Table 1: Basic Description of the AQI Results
|
AQI
|
O3
|
PM2.5
|
PM10
|
CO
|
NO2
|
SO2
|
Mean
|
117.31
|
44.87
|
117.4
|
66.87
|
5.48
|
6.84
|
6.58
|
Std Dev
|
73.33
|
16.32
|
55.95
|
27.4
|
2
|
6.94
|
6.25
|
Coef. Var
|
62.51
|
36.36
|
47.66
|
40.98
|
45.45
|
101.49
|
94.96
|
Minimum
|
41
|
15
|
41
|
3
|
2
|
0
|
0
|
Maximum
|
153
|
118
|
645
|
143
|
19
|
37
|
42
|
Q1
|
88
|
35
|
88
|
45
|
4
|
2
|
3
|
Q3
|
153
|
51
|
153
|
83
|
6
|
7
|
8
|
Skewness
|
11.21
|
1.8
|
5.02
|
0.69
|
2.22
|
1.89
|
2.33
|
Kurtosis
|
15.8
|
4.18
|
39.68
|
-0.19
|
7.76
|
3.07
|
7.11
|
The overall AQI of all locations is 117.31, with minimum and maximum values ranging from 41 to 184, respectively (Table 1). Kura (Kano State) and Idi Iroko (Ogun State) have maximum (184) and minimum (41) levels, respectively. According to the study, the ranges between 169 and 184 are obtained from the northern part of the country.
Figure 2 (a-g) shows graphical representations of the AQI for the various towns. According to the graphs, the highest values for pollutants are: 184 (Kura), 19 (Kura), 37 (Sokoto), 118 (Katgum), 645 (Burum Burum), 143 (Burum Burum), and 42 (Mongonu) for AQI, CO, NO, O3, PM2.5, PM10, and SO2. Furthermore, based on the observations, the highest concentrations of pollutants are mostly found in the country's northern regions. The high levels could be attributed to the area's intense fighting and insecurity, as well as the burning of farm waste, wood for cooking, and fossil fuels. Meteorological factors may also play a role here. There is little or no rainfall, for example, which could have washed or dissolved the pollutants. Because there is little or no rain, the temperature will be high, the humidity will be low, and the wind speed will be slow, resulting in high concentrations of pollutants. Environmental (anthropogenic) factors have a greater impact on air quality than meteorological conditions alone (Akinwumiju et al., 2021).
These air pollutant AQI variations have never been reported in Nigeria. Figure 3 depicts the daily patterns of the six pollutants (PM2.5, PM10, SO2, CO, NO2, and O3) (a & b). Table 1 also includes a summary of the variations in pollutant concentrations. In terms of air pollutant distributions, the level of PM2.5 in Burum Burum (Plateau State) is higher than in other towns. Burum Burum (143) had the highest PM10 concentration and the highest PM2.5 concentration (645), while Garko (Kano State) has the lowest PM10 concentration and Idiroko (Ogun State) has the lowest PM2.5 concentration (41). In general, local sources have the greatest influence on the spatial distributions of particulate matter pollutants. Changes in PM reflect changes in both primary and secondary particle emissions and reactions. The primary sources of PM are natural and anthropogenic processes such as road traffic and soil dust in urban areas (Charron et al., 2007; Hashim et al., 2021).
The concentration of O3 is relatively highest in Katgum, Bauchi State, northern Nigeria, and the lowest in Brass, Bayelsa State, South-South, Nigeria. It should be noted that the towns with high values of O3 above 100 are located in the northern part of the country. This could be because evidence abounds that climate change impacts in Nigeria result from climate change-related causes such as temperature increases and extreme weather events. The AQI level for the secondary pollutant ground-level O3 is determined by the rate of O3 formation via complex photochemical reactions, with the three determining factors being sunlight, NOx, and VOCs. However, the chemistry of O3 formation is highly nonlinear, and the effects of precursor concentrations on O3 production rate can be classified as NOx-sensitive or VOC-sensitive (Simon et al., 2015; Sillman 2020).
CO AQI is depicted in Figure 3a. The pictorial drawing depicts the disparities in the obtained levels on the communities. The communities in the northern states, as expected, have high values (Kura-19; Kano-17; Rano-16; Wudil-12; Sokoto-12; Katsina-12; and Burum Burum-12). Carbon monoxide is produced when fuels such as gas, oil, coal, and wood do not burn completely. Burning charcoal, running cars, and the smoke from cigarettes and shisha pipes, as well as running a car engine, petrol-powered generator, or barbecue (Suya spot) inside a garage, also produce carbon monoxide gas. When carbon monoxide is inhaled, it displaces oxygen in the blood, depriving the heart, brain, and other vital organs of oxygen. Large amounts of CO can overpower you in minutes, causing you to lose consciousness and suffocate.
The statistics (Table 1) clearly show the mean (6.84), minimum (0), and maximum (3) NO2 AQI loading levels over the country's north and south. The variation coefficient (101.49 percent). This is a large value, indicating that the results vary greatly across the 253 towns and villages. The obtained results are comparable to those obtained in Jamaica (Kingston-3), Paraguay (San Lorenso-4), Tonga (Fua'Amotu-0), and Israel (Kabul-9) (https://en.tutiempo.net). The variations could be attributed to meteorological and anthropogenic factors both before and during the monitoring. Nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO) are mostly colorless gases, in contrast to particulate pollutants. High-intensity exposure to these gases can cause serious harm, including death. Exposure to NO2 has an impact on both the respiratory tract and the human immune system. Sulfur dioxide (SO2) is linked to a number of respiratory issues.
Because of variations in SO2 pollutant, the city-wide mean concentrations of SO2 AQI in Nigeria increase from 0 to 42. As is customary, the high value is coming from the north (Mongonu). The figures obtained are comparable to those reported for Ghana (Gold Coast-28), Gambia (Banjul-3), Ethiopia (Jima-0), and Sudan (Jartum-1). SO2 can irritate the eyes and have an effect on the respiratory system and lung functions. Hospital admissions for cardiac disease and mortality rise on days with higher SO2 levels. According to the EPA, asthmatics are the most vulnerable. When SO2 reacts with water, sulfuric acid is formed, which is a key component of acid rain, which causes deforestation (Wang et al., 2018).
The Pie-Chart (Figure 4) depicts each pollutant's contribution to the environment over the course of a single day of monitoring. The most significant contributor, according to the graph, is PM2.5 (47 percent ). High particulate matter (PM2.5) concentrations are considered a serious environmental issue all over the world. Despite the fact that most research has focused on metropolitan and industrial cities, high PM2.5 episodes have also been observed in small and medium-sized cities (Byun et al., 2020). PM10>O3>NO2>CO>SO2 are some of the other contributions (27 percent, 18 percent, 3 percent, 2 percent, 2 percent respectively). The O3 values obtained in this study for the pollutants are significantly lower than the recommended limits for the 24 hour average and annual average in Table 3. The study's findings did not compare favorably with those of Xiao et al. (2018) because their air pollutants contributed to the environment in Chengdu's Inland Basin City, Southwest China, by contributing PM10 (18.9 percent), O3 (12 percent), and NO2 (0.8 percent).
There is a level of concern for human health based on the AQI values. Tables 2 and 3 are provided to categorize the levels based on the index's color, concern, and values. There are explanations and health effects provided. When the general AQI results (Figure 2a) are compared to the AQI chart in Table 2, it can be stated that Idiroko has the lowest value of 41 (Southwest), while Kura has the highest value of 184 (Northwest). The implication is that AQI of the selected towns are between ‘Good’ and ‘Unhealthy’. The low and high results obtained in this study are compared to the values reported on the Tutiempo Network website (https://en.tutiempo.net) for Europe (Italy: Bolonia-37; Turin-41; Florencia-35; Alexandra-37; Napoles-88), France (Marsella-41; Lille-68; Toulouse-41; Monteplier- 41; Lyon-40), Africa (Angola: Benguela-68; Kuito-41; N’dalatando-41, Madagascar: Antananarivo-112; Toliara-21; Toamasina-26; Fort Dauphin-31, Egypt: El Cairo-68; Suez-68; Alejandria: 68, South Africa: Ciudad del Cabo-164; Johannesburg-189; Soweto-169), South America (Argentina: Buenos Aires-38; Bahia Blanca-20; La Plata-25, Columbia: Bagota-41; Cartagena-101; Pereira-68, Uruguay: Montevideo-28; Rivera-20; Artigas-21), North America (Bahamas: High Rock-30; Alice Town, Bimini-37; Freeport, Grand Bahama-30, Nicaragua: Managua-20; Esteli-20; Tipitapa-20, Honduras: Tegucigalpa-41; El Progreso-68; San Pedro Sula-68; Ciudad Choluteca-38, Puerto Rico: San Juan-37; Buyamon-29; Guaynabo-30), Asia (China: Shanghai-184; Zhumadian-186; Beijing-110; Wuhan-153, Malaysia: Kuala Lumpur-169; Ipoh-88; Kuching-68; Sandankan-31, Japan: Tokyo-88; Yokohama-68; Fukuoka-shi-153; Kawasaki-68, India: Bombay-93; Delhi-179; Hyderabad-164), and Oceania (Australia: Sidney-68; Melbourne-33; Brisbane-41; Adelaide-41, Fiji: Lakemba-68; Lambasa-29; Nausori-41, Samoa: Afenga-31; Apia/Upolu Island-32; Malie-31). At the time of monitoring, none of the continents' AQIs exceeded 'Unhealthy.' It should be noted that some members of the community may suffer health consequences. The general public will be less affected. The AQI of the Americans is low, which may be due to strict adherence to clean air guidelines, and that of Oceania may be due to adherence to clean air guidelines and the weather of the surroundings-wet/cold region.
Table 4 displays the USEPA (2000) levels of concern and AQI descriptions for the pollutants. The health-based index used in this study was intended to alert people to potential health issues. In cases where AQI values are not associated with population-level health outcomes as part of an applied policy analysis, the multi-pollutant index based on regulatory levels may be able to better predict health risks. The values, health concerns, and colors on the table are as follows: i. (0-50, Good, Green) ii. (51-100, Moderate, Yellow) iii. (101-150, Unhealthy for sensitive groups, Orange), iv. (151-200, Unhealthy, Red), v. (201-300, Very Unhealthy, Purple), and vi. (301-500, hazardous, maroon). Government agencies use the air quality index (AQI) to inform the public about how unhealthy the air is now or may become in the future. The health risks increase as the AQI rises. It is a daily air quality index used to report on the state of the environment. Furthermore, a measure of how air pollution affects one's health over time. The AQI was created to assist people in understanding how local air quality affects their health. The study's findings should assist citizens in taking precautions to avoid health problems caused by pollutants.
Table 4: Levels of Concern and Description of AQI of the Pollutants (PM, O3, SO2, CO, NO2)
Values, Health Concern, Colour
|
Health Risks and Advice
|
|
Ozone (O3)
|
0-50 (Good), Green
|
None
|
51-100 (Moderate), Yellow
|
Unusually sensitive people should consider limiting prolonged outdoor exertion
|
101-150 (Unhealthy for sensitive groups), Orange
|
Active children and adults, and people with respiratory disease, such as asthma,
|
|
should limit prolonged outdoor exertion.
|
151-200 (Unhealthy), Red
|
Active children and adults, and people with respiratory disease, such as asthma,
|
|
should avoid prolonged outdoor exertion.
|
|
|
201-300 (Very Unhealthy), Purple
|
Active children and adults, and people with respiratory disease, such as asthma,
|
|
everyone else, especially children, should limit outdoor exertion.
|
301-500 (Hazardous), Maroon
|
Everyone should avoid all outdoor exertion.
|
|
Carbon monoxide (CO)
|
0-50 (Good), Green
|
None
|
51-100 (Moderate), Yellow
|
None
|
101-150 (Unhealthy for sensitive groups), Orange
|
Individuals suffering from cardiovascular disease, such as angina, should limit strenuous activity and minimize causes of CO, such as heavy traffic.
|
|
|
151-200 (Unhealthy), Red
|
Individuals suffering from cardiovascular disease, such asangina, should limit moderate exertion and avoid sources of CO, such as heavy traffic.
|
|
|
201-300 (Very Unhealthy), Purple
|
Individuals suffering from cardiovascular disease, such as angina, should avoid activity and sources of CO, such as heavy traffic.
|
|
|
301-500 (Hazardous), Maroon
|
Individuals suffering from cardiovascular disease, such as angina, should avoid activity and sources of CO, such as heavy traffic; others should limit heavy activity
|
|
|
|
Sulfur Dioxide (SO2)
|
0-50 (Good), Green
|
None
|
51-100 (Moderate), Yellow
|
None
|
101-150 (Unhealthy for sensitive groups), Orange
|
Asthmatics patients should consider limiting their outdoor activity.
|
151-200 (Unhealthy), Red
|
Youngsters, asthmatics patients, and individuals with heart or lung disease should
|
|
limit their physical activity outside
|
201-300 (Very Unhealthy), Purple
|
Youngsters, asthmatics patients, and individuals with heart or lung disease should avoid outdoor exertion; everyone else should limit outdoor activity.
|
|
|
301-500 (Hazardous), Maroon
|
Youngsters, asthmatics patients, and individuals with heart or lung disease should remain indoors; everyone else should avoid outdoor activity.
|
|
|
|
Nitrogen Dioxide (NO2)
|
0-50 (Good), Green
|
None
|
51-100 (Moderate), Yellow
|
None
|
101-150 (Unhealthy for sensitive groups), Orange
|
None
|
151-200 (Unhealthy), Red
|
None
|
201-300 (Very Unhealthy), Purple
|
Kids and people with respiratory diseases, such as asthma, should avoid strenuous
|
|
outdoor activity.
|
301-500 (Hazardous), Maroon
|
Kids and people with respiratory diseases, such as asthma, should avoid moderate or strenuous outdoor activity.
|
|
|
Particulate Matter (PM)
|
|
0-50 (Good), Green PM2.5
|
None
|
PM10
|
None
|
51-100 (Moderate), Yellow PM2.5
|
None
|
PM10
|
None
|
101-150 (Unhealthy for sensitive groups), Orange PM2.5
|
People with respiratory or heart disease, the elderly, and children should limit pro-longed exertion.
|
PM10
|
People with respiratory disease, such as asthma, should limit out-door exertion.
|
151-200 (Unhealthy), Red PM2.5
|
People with respiratory or heart disease, the elderly, and children should avoid prolonged exertion; every-one else should limit prolonged exertion.
|
|
|
PM10
|
Individuals with respiratory diseases, such as asthma, should avert strenuous outdoor activity; everyone, aged people and children, must also limit strenuous outdoor activity.
|
|
|
|
|
201-300 (Very Unhealthy), Purple PM2.5
|
Individuals with respiratory or heart disease, the older people, and children must also avoid all outdoor activities; others should avoid strenuous activity for an extended period of time.
|
|
|
PM10
|
Individuals with respiratory diseases, such as asthma, should avoid all outdoor activities; everyone around, particularly the older people and children, must limit their outdoor activity.
|
|
|
301-500 (Hazardous), Maroon PM2.5
|
All should avoid any outdoor activity; individuals with respiratory or cardiovascular disease, the old people, and children should stay indoors.
|
|
|
PM10
|
All should limit their outdoor activity; individuals with respiratory diseases, such as asthma, should stay indoors.
|
Table 5: Pearson Correlation Coefficient of the Pollutants
|
AQI
|
O3
|
PM2.5
|
PM10
|
CO
|
NO2
|
SO2
|
AQI
|
1
|
|
|
|
|
|
|
O3
|
0.12
|
1
|
|
|
|
|
|
PM2.5
|
0.36
|
0.29
|
1
|
|
|
|
|
PM10
|
0.31
|
0.52
|
0.52
|
1
|
|
|
|
CO
|
0.25
|
0.46
|
0.49
|
0.55
|
1
|
|
|
NO2
|
0.21
|
0.66
|
0.45
|
0.66
|
0.69
|
1
|
|
SO2
|
0.15
|
0.6
|
0.31
|
0.59
|
0.3
|
0.61
|
1
|
Different air pollutants are positively and significantly (p 0.01) correlated (Table 5). They either have a weak or strong relationship. Weakness is defined as values less than 0.5. There are significant correlations between PM10 and O3 (r=0.52), PM10 and PM2.5 (r=0.52), CO and PM10 (r=0.55), NO and O3, CO (r=0.66), SO2 and O3 (r=0.6), SO2 and PM10 (r=0.59), and SO2 and NO2 (r=0.61), indicating that these pollutants originated from the same sources (e.g., vehicle and wood/coal emissions) or were influenced by the same. Regulating traffic and wood/coal burning emission levels may thus be a method of simultaneously reducing the concentration levels of these pollutants. PM and O3 had a significant positive correlation. The correlation coefficients, on the other hand, were weaker, which can be attributed to the complex, nonlinear, and temperature-dependent chemistry of O3 concentration (Song et al., 2017, Chen et al. 2020). This implies that controlling O3 concentrations is difficult, and it suggests that more research into O3 formation and control strategies is needed in Nigeria.
The data distribution in each of the five locations using box and whisker plots is shown in Figure 5. It was performed to prove the differences in regular air pollutant concentrations. The box plot is basically a description of the underlying data's distribution. The box contains the interquartile range, with the bottom representing the first quartile (25th percentile), the middle line representing the median or second quartile (50th percentile), and the top representing the third quartile (75th percentile). The figure displays the corresponding five-number summary for the pollutants (minimum, first quartile, median, third quartile, maximum). It can be seen that the distribution of pollutants varies, implying that pollutants vary across the nation's urban and suburban areas.
Table 5 depicts the hypothesis that there is a relationship between the pollutants' AQI. Figure 6 is used to visualize and investigate the relationships between pollutants. Pollutants are strongly positively correlated, as evidenced by high Pearson's r values. The strong positive correlation between PM2.5 and PM10 demonstrated validates the findings of Janssen et al (2013). Since PM2.5 and PM10 are identified as particles with diameters of 2.5m or less and 10m or less, respectively, the correlation reveals that particle density varies stably with particle size. The positive correlation between pollutants indicates that PM2.5, PM10, and NO2 may be emitted by the same sources, or one may be emitted by the transformation of another through some type of chemical mechanism (Gong et al., 2015). To determine the specific reasons, a combined physical and chemical analysis of pollutants is desirable (Jeon et al., 2001).
Figure 7 depicts the time series of the AQI plots (a-g). The AQI trends show a small increase during the day, followed by a decrease during the night. This disparity is primarily containing high concentrations of O3, a secondary pollutant that is extremely sensitive to solar radiation (Wang and Lu, 2006). Low concentrations of nitric oxide (NO) in the monitoring station may contribute the most to the accumulation of O3. Because NO concentrations are low, it is less likely that the typical reactions of the Ozone Cycle will occur, resulting in its accumulation. Figure also depicts the trend of AQI in relation to the agglomeration where the monitoring station is positioned. Days with a high volume of vehicular traffic; in this context, high NO2 levels are identified, while O3 concentrations appear to be low (Famoso et al., 2014). Most likely, the high NO concentrations found on busy days trigger the reactions cycle characteristics of O3, greatly reducing their levels; conversely, high NO levels were found, as one of the final products of the ozone cycle (Lanzafame et al. 2015). Because the AQI of each pollutant varied, the days when the air quality standard was surpassed were not evenly distributed during the surveillance periods.