Sources and Sectoral Trend Analysis of CO₂ Emissions Data in Nigeria Using a Modified Mann-Kendall and Change Point Detection Approaches

Abstract

In Nigeria, the high dependence on fossil fuels for energy generation and utilization in various sectors of the economy has resulted in the emission of a large quantity of carbon dioxide (CO2), which is one of the criteria gaseous pollutants that is frequently encountered in the environment. The high quantity of CO2 has adverse implications on human health and serious damaging effects on the environment. In this study, multi-decade (1971–2014) CO2-emissions data for Nigeria were obtained from the World Development Indicator (WDI). The data were disaggregated into various emission sources: gaseous fuel consumption (GFC), liquid fuel consumption (LFC), solid fuel consumption (SFC), transport (TRA), electricity and heat production (EHP), residential buildings and commercial and public services (RSCPS), manufacturing industries and construction (MINC), and other sectors excluding residential buildings and commercial and public services (OSEC). The analysis was conducted for a sectorial trend using a rank-based non-parametric modified Mann–Kendall (MK) statistical approach and a change point detection method. The results showed that the CO2 emissions from TRA were significantly high, followed by LFC. The GFC, LFC, EHP, and OSEC had a positive Sen’s slope, while SFC, TRA, and MINC had a negative Sen’s slope. The trend analysis indicated multiple changes for TRA and OSEC, while other sources had a change point at a particular year. These results are useful for knowledge of CO2-emission sources in Nigeria and for future understanding of the trend of its emission for proper environmental planning. The severe effects of CO2 on the atmospheric environment of Nigeria may be worsened in the future due to some major sources such as transportation services and electricity generation that are inevitable for enviable standard of living in an urban setting.

Keywords

• CO₂
• emission sources
• WDI data
• trend analysis
• Mann-Kendall