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Original Research

JPAS. 2020; 20(3): 300-306


Assessment of Air Pollutants Using Time Series Models in Some Selected Locations of Bauchi Metropolis, Bauchi State, Nigeria.

Dauda S BUTEH.




Abstract

Gaseous samples were collected from Nov.2019 – Feb. 2020 from three (3) sampling points designated New GRA (NGRA), Railway Market (RM), and Nasarawa Jahum Street (NJS), 2km – 4 km apart in Bauchi metropolis. Control samples were also collected from Alkaleri town about 62 kilometres away from the study area. Samplings were carried out in cold and dry seasons using the Gasman detectors to assess the pollutants under investigation. Out of the four criteria air pollutants analysed (CO2, CO, NO2, and SO2) Carbon (ii) oxide had the highest concentration 1.69 ppm (±0.02).While Carbon (iv) oxide had the lowest concentration 0.05 ppm (±0.01). However, CO2, and CO are within the permissible limits of FEPA (2001) and USEPA (2008), The results obtained were subjected to statistical analysis to test the strength of the relationship between the variables with Pearson or product – moment correlation and at 95% confidence level or p – value 0.05, a very strong linear correlation exist between these variables as r - value ranged from 0.985 – 0.988. Predictive Time-Series models were developed using Minitab computer – installed software, for the pollutants concentrations obtained from datasets collected from the sampling sites. Fitted Time-Series models were obtained and expressed as Y = a + b × T (Linear Trend Model). The locations with high and low concentration levels of CO2 and CO are 0.289ppm and 0.408ppm NGRA, 0.289ppm and 0.510ppm RM and 0.425ppm and 4.930ppm Streets respectively were all found to be simple linear trend with time.

Key words: Gasman, Linear Trend Model, Pearson product correlation, Time Series






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