which could accumulate and contribute significantly to regional climatic variations and enhance levels of tropospheric ozone. This study concluded that the bespoke measuring unit performed relatively well, and air temperature has a positive influence on methane concentration at all study sites.

Pollution from vehicular emissions is a major cause of poor air quality observed in many urban and semi-urban towns and cities. As such, this study was conducted to assess air quality and the spatiotemporal distribution of vehicular and traffic-related pollutants in several air sheds of Lagos megacity, the economic nerve centre of Nigeria. A setup of low-cost air quality sensors comprising five (5) units was deployed between November 2018 and February 2019 within traffic corridors in the heart of the city. Diurnal variation of pollutants indicated that carbon dioxide (CO₂) peaked during the early hours of the day, total oxide (O_x = NO₂+O₃) peaked at mid-day while carbon monoxide (CO) had two distinct peaks which correspond to morning and evening rush hours. Nitrogen dioxide (NO₂) concentration peaked during evening hours. Average concentrations are NO₂ (97.1 ± 9.7) ppb, O_x (78.6 ± 27.2) ppb, CO₂ (450.1 ± 31.2) ppm, and CO (2285.63 ± 743.7) ppb. Average concentrations of pollutants were above thresholds set by the World Health Organization (WHO) except for NO₂ which was within the range permissible limits. The implication of this is that the atmosphere is polluted due to elevated concentrations of airborne pollutants, an indication which is of both health and environmental concern. The air quality index (AQI) indicates that the quality of ambient air varies from good to very unhealthy for O_x, and unhealthy to very unhealthy for CO, while AQI for PM_2.5 and PM₁₀ showed hazardous at all the sampling locations except at UNILAG where it is unhealthy for the sensitive group. For all of the sampling sites, conditional bivariate probability function (CBPF) plots show a significant agreement with the location of known pollution sources.

Aerosol optical thickness (AOT) has decreased substantially in Europe in the summer half year (April–September) since 1980, with almost a 50% reduction in Central and Eastern Europe, according to Modern‐Era Retrospective analysis for Research and Applications, Version 2 (MERRA‐2) reanalysis. At the same time, strong positive trends in ERA5 reanalysis surface solar radiation downward for all‐sky and clear‐sky conditions (SSRD and SSRDc, respectively) and temperature at 2 m are found for Europe in summer during the period 1979–2020. The GEBA observations show as well strong increases in SSRD during the latest four decades. Estimations of changes in SSRDc, using the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model, show similarly strong increases when fed by MERRA‐2 AOT. The estimates of warming in this study, caused by increases in SSRD and SSRDc, are based on energy budget approximations and the Stefan Boltzmann law. The increases in near surface temperature, estimated both for clear‐sky and all‐sky conditions, are up to about 1°C for Central and Eastern Europe. The total warming over large parts of this region for clear‐sky conditions is however nearly double the global mean temperature increase of 1.1°C, while somewhat less for all‐sky conditions. The effects of aerosols on warming over the southerly Iberian Peninsula are weaker compared to countries further north. The rapid total warming over the Iberian Peninsula is probably caused by greenhouse warming, drier surface conditions, and to some degree decline in aerosols. Reduced cloud cover is found for large parts of Europe in summer during the latest four decades.

The emergence of COVID‐19 brought with it panic and a sense of urgency causing governments to impose strict restrictions on human activities and vehicular movements. With anthropogenic emissions, especially waste management (domestic and municipal), traffic, and industrial activities, said to be a significant contributor to ambient air pollution, this study assessed the impacts of the imposed restrictions on the concentrations and size distribution of atmospheric aerosols and concentration of gaseous pollutants over West African subregion and seven major COVID‐19 epicenters in the subregion. Satellite retrievals and reanalysis data sets were used to study the impact of the restrictions on Aerosol Optical Depth (AOD) and atmospheric concentrations NO₂, SO₂, CO, and O₃. The anomalies were computed for 2020 relative to 2017–2019 (the reference years). In 2020 relative to the reference years, for area‐averaged AOD levels, there was a consequential mean percentage change between −6.7% ± 21.0% and 19.2% ± 27.9% in the epicenters and −10.1% ± 15.4% over the subregion. The levels of NO₂ and SO₂ also reduced substantially at the epicenters, especially during the periods when the restrictions were highly enforced. However, the atmospheric levels of CO and ozone increased slightly in 2020 compared to the reference years. This study shows that “a one cap fits all” policy cannot reduced the level of air pollutants and that traffic and industrial processes are not the predominant sources of CO in major cities in the subregion.

The emergence of COVID-19 brought panic and a sense of urgency causing governments to impose strict restrictions on human and vehicular movement. With anthropogenic emissions, especially traffic and industrial activities, said to be a significant contributor to ambient air pollution, this study assessed the impacts of the imposed restrictions on the atmospheric concentrations and size distribution of atmospheric aerosols and gaseous pollutants over West African sub-region and seven major COVID-19 epicenters in the sub-region. Satellite retrievals and reanalysis datasets were used to study the impact of the restrictions on Aerosol Optical Depth (AOD) and atmospheric concentrations NO2, SO2, CO and O3. These anomalies were computed for 2020 relative to 2017-2019 (the reference years). In 2020 relative to the reference years, there was a significant reduction of between 0.5±24.6 – 13.7±30.3% and 5.9±17.1% in area-averaged AOD levels at the epicenters and over the sub-region, respectively. The levels of NO2 and SO2 also reduced substantially at the epicenters, especially during the periods when the restrictions were highly enforced. However, the atmospheric levels of CO and ozone increased slightly in 2020 compared to the reference years. This study shows that “a one cap fits all” policy cannot reduced the level of air pollutants and that traffic and industrial processes are not the major sources of CO in major cities in the sub-region. Although not available, ground-based measurements would have given a clearer and better picture of the anomalies observed with the dataset used in this study which are on a coarser spatial resolution.

This study identified specific emission sources of atmospheric pollution in the vicinity of two secondary iron and steel smelting factories in Osun state, southwestern Nigeria, using transplanted biomonitors. A total of 120 biomonitors consisting of lichen and moss were grown under a controlled environment and later transplanted to the surroundings of each factory for monitoring of air pollutants for 3 months in both wet and dry seasons. The elemental contents (K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Br, Rb and Sr) of the biomonitors were determined by X-ray florescence (XRF) spectroscopy. The source identification was performed by applying positive matrix factorization (PMF) receptor modelling approach using the elemental data set from the two smelters. Among the measured elements, Fe had the highest average concentration in the lichen and moss samples as well as in both seasons. The average concentrations of Co, Ni, Cu, Zn, As and Br were low. The varying average elemental concentrations of lichen and moss reflect the pattern of impact of smelting on atmospheric airborne pollution around the factories. The four factors resolved by PMF and their respective contributions were metal processing (39.0%), Fe source (28.0%), crustal/soil (22.0%) and road dust (11.0%) for moss and Fe source (34.0%), crustal/soil (26.0%), coal combustion (25.0%) and road dust (15.0%) for lichen. The study showcases lichen and moss as cheaper and yet efficient uninterrupted monitoring tools of air pollution sources associated with iron and steel smelting industrial activities.