Rainfall and temperature are the two major climatic variables affecting humans and the environmen... more Rainfall and temperature are the two major climatic variables affecting humans and the environment. Hence, it is essential to study rainfall and temperature variability over urban areas. This study focused on analyzing the spatiotemporal trends and variability of rainfall and temperature over Benin metropolitan region, Nigeria. Time series analysis was used to determine temporal trends in rainfall as well as minimum and maximum atmospheric temperatures over a study period of 30 years (1990 to 2019). Analysis of variance was used to understand spatiotemporal variations of climatic elements among the spatial units (urban core, intermediate and peripheral areas). Land surface temperature (LST) and land use/land cover (LULC) classes of the study area were analyzed from Landsat TM Imagery of 2020. Results revealed a decreasing trend for rainfall and increasing trend for minimum and maximum atmospheric temperatures in all the spatial units. Rainfall distribution and temperature among the spatial units were statistically insignificant; however, significant temporal decadal variations were noticed for minimum and maximum air temperatures. This investigation provided valuable information for assessing changes in rainfall and temperature and concluded that the study area is becoming warmer; an indication of global warming and climate change.
This study investigates air pollution from the Warri Refining and Petrochemical Company (WRPC) of... more This study investigates air pollution from the Warri Refining and Petrochemical Company (WRPC) of Delta Sate, Nigeria with the intent of determining the variations in pollution levels associated with increasing distance from the refinery. The following pollutant gases: Carbon monoxide (CO), Volatile organic compounds (VOC), Hydrogen sulphide (H2S), Nitrogen dioxide (NO2), Sulphur dioxide (SO2) and Particulate Matter (PM2.5 and PM10), were monitored intermittently with the use of digital hand-held probes, at sampling points located between 1,500 meters to 16,000 meters from WRPC. Air sampling was carried out on a weekly basis, for a duration of one (1) year. The average annual concentration of CO, VOC, H2S, NO2, SO2, PM2.5 and PM10 measured were 0.2543 ppm, 4.4922 mg/m3, 0.0004 ppm, 0.0063 ppm, 0.5263 ppm, 36.3825 µg/m3, 91.7346 µg/m3 respectively. The results of the spatial analyses of air pollutants show that concentrations of VOC, NO2, PM2.5, and PM10 shared a significant inverse relationship with distance (p values 0.00 ≤.0.05). The study suggests a minimum of 10,250 meters radial extent of buffers around WRPC, as a long-term strategy in reducing exposure of residents to air pollution. Short-term strategies include enforcement of legislation reducing/banning emissions from industries and bush fires, use of alternative eco-friendly technologies and energy sources, tree planting, revamp of the hydroelectricity power sector and general sanitization of the environment.
This study determined the effects of seasonality on air pollution in a tropical city of Southern ... more This study determined the effects of seasonality on air pollution in a tropical city of Southern Nigeria. This was with a view to acquiring data that would be useful in policy formulation and planning for proper management of ailments that result from seasonal variation of air pollution in the study area. Sampling for the study covered a period of six months, between mid-October 2013 and mid-April 2014. Air pollutants, taken into consideration, include particulate matter (PM0.3, 0.5, 1.0, 2.5, 5.0 and 10µm) and carbon monoxide (CO). Particulate matter was measured using a hand-held particle counter, while CO was measured with a single gas monitor (T40 Rattler). Five sampling points were selected based on stratified sampling technique, which represented five land use types monitored in the study area. Sampling was carried out twice in a week in accordance with the guidelines of Central Pollution Control Board, Delhi India. Sampling height was two meters above ground level. The student T-test was used to determine significant differences in monthly mean concentration of air pollutants across dry and wet seasons. The results revealed the dry season with mean values of 248568.19, 64639.04, 11140.21, 2810.39, 665.84, 320.80 particle counts for PM0.3, 0.5, 1.0, 2.5, 5.0 and 10µm and 3.01 ppm for CO concentration, was characterized by higher concentration of pollutants, while the rainy season with a mean values of 94728.24, 24745.69, 4338.29, 1158.11, 262.69, 131.36 particle counts for PM0.3, 0.5, 1.0, 2.5, 5.0 and 10µm and 2.70 ppm for CO concentration was characterized with less concentration of pollutants. The study concludes that seasonality significantly influences the concentration of pollutants in the city.
The study assesses potential variables which influence the concentration of air pollution around ... more The study assesses potential variables which influence the concentration of air pollution around a point source. Seven categories of air pollutants were monitored around the Warri Refining and Petrochemical Company (WRPC) of Nigeria, which comprised carbon monoxide (CO), volatile organic compounds (VOC), Hydrogen sulphide (H 2 S), Nitrogen dioxide (NO 2), Sulphur dioxide (SO 2) and Particulate Matter (PM 2.5 and PM 10). Sampling points were located in the range of 1.5 km to 16 km. Air quality was sampled intermittently and weekly for one year. Ttest analyses was used to determine significant differences in air pollutant concentration on the basis of orientation and seasonality. Regression analysis was also used to assess the influence of selected predictors on pollutant concentration around WRPC. Except for H 2 S, the prediction models for CO, VOC, SO 2 , NO 2 , PM 2.5 and PM 10 were statistically significant with R 2 values of 0.014, 0.215, 0.022, 0.582, 0.17 and 0.45, respectively. The results revealed that the concentration of pollutants was influenced by the combination of the factors (distance from WRPC, orientation from WRPC, seasonality and climatic variables such as atmospheric temperature, relative humidity and wind speed), which served as the predictors in the model. The study recommends that arrangements of industrial and residential land uses by urban planning authorities be patterned, taking into consideration factors such as distance and orientation from pollution point-sources.
Rainfall and temperature are the two major climatic variables affecting humans and the environmen... more Rainfall and temperature are the two major climatic variables affecting humans and the environment. Hence, it is essential to study rainfall and temperature variability over urban areas. This study focused on analyzing the spatiotemporal trends and variability of rainfall and temperature over Benin metropolitan region, Nigeria. Time series analysis was used to determine temporal trends in rainfall as well as minimum and maximum atmospheric temperatures over a study period of 30 years (1990 to 2019). Analysis of variance was used to understand spatiotemporal variations of climatic elements among the spatial units (urban core, intermediate and peripheral areas). Land surface temperature (LST) and land use/land cover (LULC) classes of the study area were analyzed from Landsat TM Imagery of 2020. Results revealed a decreasing trend for rainfall and increasing trend for minimum and maximum atmospheric temperatures in all the spatial units. Rainfall distribution and temperature among the spatial units were statistically insignificant; however, significant temporal decadal variations were noticed for minimum and maximum air temperatures. This investigation provided valuable information for assessing changes in rainfall and temperature and concluded that the study area is becoming warmer; an indication of global warming and climate change.
This study investigates air pollution from the Warri Refining and Petrochemical Company (WRPC) of... more This study investigates air pollution from the Warri Refining and Petrochemical Company (WRPC) of Delta Sate, Nigeria with the intent of determining the variations in pollution levels associated with increasing distance from the refinery. The following pollutant gases: Carbon monoxide (CO), Volatile organic compounds (VOC), Hydrogen sulphide (H2S), Nitrogen dioxide (NO2), Sulphur dioxide (SO2) and Particulate Matter (PM2.5 and PM10), were monitored intermittently with the use of digital hand-held probes, at sampling points located between 1,500 meters to 16,000 meters from WRPC. Air sampling was carried out on a weekly basis, for a duration of one (1) year. The average annual concentration of CO, VOC, H2S, NO2, SO2, PM2.5 and PM10 measured were 0.2543 ppm, 4.4922 mg/m3, 0.0004 ppm, 0.0063 ppm, 0.5263 ppm, 36.3825 µg/m3, 91.7346 µg/m3 respectively. The results of the spatial analyses of air pollutants show that concentrations of VOC, NO2, PM2.5, and PM10 shared a significant inverse relationship with distance (p values 0.00 ≤.0.05). The study suggests a minimum of 10,250 meters radial extent of buffers around WRPC, as a long-term strategy in reducing exposure of residents to air pollution. Short-term strategies include enforcement of legislation reducing/banning emissions from industries and bush fires, use of alternative eco-friendly technologies and energy sources, tree planting, revamp of the hydroelectricity power sector and general sanitization of the environment.
This study determined the effects of seasonality on air pollution in a tropical city of Southern ... more This study determined the effects of seasonality on air pollution in a tropical city of Southern Nigeria. This was with a view to acquiring data that would be useful in policy formulation and planning for proper management of ailments that result from seasonal variation of air pollution in the study area. Sampling for the study covered a period of six months, between mid-October 2013 and mid-April 2014. Air pollutants, taken into consideration, include particulate matter (PM0.3, 0.5, 1.0, 2.5, 5.0 and 10µm) and carbon monoxide (CO). Particulate matter was measured using a hand-held particle counter, while CO was measured with a single gas monitor (T40 Rattler). Five sampling points were selected based on stratified sampling technique, which represented five land use types monitored in the study area. Sampling was carried out twice in a week in accordance with the guidelines of Central Pollution Control Board, Delhi India. Sampling height was two meters above ground level. The student T-test was used to determine significant differences in monthly mean concentration of air pollutants across dry and wet seasons. The results revealed the dry season with mean values of 248568.19, 64639.04, 11140.21, 2810.39, 665.84, 320.80 particle counts for PM0.3, 0.5, 1.0, 2.5, 5.0 and 10µm and 3.01 ppm for CO concentration, was characterized by higher concentration of pollutants, while the rainy season with a mean values of 94728.24, 24745.69, 4338.29, 1158.11, 262.69, 131.36 particle counts for PM0.3, 0.5, 1.0, 2.5, 5.0 and 10µm and 2.70 ppm for CO concentration was characterized with less concentration of pollutants. The study concludes that seasonality significantly influences the concentration of pollutants in the city.
The study assesses potential variables which influence the concentration of air pollution around ... more The study assesses potential variables which influence the concentration of air pollution around a point source. Seven categories of air pollutants were monitored around the Warri Refining and Petrochemical Company (WRPC) of Nigeria, which comprised carbon monoxide (CO), volatile organic compounds (VOC), Hydrogen sulphide (H 2 S), Nitrogen dioxide (NO 2), Sulphur dioxide (SO 2) and Particulate Matter (PM 2.5 and PM 10). Sampling points were located in the range of 1.5 km to 16 km. Air quality was sampled intermittently and weekly for one year. Ttest analyses was used to determine significant differences in air pollutant concentration on the basis of orientation and seasonality. Regression analysis was also used to assess the influence of selected predictors on pollutant concentration around WRPC. Except for H 2 S, the prediction models for CO, VOC, SO 2 , NO 2 , PM 2.5 and PM 10 were statistically significant with R 2 values of 0.014, 0.215, 0.022, 0.582, 0.17 and 0.45, respectively. The results revealed that the concentration of pollutants was influenced by the combination of the factors (distance from WRPC, orientation from WRPC, seasonality and climatic variables such as atmospheric temperature, relative humidity and wind speed), which served as the predictors in the model. The study recommends that arrangements of industrial and residential land uses by urban planning authorities be patterned, taking into consideration factors such as distance and orientation from pollution point-sources.
Uploads
Papers by Verere S Balogun