Data-Driven Techno-Economic and Environmental Assessment of Compressed Natural Gas (CNG) Vehicles as a Source of Transportation in Nigeria

Abstract

The transport industry in Nigeria is heavily reliant on petrol and diesel, resulting in significant cost implications, import dependence, and high air pollution. A Transitional route can be offered through Compressed Natural Gas (CNG), considering Nigeria has 200 trillion cubic feet worth of proven reserves. The goal of this study was to develop a predictive machine learning model with the aim of assessing the environmental and techno-economic feasibility of CNG vehicles in Nigeria. A quantitative, data-driven design was employed, involving a combination of primary surveys and GPS-based monitoring techniques, as well as secondary data provided by NNPC, IEA, and IPCC. Techno-economic assessment, lifecycle environmental analysis, and predictive modelling, which utilised Random Forest, Support Vector Machines, and Neural Networks, had been carried out and tested using cross-validation (10-fold) and Monte Carlo simulation. Results were impressive: CNG saved at least 41% of fuel and paid even less than 0.65 years to break even with the NPVs, surpassing the ₦2.3 million goal per vehicle. The Levelized Cost of Transport was 41.3/km, compared with petrol at 62.5/km and diesel at 70/km. Citizens' environmentally friendly CNG vehicles reduce CO2 emissions by 29%, NOx emissions by 70%, and PM emissions by 80% without projecting approximately 950 yearly premature deaths and 3,100 hospital admissions annually. Scenario modelling identified that an integrated policy-infrastructure push will create enough to save ₦220 billion annually and generate over 40,000 jobs by 2030, through a 60% penetration of the fleet. The utility of this research lies in its demonstration of the strength of machine learning in predicting transport energy, as well as the first techno-economic-environmental breakdown analysis of CNG utilisation in Nigeria. It concludes that CNG is both possible and disruptive, as long as methane escape is controlled and policies and infrastructure are in place to support it.