Prediction and Modeling of Dry Seasons Air pollution changes using multiple linear Regression Model: A Case Study of Port Harcourt and its Environs, Niger Delta, Nigeria

Prediction and Modeling of Dry Seasons Air pollution changes using multiple linear Regression Model: A Case Study of Port Harcourt and its Environs, Niger Delta, Nigeria ( Vol-3,Issue-3,May - June 2018 )

Author: Antai Raphael Eduk, Osuji Leo C., Obafemi Andrew A., Onojake Mudiaga C.

ijeab doi crossref DOI: 10.22161/ijeab/3.3.25

Keyword: Multiple linear Regressions Model, Air Pollution changes, Meteorological variables concentration.

Abstract: The influence of meteorological parameters on air pollutants over Port Harcourt and its environs in the dry season was modeled using multiple linear regressions model. Results indicated that meteorological parameters significantly influenced pollutant concentrations; results also showed poor linear relationships between meteorological parameters and pollutant concentrations, and that meteorological parameters are poor predictor variables of concentrations of air pollutants in the area. Pollution roses of pollutants dispersion pattern in the study area showed that pollutant concentrations increase with increased wind speed. Result also showed that wind speed exerts positive influence on the concentration levels of pollutants in the study area. The yearly prediction of air pollutants was also carried out using a ten-year data from previous studies conducted in the study area. The prediction was done using regression analysis and year as the predictor variable to develop a model. The relationship between air pollutants and year was therefore established for the annual prediction of the future pollutant concentrations in the dry seasons for period of the next fifteen years.

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Cite this Article:

MLA

Antai Raphael Eduk, Osuji Leo C., Obafemi Andrew A., Onojake Mudiaga C. et al."Prediction and Modeling of Dry Seasons Air pollution changes using multiple linear Regression Model: A Case Study of Port Harcourt and its Environs, Niger Delta, Nigeria ". International Journal of Environment Agriculture and Biotechnology(ISSN: 2456-1878),vol 3, no. 3, 2018, pp.0899-0915 AI Publications doi:10.22161/ijeab/3.3.25

APA

Antai Raphael Eduk, Osuji Leo C., Obafemi Andrew A., Onojake Mudiaga C., P.(2018).Prediction and Modeling of Dry Seasons Air pollution changes using multiple linear Regression Model: A Case Study of Port Harcourt and its Environs, Niger Delta, Nigeria . International Journal of Environment Agriculture and Biotechnology(ISSN: 2456-1878).3(3), 0899-0915.10.22161/ijeab/3.3.25

Chicago

Antai Raphael Eduk, Osuji Leo C., Obafemi Andrew A., Onojake Mudiaga C., P.(2018).Prediction and Modeling of Dry Seasons Air pollution changes using multiple linear Regression Model: A Case Study of Port Harcourt and its Environs, Niger Delta, Nigeria . International Journal of Environment Agriculture and Biotechnology(ISSN: 2456-1878).3(3), pp.0899-0915.

Harvard

Antai Raphael Eduk, Osuji Leo C., Obafemi Andrew A., Onojake Mudiaga C.. 2018."Prediction and Modeling of Dry Seasons Air pollution changes using multiple linear Regression Model: A Case Study of Port Harcourt and its Environs, Niger Delta, Nigeria ". International Journal of Environment Agriculture and Biotechnology(ISSN: 2456-1878).3(3):0899-0915.Doi:10.22161/ijeab/3.3.25

IEEE

Antai Raphael Eduk, Osuji Leo C., Obafemi Andrew A., Onojake Mudiaga C.."Prediction and Modeling of Dry Seasons Air pollution changes using multiple linear Regression Model: A Case Study of Port Harcourt and its Environs, Niger Delta, Nigeria ", International Journal of Environment Agriculture and Biotechnology,vol.3,no. 3, pp.0899-0915,2018.

Bibtex

@article { antairaphaeleduk2018prediction,
title={Prediction and Modeling of Dry Seasons Air pollution changes using multiple linear Regression Model: A Case Study of Port Harcourt and its Environs, Niger Delta, Nigeria },
author={Antai Raphael Eduk, Osuji Leo C., Obafemi Andrew A., Onojake Mudiaga C. , R},
journal={International Journal of Environment Agriculture and Biotechnology},
volume={3},
year= {2018} ,
}