Abstract
The level of electromagnetic radiation (EMR) exposure increases day by day as natural consequences of technological developments. In recent years, the increasing use of cellular systems has made it necessary to measure and evaluate EMR originating from base stations. In this study, broadband and band selective electric field strength (E) measurements were taken at four different times in order to evaluate the change of short term E in Atakum district of Samsun, Turkey. The measurements were collected from 46 different locations using a SRM 3006 and a PMM 8053 EMR meter in a band from 100 kHz to 3 GHz, and the maximum E (Emax) and the average E (Eavg) were recorded. The highest values have been noticed in these measurements at 9.45 V/m and 17.53 V/m for Eavg and Emax respectively. Apart from these measurements, 24 hour long term E measurements were taken at a location where the highest value was observed and analyzed, to observe the change of Es during a day. At the end of the study, a tentative mathematical model that helps in computing the total E of the medium with 95% accuracy, was obtained.
Introduction
With the rapidly evolving technology, the use of wireless communication systems increases day by day. Devices using wireless systems use electromagnetic waves for communication, and these systems conduce toward an increase in the use of electromagnetic radiation (EMR). Cellular systems occupy a large part of our daily lives in wireless systems and cellular systems users communicate with each other with the help of base stations. Users demanding communications from anywhere, increase of multimedia usage, and the ability of base stations to operate a limited number of users at the same time, force operators to install more base stations. Established base stations are actively broadcasting EMR for 24 hours a day so that people living in these areas are exposed to EMR radiation of the base stations even if they do not want to be. Each base station behaves like an EMR source, and this increase in base stations causes the level of EMR that is exposed to increase daily.
There are a number of limitations and standards that have resulted from some research by certain international organizations that are examining the effects of EMR on human health. These limitations are specified by the International Commission on Non-Ionizing Radiation Protection (ICNIRP) [1], which is based on the assumption of 24 hour exposure recognized by the World Health Organization (WHO). In Turkey, restrictions and regulations related to exposure to EM fields are established by the Information and Communication Technologies Authority of Turkey (ICTA) [2]. In Turkey, 75% of ICNIRP’s restriction values are applied by ICTA. The electric field limit values determined by ICTA and ICNIRP are shown in Table 1. The values in this table are the average values given after EMR exposure for six minutes. There are 3 communication operators in Turkey currently used by the users and they use 2G (second generation), 3G (third generation) and 4G (fourth generation) systems. According to [2], the electric field strength (E) limits are 30.9 (V/m) for 900 MHz base station, 43.7 (V/m) for 1800 MHz base station, 45.75 (V/m) for 3G systems, which is 2100 MHz, and also 45.75 (V/m) for 2600 MHz base station.
Reference EMR levels of ICNIRP and ICTA
Frequency range (MHz) | E (V/m) | |
---|---|---|
ICNIRP | ICTA | |
0.010 – 0.15 | 87 | 65.25 |
0.15 - 1 | 87 | 65.25 |
1 - 10 | 87/f1/2 | 65.25/f1/2 |
10 - 400 | 28 | 21 |
400 - 2000 | 1.375f1/2 | 1.03f1/2 |
2000 - 60000 | 61 | 45.75 |
f is frequency in MHz |
Obtaining EMR values in crowded settlements, especially where there are too many cellular systems, is very important to be able to examine the effects of EMR on human health. For this reason, a number of studies have been conducted in the literature [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13] to measure EMR contamination from base stations and to investigate the effects of these measurements on human health. Therefore, in this study, E measurements were taken at four different times in order to examine and evaluate the change of E in Atakum district which is one of the most crowded districts of Samsun, Turkey.
1 Electrical field strength measurements
In this study, the E measurements were conducted using a SRM-3006 and a PMM 8053 EMR meter in Atakum district at 46 different locations considering the number of users, distance from base stations and line of sight. In the measurements, the maximum E (Emax) and the average E (Eavg) were recorded. The total E in the band between 100 kHz – 3 GHz is measured using the PMM–8053 with the EP-330 isotropic electric field probe [14] twice in August 2015 named as M1, M2, and in December 2016, named as M3, and M4 respectively, while band selective measurements are conducted using the Narda SRM–3006 with the 3501/03 isotropic E-field probe [15] in February 2017. The E measurement locations are shown in Figure 1, and visuals of the measurements using the PMM-8053 and SRM-3006 are shown in Figure 2.

Measurement locations in Atakum district

Taking measurement with a-) PMM 8053, b-) SRM 3006 EMR meter
2 Measurement results
The changes in the Emax and the Eavg, which were measured at 46 different locations, are given in Figure 3a and Figure 3b respectively. As seen from Figure 3a, the maximum Emax acquired is 3.72 V/m at location 26 for the second measurement (M2), while maximum Eavg acquired is 2.67 V/m at location 26 for the third measurement (M3). The reason for the high E values observed at this point may be due to the fact that the location has a high user density and is close to one of the base stations. The statistical characteristics of measured values are specified and listed in Table 2.

a) Maximum (Emax) b) Average (Eavg) Es versus locations
Statistical characteristics of the measured values
Emax (V/m) | Eavg (V/m) | |||||
---|---|---|---|---|---|---|
Max. | Mean | Std. | Max. | Mean | Std. | |
M1 | 3.65 | 1.22 | 0.56 | 1.85 | 0.45 | 0.41 |
M2 | 3.72 | 0.86 | 0.63 | 2.10 | 0.40 | 0.43 |
M3 | 3.32 | 0.91 | 0.78 | 2.67 | 0.57 | 0.62 |
M4 | 3.48 | 0.94 | 0.83 | 2.41 | 0.53 | 0.58 |
Band selective measurements were fulfilled at all locations using the Narda SRM 3006 to specify the effect of E sources into the total E. All band selective measurements are shown in Figure 3. An example of the details of the SRM–3006 measurements, which involve the E sources (frequency ranges, service name etc.), caused pollution as shown in Table 3 for location 26. In the table, each E source has a specific index number and the 23rd index is the representation of E levels inclusive of undefined frequency bands, and the 24th index is the representation of total E (ET values of the medium.

Band selective E values
Frequency selective E values
Index | Service Name | Lower Frequency | Upper Frequeue | E (V/m) |
---|---|---|---|---|
I | Low Band | 30 MHz | 37.3 MHz | 0.133 |
FM Band | 87.5 MHz | 108 MHz | 0.021 | |
3 | Air Band | 108.1 MHz | 136 MHz | 0.022 |
4 | Land Band-I | 130.1MHz | 173 MHz | 0.021 |
5 | TV VHF Band | 173.1MHz | 230 MHz | 0.023 |
6 | Laud Band-II | 230.1 MHz | 400 MHz | 0.026 |
7 | Land Band-III | 400.1MHz | 470 MHz | 0.015 |
8 | TV UHF Band | 470.1 MHz | 790.9 MHz | 0.084 |
9 | LTE800 | 791MHz | 820.9 MHz | 1.402 |
10 | ETCÌ | 821MHz | 925 MHz | 0.057 |
11 | LTE900 | 925.1MHz | 935.1 MHz | 0.913 |
12 | GSM900 | 935.1 MHz | 961.0 MHz | 2.048 |
13 | ETC2 | 961.1MHz | 1.805 GHz | 0.147 |
14 | GSM1800 | 1.805 GHZ | 1.820 GHz | 0.554 |
15 | LTE1800 | 1.820 MHz | 1.879 MHz | 0.456 |
16 | DECT | 1.880 GHz | 1.899 GHz | 0.024 |
17 | ETC3 | 1.899 GHz | 2.010 GHz | 0.067 |
18 | UMTS2100 | 2.010 GHz | 2.170 GHz | 2.243 |
19 | ETC4 | 2.171 GHz | 2.399 GHz | 0.034 |
20 | WLAN | 2.400 GHz | 2.483 GHz | 0.314 |
21 | ETC 5 | 2.484 GHz | 2.569 GHz | 0.031 |
22 | LTE2600 | 2.570 MHz | 2.660 MHz | 0.082 |
23 | Residual services | 0.598 | ||
24 | Total | 3.616 |
It is seen from Table 3 that the primary sources of E are LTE900, LTE800, GSM1800, GSM900, LTE1800, and UMTS2100 bands. When total E is 3.616 V/m, 2.243 V/m of this value is produced by UMTS2100, while 2.048 V/m, 1.402 V/m, and 0.913 V/m are produced by GSM900, LTE800, and LTE900 respectively. The total E of medium is computed as follows:
where Ei is the electric field for ith band. The other transmitters excluding 18 bands give rise to E23. The contribution percentage (Pi) of each band is computed as in Eq. 2.
The pie chart illustrating the divisions of all E sources is given in Figure 5 for location 26. As seen from Figure 5, 88.7% of total E in the medium is emitted by base stations which use LTE800, LTE900, GSM900, LTE1800, UMTS2100, and the other frequency bands. Among these systems, UMTS2100 has the most contribution with 43.6%.

Pie chart of E
Long term E measurements were taken to determine the change of E values measured at location 26 during a day, and the results are given in Figure 6. Figure 7 shows the measurement location 26. Measurements started at 6pm and continued until the next day. Figure 6 shows a great variation depending on the measurement hours. It is seen that the number of users actively using the base station is the main factor influencing the E. Low E values were measured between the hours of 05:00–07:00 in the morning (mean E is 7.05 V/m), and very high E values between 12:00 and 18:00 hours (mean E is 10.5 V/m). The highest measured E value was 17.53 V/m while the 24 hour average was 9.45 V/m. The standard deviation value is 2.02 V/m for this 24 hour measurement.

E levels measured for 24 hour at location 26

A picture of location 26
3 Analysis
Total E value of medium is calculated with Eq. 3 with the use of band selective measurements. In this equation, all service names’ E value will be represented with an index number (e.g. E10 for GSM900) throughout the rest of the paper. The estimated total E of the medium (ET) can be computed with Eq. 3 using the six bands which consist of 88.7% of total E.
In order to evaluate the performance of the method Normalized Root Mean Square Error (NRMSE) is computed as follows:
where ET,i is actual E value, ÊT,i is estimated E, i is measurement location, and N is the number of measurements locations.
The NRMSE is 0.0729 between ET and ÊT for Eq. 3. In order to obtain lower NRMSE multilinear regression [16] was implemented and total E in medium is estimated as follows;
NRMSE between between ET and ÊT is calculated as 0.0705 using this equation. Figure 8 shows estimated E values using Eq. 3, and Eq. 5, and actual E values of corresponding measurement locations. It is seen from Figure 8, Eq. 3 gives the best performance especially actual E values lower than 0.5 V/m, while Eq. 5 gives better performance for high E values. Therefore a new empirical E estimation model can be proposed combined of Eq. 3 and Eq. 5 and given in Eq. 6. The NRMSE is 0.0538 between ET and ÊT for Eq. 6.

Multilinear regression analysis
4 Conclusion
In this study, for observing the change of E in Atakum district of Samsun, Turkey, three stage measurements were conducted. In the first stage, short term E measurements were taken at four different times and at 46 different locations. It can be seen from the measurements that E values may change with time and the measurement locations. It can be inferred from the measurements results that the maximum recorded Emax is 17.53 V/m while the maximum Eavg is 9.45 V/m which are below the limits determined by the ICTA and ICNIRP. It is also seen from the results that Eavg has increased within measurement periods. In the second stage, in order to define the main E source in Atakum district, band selective E measurements were performed at the same locations using the SRM 3006. An extensive analysis of band selective measurements demonstrates that the primary E sources in Atakum district are the base stations which use LTE800, LTE900, GSM900, LTE1800, UMTS2100 frequency bands, and 2100MHz has the most contribution to total E value with 43.6%. In the third stage long term E measurements were recorded to assess the changing of E during the day. It is seen from the results that the E level in the morning increases by 48.9% compared to the measurements in the afternoon. At the end of the study a tentative mathematical model was obtained to estimate E in the medium with an accuracy of up to 95%.
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© 2018 Cetin Kurnaz et al., published by De Gruyter
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.
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- Depiction and analysis of a modified theta shaped double negative metamaterial for satellite application
- An attempt to geometrize electromagnetism
- Structure of traveling wave solutions for some nonlinear models via modified mathematical method
- Thermo-convective instability in a rotating ferromagnetic fluid layer with temperature modulation
- Construction of new solitary wave solutions of generalized Zakharov-Kuznetsov-Benjamin-Bona-Mahony and simplified modified form of Camassa-Holm equations
- Effect of magnetic field and heat source on Upper-convected-maxwell fluid in a porous channel
- Physical cues of biomaterials guide stem cell fate of differentiation: The effect of elasticity of cell culture biomaterials
- Shooting method analysis in wire coating withdrawing from a bath of Oldroyd 8-constant fluid with temperature dependent viscosity
- Rank correlation between centrality metrics in complex networks: an empirical study
- Special Issue: The 18th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering
- Modeling of electric and heat processes in spot resistance welding of cross-wire steel bars
- Dynamic characteristics of triaxial active control magnetic bearing with asymmetric structure
- Design optimization of an axial-field eddy-current magnetic coupling based on magneto-thermal analytical model
- Thermal constitutive matrix applied to asynchronous electrical machine using the cell method
- Temperature distribution around thin electroconductive layers created on composite textile substrates
- Model of the multipolar engine with decreased cogging torque by asymmetrical distribution of the magnets
- Analysis of spatial thermal field in a magnetic bearing
- Use of the mathematical model of the ignition system to analyze the spark discharge, including the destruction of spark plug electrodes
- Assessment of short/long term electric field strength measurements for a pilot district
- Simulation study and experimental results for detection and classification of the transient capacitor inrush current using discrete wavelet transform and artificial intelligence
- Magnetic transmission gear finite element simulation with iron pole hysteresis
- Pulsed excitation terahertz tomography – multiparametric approach
- Low and high frequency model of three phase transformer by frequency response analysis measurement
- Multivariable polynomial fitting of controlled single-phase nonlinear load of input current total harmonic distortion
- Optimal design of a for middle-low-speed maglev trains
- Eddy current modeling in linear and nonlinear multifilamentary composite materials
- The visual attention saliency map for movie retrospection
- AC/DC current ratio in a current superimposition variable flux reluctance machine
- Influence of material uncertainties on the RLC parameters of wound inductors modeled using the finite element method
- Cogging force reduction in linear tubular flux switching permanent-magnet machines
- Modeling hysteresis curves of La(FeCoSi)13 compound near the transition point with the GRUCAD model
- Electro-magneto-hydrodynamic lubrication
- 3-D Electromagnetic field analysis of wireless power transfer system using K computer
- Simplified simulation technique of rotating, induction heated, calender rolls for study of temperature field control
- Design, fabrication and testing of electroadhesive interdigital electrodes
- A method to reduce partial discharges in motor windings fed by PWM inverter
- Reluctance network lumped mechanical & thermal models for the modeling and predesign of concentrated flux synchronous machine
- Special Issue Applications of Nonlinear Dynamics
- Study on dynamic characteristics of silo-stock-foundation interaction system under seismic load
- Microblog topic evolution computing based on LDA algorithm
- Modeling the creep damage effect on the creep crack growth behavior of rotor steel
- Neighborhood condition for all fractional (g, f, n′, m)-critical deleted graphs
- Chinese open information extraction based on DBMCSS in the field of national information resources
- 10.1515/phys-2018-0079
- CPW-fed circularly-polarized antenna array with high front-to-back ratio and low-profile
- Intelligent Monitoring Network Construction based on the utilization of the Internet of things (IoT) in the Metallurgical Coking Process
- Temperature detection technology of power equipment based on Fiber Bragg Grating
- Research on a rotational speed control strategy of the mandrel in a rotary steering system
- Dynamic load balancing algorithm for large data flow in distributed complex networks
- Super-structured photonic crystal fiber Bragg grating biosensor image model based on sparse matrix
- Fractal-based techniques for physiological time series: An updated approach
- Analysis of the Imaging Characteristics of the KB and KBA X-ray Microscopes at Non-coaxial Grazing Incidence
- Application of modified culture Kalman filter in bearing fault diagnosis
- Exact solutions and conservation laws for the modified equal width-Burgers equation
- On topological properties of block shift and hierarchical hypercube networks
- Elastic properties and plane acoustic velocity of cubic Sr2CaMoO6 and Sr2CaWO6 from first-principles calculations
- A note on the transmission feasibility problem in networks
- Ontology learning algorithm using weak functions
- Diagnosis of the power frequency vacuum arc shape based on 2D-PIV
- Parametric simulation analysis and reliability of escalator truss
- A new algorithm for real economy benefit evaluation based on big data analysis
- Synergy analysis of agricultural economic cycle fluctuation based on ant colony algorithm
- Multi-level encryption algorithm for user-related information across social networks
- Multi-target tracking algorithm in intelligent transportation based on wireless sensor network
- Fast recognition method of moving video images based on BP neural networks
- Compressed sensing image restoration algorithm based on improved SURF operator
- Design of load optimal control algorithm for smart grid based on demand response in different scenarios
- Face recognition method based on GA-BP neural network algorithm
- Optimal path selection algorithm for mobile beacons in sensor network under non-dense distribution
- Localization and recognition algorithm for fuzzy anomaly data in big data networks
- Urban road traffic flow control under incidental congestion as a function of accident duration
- Optimization design of reconfiguration algorithm for high voltage power distribution network based on ant colony algorithm
- Feasibility simulation of aseismic structure design for long-span bridges
- Construction of renewable energy supply chain model based on LCA
- The tribological properties study of carbon fabric/ epoxy composites reinforced by nano-TiO2 and MWNTs
- A text-Image feature mapping algorithm based on transfer learning
- Fast recognition algorithm for static traffic sign information
- Topical Issue: Clean Energy: Materials, Processes and Energy Generation
- An investigation of the melting process of RT-35 filled circular thermal energy storage system
- Numerical analysis on the dynamic response of a plate-and-frame membrane humidifier for PEMFC vehicles under various operating conditions
- Energy converting layers for thin-film flexible photovoltaic structures
- Effect of convection heat transfer on thermal energy storage unit