Assessment of Air Pollution in Gboko, Benue State, Nigeria

The study assessed the spatio-temporal and seasonal variation in the concentration of CO, NO2, SO2 and PM10 in Gboko, Benue State, Nigeria. Data on the air pollutants were collected at four points between 8:00am-10:00am and 3:00pm-5:00pm daily, from 16 January to 24 February (dry season) and 5 June to 14 July (rainy season) in 2017 using Gasman hand-held gas monitors. Data were analysed using mean, coefficient of variation (CV) and Analysis of Variance (ANOVA). The result showed highest and lowest mean concentrations of CO of 21.86ppm (rainy season) and 17.00ppm (dry season) in the town center (Point 2, GBKC) and 2.46ppm (rainy season) and 2.45ppm (dry season) in the suburb (Point 1, YRA). The mean concentrations of CO, NO2 and SO2 were higher in rainy season, and the mean concentration of PM10 was higher in dry season, with the mean concentrations of NO2, SO2 and PM10 higher than the national acceptable levels in both seasons. The spatial variation in concentration of the air pollutants was significant with respect to land use/land cover types than seasons. There should be regular monitoring of air quality as the population and human activities increase in the town.

Studies have demostrated the bidirectional relationship between air pollution and climate. Rain washes pollutants out of the air so that there is improved air qaulity after prolong rain. Wind disperses air pollutants and temperature inversion worsens air pollution by trapping pollutants close to the ground (Landsberg, 1981;Manning et al., 2001). Urban heat island is demostrated to impact positively on air pollutants (Sarrat et al., 2006) and SO 2 , NO x and dust are found to be positively correlated with land surface temperature (LST) (Weng & Yang, 2006). On the other hand, air pollution is reported to affect urban thermal structure due to changes in radiative budget (Atwater, 1977), increase in cloud cover by 5% (Kaufman & Koren, 2006), linked to adavance and intensification of Asian monsoon (Lau et al., 2005) and increase in the concentration of Cloud Condensation Nuclei (CCN) and cloud drops (Shepherd, 2005).
Nigeria is one of the fastest urbanising countries in Africa. According to United Nations (2018) report, 98 million people, representing 50.3% of the total population, live in towns and cities in Nigeria in 2018. Several studies have been carried out on different aspects of air pollution in some cities and towns in the country (Tyubee, 2008;Oluyemi & Asubiojo, 2001;Abam & Unachukwu, 2009;Utang & Peterside, 2011;Okunola et al., 2012;Hassan & Abdullahi, 2012;Yusuf et al., 2013;Akinfolarin et al., 2017). Yusuf et al. (2013) adopted Factor Analysis (FA) to assess the spatial distribution and estimate the major sources of seven pollutants in Lagos and found that Factor 1, comprising CO, SO 2 , H 2 S, Noise and PM 10 , and Factor 2, comprising CH 4 and NO 2, contributed 43.72% and 17-53% to the total variation in concentration of the pollutants. Hassan and Abdullahi (2012) assessed variation in low explosive limit (LEL) gases, H 2 S and CO in densely populated Abuja Municipal Area Council (AMAC) and Kuje Area Council (KAC), and Dobi village in Gwagwalada Area Council (GAC) and reported that the concentration of the pollutants were higher in AMAC, Abuja metropolitan area, in both wet and dry season. In their study, Akinfolarin et al. (2017) documented the status of particulate matter (PM 2.5 and PM 10 ) in three industrial sites and one non-industrial site in Port Harcourt and reported higher concentration of particulate matter in industrial sites compared to non-industrial site. Tyubee (2008) investigated the effect of Urban Heat Island Intensity (UHII) and Urban Wind Speed Intensity (UWSI) on CO, NO, and SO 2 concentrations in Makurdi and found that the combined effect of the two proxies of urban growth varies from 2% (SO 2 ; 9:00am) to 24% (CO; 3:00pm), and mean concentrations of the pollutants exceeded the tolerance limit of Federal Environmtal Protection Agency's (FEPA) National Ambient Air Quality Standards (NAAQS). Abam and Unachukwu (2009) study on the impact of vehicular emmission on CO, NO 2 , SO 2 , PM 10 and Noise in three locations in Calabar found that the concentration of NO 2 and PM 10 , and Noise level were highest where traffic intersections and traffic count were high.
With the increasing rate of urbanisation in Nigeria, the number of urban dwellers vulnerable to the negative health impact of or expose to the health risks associated with air pollution may likely increase. 40 www.scholink.org/ojs/index.php/uspa Urban Studies and Public Administration Vol. 3, No. 4, 2020 This situation will be worsened in towns and cities that lack planning ordinance relating land use zonation, experience collapse in public energy supply and over depend on biofuels for household, commercial and industrial energy supply. Studies on urban air pollution in the country are crucial for policy and decision making in urban planning, environmental and public health, sustainable energy and environmental conservation. The main objectives of the study are to (1) investigate the spatio-temporal and seasonal variation in concentration of CO, NO 2 , SO 2 and PM 10 , (2) compare the mean concentrations of the pollutants with the NAAQS of the country and (3) determine whether the spatial variation in concentration of the air pollutants among land use/land cover types and climate seasons was significant or not.

Study Area
Gboko, the second largest town in Benue State, Nigeria, is located in the southern part of Gboko Local It is widely believed that half of the population of the Gboko LGA, which grew from 361,000 people in 2006 (National census data) to a projected population of approximately 490,000 people in 2016 using 3.0% growth rate per anum, lives in the town.
The study area experiences a tropical wet and dry climate (Aw) with a characteristically rainy and dry season. The rainy season occurs from April to October and dry season from November to March ( Figure 2). Annual rainfall ranges from 900-1900mm, with a mean annual rainfall of 1300 mm  and 94% of the total rainfall occurs in the rainy season. The prevailing wind direction is 41 www.scholink.org/ojs/index.php/uspa Urban Studies and Public Administration Vol. 3, No. 4, 2020 NE in the dry season, and SW in the rainy season. The mean monthly temperature peaks in March/April (30 o C) and then decreases to 27 o C in January and the mean temperature of the study area is 28 o C.

Data Collection
Data on the concentration of carbon dioxide (CO), nitrogen dioxide (NO 2 ), surful dioxide (SO 2 ) and particulate matter (PM 10 ) were collected twice daily between 8:00am-10:00am and 3:00pm-5:00pm from 16 th January to 24 th February (dry season) and 5 th June to 14 th July (rainy season) in 2017 using Gasman hand-held gas monitors acquired from Benue State Environmental Sanitation Agency (BENSESA), Makurdi (Plate 1). Data collection on air pollutants were carried out, on working days only, by a staff of BENSESA assigned for that purpose. Initially, data on hydrogen sulfide (H 2 S) were collected but not used in the study.

Plate 1. Hand-Held Gasman Pollutant Monitors Used in the Study (Photo by Grace H. Yiyeh)
A total of four locations were selected in the study area to represent the dominant land use/land cover (LULC) types and population density in order to assess the impact of LULC types on air pollutants.
The choice of dry and rainy season is to examine the influence of climate on air pollution. The spatial location of the selected study points and their characteristics are presented in Figure 1 and Table 1

Data Analysis
Frequency distribution tables, means and Coefficient of Variation (CV) were used to analyse the data.
Analysis of Variance (ANOVA) was used to test the hypotheses that variation in concentration of air pollutants was not statistically significant among LULC types and climate seasons. The result was also compared to the National Air Quality Control Standards (NAAQS) as stipulated by National Environmental Regulations (NER) (2014) to assess whether the mean concentrations of the air pollutants exceed the acceptable limits.

Daily Variation in the Concentration of Pollutants in the Dry Season
The result of daily variation in the concentration of CO, NO 2 , SO 2 and PM 10 in the dry season is presented in Figures 3-6, and Table 2  were highest and least in Point 2 (GBKC) and Point 1 (YRA) ( Table 2). The daily variation in concentration of CO was higher and least in Point 2 (GBKC) and Point 3 (GRA) with CV of 35.13% and 28.54% (Table 2). The town center, as expected, has higher CO concentration, while the suburbs have lower concentration. The result clearly demostrates a typical urban-rural gradient of CO concentration.   Vol. 3, No. 4, 2020 whereas the day-to-day variation in the concentration was highest in Point 3 (GBKC) with a CV of 22.58% and lowest in Point 1 (YRA) with a CV of 15.71% (Table 2).
The daily variation in concentration of SO 2 in dry season is similar to that of NO 2 ( Figure 5). However, the highest daily concentration of 0.23ppm was observed on 18 th January in Point 1 (YRA). In addition, Point 1 (YRA) and Point 2 (GRA) have the largest and least daily variation in SO 2 concentration with CV of 22.47% and 5.22% respectively ( Table 2).
The daily variation in concentration of PM 10 in dry season shows that the beginning and end of the study period were very active in terms of emissions in all the four Points, and the highest and least daily concentration of 2.56mg/m 3 and 0.10mg/m 3 occured on 20 th January in Point 2 (GRA) and 28 th January in Point 1 (YRA) (Figure 6). The concentration of PM 10 was highest in Point 2 (GRA), with a mean of 1.01mg/m 3 , and least in Point 1 (YRA), with a mean of 0.68mg/m 3 whereas the day-to-day variation in concentration of PM 10 is highest in Point 2 (GRA), with a CV of 97.89%, and least in Point 3 (GBKC), with a CV of 31.96% (Table 2).

Daily Variation in Concentration of Pollutants in the Rainy Season
The result of daily variation in concentration of CO, NO 2 , SO 2 and PM 10 in rainy season is presented in Point 2 (GRA) with CV of 32.72% and 22.10% (Table 3). The result clearly shows a typical urban-rural gradient of higher and lower CO concentration in urban and rural areas.
For NO 2 , the highest daily concentration of 0.34ppm occurred on 29 th June in Point 3 (GBKC) and least daily concentration of 0.10ppm occurred in all Points but on different dates (Figure 8) concentrations of NO 2 were highest and least at Point 3 (GBKC) and Point 1 (YRA), with mean of 0.16ppm and 0.11ppm respectively, and the CV varies from 33.22% (Point 3, GBKC) to 16.29% (Point 1, YRA) ( Table 3).
As is shown in Figure 9, the daily variation in concentration of SO 2 in the rainy season is generally uniform among the four points, and the highest daily concentration of 0.26ppm occurred on 29 th June in Point 4 (Rice Mill). However, the day-to-day variation was relatively higher and lower in Point 4 (Rice Mills) and Point 1 (YRA) with CV of 31.36% and 22.96% respectively ( Table 3).

Seasonal Variation in Concentration of Air Pollutants
The results of mean seasonal concentrations of CO, NO 2 , SO 2 and PM 10 , presented in Figures 11-14, are compared with the National Ambient Air Quality Standards (NAAQS) as stipulated by NER (2014) using 24-hour average concentration for SO 2 (120μg/m 3 or 0.0458ppm), NO 2 (120μg/m 3 or 0.0677ppm) and PM 10 (150μg/m 3 or 0.150mg/m 3 ), and 1-hour average concentration for CO (10 mg/m 3 or 11.46ppm) to ascertain whether the concentrations are within or above the acceptable limit. Figure 11 shows that the mean concentration of CO was higher in rainy season (9.67ppm) compares to dry season (7.83ppm), and mean concentrations of CO are consistently highest in Point 3 (GKBC) in both seasons, followed by Point 2 (GRA) and least in Point 1 (YRA). However, only the mean concentrations in Point 3 (GBKC), for both seasons, and Point 2 (GRA), for rainy season, are above the national acceptable limit of 10mg/m 3 (11.46ppm).
The mean seasonal concentrations of SO 2 and NO 2 are presented in Figures 12 and 13. The pattern of mean seasonal concentrations of both gases is similar though the mean season concentrations are higher in rainy season compared to dry season. However, the seasonal concentrations of both gases have exceeded the national acceptable limit of 120μg/m 3 or 0.0458ppm (SO 2 ) and 120μg/m 3 or 0.0458ppm (NO 2 ).
The result of seasonal variation in PM 10 shows that the mean concentration is higher during dry season   Vol. 3, No. 4, 2020 least in Point 1 (YRA) with mean of 0.49mg/m 3 (rainy season) and 0.68mg/m 3 (dry season) (Figure 14).
The mean seasonal concentrations of PM 10 in all the points and seasons have exceeded the national tolerance limit of 0.15mg/m 3 .

Testing for Spatial Variation in Concentration of Pollutants among Land Use/Land Cover Types
The null hypothesis (Ho), there is no significant variation in the concentrations of pollutants among land use types in Gboko (i.e., pollutants concentrations = land use types = 0), is tested using one-way analysis of variance (ANOVA) at 0.05 confidence level. The result is presented in Table 4 and shows that Ho is rejected since the calculated F value (18.63) is higher than the critical F table value (3.24) at 0.05 confidence level. The result indicates that there is a significant spatial variation in the concentrations of air pollutants among the four points in Gboko town. This suggests that the observed differences in the level of concentration of air pollutants in different parts of Gboko town during the study period did not occur by chance but are influenced by underlying LULC types.

Testing of Seasonal Variation in Concentration of Air Pollutants
The null hypothesis (Ho), there is no significant variation in concentrations of pollutants between the climate seasons in Gboko (i.e.,pollutants concentrations = seasons = 0), is tested using one-way analysis of variance (ANOVA) at 0.05 confidence level. The result is presented in Table 5 and shows that Ho is accepted since the calculated F value (1.60) is lower than the critical F table value (5.32) at 0.05 confidence level. The result indicates that there is no significant difference in variation in the concentration of air pollutants in dry and rainy seasons in Gboko town. Therefore the null hypothesis is accepted, while the alternative is rejected. This suggests that climate is not a major factor in the observed spatial differences in seasonal variation in concentration of air pollutants in Gboko town during the period of study. Note. Critical table value of F at 0.05 confidence level is 5.32.

Discussion
The spatial variation in air pollutants suggests a strong link between emmissions of pollutants and human activities. The higher concentration of CO in Point 2 (GBKC), the town center, is due to higher human and vehicular activities particularly the use of biofuels such as premiun motor spirit (PMS), kerosine, charcoal and fuelwood which are the major sources of CO. In addition, higher CO concentration in the town center may be attributed to decrease in vegetation cover that sequestrates carbon from the atmosphere thus lowering the atmospheric concentration of CO.
The higher mean concentrations of NO 2 and SO 2 in the rainy season is attributed to secondary sources in the atmosphere, through oxidation of nitric oxides (NO) and sulfur oxides (SO x ) to form NO 2 and SO 2 (Oke, 1987). Primary sources of NO 2 and SO 2 emissions include incomplete combustion in vehicles, electricity generators, rice milling mechines and other electrical appliances that use biofuels.
Higher concentrations of PM 10 in the dry season is related to the Saharan dust plume associated with the NE trade winds which prevail during the dry season, and locally derived dust from roads, markets, exposed and desiccated soils and fires. This is in agreement with Akinfolarin et al. (2017) Vol. 3, No. 4, 2020 from the area of plume deposition of cement factory (Ujoh et al., 2014) that may have influenced PM 10 concentration. Bush and agricultural fires are major sources of particulate matter (Cusworth et al., 2018) that are also common in dry season in Gboko town.
The higher mean concentrations of NO 2 , SO 2 and PM 10 , above the acceptable levels, indicate that the town's atmosphere is polluted and urban dwellers are exposed to the health related risks of air pollution.
Particulate matter (PM 10 ) is mostly associated with respiratory diseases (Ediagbonya & Tobin, 2013), while NO 2 and SO 2 are related to pulmonary and cardiovascular diseases (Oke, 1987).
The result of test of significant variation of air pollutants comfirms land use/land cover as the major factor of urban air pollution. This agrees with Utang and Peterside (2011)  Guangzhou city (Weng & Yang, 2006), Wuhan  and Changsha-Zhouzhou-Xiangtan (CZT) agglomeration (Zou et al., 2016). The result of non-significant variation of air polluants in dry and rainy season is attributed to the fact that micro climates of cities differ significantly from the regional (macro) climate, with local pollution dispersion patterns relating more to the latter than the former. For instance, eddies caused by mechanical convection, due to buildings and chanelling effects on winds by streets orientation, may impact local dispersion of pollutants more than regional airflow.
This confirms Fameli et al. (2013) who found that the diurnal variation in O 3 in the Greater Athens Area (GAA) was influenced more by land and sea breeze than planetary winds.
The result of spatio-temporal and seasonal variation in the concentration of CO, NO 2 , SO 2 and PM 10 concentration has implication on sustainable and renewable energy in Gboko town. The use of alternative, cleaner and environmentally friendly energy sources for household and demestic use should be encouraged. The Federal Government in 2009 announced the replacement of fuel wood and kerosene, the dominant cooking fossil fuels and major sources of CO 2 in the country, with biofuels such as ethanol and biogas. The ethanol fuel, produced from cassava feedstock, has lower CO 2 emmission (Ohimain, 2013), and biogas fuel, produced from agricultural residues and wastes, would reduce 357-60, 952 tons of CO 2 per annum in the country (Akinbami et al., 2001).

Conclusion
The result of variation in concentration of CO, NO 2 , SO 2 and PM 10 among four land use/land cover types and two climate seasons indicated higher concentrations of CO in the center of Gboko town compared to the suburbs. The mean concentration of CO, NO 2 , and SO 2 were higher in rainy season compared to dry season, and the mean concentrations of PM 10 were higher in the dry season compared to the rainy season, with NO 2 , SO 2 and PM 10 concentrations higher than the national acceptable levels in both seasons. The result of test of spatial variation in concentration of the pollutants showed that the variation was only significant among the four points compared to the seasons, suggesting that land use/land cover types have greater influence on spatial distribution of air pollutants than climate. 54 www.scholink.org/ojs/index.php/uspa Urban Studies and Public Administration Vol. 3, No. 4, 2020 Stationary air pollution monitoring and meteorological stations should be established in Gboko for regular monitoring of air quality as the population and human activities increase and to provide baseline data for numerical simulations and empirical statistical modelling in analysing the relationship between land use and air pollution in the town. The influence of urban heat island induced circulation (UHIC), due to temperature gradient between the high pressure (cooler and moist condition) over the Mkar hills, in the east, and the low pressure (warmer and dry condition) in the town center, on spatial distribution of air pollutants in the town needs further scientific investigation.