Influence of traffic variations on exposure to wireless signals in realistic environments

Abstract

In this article, the general public daily exposure to broadcast signals and Global System for Mobile Communications (GSM) or Universal Mobile Telecommunications System (UMTS) mobile telephone signals in indoor areas is investigated. Temporal variations and traffic distributions during a day at different indoor sites in urban and rural zones are presented. The goal is to analyze the real exposure compared to the maximum assessment imposed by radio protection standards and to characterize the ratio between daily and maximum theoretical values. Hence, a realistic maximum is proposed based on the statistical analysis performed using measurements. Broadcast signals remain constant over the day so they are best fitted with a Normal distribution while the mobile telephone signals depend on the traffic demand during the day so they fit a three-Gaussian distribution model. A general mask is also constructed for underlining the maximum equivalent active traffic for different periods in the day. Also, relations between the mean values over 24 h, the realistic maximal values (at 99%) and the maximal theoretical values are presented. The realistic maximum is also presented with a sliding time average of 6 min applied to the measurements in accordance with international standards. An extrapolation factor is given for the different systems to easily assess the maximum values starting from an instantaneous measurement. The extrapolation factor is also given for a broadband measurement to estimate the maximum potential exposure during the day.

Temporal trends of radio-frequency electromagnetic field (RF-EMF) exposure in everyday environments across European cities

“…However, difference in exposure has been found to be low between different days of the week (Beekhuizen et al, 2013;Joseph and Verloock, 2010;Joseph et al, 2009). Exposure from mobile phone base stations seems to be slightly higher during weekdays than weekend (Joseph et al, 2009, Mahfouz et al, 2013 and electric field strength was found to be about 10-30 percent higher during daytime than during nighttime (Manassas et al, 2012, Mahfouz et al, 2011, indicating some overestimation of the average exposure situation.…”

“…These studies found that RF-EMF levels in the everyday environment are far below the regulatory limits. Several studies examined short-term temporal variability of RF-EMF exposure during one day (Mahfouz et al, 2011;Mahfouz et al, 2013;Manassas et al, 2012;Miclaus et al, 2013) or up to one week (Joseph and Verloock, 2010;Joseph et al, 2009;Vermeeren et al, 2013) addressing variation between daytime and nighttime or during weekdays and weekends (Joseph et al, 2009). However, studies evaluating temporal trends over longer time periods as one year are lacking so far.…”

Evaluation of farmers' OSH hazard in operationnearby mobile telephone radio base stations

“…In planning the field test, particular care was given in considering the lowest usage rate of mobile phone in non-urban areas if compared to urban ones [13] and during week-end if compared to working days. [23]: the field test took place on working days daytime which can be considered the periods with a much more extensive phone usage [21][22].…”

Temporal 24-hour assessment of radio frequency exposure in schools and homes

“…Only limited data about temporal variations are available [8,9,10,11,12,13,15]. Existing literature and procedures are discussed in detail in [8] and [10] and a CENELEC standard has been proposed for the in-situ measurement of electromagnetic-field strength [16].…”

“…In [10], Erlang data (representing average mobile phone traffic intensity during a period of time) is related to RF exposure using temporal measurements during a week. [11] compared real exposure with the maximal estimated exposure to characterize the ratio between daily and maximum theoretical exposure values, while [12] compared various realistic extrapolation methods in two countries. The authors of [13] also stated that short-term exposure assessment is not reliable for evaluation of long-term exposure.…”