The Influence of Atmospheric Parameters on Production and Distribution of Air Pollutants in Bayelsa: A State in the Niger Delta Region of Nigeria

• 作者: E. I. Njoku E. O. Oladiran O. E. Ogunsola
• 来源期刊: 大气和气候科学(英文)
• 学科: 医学
• 关键词: Air POLLUTION ATMOSPHERIC PARAMETERS ATMOSPHERIC POLLUTANTS Regression Analysis CORRELATIONS
• 年，卷（期）: 2019,（1）
• 页码范围: 159-171
• 页数: 13页
• 分类号: R73

摘要

Air pollution is a primary environmental problem in the Niger Delta region of Nigeria due to oil spills including the gas emissions associated with industrial effluents. However, a good understanding and quantification of atmospheric parameters (wind speed, wind direction, temperature, relative humidity, solar radiation and cloud cover) that influence air pollution (CH4, NO2 and O3) concentrations in this region could assist in the mitigation and distribution of these pollutants. This work examines the influence of atmospheric parameters on the production and distribution of air pollutants in the Niger Delta region of Nigeria for the development of control strategies that will enhance the mitigation and amelioration of the significant impacts that these atmospheric pollutants could have on the populace in this part of the country. The CH4 and NO2 data utilized in this study were sourced from the European Space Agency (ESA), while that of tropospheric ozone (O3) was obtained from the National Aeronautics and Space Administration (NASA), and the atmospheric parameters data were provided by the Nigeria Meteorological Agencies (NIMET), Lagos. The analysis of the daily pollutants (CH4, NO2 and O3) including the atmospheric parameters in this region of the Niger Delta for the period 2003 to 2010 was carried out using standard statistical approach including the graphical method, stepwise regression model, least-square method, and correlation analysis. The Mann-Kendal rank statistics was also utilized in identifying the meaningful long-term trends, validation and testing of the homogeneity of the concentrations of the pollutants. The results of the correlations of CH4, NO2 and O3 concentrations with their previous day’s concentrations showed a strong significance in regression analysis for both CH4 and O3. The coefficient of determination of CH4 and O3 was obtained as 0.654 and 0.810 respectively, while a very weak correlation was obtained for NO2. However, despite that a very strong negative correlation of -0.809 and