Spatiotemporal distribution of pollutants and impact of local meteorology on source influence on pollutants' level in a traffic air-shed in Lagos megacity, Nigeria.

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 (Ox = 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, Ox (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 Ox, and unhealthy to very unhealthy for CO, while AQI for PM2.5 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.

Impacts of COVID-19 Restrictions on Regional and Local Air Quality Across Selected West African Cities.

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.

Analysis of the variability of airborne particulate matter with prevailing meteorological conditions across a semi-urban environment using a network of low-cost air quality sensors.

The concentrations of fine and coarse fractions of airborne particulate matter (PM) and meteorological variables (wind speed, wind direction, temperature and relative humidity) were measured at six selected locations in Ile Ife, a prominent university town in Nigeria using a network of low-cost air quality (AQ) sensor units. The objective of the deployment was to collate baseline air quality data and assess the impact of prevailing meteorological conditions on PM concentrations in selected residential communities downwind of an iron smelting facility. The raw data obtained from OPC-N2 of the AQ sensor units was corrected using the RH correction factor developed based k-Kohler theory. This PM (corrected) fast time resolution data (20 s) from the AQ sensor units were used to create daily averages. The overall mean mass concentrations for PM2.5 and PM10 were 213.3, 44.1, 23.8, 27.7, 20.2 and 41.5 µg/m3 and; 439.9, 107.1, 55.0, 72.4, 45.5 and 112.0 µg/m3 for Fasina (Iron-Steel Smelting Factory, ISSF), Modomo, Eleweran, Fire Service, O.A.U. staff quarters and Obafemi Awolowo University Teaching and Research Farm (OAUTRF), respectively. PM concentration and wind speed showed a negative exponential distribution curve with the lowest exponential fit coefficient of determination (R2) values of 0.08 for PM2.5 and 0.03 for PM10 during nighttime periods at Eleweran and Fire service sites, respectively. The relationship between PM concentration and temperature gave a decay curve indicating that higher PM concentrations were observed at lower temperatures. The exponential distribution curve for the relationship between PM concentration and relative humidity (RH) showed that PM concentrations do not vary for RH < 80 % while stronger relationship was noticed with higher PM concentration for RH > 80 % for both day and nighttime. The performances of the MLR model were slightly poor and as such not too reliable for predicting the concentration but useful for improving predictive model accuracy when other variables contributing to the variability of PM is considered. The study concluded that the anthropogenic and industrial activities at the smelting factory contribute significantly to the elevated PM mass concentration measured at the study locations.

Biomonitoring of environmental pollution in the vicinity of iron and steel smelters in southwestern Nigeria using transplanted lichens and mosses.

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.

Dispersion of gas flaring emissions in the Niger delta: Impact of prevailing meteorological conditions and flare characteristics.

An understanding of the dispersion and level of emissions source of atmospheric pollutants; whether point, area or volume sources, is required to inform policies on air pollution and day-to-day predictions of pollution level. Very few studies have carried out simulations of the dispersion pattern and ground-level concentration of pollutants emitted from real-world gas flares. The limited availability of official data on gas flares from the oil and gas industries makes accurate dispersion calculations difficult. Using ADMS 5 and AERMOD, this study assessed the sensitivity of dispersion and ground-level concentration of pollutants from gas flares in the Niger Delta to prevailing meteorological condition; fuel composition; and flare size. Although, during the non-WAM (West African Monsoon) months (November and March), the simulated ground-level concentrations of pollutants from a single flare are lower, the dispersion of pollutants is towards both the inland and coastal communities. In the WAM months, the ground-level concentrations are higher and are dispersed predominantly over the inland communities. Less buoyant plumes from smaller flares (lower volume flow rates) and/or flaring of fuel with lower heat content results in higher ground-level concentrations in areas closer to the flare. Considering the huge number of flares scattered around the region, a mitigation of the acute local pollution level would be to combine short stacks flaring at lower volume flow rates to enhance the volume flow rate of a single exhaust, and hence, the buoyancy of the plume exiting the stack.

Gas flaring and resultant air pollution: A review focusing on black carbon.

Gas flaring is a prominent source of VOCs, CO, CO2, SO2, PAH, NOX and soot (black carbon), all of which are important pollutants which interact, directly and indirectly, in the Earth's climatic processes. Globally, over 130 billion cubic metres of gas are flared annually. We review the contribution of gas flaring to air pollution on local, regional and global scales, with special emphasis on black carbon (BC, "soot"). The temporal and spatial characteristics of gas flaring distinguishes it from mobile combustion sources (transport), while the open-flame nature of gas flaring distinguishes it from industrial point-sources; the high temperature, flame control, and spatial compactness distinguishes gas flaring from both biomass burning and domestic fuel-use. All of these distinguishing factors influence the quantity and characteristics of BC production from gas flaring, so that it is important to consider this source separately in emissions inventories and environmental field studies. Estimate of the yield of pollutants from gas flaring have, to date, paid little or no attention to the emission of BC with the assumption often being made that flaring produces a smokeless flame. In gas flares, soot yield is known to depend on a number of factors, and there is a need to develop emission estimates and modelling frameworks that take these factors into consideration. Hence, emission inventories, especially of the soot yield from gas flaring should give adequate consideration to the variation of fuel gas composition, and to combustion characteristics, which are strong determinants of the nature and quantity of pollutants emitted. The buoyant nature of gas flaring plume, often at temperatures in the range of 2000 K, coupled with the height of the stack enables some of the pollutants to escape further into the free troposphere aiding their long-range transport, which is often not well-captured by model studies.

Characterization and source identification of airborne particulate loadings at receptor site-classes of Lagos Mega-City, Nigeria.

Size segregated suspended particulate matter (PM2.5 and PM2.5-10) were collected using Gent low-volume air sampler at four different receptor site-classes in Lagos Mega City, Nigeria. The particulate mass loading was quantified and the concentration was analyzed to examine the pattern and variation from one receptor site-class to another. The PM2.5/PM10 ratio varied among the site-classes with the residential and marine sites having the least and highest ratio of 0.31 +/- 0.13 and 0.49 +/- 0.17 respectively. Particulate loading was higher on weekdays than on weekends (by a factor of about 1.5) in all but the marine site-class.The mean PM2.5/PM10 ratio is 0.41 +/- 0.15, which suggests that traffic emission is not the principal source of the Particulate Matter (PM). The INAA assay of the particulates detected ten elements: As, Br, Ce, K, La, Mo, Na, Sb, Sm and Zn. Except for Br, Mo and Sb, the detected elements were more pronounced in the coarse-fractioned filter Principal Component Factor Analysis (PCFA) of the detected elements identified some common sources (traffic-related, traffic emission, sea-salt and industrial emission) for both PM fractions at the four receptor site-classes.