Over the decades there have been problems associated with Particulate Matter (PM) arising from anthropogenic activities. Evaluation and health risk assessment of PM associated with football field was carried out in 5 sampling locations, including the control station. Digital portable AEROCET 513 (Metone instrument) PM meter was used for the evaluation Results showed levels of PM for; PM1.0(13.73 – 20.18 µg/m3), PM2.5 (19.11 – 28.83 µg/m3), PM4.0 (24.73 – 44.63 µg/m3), PM7.0 (41.07 – 67.04 µg/m3), and PM10 ranging from 65.48 – 90.82 µg/m3. In addition, value of the control station was lowest amongst all recorded values of PM (p<0.05). Based on Air Quality Index evaluation, the football fields were predominantly rated as unhealthy, with other cases rates as; hazardous and unsafe for sensitive group. This investigation therefore concludes that the emission of PM from the football field are reflection of vehicular emissions and agitated dust particles. Hence mitigable measure must be applied without much ado, in order to ameliorate the daily chronic exposure to PM.
Academic Editor: Wei Wu, Nanjing Medical University, China
Checked for plagiarism: Yes
Review by: Single-blind
Copyright © 2019 Enetimi I Seiyaboh, et al.
The authors have declared that no competing interests exist.
Air pollution is the release of substances that are capable of infringing on ambient quality of the air 1, 2. The adverse effects of the pollutant might be acute or chronic, depending on the on the specie, concentration, physical, biological or chemical properties of the pollutant 3. Pollution is also seen as a process that involves the infringement of the environment by substances capable of inducing adverse effects to the environment including other forms of biota 4, 5, 6. Air pollutants includes organic or inorganic agents such as particulate matter, microbes, heavy metals, metabolites etc 2. Statistically, on annual basis there are over two million global cases of mortality linked to air pollution, with adverse effects on the respiratory system 7. Furthermore, most cases of mortalities were due to emission of fine PM whose size is less than 2.5 µm in diameter 7, 8.
Particulate matter is a compounding aggregation of solid or liquid particulates that is suspended or persistent in the air over a period of time. Particulate matter vary in sizes, notwithstanding, they are broadly characterized as fine (≤2.5 µm), and coarse PM whose diameter is greater than 2.5 µm. Finer PM poses more health problems due to their ability to penetrate the lung as opposed to coarse and larger PM 8. For instance, PM1.0 which is a fine PM and rated as the most lethal, with cases of infant mortality and heart problems 9.
As established in literature by Araújo et al., 1, in the regulatory determination of the extent of pollution in any country, it is habitual to establish references backgrounds. These air quality background will be become standards that describe the threshold concentration of air pollutant, whose exceedances can affect biodiversities 1, 10. Currently, there are no comprehensive air quality backgrounds for most developing countries as most researchers often depends on guideline from the World Health Organisation 11. The study area (Yenagoa Metropolis), is the State Capital Territory of Bayelsa State. It is a wet land located on the southernmost part of Nigeria. It has a deltaic landmass, and characterized by shallow aquifer with several networks of creek and creeklets. It have two prevailing seasons, which are dry and wet season. During the dry season it is usually windy and dusty with no precipitation, while in wet season there is high level of precipitation 12. Yenagoa metropolis is the capital city of Bayeslsa state, and with dusty football field having poor vegetation cover, in addition to their proximity to traffic zone. Engagement of this field for sporting activities might induce exposure to suspended particulate matter. As such this investigation has become necessary.
Material and Method
The sampling of particulate matter was carried out in 4 randomly selected football field, and a control station (a garden). The four sampling stations were randomly selected with distance of about 1km apart, while the control station had a distance of over 2km. Portable Metone AEROCET 531 Particulate matter meter was used during the sampling. During sampling, the meter was power on with the probe facing the windward direction. The meter runs for approximately 1 minute, after which the result was ready for reading on the screen. Depending on the sizes of the particulate matter, the meter spetiates particulates based on their diameter per cubic meter (µg/m3). As such particulates are characterized as PM1.0, PM2.5, PM4.0, PM7.0, PM10 and Total Suspended Particulate (TSP).
Air Quality Index (AQI)
The Air Quality Index (AQI) is a model scheme developed to quantify the health risk for air quality in the atmosphere, based on individual air quality and a certain reference of background value. This may include; geometric mean, control or the regulatory limit value of the geographical area 13, 14. The health risk was calculated using the AQI scheme of Lingan et al., 13, with slight modification. The health risk values were calculated using the AQI equation below. Furthermore, magnitude of the health risk were interpreted based on value ranges, with different colour codes as presented in Table 1. The value of the control station (VS) was used as the reference background.Table 1. Scheme for assessment of Air Quality Index
|Safe0 -50||Moderate51 - 100||Unsafe for Sensitive group 101 - 150||Unhealthy151 - 200||Very Unhealthy201 - 300||Hazardous>301|
Where V is individual concentration of particulate matter (PM) VS is the particulate matter (PM) value of the control station
All results are expressed as Mean ±Standard Deviation. Analysis of variance was carried out. The applied Post-Hoc was used to establish differences was Duncan’s multiple range test (P<0.05). The Mean data were used to plot charts using Microsoft excel (2013 version).
Result and Discussion
Result on the spatial levels of particulate matter associated with the football field is presented in Figure 1. Based on spatial distribution of the football field, higher levels of PM1.0 particulate matter ranging from 13.33 – 20.39 µg/m3was reported, compared to the control station that had the lower value (9.97 µg/m3). However, the highest level of PM1.0 particulate matter was reported in station L4 (Figure 1). On the other hand the lowest value was reported in station L1. Moreover, based on the model for health risk of PM1.0 particulate matter associated with the football field indicated that it was unsafe for sensitive group in station L1. An unhealthy condition was indicated in stations; L2 and L3, while station L4 indicated a very unhealthy condition (Table 2).
The level of PM2.5 particulate matter associated with the football field ranged from 19.11 – 29.83 µg/m3. The highest value was reported in station L4, while the lowest value was reported in station L1 (Figure 1). In addition, the control station (13.27 µg/m3) indicated the lowest level of PM2.5 particulate matter (Figure 1). Based on the model for health risk assessment, the levels of PM2.5 particulate matter station L1 was unsafe for sensitive group, stations L2 and L3 were unhealthy, while station L4 was very unhealthy (Table 2).
Based on spatial distribution, the levels of PM4.0 particulate matter in the football field ranges from 24.73 – 44.63 µg/m3, with a much more lower value in the control station (19.45 µg/m3) as presented in figure 1. In addition the highest level of PM4.0 particulate matter was reported in station L4, while the lowest value was reported in station L1 (Figure 1). Based on health risk assessment, PM4.0 particulate matter it was unsafe for sensitive group in station L1. Meanwhile it was unhealthy in station L3 (Table 2). Stations L2 and L4 indicated a very unhealthy condition (Table 2).Table 2. Health Risk Assessment of Air Quality in the Study Area
|Safe0 -50||Moderate51 - 100||Unsafe for Sensitive group 101 - 150||Unhealthy151 - 200||Very Unhealthy201 - 300||Hazardous>301|
As presented in Figure 1, the spatial levels of PM7.0 particulate matter ranges from 41.07 – 67.04 µg/m3, with a lower value in the control station (33.41 µg/m3). Meanwhile, the highest and lowest values of PM7.0 particulate matter was reported in stations L4 and L1 respectively. Based on the modelling for health risk assessment of the football field, station L4 was very unhealthy, station L1 was unsafe for sensitive group, while stations L2 and L3 was unhealthy (Table 1). The spatial level if PM10 particulate matter associated with the football field ranges from 65.48 – 90.82 µg/m3(Figure 1). Meanwhile, the highest level of PM10 particulate matter was indicated in station L2, while the lowest value was indicated in station L1 (Figure 1). Notwithstanding, based on model for health risk assessment of the football field, stations L1and L3 were unhealthy for sensitive group, while L2 and L4 were rated to be unhealthy.
Result of this study is comparable to previous study of Angaye et al. 2, for temporal spatiation of particulate matter (dry and wet season respectively), associated with dumpsites for; PM1 (17.04 – 32.81and 14.03 – 19.03 µg/m3), PM2.5 (23.11 – 44.87 and 20.41 – 32.07µg/m3), PM4 (32.03 – 62.80 and 29.82 – 50.54 µg/m3), PM7 (75.01 – 197.11 and 45.17 – 71.27 µg/m3), PM10 (109.40 – 305.10 and 56.53 – 93.07 µg/m3), and Total Suspended Particulate (227.66 – 597.26 and 72.40 – 172.23 µg/m3). The result indicated that levels of particulate matter in dry season was significantly (p<0.05) higher compared to wet season.
As established in literature by several authors, ambient air quality in major cities across Nigeria's have been impaired by emission of Particulate Matter. Total Suspended Particulate ranging from 1033 - 40000 μg/m3 in industrial area of Lagos city 15. In Maiduguri and Abuja PM10 ranging from 118.3 - 132.0 μg/m3 was reported 16. In some randomly selected Lagos levels of PM2.5 and PM10 were 27 and 69 μg/m3 respectively 17. In Abuja and Aba the level of PM2.5 were 14 μg/m3 and 102 μg/m3 while PM10 level were reported as 38 μg/m3 and 553 μg/m3.
The reports of Obioh et al. 11, has revealed PM10 concentration of 38 μg/m3 in Abuja and 553 μg/m3 in Aba; and PM2.5 concentration varying between 14 μg/m3 in Abuja and 102 μg/m3 in Aba. Ideriah et al. 18, have evaluated TSP concentrations in the range of 19.0 -1677.9 μg/m3 in five communities in southeastern Nigeria. A study by Ohimain et al. 19, at a palm oil processing industry in Elele, Rivers recorded the TSP values between 1634 and 7853 μg/m3. These reported PM values were greater than the US-EPA daily and annual mean standards of 150 and 50 μg/m3, respectively. Another study at a steel and iron industry in Lagos by Owoade et al. 17, for PM10 and PM2.5 revealed concentration ranges of 86 - 8765 μg/m3 and 10 - 462 μg/m3, respectively. High concentrations of these PM size fractions may be harmful to the public, especially the residents living around the vicinity of the steelworks industry.
Higher level of particulate matter exceeding regulatory limits of the World Health Organisation (90 μg/m3) have been previously reported across major cities in Nigeria. For instance, the value of PM10 and Total Suspended Particulate (TSP), ranging from 118.3 -132.0 and 1033 to 40000 μg/m3 were reported 16. As reported by several authors, health cases linked to exposure of particulate matter includes but not limited to; untimely death of persons who present cases of heart or lung infection, intensified asthma, heart attacks, asymmetrical heartbeat, deteriorated lung function, and amplified respiratory symptoms which includes; coughing, irritation of the airways, or difficulty breathing 20, 21, 22, 23.
Evaluation and Health Risk Assessment of Particulate Matter around football field of Yenagoa Metropolis Nigeria was investigated. Model for Air Quality Index (AQI) was used to determine the health risk. Unfortunately, most of the all the football field had significant levels of particulate matter for PM1.0, PM2.5, PM4.0, PM7.0 and PM10. Based on AQI modelling, none of the playground relatively. Health risk indications were; unsafe for sensitive group, unhealthy and very unhealthy. The levels of particulate matter emission is a reflection of anthropogenic activities from agitated dust particles from poor vegetation cover of the field, we also recommend the monitoring of air quality in public places in order to avert chronic intake of particulate matter.
- 1.Araújo I P S, D B Costa, Morales R J B de. (2014) . , Identification and Characterization of Particulate Matter Concentrations at Construction Jobsites.Sustainability 6, 7666-7668.
- 2.Angaye T C N, Abowei J F N. (2018) Evaluation of suspended particulate matter (SPM) around municipal solid waste dumpsites in yenagoa metropolis,Nigeria. , MOJ Toxicol 4(2), 54-57.
- 3.Daly A, Zannetti P. (2007) An Introduction to Air Pollution—Definitions, Classifications, and History. Chapter 1 of Ambient Air Pollution;Zannetti,P.,Al-Ajmi,D.,Al-Rashied,S.,Eds.;The Arab School for Science and Technology (ASST), The Enviro Comp Institute: Freemont. , CA, USA
- 5.Brauer M, Amann M, Burnett R T, Cohen A, Dentener F et al. (2012) Exposure assessment for estimation of the global burden of disease attributable to outdoor air pollution Environ. , Sci Technol 46, 652-60.
- 6.Kim K-H, Jahan S A, Kabir E. (2013) A review on human health perspective of air pollution with respect to allergies and asthma. , Environ Int 59, 41-52.
- 7.ASV Shah, Langrish J P, Nair H, McAllister D A, Hunter A L et al. (2013) Global association of air pollution and heart failure: a systematic review and meta-analysis. , The Lancet; 382, 1039-48.
- 8.J S Brown, Gordons T, Price O, Asghrian B. (2013) Thoracic and Reparable Particulate definition for Human Health Risk Assessment. Part Fibre Toxicol. 10, 12.
- 10.P F Liu, C S Zhao, Gbel T, Hallbauer E, Nowak A et al. (2011) Hygroscopic properties of aerosol particles at high relative humidity and their diurnal variations in the north china plain. , Atmos. Chem. Phys 11, 3479-3794.
- 11.I B Obioh, G C Ezeh, O E Abiye, Alpha A, E O Ojo et al. (2013) Atmospheric particulate matter in Nigerian megacities. , Toxicol Environ Chem 95(3), 379-385.
- 12.Angaye T C N, Abowei J F N. (2017) Review on the Environmental Impacts of Municipal Solid Waste in Nigerian Challenges and Prospects. , Greener Journal of Environmental Management and Public Safety 6(2), 18-33.
- 13.B A Lingan, Poyyamoli G, U B Chandra. (2014) Assessment of Air Pollution and Its Impacts near Municipal Solid Waste Dumping Site. , Kammiyampet, Cuddalore, India, International Journal of Innovative Research in Science, Engineering and Technology 3(5), 12588-12593.
- 14.Bhutiani R, D B Kulkarni, D R Khanna, Gautam A. (2017) Geochemical distribution and environmental risk assessment of heavy metals in groundwater of an industrial area and its surroundings. , Haridwar, India.Energy, Ecology and 2(2), 155-167.
- 15.E O Oluyemi, O I Asubiojo, A F Oluwole, Toussaint C J N. (1994) Elemental concentrations and source identification of air particulate matter at a Nigerian site: A preliminary study. , J Radioanal Nucl Chem 179(2), 187-194.
- 16.A M Taiwo, T A Arowolo, K I Abdullahi, O T Taiwo. (2015) . Particulate Matter Pollution in Nigeria: A review.Proceedings of the 14th International Conference on Environmental Science and TechnologyRhodes,Greece.September2015.3-5 .
- 17.Owoade O K, O G Fawole, F S Olise, L T Ogundele, H B Olaniyi et al. (2013) Characterization and source identification of airborne particulate loadings at receptor site-classes of Lagos mega-city. , Nigeria. J Air & Waste Managt Assoc 63, 1026-1029.
- 18.Ideriah T J K, S A Braide, Fekarurhobo G, Oruambo I. (2001) Determination of indoor and outdoor concentrations of suspended particulate matter in Southeastern Nigeria. , Ghana J Sci 41, 23-27.
- 19.E I Ohimain, S C Izah, S O Abah. (2013) Air Quality Impacts of Smallholder Oil Palm Processing in Nigeria. , J. Environ Protect 4, 83-98.
- 20.R W Atkinson, G W Fuller, H R Anderson, R M Harrison, Armstrong B. (2010) Urban ambient particle metrics and health. A time series analysis. , Epidemiology 21, 501-11.
- 21.Cadelis G, Tourres R, Molinie J. (2014) Short-term effects of the particulate pollutants contained in Saharan dust on the visits of children to the emergency department due to asthmatic conditions in Guadeloupe (French Archipelago of the Caribbean). , PLoS ONE 9(3), 91136.
- 22.Correia A W, Pope C A, Dockery D W, Wang Y, Ezzati M et al. (2013) The effect of air pollution control on life expectancy in the United States: an analysis of 545 us counties for the period2000to2007. , Epidemiology 24(1), 23-31.
Cited by (3)
- 1.Zhang Biao, Wang Chen, Song Zhao-Long, Xu Chuan-Long, He Zhen-Zong, 2020, Determination of particle size distribution based on dynamic light scattering measurements in the near field, Optics and Lasers in Engineering, 127(), 105980, 10.1016/j.optlaseng.2019.105980
- 2.Blamah Nunyi Vachaku, Magidimisha-Chipungu Hangwelani, Dayomi Matthew, 2022, The socio-spatial expression of the metropolitan structure of Abuja and the impact of vehicular emissions on the ambient environment, GeoJournal, 87(S4), 583, 10.1007/s10708-022-10616-5
- 3.Okoye Chukwuma, Okoye Chukwuma, Asegbeloyin Jonnie, Ihedioha Janefrances, 2021, Chemical characteristics and health risk assessment of potential toxic elementsin atmospheric PM10 around Ashaka cement factory, Gombe, Nigeria, French-Ukrainian Journal of Chemistry, 9(2), 72, 10.17721/fujcV9I2P72-82