Longitudinal study of exposure to radio frequencies at population scale
Longitudinal study of exposure to radio frequencies at population scale
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DOI：
10.1016/j.envint.2022.107144
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发表时间：
2022-03-24
影响因子：
11.8
通讯作者：
Dabbous, Walid
中科院分区：
文献类型：
--
作者：
Boussad, Yanis;Chen, Xi (Leslie);Dabbous, Walid
评估人群规模的无线电频率暴露对于开展关于射频辐射可能对健康造成的影响的健全的流行病学研究是重要的。许多研究报告称，人们暴露在无线电信技术中使用的射频辐射中，但使用的人口样本非常少。在这种情况下，人们对人口规模的真实暴露仍然知之甚少。在这里，据我们所知，我们报告了从2017年1月到2020年12月，13个国家/地区的254,410名独立用户对蜂窝天线、Wi-Fi接入点和蓝牙设备产生的射频暴露的最大基于人群的测量。首先，我们介绍了使用使用ElectrSmart Android应用程序获得的智能手机测量结果来评估人群暴露在射频辐射中的方法。然后，我们使用这些方法来评估和表征射频暴露的演变。我们显示，在所考虑的四年期间，总曝光量增加了2.3倍，Wi-Fi是最大的贡献者。细胞暴露水平比监管限值低几个数量级，与国家监管政策无关。人们往往更多地暴露在家里；对于一半的研究对象来说，个人Wi-Fi路由器和蓝牙设备占他们总暴露的50%以上。在这项工作中，我们展示了基于众源的数据如何允许对人群暴露于射频辐射的大规模和长期评估。
Evaluating exposure to radio frequencies (RF) at population-scale is important for conducting sound epidemiological studies about possible health impact of RF radiations. Numerous studies reported population exposure to RF radiations used in wireless telecommunication technologies, but used very small population samples. In this context, the real exposure of the population at scale remains poorly understood. Here, to the best of our knowledge, we report the largest crowd-based measurement of population exposure to RF produced by cellular antennas, Wi-Fi access points, and Bluetooth devices for 254,410 unique users in 13 countries from January 2017 to December 2020. First, we present methods to assess the population exposure to RF radiations using smart phone measurements obtained using the ElectroSmart Android app. Then, we use these methods to evaluate and characterize the evolution of RF exposure. We show that total exposure has been multiplied by 2.3 in the fouryear period considered, with Wi-Fi as the largest contributor. The cellular exposure levels are orders of magnitude lower than regulation limits and are not correlated to national regulation policies. The population tends to be more exposed at home; for half of the study subjects, personal Wi-Fi routers and Bluetooth devices contributed to more than 50% of their total exposure. In this work, we showcase how crowdsource-based data allow large-scale and long-term assessment of population exposure to RF radiations.