POLLUTANT STANDARD INDEX AND AIR QUALITY INDEX OF THE DRY SEASON CRITERIA AIR POLLUTANTS OF PORT HARCOURT AND ITS ENVIRONS, NIGER DELTA, NIGERA.

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1 POLLUTANT STANDARD INDEX AND AIR QUALITY INDEX OF THE DRY SEASON CRITERIA AIR POLLUTANTS OF PORT HARCOURT AND ITS ENVIRONS, NIGER DELTA, NIGERA. ANTAI, RAPHAEL EDUK 1 OSUJI, LEO C. 2, OBAFEMI, ANDREW A. 3 ONOJAKE, MUDIAGA C. 4 1 Institute of Natural Resources, Environment and Sustainable Development, University of Port Harcourt, Choba, Nigeria. 1 Inter - Environments Limited, Rumudara, Port Harcourt, Nigeria. 2,4 Department of Pure and Industrial Chemistry, University of Port Harcourt, Choba, Nigeria. 3 Department of Geography and Environmental Management, University of Port Harcourt, Choba, Nigeria ABSTRACT Pollutant standards indices () were computed for each study area to indicate the concentration level of each pollutant in the area, while air quality indices were computed to show the degree of air pollution effects on human health in the respective study area. The Air Quality index AQI revealed the health effects on people in the respective study area may be experienced. Results of AQI indicated that Eleme, Obio/Akpor and Port Harcourt are most polluted areas compared to Oyigbo, Ikwerre and Etche in the dry season. Keywords: Dry Season, Air Pollutants, Nigeria. 1. INTRODUCTION Generally, the study revealed that Eleme, Obio/Akpor and Port Harcourt areas are exposed to high pollutants concentrations, especially sulphur dioxide, methane hydrocarbon, nitrogen dioxide and particulate matter, which may adversely affect public health or aggravate the health conditions of the exposed population. Potential health issues likely to prevail in these areas may include asphyxiation, narcosis (that is depression of the central nervous system), cardiac arrest and aspiration. Cases of chronic bronchitis, pulmonary emphysema, and cancer of the bronchus mucous membrane caused by air pollutants may be prevalent in these areas. Prolonged exposure to these pollutants may result in increased cases of Asthma, and respiratory diseases. Long-term health effects due to continuous daily exposure of the general public are therefore envisaged. This study was designed specifically to assess air quality of Port Harcourt and its environs and develop its air quality index model in the dry season. This study has created Port Harcourt and its environs air quality data base for future reference of the study area. STUDY LOCATION Port Harcourt metropolis is located between latitude and North and between longitude and east. It covers an estimated area of square kilometer. Port Harcourt is the capital of Rivers State. Port Harcourt was established in 1914 by the British colonial administration under Lord Lugard to meet the pressing economic needs of the European. Port Harcourt which lies at the heart of the Niger Delta, one of the world s richest wetland, is bounded on the south by the Atlantic Ocean, to the North by Imo and Abia state to the East by Akwa Ibom State and to the West by Bayelsa and Delta. Some of the well-known residential areas in Port Harcourt and its environs include: Port Harcourt, Obio/Akpor, Eleme, Oyibo, Ikwerre and Etche 2. MATERIALS AND METHOD Sample and Sampling Techniques The study primarily include selection of sampling sites, field assessment/measurement, data reading, data storage, statistical data analysis, data interpretation and report writing. Hand held in-situ portable meters were used and application of standard ambient air quality assessment procedures were strictly adhere to. Field data measurement was done in-situ with the calibrated portable meters in accordance with the recommended standard procedures for environmental data collection in Nigeria FMEnv, (2002), DPR, (2002) and WHO s (2005) procedures for population density, topography, industrial cluster, and heavy traffic 1

2 studies. The field data assessment of the air quality were sampled on hourly basis three hours per sampling point (morning, afternoon and evening peak, off peak and peak period). Pollutant Standards Index () and Air Quality Index (AQI) I I i i, j 1 X i X i, j I i j i, j 1 i, j I i, X i, j 1 X i, j for X i,j X X A type of air quality index known as Pollutant Standards Index was used to determine the level of pollutants in air. This was computed using the following equation and air quality index table (equation 1) (1) Concentrations of pollutants were expressed in terms of low, moderate, high and critical based on the computed values of EF and (CPCB, 2006). Figure 1: Map of Port Harcourt and its Environs showing Sampling Points of the Study Area 2

3 Values 3. RESULTS AND DISCUSSION Computation of Pollutant Standard Index () and Air Quality Index (AQI) in Eleme area The is a sub air quality index (sub-aqi), a number which indicates the concentration level of each pollutant in the air. Pollutant standards indices () were computed using concentrations of criteria pollutants (SO 2, NO 2, CO, PM 10 and PM 2.5). The computed for each pollutant in the dry season in Eleme area are shown in Figures 2 to 6, while plots of corresponding AQI are shown in Figure 7. Computed showed high values of SO 2, NO 2 and PM 2.5 (Figure 2 to 6). This implies that SO 2, NO 2 and PM 2.5 are the main air pollutants prevailing in the Eleme area in the dry season. This may be as a result of industrial activities in the area. The air quality indices computed for the Eleme area in the dry season (Table 1 and Figure 7) showed very unhealthy values (between 201 and 300) at station SP1, SP2, SP5 and SP6. This may potentially affect the entire exposed population, thus the people in these areas may experience more serious health effects. Similarly, stations SP3, SP4 and SP7 (Table 1) showed hazardous values (between 301 and 500). This implies that the entire people in these areas may experience more severe health effects. Table 1: Dry Season Pollutant Standard Index and Air Quality Index in Eleme Area SO2 NO2 CO PM10 PM2.5 AQI AQI rating SP Very Unhealthy SP Very Unhealthy SP Hazardous SP Hazardous SP Very Unhealthy SP Very Unhealthy SP Hazardous Dry Season SO2 Wet Season SO SP1 SP2 SP3 SP4 SP5 SP6 SP7 Figure 2: Computed Pollutant Standard Index of SO2 around Eleme Area 3

4 values values values Dry Season NO2 Wet Season NO SP1 SP2 SP3 SP4 SP5 SP6 SP7 Figure 3: Computed Pollutant Standard Index of NO2 around Eleme Area Dry Season CO Wet Season CO SP1 SP2 SP3 SP4 SP5 SP6 SP7 Figure 4: Computed Pollutant Standard Index of CO around Eleme Area Dry Season PM10 Wet Season PM SP1 SP2 SP3 SP4 SP5 SP6 SP7 Figure 5: Computed Pollutant Standard Index of PM10 around Eleme Area 4

5 AQI Values values Dry Season PM2.5 Wet Season PM SP1 SP2 SP3 SP4 SP5 SP6 SP7 Figure 6: Computed Pollutant Standard Index of PM2.5 around Eleme Area Dry Season AQI Values Wet Season AQI Values SP1 SP2 SP3 SP4 SP5 SP6 SP7 Figure 7: Computed Air Quality Index around Eleme Area Assessment of Air Quality Index of Etche area The computed for each pollutant in the dry season in Etche area are shown in Figures 8 to 12, while plots of corresponding AQI values are shown in Figure 13. Computed (Figure 8 to 12) showed that SO 2, NO 2 and PM 2.5 are the main cause of in the area, while PM 10pollution levels are higher in the dry season. This implies that SO 2, NO 2, PM 2.5 and PM 10 are the main air pollutants prevailing in the Etche area. This may be as a result of road construction activities and gas flaring in the area.the air quality indices computed for the Etche area in the dry season (Table 2 and Figure 13) showed hazardous air quality around station SP12 (between 300 and 500) which may severely affect the health of people in the area. Station SP13 showed unhealthy air quality for sensitive groups, while station SP14 showed unhealthy air quality which may affect everyone in the area particularly members of sensitive groups may be more affected. 5

6 values values Table 2: Dry Season Pollutant Standard Index and Air Quality Index in Etche area SO2 NO2 CO PM10 PM2.5 AQI AQI Rating SP Hazardous Unhealthy for SP Sensitive Groups SP Unhealthy Dry Season SO2 Wet Season SO2 SP12 SP13 SP14 Figure 8: Computed Pollutant Standard Index of SO2 around Etche Area Dry Season NO2 Wet Season NO2 5 SP12 SP13 SP14 Figure 9: Computed Pollutant Standard Index of NO2 around Etche Area 6

7 values values values Dry Season CO Wet Season CO SP12 SP13 SP14 Figure 10: Computed Pollutant Standard Index of CO around Etche Area SP12 SP13 SP14 Dry Season PM10 Wet Season PM10 Figure 11: Computed Pollutant Standard Index of PM10 around Etche Area SP12 SP13 SP14 Dry Season PM2.5 Wet Season PM2.5 Figure 12: Computed Pollutant Standard Index of PM2.5 around Etche Area 7

8 values AQI values SP12 SP13 SP14 Dry Season AQI values Wet Season AQI values Figure 13: Computed Air Quality Index around Etche Area Assessment of Air Quality Index of Ikwerre Area The computed for each pollutant in the dry season in Ikwerre area are shown in Figures 14 to 18, while plots of corresponding AQI values are shown in Figure 19. Computed (Figure 14 to 18) showed that SO 2 is the main cause of pollution in the dry season in the area,.(table 3). Computed Air quality indices for Ikwerre area in the dry season (Table 3) showed moderate air quality around station SP25, this may pose a moderate health concern for a very small number of people with respiratory symptoms. Station SP26 showed unhealthy air quality which may affect the health of everyone in the area. Similarly, station SP27 showed unhealthy air quality for sensitive groups while SP28 showed very unhealthy air quality, this may pose widespread health effects among the people in this area, and members of sensitive groups may experience more serious effects. Table 3: Dry Season Pollutant Standard Index and Air Quality Index in Ikwerre area SO2 NO2 CO PM10 PM2.5 AQI AQI Rating SP Moderate SP Unhealthy Unhealthy for Sensitive SP Groups SP Very Unhealthy SP25 SP26 SP27 SP28 Dry Season SO2 Wet Season SO2 Figure 14: Computed Pollutant Standard Index of SO2 around Ikwerre Area 8

9 values values values Dry Season NO2 Wet Season NO2 5 SP25 SP26 SP27 SP28 Figure 15: Computed Pollutant Standard Index of NO2 around Ikwerre Area Dry Season CO Wet Season CO SP25 SP26 SP27 SP28 Figure 16: Computed Pollutant Standard Index of CO around Ikwerre Area Dry Season PM10 Wet Season PM10 SP25 SP26 SP27 SP28 Figure 17: Computed Pollutant Standard Index PM10 around Ikwerre Area 9

10 AQI Values values SP25 SP26 SP27 SP28 Dry Season PM2.5 Wet Season PM2.5 values Figure 18: Computed Pollutant Standard Index PM2.5 around Ikwerre Area Dry Season AQI Values Wet Season AQI Values SP25 SP26 SP27 SP28 Figure 19: Computed Air Quality Index around Ikwerre Area Assessment of Air Quality Index of Obio/Akpor Area The computed for each pollutant in the dryseason in Obio/Akpor area are shown in Figures 20 to 24, while plots of corresponding AQI values are shown in Figure 25. Computed (Figure 20 to 24) showed that SO 2, NO 2, CO, PM 10 and PM 2.5 are the main cause of pollution in the dry season in the area, however, the pollution levels are higher in the dry season compared to the wet season. This implies that there is high pollution in Obio/Akpor which may be caused by vehicular exhaust emissions, gas flaring, oil and gas exploitation and industrial activities as well road construction activities in the area. The dry season computed air quality indices for Obio/Akpor area (Table 4, and Figure 25) showed very unhealthy air quality around stations SP15, SP16, SP20, SP21, SP22, SP23, SP29, SP32, SP36, SP37, SP38, SP46, SP50, and SP63. This may pose widespread health effects among the people in these areas, and members of sensitive groups may experience more serious effects. Stations SP17, SP18, SP19, SP24, SP30, SP31, SP33, SP35, SP40, 10

11 SP15 SP16 SP17 SP18 SP19 SP20 SP21 SP22 SP23 SP24 SP29 SP30 SP31 SP32 SP33 SP34 SP35 SP36 SP37 SP38 SP40 SP46 SP47 SP48 SP49 SP50 SP51 SP62 SP63 values SP15 SP16 SP17 SP18 SP19 SP20 SP21 SP22 SP23 SP24 SP29 SP30 SP31 SP32 SP33 SP34 SP35 SP36 SP37 SP38 SP40 SP46 SP47 SP48 SP49 SP50 SP51 SP62 SP63 values and SP62 showed unhealthy air quality in the dry season (Table 4). Everyone in these stations may experience health effects; particularly sensitive people with respiratory symptoms may experience more serious health effects. Stations SP34 and SP47 showed moderate air quality in the dry season. This may affect few people and those who are unusually sensitive to particles quality may experience respiratory symptoms. Stations SP48 and SP51 showed unhealthy air quality for sensitive groups in the dry season. This may affect only sensitive groups while the general public may not be affected. Station SP49 indicated hazardous air quality which may affect the entire people with serious health effects Dry Season SO2 Wet Season SO Figure 20: Computed Pollutant Standard Index of SO2 around Obio/Akpor Dry Season NO2 Wet Season NO2 Figure 21: Computed Pollutant Standard Index of NO2 around Obio/Akpor 11

12 SP15 SP16 SP17 SP18 SP19 SP20 SP21 SP22 SP23 SP24 SP29 SP30 SP31 SP32 SP33 SP34 SP35 SP36 SP37 SP38 SP40 SP46 SP47 SP48 SP49 SP50 SP51 SP62 SP63 values SP15 SP16 SP17 SP18 SP19 SP20 SP21 SP22 SP23 SP24 SP29 SP30 SP31 SP32 SP33 SP34 SP35 SP36 SP37 SP38 SP40 SP46 SP47 SP48 SP49 SP50 SP51 SP62 SP63 values SP15 SP16 SP17 SP18 SP19 SP20 SP21 SP22 SP23 SP24 SP29 SP30 SP31 SP32 SP33 SP34 SP35 SP36 SP37 SP38 SP40 SP46 SP47 SP48 SP49 SP50 SP51 SP62 SP63 values Dry Season CO Wet Season CO Figure 22: Computed Pollutant Standard Index of CO around Obio/Akpor Dry Season PM10 Wet Season PM Figure 23: Computed Pollutant Standard Index of PM10 around Obio/Akpor Dry Season PM2.5 Wet Season PM2.5 Figure 24: Computed Pollutant Standard Index of PM2.5 around Obio/Akpor 12

13 values SP15 SP16 SP17 SP18 SP19 SP20 SP21 SP22 SP23 SP24 SP29 SP30 SP31 SP32 SP33 SP34 SP35 SP36 SP37 SP38 SP40 SP46 SP47 SP48 SP49 SP50 SP51 SP62 SP63 values Dry Season PM2.5 Wet Season PM2.5 Figure 25: Computed Air Quality Index around Obio/Akpor Assessment of Air Quality Index of Oyigbo Area The computed for each pollutant in the dry season in Oyigbo area are shown in Figures 26 to 30, while plots of corresponding AQI values are shown in Figure 31. Computed (Figure 26 to 30) showed that SO 2, NO 2 and PM 2.5 are the main cause of pollution in the area in the dry season. The dry season computed air quality indices for Oyigbo area (Table 5) showed unhealthy air quality around station SP8. This may affect the health of everyone in the area; especially sensitive people with respiratory symptoms may experience more serious health effects. Station SP10 showed unhealthy air quality for sensitive groups in the dry season. This may affect only sensitive groups while the general public may not be affected. Also, stations SP9 and SP11 indicated hazardous air quality which may affect the entire people with serious health effects. Table 5: Dry Season Pollutant Standard Index and Air Quality Index in Oyigbo Area SO2 NO2 CO PM10 PM2.5 AQI AQI Rating SP Unhealthy SP Hazardous Unhealthy for Sensitive SP Groups SP Hazardous Dry season SO2 Wet season SO2 SP8 SP9 SP10 SP11 Figure 26: Computed Pollutant Standard Index of SO2 around Oyigbo 13

14 values values values Dry season NO2 Wet season NO SP8 SP9 SP10 SP11 Figure 27: Computed Pollutant Standard Index of NO2 around Oyigbo Dry season CO Wet season CO SP8 SP9 SP10 SP11 Figure 28: Computed Pollutant Standard Index of CO around Oyigbo 90 Dry season PM10 80 Wet season PM SP8 SP9 SP10 SP11 Figure 29: Computed Pollutant Standard Index of PM10 around Oyigbo 14

15 values values Dry season PM2.5 Wet season PM SP8 SP9 SP10 SP11 Figure 30: Computed Pollutant Standard Index of PM2.5 around Oyigbo Dry season AQI Values Wet season AQI Values SP8 SP9 SP10 SP11 SO2 Figure 31: Computed Air Quality Index for Oyigbo NO2 CO PM10 15 PM2.5 AQI AQI Rating SP Good Unhealthy for Sensitive SP Groups SP Unhealthy SP Unhealthy SP Unhealthy SP Very Unhealthy

16 SP Hazardous SP Unhealthy SP Hazardous Unhealthy for Sensitive SP Groups SP Hazardous SP Unhealthy SP Unhealthy SP Unhealthy SP Good SP Hazardous Unhealthy for Sensitive SP Groups SP Unhealthy SP Very Unhealthy SP Unhealthy SP Very Unhealthy Unhealthy for Sensitive SP Groups SP Unhealthy SP Good Table 6: Dry Season Pollutant Standard Index and Air Quality Index in Port Harcourt Area Assessment of Air Quality Index of Port Harcourt Area The computed for each pollutant in the dry season in Port Harcourt area are shown in Figures 32 to 36, while plots of corresponding AQI values are shown in Figure 37. Computed (Figures 32 to 36) showed that SO 2, NO 2, CO, PM 10 and PM 2.5 are the main cause of pollution in the dry season in the area, however, the pollution levels are higher in the dry season compared to the wet season. This implies that there is high pollution in Port Harcourt which may be caused by vehicular exhaust emissions, gas flaring, oil and gas exploitation, industrial activities as well road construction activities in the area. The dry season computed air quality indices for Port Harcourt area (Table 6 and Figure 37) showed very unhealthy air quality around stations SP45, SP66 and SP68. This may cause widespread health problems among the people in these areas, and members of sensitive groups may experience more serious effects. Stations SP42, SP43, SP44, SP53, SP57, SP58, SP59, SP65, SP67 and SP70 showed unhealthy air quality in the dry season (Table 6). This may affect the health of everyone in these stations; particularly sensitive people with respiratory symptoms may experience more severe health effects. Stations SP41, SP55, SP64 and SP69 showed unhealthy air quality for sensitive groups in the dry season. This may affect only sensitive groups while the general public may not be affected. Stations SP52, SP54, SP56 and SP61 indicated hazardous air quality which may have serious health effects on the entire people. Also, stations SP39, SP60 and SP71 showed good air quality which poses minor or no health risk to the people. 16

17 SP39 SP41 SP42 SP43 SP44 SP45 SP52 SP53 SP54 SP55 SP56 SP57 SP58 SP59 SP60 SP61 SP64 SP65 SP66 SP67 SP68 SP69 SP70 SP71 values SP39 SP41 SP42 SP43 SP44 SP45 SP52 SP53 SP54 SP55 SP56 SP57 SP58 SP59 SP60 SP61 SP64 SP65 SP66 SP67 SP68 SP69 SP70 SP71 values SP39 SP41 SP42 SP43 SP44 SP45 SP52 SP53 SP54 SP55 SP56 SP57 SP58 SP59 SP60 SP61 SP64 SP65 SP66 SP67 SP68 SP69 SP70 SP71 values Dr season SO2 Wet season SO2 Figure 32: Computed Pollutant Standard Index of SO2 around Port Harcourt Area Dry season NO2 Wet season NO2 Figure 33: Computed Pollutant Standard Index of NO2 around Port Harcourt Area Figure 34: Computed Pollutant Standard Index of CO around Port Harcourt Area 17

18 SP39 SP41 SP42 SP43 SP44 SP45 SP52 SP53 SP54 SP55 SP56 SP57 SP58 SP59 SP60 SP61 SP64 SP65 SP66 SP67 SP68 SP69 SP70 SP71 AQI values SP39 SP41 SP42 SP43 SP44 SP45 SP52 SP53 SP54 SP55 SP56 SP57 SP58 SP59 SP60 SP61 SP64 SP65 SP66 SP67 SP68 SP69 SP70 SP71 values SP39 SP41 SP42 SP43 SP44 SP45 SP52 SP53 SP54 SP55 SP56 SP57 SP58 SP59 SP60 SP61 SP64 SP65 SP66 SP67 SP68 SP69 SP70 SP71 values Dry season PM10 Wet season PM10 Figure 35: Computed Pollutant Standard Index of PM10 around Port Harcourt Area 30 Dry season PM Wet season PM Figure 36: Computed Pollutant Standard Index of PM2.5 around Port Harcourt Area Dry season AQI Values Wet season AQI Values Figure 37: Computed Air Quality Index for Port Harcourt Area 18

19 CONCLUSION Computed showed that SO 2, NO 2, CO, PM 10 and PM 2.5 are the main cause of pollution in the dry season in the area, however, the pollution levels are REFERENCES 1. Antai, R. E., (2016). An Investigative Approach on the Effects of Air and Noise Pollution in 2. Uyo Metropolis, Akwa Ibom State, Nigeria. Journal of Scientific and Engineering Research, Vol. 3 Issue 6, p Antai, R. E., Osuji, L. C. and Beka, F. T. (2016). The Concentration and Health Risk 4. Assessment of Air and Noise Pollution: A case study of Uyo Metropolis, Niger Delta, Nigeria. International Journal for Innovative Research in Multidisciplinary Field. Vol. 2 Issue 10, October. 5. Antai, R. E., Osuji, L. C. and Beka, F. T. (2016). Ambient Air Quality and Noise Pollution 6. Monitoring in Uyo Metropolis, Akwa Ibom State, Nigeria. International Journal for Innovative Research in Multidisciplinary Field. Vol. 2 Issue 10, October. 7. Efe, S.I., (2006). Particulate Pollution and its Health Implications in Warri Metropolis. Delta State Nigeria. Env Anal. 11, Elangasinghe, M.A., Singhai, N., Dirks, K.N. and Salmond, J.A (2014). Development of an ANN-based air Pollution Forecasting System with Explicit Knowledge through Sensitivity Analysis. Atmospheric Pollution Research www. atmospolres.com 9. Emmanuel,.E.E., Justina,.E.U, Felix,.E, Justice,.I.O., and Dike, O., (2009). Spatial and Diurnal Variations of Carbon monoxide (CO) Pollution from Motor Vehicles in an Urban Centre. Journal of Environmental Studies. 19(4), Esplin, G.L.,(1995) Approximate Explicit Solution to the General Line Source Problem. Atmospheric Environment 29, Everitt, R,R. (1992). Environmental Effects Monitoring Manual. Prepared for the Federal Environmental Assessment Review office and Environment Canada, Environmental higher in the dry season. The results of AQI also indicated that Eleme, Obio/Akpor and Port Harcourt are most polluted areas compared to Oyigbo, Ikwerre and Etche in the dry season. Assessment Division, Inland Waters Directorate, Ottawa, CN. 12. FMENV. (1992). Federal Ministry of Environment Guideline for air Quality Monitoring. 13. Folorunsho, R. and Awosika, L.F. (1995). Meteorological Induced Changes along the Nigerian Coastal Zone and Implications for Integrated coastal Zone Management Plan. 14. FORMECU. (1998). Assessment of Vegetation and Land Use Changes in Nigeria, Between 1976/78 and 1993/95. Unpublished Report by Germatizs International Inc, and Beak International Inc; Kumar, A., Gary A. and Pandel, U. (2011). A Study of Ambient Air Quality Status in Jaiper City, Rajasthan, India, Using Air Quality Index. Nature and Science. 9: Longhurst, J. (2005). Creating an Air Quality Index in Pittsburg. Environment Monitoring Assess, 106: Mbakwem-Aniebo, C., Stanley, H. O. and Onwukwe, C. D. (2016). Assessment of the Indoor 18. Air Quality of Majors Biological Laboratories in Ofrima Complex, University of Port Harcourt, Nigeria. Journal of Petroleum and Environmental Biotechnology. Vol. 7 Issue 4 DOI: / Mmom, P.C. and Essiet U. (2014). Spatio - Temporal Variations in Urban Vehicular Emissions in Uyo City, Akwa Ibom State, Nigeria. Journal of Sustainable Development vol. 7, No4 p Nevers, N.D. (1995). Air Pollution Control Engineering. McGraw-Hill Inc. United States of America. 21. Nwokocha, C. O., Edebeatu, C. C. and Okujagu, C. U. (2015). Measurement, Survey and 22. Assessment of Air Quality in Port Harcourt, South-South Nigeria.. International Journal of Advanced Research in Physical Science Volume 2, Issue 7, PP