Regulatory Deficits and the Socio-Environmental Footprint of GSM Mast Operations in Jalingo LGA, Nigeria

This study investigates the systemic challenges within the environmental regulatory framework. It evaluates the perceived environmental and health impacts of Global System for Mobile Communications (GSM) mast operations in Jalingo Local Government Area (LGA), Taraba State, Nigeria. Utilizing a 2025 field survey of 60 regulatory stakeholders and 150 residents, the research identifies critical institutional weaknesses and their tangible consequences for host communities. The findings reveal profound regulatory deficits, with inadequate monitoring (81.7%), overlapping agency functions (75.0%), and weak enforcement of penalties (70.0%) identified as primary barriers to compliance. Consequentially, residents reported significant negative impacts, including pervasive noise pollution (79.3%), visual intrusion (70.7%), and widespread health anxieties related to radiation exposure (62.7%). Environmental degradation, such as vegetation loss and drainage obstruction, was also prevalent. The study concludes that the low level of operator compliance is not merely an issue of corporate negligence but a direct outcome of a structurally deficient governance system, which in turn creates significant socio-environmental burdens for urban communities.

Regulatory Deficits, GSM Mast Operator, Socio-environmental

1. Afolabi, O. (2019). Compliance in the telecommunications sector in Sub-Saharan Africa: A review of regulatory frameworks and challenges. Journal of African Studies, 27(1), 88–105. [Google Scholar] [Crossref]

2. Arowolo, A. O. (2018). Modernizing environmental enforcement in Nigeria's telecom sector: Capacity building and digital solutions. Journal of Environmental Policy & Planning, 20(6), 712–728. https://doi.org/10.1080/1523908X.2018.1476789 [Google Scholar] [Crossref]

3. Chinedu, O. O., Henry, A. T., Nene, J. J., & Okwudili, J. D. (2020). Work-related musculoskeletal disorders among office workers in higher education institutions: A cross-sectional study. Ethiopian journal of health sciences, 30(5). [Google Scholar] [Crossref]

4. Edeh, C. O. (2020). Challenges of environmental regulation enforcement in Nigeria: A sectorial analysis. Nigerian Environmental Law Review, 12(1), 34–52. https://www.nelr.org.ng/vol12/issue1/edeh.pdf [Google Scholar] [Crossref]

5. Jibasen, A., Shempan, D. G., Danjuma, A. K., & Sankun, W. P. (2026). Assessment of GSM mast distribution and compliance with environmental regulations in Jalingo Local Government Area, Taraba State, Nigeria. International Journal of Research in Environmental Science, 12(1), 9–16. https://doi.org/10.20431/2454-9444.1201002 [Google Scholar] [Crossref]

6. Nwokedi, C. I., & Bello, M. A. (2022). Variations in environmental compliance among telecom operators in Abuja: Capacity and policy implications. Journal of Sustainable Development in Africa, 24(5), 112–128. https://doi.org/10.4314/jsda.v24i5.3 [Google Scholar] [Crossref]

7. Ogunleye, E. O. (2021). Inter-agency coordination challenges in Nigerian environmental governance: Telecom sector evidence. Nigerian Institute of Environmental Regulators Journal, 5(2), 78–94. https://doi.org/10.5897/NIERJ2021.0101 [Google Scholar] [Crossref]

8. Oruonye E.D., Felix J, & Ahmed Y.M. (2021). An Assessment of the Level of Compliance of GSM Mast Location to Environmental Standard Regulations. Scholars Academic Journal of Biosciences 9(4): 103-110. DOI: 10.36347/sajb.2021.v09i04.001 [Google Scholar] [Crossref]

9. World Health Organization. (2023). Electromagnetic fields and public health: Base stations and wireless technologies. WHO Press. https://www.who.int/publications/i/item/9789240076097 [Google Scholar] [Crossref]

10. Yusuf, H. A., & Nwachukwu, E. O. (2022). Stakeholder consultation deficits in Nigerian telecom infrastructure: A 180-site audit. Journal of Sustainable Development in Africa, 24(7), 189–205. https://doi.org/10.4314/jsda.v24i7.5 [Google Scholar] [Crossref]

11. Yusuf, H. A., & Nwafor, C. O. (2023). Multi-city analysis of GSM generator emissions: Noise and PM2.5 exceedances. Atmospheric Environment, 310, 119678. https://doi.org/10.1016/j.atmosenv.2023.119678 [Google Scholar] [Crossref]

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