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.

Highlights

  • In terms of the direction of the trend, the positive value of the S-statistic for gaseous fuel consumption (GFC), liquid fuel consumption (LFC), electricity and heat production (EHP), and OSEC indicated that these variables had an upward trend during the period under consideration, while emissions from solid fuel consumption (SFC), TRA, residential buildings and commercial and public services (RBCPS), and manufacturing industries and construction (MINC) had a downward trend

  • The simulation results indicate the significance of monotonic trends in CO2 emissions from gaseous fuel consumption, solid fuel consumption, electricity and heat production, residential buildings, and manufacturing industries and construction sectors

  • The study focused on the trend analysis of carbon dioxide emissions, which was disaggregated into various components based on the sources and sectors of the economy generating them

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Summary

Introduction

A large number of studies have been conducted on CO2 emissions globally by employing different statistical tools in developed and developing countries. Most studies ascertained both local and global atmospheric implications of CO2 and reported energy consumption due to economic growth and development as the main reason for increased. To the best of our knowledge, this is the first study exploring the possible trends and tipping point in CO2 emissions across different sectors in an oil-dependent developing country. World Development Indicator (WDI) data to conduct the trend analysis of CO2 emissions from different sources and sectors in Nigeria using a non-parametric Mann-Kendall test. The research questions driving the study were: is there a presence of monotonic trend in the disaggregated CO2 emission data? what is the magnitude of the trend change? and what is the change point of the trend in each of the CO2 emissions data? The remainder of the article is structured as follows: Section 2 discusses the methodology; Section 3 presents statistical tools employed to answer the research questions put forward in the study; results, discussion, and policy implications are presented in Sections 4 and 5 has the conclusion

Source of Data and Coverage
The Mann-Kendall Test
Statistical Analysis
Findings
Conclusions
Full Text
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