Monopolar tDCS might affect brainstem reflexes: A computational and neurophysiological study.

OBJECTIVE: To assess whether monopolar multi-electrode transcranial direct current stimulation (tDCS) montages might selectively affect deep brain structures through computational predictions and neurophysiological assessment. METHODS: Electric field distribution in deep brain structures (i.e., thalamus and midbrain) were estimated through computational models simulating tDCS with two monopolar and two monopolar multi-electrode montages. Monopolar multi-electrode tDCS was then applied to healthy subject, and effects on pontine and medullary circuitries was evaluated studying changes in blink reflex (BR) and masseter inhibitory reflex (MIR). RESULTS: Computational results suggest that tDCS with monopolar multi-electrode montages might induce electric field intensities in deep brain structure comparable to those in grey matter, while neurophysiological results disclosed that BR and MIR were selectively modulated by tDCS only when cathode was placed over the right deltoid. CONCLUSIONS: Multi-electrode tDCS (anodes over motor cortices, cathode over right deltoid) could induce significant electric fields in the thalamus and midbrain, and selectively affect brainstem neural circuits. SIGNIFICANCE: Multi-electrode tDCS (anodes over motor cortices, cathode over right deltoid) might be further explored to affect brainstem activity, also in the context of non-invasive deep brain stimulation.

Assessment of the Variability of Human Exposure to Radiofrequency Electromagnetic Fields Arising from 5.9 GHz Vehicular Communication in Urban Environments.

This paper assessed the variability of radiofrequency exposure among road users in urban settings due to vehicle-to-vehicle (V2V) communication operating at 5.9 GHz. The study evaluated the absorbed dose of radiofrequencies using whole-body specific absorption rate (SAR) in human models spanning different age groups, from children to adults. To overcome limitations of previous studies, we developed a novel hybrid procedure that combines deterministic and stochastic approaches, enabling assessment across multiple urban layouts. Real urban conditions and varying propagation scenarios were considered in SAR calculations. By varying the road user's position within 1.5-300 m from transmitting cars, the SAR distribution was determined. Median SAR remained consistently low, around 0.70 mW/kg, even with multiple transmitting cars and multiple emitting antennas, using maximum power allowed in US (44.8 dBm). The 99th percentile of SAR distribution varied based on body mass, decreasing for heavier models (typically adults) and increasing with the number of transmitting cars and antennas. The highest absorbed dose (73 mW/kg) occurred in a child model. The SAR consistently remained below the 80 mW/kg limit for whole-body exposure to electromagnetic fields in the 100 kHz-300 GHz range.

Assessment of Children's Exposure to Intelligent Transport System 5.9 GHz Vehicular Connectivity Using Numerical Dosimetry.

This study investigates the radio-frequency electromagnetic field exposure (RF-EMF) levels in pedestrians generated by vehicular communication technology. We specifically investigated exposure levels in children of different ages and both genders. This study also compares the children's exposure levels generated by such technology with those of an adult investigated in our previous study. The exposure scenario consisted of a 3D-CAD model of a vehicle equipped with two vehicular antennas operating at 5.9 GHz, each fed with 1 W power. Four child models were analyzed near the front and back of the car. The RF-EMF exposure levels were expressed as the Specific Absorption Rate (SAR) calculated over the whole body and 10 g mass (SAR10g) of the skin and 1 g mass (SAR1g) of the eyes. The maximum SAR10g value of 9 mW/kg was found in the skin of the head of the tallest child. The maximum whole-body SAR was 0.18 mW/kg and was found in the tallest child. As a general result, it was found that children's exposure levels are lower than those of adults. All the SAR values are well below the limits recommended by the International Commission on Non-Ionizing Radiation Protection (ICNIRP) in the general population.

Framework for multirisk climate scenarios across system receptors with application to the Metropolitan City of Venice.

Climate change influences the frequency of extreme events that affect both human and natural systems. It requires systemic climate change adaptation to address the complexity of risks across multiple domains and tackle the uncertainties of future scenarios. This paper introduces a multirisk analysis of climate hazard, exposure, vulnerability, and risk severity, specifically designed to hotspot geographic locations and prioritize system receptors that are affected by climate-related extremes. The analysis is demonstrated for the Metropolitan City of Venice. Representative scenarios (RCP4.5 and RCP8.5) of climate threats (i.e., storm surges, pluvial flood, heat waves, and drought) are selected and represented by projections of Regional Climate Models for a 30-year period (2021-2050). A sample of results is as follows. First, an increase in the risk is largely due to drought, pluvial flood, and storm surge, depending on the areas of interest, with the overall situation worsening under the RCP8.5 scenario. Second, particular locations have colocated vulnerable receptors at higher risk, concentrated in the urban centers (e.g., housing, railways, roads) and along the coast (e.g., beaches, wetlands, primary sector). Third, risk communication of potential environmental and socio-economic losses via the multirisk maps is useful to stakeholders and public administration. Fourth, the multirisk maps recommend priorities for future investigation and risk management, such as collection of sensor data, elaboration of mitigations, and adaptation plans at hotspot locations.

Assessment of SAR in Road-Users from 5G-V2X Vehicular Connectivity Based on Computational Simulations.

(1) Background: Cooperative Intelligent Transportation Systems (C-ITS) will soon operate using 5G New-Radio (NR) wireless communication, overcoming the limitations of the current V2X (Vehicle-to-Everything) wireless communication technologies and increasing road-safety and driving efficiency. These innovations will also change the RF exposure levels of pedestrians and road-users in general. These people, in fact, will be exposed to additional RF sources coming from nearby cars and from the infrastructure. Therefore, an exposure assessment of people in the proximity of a connected car is necessary and urgent. (2) Methods: Two array antennas for 5G-V2X communication at 3.5 GHz were modelled and mounted on a realistic 3D car model for evaluating the exposure levels of a human model representing people on the road near the car. Computational simulations were conducted using the FDTD solver implemented in the Sim4Life platform; different positions and orientations between the car and the human model were assessed. The analyzed quantities were the Specific Absorption Rate on the whole body (SARwb), averaged over 10 g (SAR10g) in specific tissues, as indicated in the ICNIRP guidelines. (3) Results: the data showed that the highest exposure levels were obtained mostly in the head area of the human model, with the highest peak obtained in the configuration where the main beam of the 5G-V2X antennas was more direct towards the human model. Moreover, in all configurations, the dose absorbed by a pedestrian was well below the ICNIRP guidelines to avoid harmful effects. (4) Conclusions: This work is the first study on human exposure assessment in a 5G-V2X scenario, and it expands the knowledge about the exposure levels for the forthcoming use of 5G in connected vehicles.

Modeling of core-shell magneto-electric nanoparticles for biomedical applications: Effect of composition, dimension, and magnetic field features on magnetoelectric response.

The recent development of core-shell nanoparticles which combine strain coupled magnetostrictive and piezoelectric phases, has attracted a lot of attention due to their ability to yield strong magnetoelectric effect even at room temperature, thus making them a promising tool to enable biomedical applications. To fully exploit their potentialities and to adapt their use to in vivo applications, this study analyzes, through a numerical approach, their magnetoelectric behavior, shortly quantified by the magnetoelectric coupling coefficient (αME), thus providing an important milestone for the characterization of the magnetoelectric effect at the nanoscale. In view of recent evidence showing that αME is strongly affected by both the applied magnetic field DC bias and AC frequency, this study implements a nonlinear model, based on magnetic hysteresis, to describe the responses of two different core-shell nanoparticles to various magnetic field excitation stimuli. The proposed model is also used to evaluate to which extent realistic variables such as core diameter and shell thickness affect the electric output. Results prove that αME of 80 nm cobalt ferrite-barium titanate (CFO-BTO) nanoparticles with a 60:40 ratio is equal to about 0.28 V/cm∙Oe corresponding to electric fields up to about 1000 V/cm when a strong DC bias is applied. However, the same electric output can be obtained even in absence of DC field with very low AC fields, by exploiting the hysteretic characteristics of the same composites. The analysis of core and shell dimension is as such to indicate that, to maximize αME, larger core diameter and thinner shell nanoparticles should be preferred. These results, taken together, suggest that it is possible to tune magnetoelectric nanoparticles electric responses by controlling their composition and their size, thus opening the opportunity to adapt their structure on the specific application to pursue.

Modelling of magnetoelectric nanoparticles for non-invasive brain stimulation: a computational study.

Objective.Recently developed magnetoelectric nanoparticles (MENPs) provide a potential tool to enable different biomedical applications. They could be used to overcome the intrinsic constraints posed by traditional neurostimulation techniques, namely the invasiveness of electrodes-based techniques, the limited spatial resolution, and the scarce efficiency of magnetic stimulation.Approach.By using computational electromagnetic techniques, we modelled the behaviour of recently designed biocompatible MENPs injected, in the shape of clusters, in specific cortical targets of a highly detailed anatomical head model. The distributions and the tissue penetration of the electric fields induced by MENPs clusters in each tissue will be compared to the distributions induced by traditional transcranial magnetic stimulation (TMS) coils for non-invasive brain stimulation positioned on the left prefrontal cortex (PFC) of a highly detailed anatomical head model.Main results.MENPs clusters can induce highly focused electric fields with amplitude close to the neural activation threshold in all the brain tissues of interest for the treatment of most neuropsychiatric disorders. Conversely, TMS coils can induce electric fields of several tens of V m-1over a broad volume of the PFC, but they are unlikely able to efficiently stimulate even small volumes of subcortical and deep tissues.Significance.Our numerical results suggest that the use of MENPs for brain stimulation may potentially led to a future pinpoint treatment of neuropshychiatric disorders, in which an impairment of electric activity of specific cortical and subcortical tissues and networks has been assumed to play a crucial role.

Road User Exposure from ITS-5.9 GHz Vehicular Connectivity.

This study addressed an important but not yet thoroughly investigated topic regarding human exposure to radio-frequency electromagnetic fields (RF-EMF) generated by vehicular connectivity. In particular, the study assessed, by means of computational dosimetry, the RF-EMF exposure in road users near a car equipped with vehicle-to-vehicle (V2V) communication antennas. The exposure scenario consisted of a 3D numerical model of a car with two V2V antennas, each fed with 1 W, operating at 5.9 GHz and an adult human model to simulate the road user near the car. The RF-EMF dose absorbed by the human model was calculated as the specific absorption rate (SAR), that is, the RF-EMF power absorbed per unit of mass. The highest SAR was observed in the skin of the head (34.7 mW/kg) and in the eyes (15 mW/kg); the SAR at the torso (including the genitals) and limbs was negligible or much lower than in the head and eyes. The SAR over the whole body was 0.19 mW/kg. The SAR was always well below the limits of human exposure in the 100 kHz-6 GHz band established by the International Commission on Non-Ionizing Radiation Protection (ICNIRP). The proposed approach can be generalized to assess RF-EMF exposure in different conditions by varying the montage/number of V2V antennas and considering human models of different ages.

Simultaneous Bilateral Frontal and Bilateral Cerebellar Transcranial Direct Current Stimulation in Treatment-Resistant Depression-Clinical Effects and Electrical Field Modelling of a Novel Electrodes Montage.

Depressive disorders are one of the leading causes of disability worldwide. Transcranial direct current stimulation (tDCS) is a safe, simple, non-invasive brain stimulation technique showing considerable effectiveness in improving depressive symptoms. Most studies to date have applied anodal tDCS to the left dorsolateral prefrontal cortex (DLPFC), in line with the hypothesis that depressed patients exhibit relative hypoactivity in the left DLPFC compared to the right. Considering the emerging role of the cerebellum in emotional processes, we aimed to study the effect of combining bilateral cerebellar tDCS with the commonly used bifrontal stimulation in patients with severe depression. This open-label pilot study entailed the simultaneous administration of bilateral cerebellar (anode over the left cerebellum, cathode over the right cerebellum) and bilateral frontal (anode over the left DLPFC, cathode over the right DLPFC) tDCS to patients (N = 12) with treatment-resistant depression. The 21-item Hamilton Depression Rating Scale (HDRS) and Beck's Depression Inventory-II (BDI-II) were selected as outcome measures. Electric fields distribution originating from this novel electrode montage was obtained by a computational method applied to a realistic human head model. We observed a 30% reduction of both clinician-rated and self-reported severity of depressive symptoms after only five days (10 sessions) of treatment. Younger age was associated with greater clinical improvement. Adverse events were similar to those of the conventional electrodes montage. The modelling studies demonstrated that the electric fields generated by each pair of electrodes are primarily distributed in the cortical areas under the electrodes. In conclusion, the cerebellum could represent a promising adjunctive target for tDCS interventions in patients with TRD, particularly for younger patients.

Human Exposure Assessment to Wearable Antennas: Effect of Position and Interindividual Anatomical Variability.

(1) Background: This work aims to assess the human exposure to the RF-EMFs emitted by a wearable antenna. (2) Methods: a wearable antenna tuned at f = 2.45 GHz was tested by placing it in six realistic configurations relative to a male and female human model. The exposure assessment was performed by means of computational methods to estimate the SAR10g distributions at 1W of input power. (3) Results: (i) for all the configurations the SAR10g distributions resulted always mainly concentrated on a superficial area immediately below the antenna itself; (ii) the obtained values have shown that the configuration with the highest exposure value was when the antenna was posed on the arm; (iii) the exposure tends to be higher for male model. (4) Discussion and Conclusions: This work highlights the importance of performing an exposure assessment when the antenna is placed on the human wearer considering the growth of the wearable technology and its wide variety of fields of application, e.g., medical and military.

Assessment of Human Exposure Levels Due to Mobile Phone Antennas in 5G Networks.

The recent deployment of 5G networks is bringing benefits to the population but it is also raising public concern about human RF-EMF exposure levels. This is particularly relevant considering the next 5G mobile devices, which are placed in close proximity to the subjects. Therefore, the aim of the following paper is focused on expanding the knowledge of the exposure levels in 5G exposure scenarios, specifically for mobile applications, using computational methods. The mobile antenna was designed considering the 5G technology innovations (i.e., mm-wave spectrum, beamforming capability, high gain and wide coverage), resulting in a phased-array antenna with eight elements at the working frequency of 27 GHz. To assess the exposure levels, different types of skin models with different grades of details and layers were considered. Furthermore, not only was the presence of a mobile phone user simulated, but also that of a person in their proximity, who could be hit by the main beam of the phased-array antenna. All the simulations were conducted in Sim4Life platform, where the exposure levels were assessed in terms of absorbed power density averaged over 4 cm2 and 1 cm2, following the ICNIRP guidelines. The results highlighted that the use of the homogeneous skin model led to the absorbed power density peaks being greatly underestimated, with respect to those obtained in multilayer skin models. Furthermore, interestingly, we found that the exposure levels obtained for the person passing nearby were slightly higher than those experienced by the mobile phone user himself. Finally, using the allowed input power for real mobile applications, all the values remained below the limits indicated by the ICNIRP guidelines.

Exposure Assessment to Radiofrequency Electromagnetic Fields in Occupational Military Scenarios: A Review.

(1) Background: Radiofrequency radiations are used in most devices in current use and, consequently, the assessment of the human exposure to the radiofrequency radiations has become an issue of strong interest. Even if in the military field there is wide use of radiofrequency devices, a clear picture on the exposure assessment to the electromagnetic field of the human beings in the military scenario is still missing. (2) Methods: a review of the scientific literature regarding the assessment of the exposure of the military personnel to the RF specific to the military environment, was performed. (3) Results: the review has been performed grouping the scientific literature by the typology of military devices to which the military personnel can be exposed to. The military devices have been classified in four main classes, according to their intended use: communication devices, localization/surveillance devices, jammers and EM directed-energy weapons. (4) Discussion and Conclusions: The review showed that in the exposure conditions here evaluated, there were only occasional situations of overexposure, whereas in the majority of the conditions the exposure was below the worker exposure limits. Nevertheless, the limited number of studies and the lack of exposure assessment studies for some devices prevent us to draw definitive conclusions and encourage further studies on military exposure assessment.

Prioritization of Resilience Initiatives for Climate-Related Disasters in the Metropolitan City of Venice.

Increases in the magnitude and frequency of climate and other disruptive factors are placing environmental, economic, and social stresses on coastal systems. This is further exacerbated by land use transformations, urbanization, over-tourism, sociopolitical tensions, technological innovations, among others. A scenario-informed multicriteria decision analysis (MCDA) was applied in the Metropolitan City of Venice integrating qualitative (i.e., local stakeholder preferences) and quantitative information (i.e., climate-change projections) with the aim of enhancing system resilience to multiple climate-related threats. As part of this analysis, different groups of local stakeholders (e.g., local authorities, civil protection agencies, SMEs, NGOs) were asked to identify critical functions that needs to be sustained. Various policy initiatives were considered to support these critical functions. The MCDA was used to rank the initiatives across several scenarios describing main climate threats (e.g., storm surges, floods, heatwaves, drought). We found that many climate change scenarios were considered to be disruptive to stakeholders and influence alternative ranking. The management alternatives acting on physical domain generally enhance resilience across just a few scenarios while cognitive and informative initiatives provided resilience enhancement across most scenarios considered. With uncertainty of multiple stressors along with projected climate variability, a portfolio of cognitive and physical initiatives is recommended to enhance resilience.

Assessment of EMF Human Exposure Levels Due to Wearable Antennas at 5G Frequency Band.

(1) Background: This work aims to assess human exposure to EMF due to two different wearable antennas tuned to two 5G bands. (2) Methods: The first one was centered in the lower 5G band, around f = 3.5 GHz, whereas the second one was tuned to the upper 5G band, at 26.5 GHz. Both antennas were positioned on the trunk of four simulated human models. The exposure assessment was performed by electromagnetic numerical simulations. Exposure levels were assessed by quantifying the specific absorption rate averaged on 10 g of tissue (SAR10g) and the absorbed power density (Sab), depending on the frequency of the wearable antenna. (3) Results: the higher exposure values that resulted were always mainly concentrated in a superficial area just below the antenna itself. In addition, these resulting distributions were narrowed around their peak values and tended to flatten toward lower values in farther anatomical body regions. All the exposure levels complied with ICNIRP guidelines when considering realistic input power. (4) Conclusions: This work highlights the importance of performing an exposure assessment when the antenna is placed on the human wearer, considering the growth of wearable technology and its wide variety of application, particularly regarding future 5G networks.

Use of Machine Learning for the Estimation of Down- and Up-Link Field Exposure in Multi-Source Indoor WiFi Scenarios.

A novel Machine Learning (ML) method based on Neural Networks (NN) is proposed to assess radio-frequency (RF) exposure generated by WiFi sources in indoor scenarios. The aim was to build an NN capable of addressing the complexity and variability of real-life exposure setups, including the effects of not only down-link transmission access points (APs) but also up-link transmission by different sources (e.g. laptop, printers, tablets, and smartphones). The NN was fed with easy to be found data, such as the position and type of WiFi sources (APs, clients, and other users) and the position and material characteristics (e.g. penetration loss) of walls. The NN model was assessed using an additional new layout, distinct from that one used to build and optimize the NN coefficients. The NN model achieved a remarkable field prediction accuracy across exposure conditions in both layouts, with a median prediction error of -0.4 to 0.6 dB and a root mean square error of 2.5-5.1 dB, compared with the target electric field estimated by a deterministic indoor network planner. The proposed approach performs well for the different layouts and is thus generally used to assess RF exposure in indoor scenarios. © 2021 The Authors. Bioelectromagnetics published by Wiley Periodicals LLC on behalf of Bioelectromagnetics Society.

Cluster Analysis of Residential Personal Exposure to ELF Magnetic Field in Children: Effect of Environmental Variables.

Personal exposure to Extremely Low Frequency Magnetic Fields (ELF MF) in children is a very timely topic. We applied cluster analysis to 24 h indoor personal exposures of 884 children in France to identify possible common patterns of exposures. We investigated how electric networks near child home and other variables potentially affecting residential exposure, such as indoor sources of ELF MF, the age and type of the residence and family size, characterized the magnetic field exposure patterns. We identified three indoor personal exposure patterns: children living near overhead lines of high (63-150 kV), extra-high (225 kV) and ultra-high voltage (400 kV) were characterized by the highest exposures; children living near underground networks of low (400 V) and mid voltage (20 kV) and substations (20 kV/400 V) were characterized by mid exposures; children living far from electric networks had the lowest level of exposure. The harmonic component was not relevant in discriminating the exposure patterns, unlike the 50 Hz or broadband (40-800 Hz) component. Children using electric heating appliances, or living in big buildings or in larger families had generally a higher level of personal indoor exposure. Instead, the age of the residence was not relevant in differentiating the exposure patterns.

Use of Machine Learning in the Analysis of Indoor ELF MF Exposure in Children.

Characterization of children exposure to extremely low frequency (ELF) magnetic fields is an important issue because of the possible correlation of leukemia onset with ELF exposure. Cluster analysis-a Machine Learning approach-was applied on personal exposure measurements from 977 children in France to characterize real-life ELF exposure scenarios. Electric networks near the child's home or school were considered as environmental factors characterizing the exposure scenarios. The following clusters were identified: children with the highest exposure living 120⁻200 m from 225 kV/400 kV overhead lines; children with mid-to-high exposure living 70⁻100 m from 63 kV/150 kV overhead lines; children with mid-to-low exposure living 40 m from 400 V/20 kV substations and underground networks; children with the lowest exposure and the lowest number of electric networks in the vicinity. 63⁻225 kV underground networks within 20 m and 400 V/20 kV overhead lines within 40 m played a marginal role in differentiating exposure clusters. Cluster analysis is a viable approach to discovering variables best characterizing the exposure scenarios and thus it might be potentially useful to better tailor epidemiological studies. The present study did not assess the impact of indoor sources of exposure, which should be addressed in a further study.

Radio Frequency Electromagnetic Fields Exposure Assessment in Indoor Environments: A Review.

Exposure to radiofrequency (RF) electromagnetic fields (EMFs) in indoor environments depends on both outdoor sources such as radio, television and mobile phone antennas and indoor sources, such as mobile phones and wireless communications applications. Establishing the levels of exposure could be challenging due to differences in the approaches used in different studies. The goal of this study is to present an overview of the last ten years research efforts about RF EMF exposure in indoor environments, considering different RF-EMF sources found to cause exposure in indoor environments, different indoor environments and different approaches used to assess the exposure. The highest maximum mean levels of the exposure considering the whole RF-EMF frequency band was found in offices (1.14 V/m) and in public transports (0.97 V/m), while the lowest levels of exposure were observed in homes and apartments, with mean values in the range 0.13⁻0.43 V/m. The contribution of different RF-EMF sources to the total level of exposure was found to show slightly different patterns among the indoor environments, but this finding has to be considered as a time-dependent picture of the continuous evolving exposure to RF-EMF.

3D space-dependent models for stochastic dosimetry applied to exposure to low frequency magnetic fields.

In this study, an innovative approach that combines Principal Component Analysis (PCA) and Gaussian process regression (Kriging method), never used before in the assessment of human exposure to electromagnetic fields (EMF), was applied to build space-dependent surrogate models of the 3D spatial distribution of the electric field induced in central nervous system (CNS) of children of different ages exposed to uniform magnetic field at 50 Hz of 200 µT of amplitude with uncertain orientation. The 3D surrogate models showed very low normalized percentage mean square error (MSE) values, always lower than 0.16%, confirming the feasibility and accuracy of the approach in estimating the 3D spatial distribution of E with a low number of components. Results showed that the electric field values induced in CNS tissues of children were within the ICNIRP basic restrictions for general public, with 99th percentiles of the E values obtained for each orientation showing median values in the range 1.9-2.1 mV/m. Similar 3D spatial distributions of the electric fields were found to be induced in CNS tissues of children of different ages. Bioelectromagnetics. 9999:1-10, 2018. © 2019 Bioelectromagnetics Society.

Characterization of Children's Exposure to Extremely Low Frequency Magnetic Fields by Stochastic Modeling.

In this study, children's exposure to extremely low frequency magnetic fields (ELF-MF, 40⁻800 Hz) is investigated. The interest in this thematic has grown due to a possible correlation between the increased risk of childhood leukemia and a daily average exposure above 0.4 µT, although the causal relationship is still uncertain. The aim of this paper was to present a new method of characterizing the children's exposure to ELF-MF starting from personal measurements using a stochastic approach based on segmentation (and to apply it to the personal measurements themselves) of two previous projects: the ARIMMORA project and the EXPERS project. The stochastic model consisted in (i) splitting the 24 h recordings into stationary events and (ii) characterizing each event with four parameters that are easily interpretable: the duration of the event, the mean value, the dispersion of the magnetic field over the event, and a final parameter characterizing the variation speed. Afterward, the data from the two databases were divided in subgroups based on a characteristic (i.e., children's age, number of inhabitants in the area, etc.). For every subgroup, the kernel density estimation (KDE) of each parameter was calculated and the p-value histogram of the parameters together was obtained, in order to compare the subgroups and to extract information about the children's exposure. In conclusion, this new stochastic approach allows for the identification of the parameters that most affect the level of children's exposure.