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Research Article Open access CC BY 4.0

Measurement and Evaluation of Radiation Power Density Emitted from Mobile Cellular Base Stations in Abuja and its Environ, Nigeria

Ibrahim Aminu, J. T. Zhimwang, D. Adewumi, R. S. Ibrahim, M. Z. Musa, D. D. Matthew

Asian Journal of Research and Reviews in Physics · pp. 7–13 · Published 21 Jan 2021

10.9734/ajr2p/2021/v4i130132

Abstract

This paper presents measurement and evaluation of radiation power density emitted from mobile cellular base stations in Abuja and it’s environ. Forty (40) mobile base stations with ten (10) each from AIRTEL, ETISALAT, GLO and MTN located in areas with high population were randomly examined across Abuja. Broadband analysis method was employed in the measurement of the radiation power density. The results obtained shows that most of the base stations recorded lower radiation power density below the safety standard value of 4.5watt/m2 , 22.5 watt/m2 for 900MHz frequency though few base stations recorded above standard value: GLO-BS02, GLO-BS03 and MTN-BS02 recorded 59.02 mW/m2, 39.76 mW/m2 and 46.70 mW/m2 respectively. The result also revealed that as distance increases, the mean power density reduces. This is to said that human exposure to radio frequency radiation have less or no health hazard at distance far away from the mobile cellular base station.

Mobile cellular radio frequency and radiation power density.

References (6)

  1. 1 Comparative international analysis of radiofrequency exposure surveys of mobile communication radio base stations [DOI]
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  3. 3 High Frequency Radiation and Human Exposure
  4. 4 Absorption of EM energy by human body in the vicinity of the GSM base station antenna [DOI]
  5. 5 Occupational Exposure to Base Stations—Compliance With EU Directive 2004/40/EC [DOI]
  6. 6 Power-Frequency Fields and Cancer [DOI]

Cited by 4

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Prediction of electromagnetic power density emitted from GSM base stations by using multiple linear regression

Sema Atasever, Uğur Sorgucu · International Journal of Applied Mathematics Electronics and Computers · 2023

Mobile Base Station User Scheduling Optimization Algorithm Based on Graph Neural Network

Jingya Zhang · Engineering Reports · 2026

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