The Carbon Footprint Paradox: CO2 Emissions, Regulatory Gaps, and Mitigation Pathways of AI-Powered Data Centres in Nigeria

JEFFREY Tersugh Chinyam, MOHAMMED Jibril, I. Y. Chindo, MUDATHIR Qossim

Abstract


Data centre emissions are still relatively small compared to large sectors such as electricity generation and industry. However, there is pressure on power supplies and water resources and this has made AI to be considered potential to cut emissions in other areas and could offset many times its own carbon footprint when used effectively. The study aimed to of assess the environmental footprint of AI-powered data centres in Nigeria, with a particular emphasis on carbon dioxide (CO) emissions, which was structured across three complementary analytical levels namely; the macro-level, which focused on national CO emissions projections under various electricity demand and power mix scenarios; the meso-level, which conducts state-by-state siting analysis using spatial data on renewable energy potential, grid stability, and policy framework, the micro-level, which develops facility-specific emissions profiles for selected Nigerian data centre operators and multi-level approach that ensures the findings are directly relevant and actionable for national policymakers, state governments, and private sector operators. The results shows that natural gas as the dominant source of electricity generation in the dataset, with an average quarterly output of 18.4 billion kWh, accounting for 75.4% of total generation. The OLS Linear Regression model achieved the best performance, with an R² of 0.996, RMSE of 0.65 MMT CO, MAE of 0.51 MMT CO, and a maximum prediction error of just 0.98% while projected that CO emissions from data centres in Nigeria will increase rapidly across all scenarios, with compound annual growth rates (CAGR) ranging from 15.2% (Low demand, NDC Conditional) to 57.7% (High demand, Reference Mix). In conclusion, this study demonstrates that AI-powered data centres in Nigeria are on a trajectory to become a materially significant source of greenhouse gas emissions, e-waste, and water consumption in the near future and recommend that Nigeria’s next Nationally Determined Contribution (NDC) should formally incorporate the data centre sector and establish a specific emissions intensity.


Full Text:

PDF

References


AFDC, 2024. Nigeria Data Centre Industry Report 2024. Africa Data Centres Association.

Adeyemi, O.I., Adeleke, O.A., Afolabi, R.T., 2023. Commercial electricity demand dynamics across Nigeria's geopolitical zones. Energy Policy 182, Article 113752. https://doi.org/10.1016/j.enpol.2023.113752

Akintunde, A.O., Olatunde, T.M., 2023. Nigeria's NDC implementation: Financing gaps and renewable energy transition prospects. Renewable and Sustainable Energy Reviews 187, Article 113797.

Alcott, B., 2005. Jevons' paradox. Ecological Economics 54(1), 9–21.

Armstrong, J.S., Overton, T.S., 1977. Estimating nonresponse bias in mail surveys. Journal of Marketing Research 14(3), 396–402.

Bello, S., Wada, I., Ige, O., Chianumba, E., Adebayo, S., 2024. AI-driven predictive maintenance and optimization of renewable energy systems. International Journal of Scientific Research Archive 13, 2823–2837.

Braun, V., Clarke, V., 2006. Using thematic analysis in psychology. Qualitative Research in Psychology 3(2), 77–101.

Chainalysis, 2024. The 2024 Crypto Crime Report. Chainalysis Inc., New York.

Creswell, J.W., Plano Clark, V.L., 2017. Designing and Conducting Mixed Methods Research, 3rd ed. SAGE Publications, Thousand Oaks.

ECN, 2023. Annual Energy Report 2023. Energy Commission of Nigeria, Abuja.

Federal Republic of Nigeria, 2021. Nigeria's Updated Nationally Determined Contribution. FMENV/UNFCCC, Abuja.

Federal Republic of Nigeria, 2023. Electricity Act 2023. Federal Republic of Nigeria Official Gazette, Abuja.

FMENV, 2021. Nigeria's First Biennial Update Report to the UNFCCC. Federal Ministry of Environment, Abuja.

GHG Protocol, 2015. The Greenhouse Gas Protocol: A Corporate Accounting and Reporting Standard, revised ed. World Resources Institute and WBCSD.

Grand View Research, 2024. Nigeria Cloud Computing Market Size and Forecast. Grand View Research, San Francisco.

Grossman, G.M., Krueger, A.B., 1991. Environmental impacts of a North American free trade agreement. NBER Working Paper 3914.

Hajer, M.A., 1995. The Politics of Environmental Discourse. Oxford University Press, Oxford.

IEA, 2023. Data Centres and Data Transmission Networks. International Energy Agency, Paris.

IPCC, 2021. Climate Change 2021: The Physical Science Basis. Sixth Assessment Report, Annex II. Cambridge University Press, Cambridge.

IRENA, 2023. Renewable Power Generation Costs in 2022. International Renewable Energy Agency, Abu Dhabi.

Jevons, W.S., 1865. The Coal Question. Macmillan, London.

Jha, A., Jha, P., 2024. Forecasting Nigeria's power sector emissions using linear regression. Energy Policy 188, Article 114054. https://doi.org/10.1016/j.enpol.2024.114054

Keerthana, M., Suresh, A., Meganathan, D., Kumar, M., 2023. A comparative study of machine learning algorithms for CO₂ emission prediction. Computational Intelligence and Neuroscience 2023, Article 7598441.

Landis, J.R., Koch, G.G., 1977. The measurement of observer agreement for categorical data. Biometrics 33(1), 159–174.

Masanet, E., Shehabi, A., Lei, N., Smith, S., Koomey, J., 2020. Recalibrating global data center energy-use estimates. Science 367(6481), 984–986. https://doi.org/10.1126/science.aba3758

McKinsey, 2023. The economic potential of generative AI: The next productivity frontier. McKinsey Global Institute, New York.

Mol, A.P.J., 1995. The Refinement of Production: Ecological Modernisation Theory and the Chemical Industry. International Books, Utrecht.

NCC, 2024. State of the Industry Report Q4 2023. Nigerian Communications Commission, Abuja.

NERC, 2023. Annual Report and Statement of Accounts 2022. Nigerian Electricity Regulatory Commission, Abuja.

NESREA Act, 2007. National Environmental Standards and Regulations Enforcement Agency (Establishment) Act. Federal Republic of Nigeria Official Gazette.

Nunnally, J.C., 1978. Psychometric Theory, 2nd ed. McGraw-Hill, New York.

Osibo, B.K., Adamo, F., 2023. Water consumption benchmarking for data centres in Sub-Saharan Africa. International Journal of Environmental Science and Technology 20(11), 7841–7854.

Patterson, D., Gonzalez, J., Le, Q.V., et al., 2021. Carbon emissions and large neural network training. arXiv:2104.10350.

Rack Centre, 2024. Nigeria Data Centre Capacity Overview 2024. Rack Centre, Lagos.

Shehabi, A., Smith, S.J., Sartor, D.A., et al., 2016. United States Data Center Energy Usage Report (LBNL-1005775). Lawrence Berkeley National Laboratory.

Siddik, M.A.B., Shehabi, A., Marston, L., 2021. The environmental footprint of data centers in the United States. Environmental Research Letters 16(6), Article 064017.

Strubell, E., Ganesh, A., McCallum, A., 2019. Energy and policy considerations for deep learning in NLP. Proceedings ACL 2019, 3645–3650.

UNEP, 2023. E-Waste in West Africa: A Baseline Assessment of Nigeria. United Nations Environment Programme, Nairobi.


Refbacks

  • There are currently no refbacks.