ABSTRACT
Mining and beneficiation of solid minerals impact adversely on communities where such activities take place. Thus, their ambient air quality needs to be monitored to ascertain the level of pollutants discharged into the atmosphere, the temporal and spatial distribution of the pollutants, and her vulnerability to adverse environmental impacts in order to recommend mitigation measures. Most studies have relied on the effect of air pollution on public health and welfare but the baseline data relating to the actual concentration to which humans and the environment are exposed to air pollution risk is critically unavailable. Ambient air quality of Evbonogbon and Ikpeshi communities were monitored due to the high level of mining and beneficiation in these areas.
Ambient Sulfur dioxide (SO2), Nitrogen dioxide (NO2), Carbon monoxide (CO), Particulate matter of diameter less than 2.5 microns (PM2.5), and that less than 10 microns (PM10) were monitored in both communities for four seasons using BW GasAlert SO2 EXTREME, BW GasAlert NO2 EXTREME and GasAlert MicroClip XL monitors respectively, as well as Double Parameter HoldPeak HP-5800D model Laser PM2.5 Meter for PM2.5 and PM10. Geospatial data were collected by means of Garmin GPSmap 78s model receiver. Gases were not detected throughout the four seasons, and the PM2.5 and PM10 values were preprocessed in MS Excel 2010 to obtain their seasonal averages. Using excel’s real statistics ad in, ANOVA single factor, and post hoc tests were conducted at 95% confidence level to validate the existence of seasonal variation and to generate quantitative values for describing the seasonal variation of ambient air quality in both communities. Also, the data were analyzed in ArcGIS ArcInfo 10 to obtain the most suitable semivariogram models for spatial interpolation. Various geostatistical surfaces needed to evaluate the ambient air quality in both communities were generated as well.
The results showed that statistically significant seasonal variation in ambient air quality exists in both communities (p < 0.05), and with large effect size (Ω2 >14%, and Cohen d 1 sd). Also, Stable, Gaussian, J-Bessel, Hole Effect, Pentaspherical and Spherical were the most suitable models for Evbonogbon while the Exponential, Pentaspherical, Hole Effect, Stable and Circular were the best for Ikpeshi. PM2.5 and PM10 concentrations ranging from 2.47µg/m3 to 288.6µg/m3, and 2.93µg/m3 to 754.5µg/m3 were respectively generated in Ikpeshi, and recorded almost 100% chances of exceeding the WHO and NESREA standard threshold limits in all the four seasons. The range of PM2.5 and PM10 pollutant concentrations for Evbonogbon was 1.17µg/m3 - 222.15µg/m3, and 1.47µg/m3 - 360.5µg/m3 respectively during the rainy seasons and there was relatively less chances of exceeding the two standards while the dry season values were 13.7µg/m3 - 143.68µg/m3 for PM2.5 and 49.4µg/m3 – 302.28µg/m3 for PM10 and there was high likelihood of exceeding the WHO and NESREA thresholds. Bearing in mind that mining projects require huge investments, these findings will be helpful to air pollution managers; the Regulators, Mineral Title Holders, and Solid Mineral Processors in the optimization and implementation of pollution abatement programs for the two communities.
