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Exposure to pollen has been associated with an increased risk of respiratory symptoms in both allergic and nonallergic individuals. However, the association of pollen exposure with respiratory symptoms during infancy, a particularly vulnerable period for lung development, remains unclear. The goal of this study was to examine whether pollen exposure is associated with respiratory symptoms (cough, wheezing, and dyspnoea) during the first year of life and to test if maternal atopy, infant’s sex, and air pollution modify this association.

INTRODUCTION: The real-life short-term implications of electromagnetic fields (RF-EMF) on cognitive performance and health-related quality of life have not been well studied. The SPUTNIC study (Study Panel on Upcoming Technologies to study Non-Ionizing radiation and Cognition) aimed to investigate possible correlations between mobile phone radiation and human health, including cognition, health-related quality of life and sleep. METHODS: Adult participants tracked various daily markers of RF-EMF exposures (cordless calls, mobile calls, and mobile screen time 4 h prior to each assessment) as well as three health outcomes over ten study days: 1) cognitive performance, 2) health-related quality of life (HRQoL), and 3) sleep duration and quality. Cognitive performance was measured through six "game-like" tests, assessing verbal and visuo-spatial performance repeatedly. HRQoL was assessed as fatigue, mood and stress on a Likert-scale (1-10). Sleep duration and efficiency was measured using activity trackers. We fitted mixed models with random intercepts per participant on cognitive, HRQoL and sleep scores. Possible time-varying confounders were assessed at daily intervals by questionnaire and used for model adjustment. RESULTS: A total of 121 participants ultimately took part in the SPUTNIC study, including 63 from Besancon and 58 from Basel. Self-reported wireless phone use and screen time were sporadically associated with visuo-spatial and verbal cognitive performance, compatible with chance findings. We found a small but robust significant increase in stress 0.03 (0.00-0.06; on a 1-10 Likert-scale) in relation to a 10-min increase in mobile phone screen time. Sleep duration and quality were not associated with either cordless or mobile phone calls, or with screen time. DISCUSSION: The study did not find associations between short-term RF-EMF markers and cognitive performance, HRQoL, or sleep duration and quality. The most consistent finding was increased stress in relation to more screen time, but no association with cordless or mobile phone call time.

ZusammenfassungDie Exposition der Bevölkerung durch hochfrequente elektromagnetische Felder (HF-EMF) wird durch die körpernahe Nutzung von drahtlosen Kommunikationsgeräten dominiert. Die Exposition durch körperferne Sendeanlagen liegt im Durchschnitt mehrere Größenordnungen unterhalb der internationalen Richtwerte. Mit der zunehmenden mobilen Datennutzung und der damit verbundenen Nutzung von höheren Frequenzen für 5G ist mit einer Verdichtung des Mobilfunknetzes zu rechnen. Damit steigt aber nicht notgedrungen die HF-EMF-Gesamtexposition der Bevölkerung, da Mobiltelefone bei besserer Signalqualität weniger stark emittieren. 5G ist eine technologische Weiterentwicklung der bisherigen Mobilfunktechnologie mit gleichen biophysikalischen Eigenschaften. Bisher konnten keine gesundheitlichen Auswirkungen unterhalb der Richtwerte konsistent nachgewiesen werden. Beobachtete biologische Effekte wie beispielsweise auf die elektrische Aktivität des Gehirns oder auf das oxidative Gleichgewicht bei hoher lokaler Exposition im Bereich der Expositionsrichtwerte stellen nach heutigem Kenntnisstand kein Gesundheitsrisiko dar.

Personal measurements of radiofrequency electromagnetic fields (RF-EMF) have been used in several studies to characterise personal exposure in daily life, but such data are limitedly available for adolescents, and not yet for the United Kingdom (UK). In this study, we aimed to characterise personal exposure to RF-EMF in adolescents and to study the association between exposure and rules applied at school and at home to restrict wireless communication use, likely implemented to reduce other effects of mobile technology (e.g. distraction). We measured exposure to RF-EMF for 16 common frequency bands (87.5 MHz–3.5 GHz), using portable measurement devices (ExpoM-RF), in a subsample of adolescents participating in the cohort Study of Cognition, Adolescents and Mobile Phones (SCAMP) from Greater London (UK) (n = 188). School and home rules were assessed by questionnaire and concerned the school's availability of WiFi and mobile phone policy, and parental restrictions on permitted mobile phone use. Adolescents recorded their activities in real time using a diary app on a study smartphone, while characterizing their personal RF-EMF exposure in daily life, during different activities and times of the day. Data analysis was done for 148 adolescents from 29 schools who recorded RF-EMF data for a median duration of 47 h. The majority (74%) of adolescents spent part of their time at school during the measurement period. Median total RF-EMF exposure was 40 μW/m2 at home, 94 μW/m2 at school, and 100 μW/m2 overall. In general, restrictions at school or at home made little difference for adolescents’ measured exposure to RF-EMF, except for uplink exposure from mobile phones while at school, which was found to be significantly lower for adolescents attending schools not permitting phone use at all, compared to adolescents attending schools allowing mobile phone use during breaks. This difference was not statistically significant for total personal exposure. Total exposure to RF-EMF in adolescents living in Greater London tended to be higher compared to exposure levels reported in other European countries. This study suggests that school policies and parental restrictions are not associated with a lower RF-EMF exposure in adolescents.

Introduction Land use regression models environmental predictors to estimate ground-floor air pollution concentration surfaces of a study area. While many cities are expanding vertically, such models typically ignore the vertical dimension. Methods We took integrated measurements of NO2 at up to three different floors on the facades of 25 buildings in the mid-sized European city of Basel, Switzerland. We quantified the decrease in NO2 concentration with increasing height at each facade over two 14-day periods in different seasons. Using predictors of traffic load, population density and street configuration, we built conventional land use regression (LUR) models which predicted ground floor concentrations. We further evaluated which predictors best explained the vertical decay rate. Ultimately, we combined ground floor and decay models to explain the measured concentrations at all heights. Results We found a clear decrease in mean nitrogen dioxide concentrations between measurements at ground level and those at higher floors for both seasons. The median concentration decrease was 8.1% at 10 m above street level in winter and 10.4% in summer. The decrease with height was sharper at buildings where high concentrations were measured on the ground and in canyon-like street configurations. While the conventional ground floor model was able to explain ground floor concentrations with a model R2 of 0.84 (RMSE 4.1 μg/m3), it predicted measured concentrations at all heights with an R2 of 0.79 (RMSE 4.5 μg/m3), systematically overpredicting concentrations at higher floors. The LUR model considering vertical decay was able to predict ground floor and higher floor concentrations with a model R2 of 0.84 (RMSE 3.8 μg/m3) and without systematic bias. Discussion Height above the ground is a relevant determinant of outdoor residential exposure, even in medium-sized European cities without much high-rise. It is likely that conventional LUR models overestimate exposure for residences at higher floors near major roads. This overestimation can be minimized by considering decay with height.

Objective Children and adolescents living in agricultural areas are likely to be exposed to mixtures of pesticides during their daily activities, which may impair their neurodevelopment. We investigated various such activities in relation to headache severity and neurodevelopment of school-children living in rural agricultural areas in the Western Cape of South Africa. Method We used baseline date from 1001 school-children of the Child Health Agricultural Pesticide Cohort Study in South Africa (CapSA) aged 9–16 from seven schools and three agriculture areas in the Western Cape. Questionnaires were administrated to assess activities related to pesticide exposure and health symptoms addressing four types of activities: 1) child farm activities related to pesticide handling, 2) eating crops directly from the field, 3) contact with surface water around the field, and 4) seen and smelt pesticide spraying activities. Neurocognitive performance across three domains of attention, memory and processing speed were assessed by means of an iPad-based cognitive assessment tool, Cambridge Automated NeuroPsychological Battery (CANTAB). Headache severity was enquired using a standard Headache Impact Test (HIT-6) tool. Cross-sectional regression analysis was performed. Results About 50% of the cohort report to have ever been engaged in activities related to pesticide exposure including farm activities, eating crops directly from the field and leisure activities. Headache severity score was consistently increased in relation to pesticide-related farm activities (score increase of 1.99; 95% CI: 0.86, 3.12), eating crops (1.52; 0.41, 2.67) and leisure activities of playing, swimming or bathing in nearby water (1.25; 0.18, 2.33). For neurocognitive outcomes, an overall negative trend with pesticide exposure-related activities was observed. Among others, involvement in pesticide-related farm activities was associated with a lower multi-tasking accuracy score (−2.74; −5.19, −0.29), while lower strategy in spatial working memory (−0.29; −0.56; −0.03) and lower paired associated learning (−0.88; −1.60, −0.17) was observed for those who pick crops off the field compared to those who do not pick crops off the field. Eating fruits directly from the vineyard or orchard was associated with a lower motor screening speed (−0.06; −0.11, −0.01) and lower rapid visual processing accuracy score (−0.02; −0.03, 0.00). Conclusions Children who indicate activities related to pesticide exposure may be at higher risk for developing headaches and lower cognitive performance in the domains of attention, memory and processing speed. However, self-reported data and cross-sectional design are a limitation. Future research in CapSA will consider pesticide exposure estimations via urinary biomarkers and longitudinal assessment of cognitive functions.

Longitudinal shifts in pollen onset, duration, and intensity are public health concerns for the growing number of individuals with pollen sensitization. National analyses of long-term pollen changes are influenced by how a plant's main pollen season (MPS) is defined. Prior Swiss studies have inconsistently applied MPS definitions, leading to heterogeneous conclusions regarding the magnitude, directionality, and significance of multi-decade pollen trends. We examined national pollen data in Switzerland between 1990 and 2020, applying six MPS definitions (2 percentage-based and 4 threshold-based) to twelve relevant allergenic plants. We analyzed changes in pollen season using both linear regression and locally estimated scatterplot smoothing (LOESS). For 4 of the 12 plant species, there is unanimity between definitions regarding earlier onset of pollen season (p < 0.05), with magnitude of 31-year change dependent on specific MPS definition (hazel: 9–18 days; oak: 5–13 days; grasses: 8–25 days; and nettle/hemp: 6–25 days). There is also consensus (p < 0.05) for modified MPS duration among hazel (21–104% longer), nettle/hemp (8–52% longer), and ash (18–38% shorter). Between-definition agreement is highest for MPS intensity analysis, with consensus for significant increases in seasonal pollen quantity (p < 0.05) among hazel, birch, oak, beech, and nettle/hemp. The largest relative intensification is noted for hazel (110–146%) and beech (162–237%). LOESS analysis indicates that these multi-decade pollen changes are typically nonlinear. The robustness of MPS definitions is highly dependent on annual pollen accumulation, with definition choice particularly influential for long-term analysis of low-pollen plants such as ragweed. We identify systematic differences between MPS definitions and suggest future aerobiologic studies apply multiple definitions to minimize bias. In summary, national pollen onset, duration, and intensity have shifted for some plants in Switzerland, with MPS definition choice affecting magnitude and significance of these variations. Future public health research can determine whether these temporal and quantitative pollen changes correlate with longitudinal differences in population pollen sensitization., Graphical abstract Unlabelled Image, Highlights • We analyzed 3 decades of Swiss data for 12 plants using 6 pollen season definitions. • Over 1990–2020, pollen seasons began earlier for hazel, oak, grasses and nettle/hemp. • Pollen accumulation intensified for hazel, birch, oak, beech and nettle/hemp. • Pollen season definition impacts magnitude, direction, and significance of trends. • Climate change is impacting public health through changes in pollen release.

Portable devices measuring radiofrequency electromagnetic fields (RF-EMF) are affected by crosstalk: signals originating in one frequency band that are unintentionally registered in another. If this is not corrected, total exposure to RF-EMF is biased, particularly affecting closely spaced frequency bands such as GSM 1800 downlink (1,805-1,880 MHz), DECT (1,880-1,900 MHz), and UMTS uplink (1,920-1,980 MHz). This study presents an approach to detect and correct crosstalk in RF-EMF measurements, taking into account the real-life setting in which crosstalk is intermittently present, depending on the exact frequency of the signal. Personal measurements from 115 volunteers from Zurich canton, Switzerland were analyzed. Crosstalk-affected observations were identified by correlation analysis, and replaced by the median value of the unaffected observations, measured during the same activity. DECT is frequently a victim of crosstalk, and an average of 43% of observations was corrected, resulting in an average exposure reduction of 38%. GSM 1800 downlink and UMTS uplink were less often corrected (6.9% and 8.9%), resulting in minor reductions in exposure (7.1% and 0.92%). The contribution of DECT to total RF-EMF exposure is typically already low (3.2%), but is further reduced after correction (3.0%). Crosstalk corrections reduced the total exposure by 1.0% on average. Some individuals had a larger reduction of up to 16%. The code developed to make the corrections is provided for free as an R function which is easily applied to any time series of EMF measurements. Bioelectromagnetics. 39:529-538, 2018. © 2018 Wiley Periodicals, Inc.

Mobile phone use, predominantly smartphones, is almost ubiquitous amongst both adults and children. However adults and children have different usage patterns. A major challenge with research on mobile phone use is the reliability of self-reported phone activity for accurate exposure assessment. We investigated the agreement between self-reported mobile phone use data and objective mobile operator traffic data in a subset of adolescents aged 11–12 years participating in the Study of Cognition, Adolescents and Mobile Phones (SCAMP) cohort. We examined self-reported mobile phone use, including call frequency, cumulative call time duration and text messages sent among adolescents from SCAMP and matched these data with records provided by mobile network operators (n = 350). The extent of agreement between self-reported mobile phone use and mobile operator traffic data use was evaluated using Cohen's weighted Kappa (ĸ) statistics. Sensitivity and specificity of self-reported low (< 1 call/day, ≤ 5 min of call/day or ≤ 5 text messages sent/day) and high (≥ 11 calls/day, > 30 min of call/day or ≥ 11 text messages sent /day) use were estimated. Agreement between self-reported mobile phone use and mobile operator traffic data was highest for the duration spent talking on mobile phones per day on weekdays (38.9%) and weekends (29.4%) compared to frequency of calls and number of text messages sent. Adolescents overestimated their mobile phone use during weekends compared to weekdays. Analysis of agreement showed little difference overall between the sexes and socio-economic groups. Weighted kappa between self-reported and mobile operator traffic data for call frequency during weekdays was κ = 0.12, 95% CI 0.06–0.18. Of the three modes of mobile phone use measured in the questionnaire, call frequency was the most sensitive for low mobile phone users on weekdays and weekends (77.1, 95% CI: 69.3—83.7 and 72.0, 95% CI: 65.0–78.4, respectively). Specificity was moderate to high for high users with the highest for call frequency during weekdays (98.4, 95% CI: 96.4–99.5). Despite differential agreement between adolescents’ self-reported mobile phone use and mobile operator traffic data, our findings demonstrate that self-reported usage adequately distinguishes between high and low use. The greater use of mobile smartphones over Wi-Fi networks by adolescents, as opposed to mobile phone networks, means operator data are not the gold standard for exposure assessment in this age group. This has important implications for epidemiologic research on the health effects of mobile phone use in adolescents., Highlights • We assessed the validity of adolescents’ self-reported mobile phone use. • The study accounted for weekday and weekend use of mobile phones separately. • Findings show that self-reported usage distinguishes between high and low use. • We recommend a combination of self-reported use over Wi-Fi & operator traffic data. • Combined data will improve accurate exposure estimation in epidemiological studies.

Oxidative potential (OP) has been suggested as a health-relevant measure of air pollution. Little information is available about OP spatial variation and the possibility to model its spatial variability. Our aim was to measure the spatial variation of OP within and between 10 European study areas. The second aim was to develop land use regression (LUR) models to explain the measured spatial variation. OP was determined with the dithiothreitol (DTT) assay in ten European study areas. DTT of PM2.5 was measured at 16–40 sites per study area, divided over street, urban and regional background sites. Three two-week samples were taken per site in a one-year period in three different seasons. We developed study-area specific LUR models and a LUR model for all study areas combined to explain the spatial variation of OP. Significant contrasts between study areas in OP were found. OP DTT levels were highest in southern Europe. DTT levels at street sites were on average 1.10 times higher than at urban background locations. In 5 of the 10 study areas LUR models could be developed with a median R2 of 33%. A combined study area model explained 30% of the measured spatial variability. Overall, LUR models did not explain spatial variation well, possibly due to low levels of OP DTT and a lack of specific predictor variables. © 2016 Elsevier Ltd

Several studies have indicated weakly increased risk for kidney cancer among occupational groups exposed to gasoline vapors, engine exhaust, polycyclic aromatic hydrocarbons and other air pollutant ...

Communication technologies are rapidly changing and this may affect public exposure to radiofrequency electromagnetic fields (RF-EMF). This systematic review of literature aims to update a previous review on public everyday RF-EMF exposure in Europe, which covered publications until 2015. From 144 eligible records identified by means of a systematic search in PubMed, Embase and Web of Knowledge databases, published between May 2015 and 1 July 2018, 26 records met the inclusion criteria. We extracted quantitative data on public exposure in different indoors, outdoors and transport environments. The data was descriptively analyzed with respect to the exposure patterns between different types of environments. Mean RF-EMF exposure in homes, schools and offices were between 0.04 and 0.76 V/m. Mean outdoor exposure values ranged from 0.07 to 1.27 V/m with downlink signals from mobile phone base stations being the most relevant contributor. RF-EMF levels tended to increase with increasing urbanity. Levels in public transport (bus, train and tram) and cars were between 0.14 and 0.69 V/m. The highest levels, up to 1.97 V/m, were measured in public transport stations with downlink as the most relevant contributor. In line with previous studies, RF-EMF exposure levels were highest in the transportation systems followed by outdoor and private indoor environments. This review does not indicate a noticeable increase in everyday RF-EMF exposure since 2012 despite increasing use of wireless communication devices.

A multi-band body-worn distributed exposure meter (BWDM) is designed and calibrated for diffuse fields in a reverberation chamber (RC) for personal exposure assessment in indoor environments. The BWDM uses 22 nodes distributed over the torso and measures the incident power density ( $S_{\mathrm{ inc}}$ ) on body for 11 telecommunication bands in the frequency range of 790–5513 MHz. In order to calibrate the measurement device in diffuse fields, a protocol is proposed for on-body calibration of the BWDM. This protocol is applicable to wearable personal exposure meters in general. The BWDM and the proposed calibration protocol are validated in five indoor locations and five frequency bands (the downlink bands at 800, 900, 1800, and 2100 MHz as well as Wi-Fi 2 GHz) using a tri-axial broadband antenna and a spectrum analyzer (SA). The calibration shows that the BWDM has a relatively low measurement uncertainty with a 68% confidence interval on its antenna apertures, in the range 3.4–5.5 dB. A maximum difference of 0.9 dB is obtained for the total exposure in the test areas between the measurements of the BWDM and SA, which is an excellent agreement.

This paper studies the effect of antenna polarization on measurement uncertainty of a multi-band body-worn distributed exposure meter (BWDM). The BWDM is a device for assessing electromagnetic fields in real environments accurately. The BWDM consists of 8 nodes and is calibrated on the body for simultaneous measurement of the incident power density in four frequency bands. Each node contains an antenna that can have two potential antenna polarizations.The BWDM is calibrated on four human subjects in an anechoic chamber to determine its measurement uncertainty in terms of 68% confidence interval (CI68) of the on-body antenna aperture. The results show that using a fixed polarization of the antennas on body can lead to a different CI68 up to maximum 4.9 dB when worn by another person which is still 9.6 dB lower than the measurement uncertainty of commercial exposure meters.

Background: Exposure to ambient air pollution may be associated with impaired mental health, including depression. However, evidence originates mainly from animal studies and epidemiological studies in specific subgroups. We investigated the association between air pollution and depressed mood in four European general population cohorts.Methods: Data were obtained from LifeLines (the Netherlands), KORA (Germany), HUNT (Norway), and FINRISK (Finland). Residential exposure to particles (PM2.5, PM(2.5)absorbance, PM10) and nitrogen dioxide (NO2) was estimated using land use regression (LUR) models developed for the European Study of Cohorts for Air Pollution Effects (ESCAPE) and using European wide LUR models. Depressed mood was assessed with interviews and questionnaires. Logistic regression analyses were used to investigate the cohort specific associations between air pollution and depressed mood.Results: A total of 70,928 participants were included in our analyses. Depressed mood ranged from 1.6% (KORA) to 11.3% (FINRISK). Cohort specific associations of the air pollutants and depressed mood showed heterogeneous results. For example, positive associations were found for NO2 in LifeLines (odds ratio [OR] = 1.34; 95% CI: 1.17, 1.53 per 10 mu g/m(3) increase in NO2), whereas negative associations were found in HUNT (OR= 0.79; 95% CI: 0.66, 0.94 per 10 mu g/m(3) increase in NO2).Conclusions: Our analyses of four European general population cohorts found no consistent evidence for an association between ambient air pollution and depressed mood. (C) 2015 Elsevier GmbH. All rights reserved.

Background Electronic media use is increasing in low- and middle-income countries, thus we aim to investigate the prevalence of different aspects of e-media use and its association to symptoms and neurocognitive outcomes in rural South Africa. Methods In the cohort study, “Child health Agricultural Pesticide study in South Africa (CapSA)”, of 1001 children and adolescents, aged 9–16 years, we enquired at baseline about the following aspects of e-media use: (1) call duration (2) total screen time (3) night-time awakenings from mobile phone use, and (4) Mobile Phone Problematic Use. Four health outcomes were included: sleep disturbance, health related quality of life (HRQoL), headaches and cognitive performance, assessed through six tests on domains of attention, memory and processing speed, using the iPad-based software, CAmbridge Neuropsychological Test Automated Battery (CANTAB). Linear regression analysis adjusted for relevant confounders was conducted with categorized exposure variables low, medium and high use. Results One third of the cohort (31.8%) are mobile phone users reporting average duration of calls per day up to 75 min (mean = 2.5 mins; SD = 8.9 mins). Amongst 46% of the cohort who report e-media device use, total screen time ranged from 1 min to 441 min (mean = 28.3; SD = 53.0). Findings Amongst those reporting regular night-time awakenings (≥1 times per week) from mobile phones, HRQol declined by 2.9 (95% CI: −6.1, 0.3), the sleep disturbance score increased by 2.0 (1.1, 2.9) units and headache impact score significantly increased by 5.4 (2.6; 8.2) units compared to non-exposed. Cognitive performance scores tended to be slightly improved mostly in moderate e-media users. The reaction response speed was consistently improved amongst all four exposure groups compared to non-users. Conclusion These results are among the first from Africa on benefits and risks associated with e-media use. Our findings imply that with regard to the education of adolescents, a vigilant balance is needed to profit from the beneficial effects of moderate e-media use on cognition, while preventing the negative side effects for HRQoL, sleep disturbance and headache severity.

Background/aim Exposure to radiofrequency electromagnetic fields (RF-EMF) has rapidly increased and little is known about exposure levels in children. This study aims to describe personal RF-EMF environmental exposure levels from handheld devices and fixed site transmitters in European children and its day-to-day and year-to-year repeatability. Methods Environmental RF-EMF exposure (µW/m 2 ) was measured in 529 children (ages 8–18) in Denmark, the Netherlands, Slovenia, Switzerland, and Spain using personal portable exposure metres over 3 days in 2014–2016, and repeated in 28 children one year later. Metres captured exposure every 4 s. Activity diaries collected children’s location and use of mobile devices. Six general frequency bands were defined: total, digital enhanced cordless telecommunications (DECT), television and radio antennas (broadcast), mobile phones (uplink), mobile phone base stations (downlink), and WiFi. We used mixed effects models with region random effects to estimate associations between mobile device use and exposure. Day-to-day and year-to-year repeatability was calculated through Spearman correlations. Results Median total exposure was 75.5 µW/m 2 . Downlink was the largest contributor to total exposure (27.2 µW/m 2 ) followed by broadcast (9.9 µW/m 2 ). Exposure from uplink was lower (4.7 µW/m 2 ). WiFi and DECT contributed very little to exposure levels. Exposure was higher during day (94.2 µW/m 2 ) than night (23.0 µW/m 2 ), and slightly higher during weekends than weekdays, although varying across regions. Exposure was generally highest while children were travelling (171.3 µW/m 2 ) and outside (157.0 µW/m 2 ). Children living in urban environments had higher exposure. Older children, girls, and users of mobile phones had higher uplink exposure but not total exposure. Repeatability was high for total, downlink, and broadcast in the year-to-year repeatability (rho between 0.54 and 0.66). Conclusion Largest contributors to total RF-EMF exposure were downlink and broadcast, which was consistent one year later. Location of home (region and urbanicity) was associated with higher exposure. More frequent mobile phone use was associated with higher uplink exposure. It is important to continue evaluating RF-EMF exposure in children as mobile devices, use habits, and technologies continue to evolve.

We aimed to assess the personal radiofrequency electromagnetic field (RF-EMF) exposure levels of children and adults through their activities, with consideration to the body shadowing effect. We recruited 50 child-adult pairs, living in Seoul, Cheonan, and Ulsan, South Korea. RF-EMF measurements were performed between September and December 2016, using a portable exposure meter tailored to capture 14 Korean radiofrequency (RF) bands ranging from 87.5 to 5875MHz. The participants carried the device for 48h and kept a time-activity diary using a smartphone application in flight mode. To enhance accuracy of the exposure assessment, the body shadowing effect was compensated during the statistical analysis with the measured RF-EMF exposure. The compensation was conducted using the hybrid model that represents the decrease of the exposure level due to the body shadowing effect. A generalized linear mixed model was used to compare the RF-EMF exposure levels by subjects and activities. The arithmetic (geometric) means of the total power density were 174.9 (36.6) μW/m2 for all participants, 226.9 (44.6) for fathers, 245.4 (44.8) for mothers, and 116.2 (30.1) for children. By compensating for the body shadowing effect, the total RF-EMF exposure increased marginally, approximately 1.4 times. Each frequency band contribution to total RF-EMF exposure consisted of 76.7%, 2.4%, 9.9%, 5.0%, 3.3%, and 2.6% for downlink, uplink, WiFi, FM Radio, TV, and WiBro bands, respectively. Among the three regions, total RF-EMF exposure was highest in Seoul, and among the activities, it was highest in the metro, followed by foot/bicycle, bus/car, and outside. The contribution of base-station exposure to total RF-EMF exposure was the highest both in parents and children. Total and base-station RF-EMF exposure levels in Korea were higher than those reported in European countries.

A multi-band Body-Worn Distributed exposure Meter (BWDM) calibrated for simultaneous measurement of the incident power density in 11 telecommunication frequency bands, is proposed. The BDWM consists of 22 textile antennas integrated in a garment and is calibrated on six human subjects in an anechoic chamber to assess its measurement uncertainty in terms of 68% confidence interval of the on-body antenna aperture. It is shown that by using multiple antennas in each frequency band, the uncertainty of the BWDM is 22 dB improved with respect to single nodes on the front and back of the torso and variations are decreased to maximum 8.8 dB. Moreover, deploying single antennas for different body morphologies results in a variation up to 9.3 dB, which is reduced to 3.6 dB using multiple antennas for six subjects with various body mass index values. The designed BWDM, has an improved uncertainty of up to 9.6 dB in comparison to commercially available personal exposure meters calibrated on body. As an application, an average incident power density in the range of 26.7-90.8 muW.m - 2 is measured in Ghent, Belgium. The measurements show that commercial personal exposure meters underestimate the actual exposure by a factor of up to 20.6.

Background: The potential impact of microwave radiofrequency electromagnetic fields (RF-EMF) emitted by wireless communication devices on neurocognitive functions of adolescents is controversial. In a previous analysis, we found changes in figural memory scores associated with a higher cumulative RF-EMF brain dose in adolescents. Objective: We aimed to follow-up our previous results using a new study population, dose estimation, and approach to controlling for confounding from media usage itself. Methods: RF-EMF brain dose for each participant was modeled. Multivariable linear regression models were fitted on verbal and figural memory score changes over 1 y and on estimated cumulative brain dose and RF-EMF related and unrelated media usage (n=669–676). Because of the hemispheric lateralization of memory, we conducted a laterality analysis for phone call ear preference. To control for the confounding of media use behaviors, a stratified analysis for different media usage groups was also conducted. Results: We found decreased figural memory scores in association with an interquartile range (IQR) increase in estimated cumulative RF-EMF brain dose scores: −0.22 (95% CI: −0.47, 0.03; IQR: 953 mJ/kg per day) in the whole sample, −0.39 (95% CI: −0.67, −0.10; IQR: 953 mJ/kg per day) in right-side users (n=532), and −0.26 (95% CI: −0.42, −0.10; IQR: 341 mJ/kg per day) when recorded network operator data were used for RF-EMF dose estimation (n=274). Media usage unrelated to RF-EMF did not show significant associations or consistent patterns, with the exception of consistent (nonsignificant) positive associations between data traffic duration and verbal memory. Conclusions: Our findings for a cohort of Swiss adolescents require confirmation in other populations but suggest a potential adverse effect of RF-EMF brain dose on cognitive functions that involve brain regions mostly exposed during mobile phone use. https://doi.org/10.1289/EHP2427

Indoor air quality is a growing concern as we spend the majority of time indoors and as new buildings are increasingly airtight for energy saving purposes. For a better understanding of residential indoor air pollution in Switzerland we conducted repeated 1 2 week long indoor and outdoor measurements of particle number concentrations (PNC) particulate matter (PM) light absorbance of PM2.5 (PMabsorbance) and nitrogen dioxide (NO2). Residents of all homes were enrolled in the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA). Indoor levels were comparable in urban areas and generally low in rural homes. Average indoor levels were 7800 particles/cm(3) (interquartile range=7200); 8.7?µg/m(3) (6.5) PM2.5 and 10.2?µg/m(3) (11.2) NO2. All pollutants showed large variability of indoor/outdoor ratios between sites. We observed similar diurnal patterns for indoor and outdoor PNC. Nevertheless the correlation of average indoor and outdoor PNC between sites as well as longitudinal indoor/outdoor correlations within sites were low. Our results show that a careful evaluation of home characteristics is needed when estimating indoor exposure to pollutants with outdoor origin.Journal of Exposure Science and Environmental Epidemiology advance online publication 11 February 2015; doi:10.1038/jes.2015.3.

Aims: Elevation of a child's blood pressure may cause possible health risks in later life. There is evidence for adverse effects of exposure to air pollution and noise on blood pressure in adults. Little is known about these associations in children. We investigated the associations of air pollution and noise exposure with blood pressure in 12-year-olds. Methods: Blood pressure was measured at age 12 years in 1432 participants of the PIAMA birth cohort study. Annual average exposure to traffic-related air pollution [NO2, mass concentrations of particulate matter with diameters of less than 2.5 μm (PM2.5) and less than 10 μm (PM10), and PM2.5 absorbance] at the participants' home and school addresses at the time of blood pressure measurements was estimated by land-use regression models. Air pollution exposure on the days preceding blood pressure measurements was estimated from routine air monitoring data. Long-term noise exposure was assessed by linking addresses to modelled equivalent road traffic noise levels. Associations of exposures with blood pressure were analysed by linear regression. Effects are presented for an interquartile range increase in exposure. Results: Long-term exposure to NO2 and PM2.5 absorbance were associated with increased diastolic blood pressure, in children who lived at the same address since birth [adjusted mean difference (95% confidence interval) [mmHg] 0.83 (0.06 to 1.61) and 0.75 (-0.08 to 1.58), respectively], but not with systolic blood pressure. We found no association of blood pressure with short-term air pollution or noise exposure. Conclusions: Long-term exposure to traffic-related air pollution may increase diastolic blood pressure in children.

BACKGROUND: Research examining associations between air pollution exposure and respiratory symptoms in adults has generally been inconclusive. This may be related in part to sample size issues, which also preclude analysis in potentially vulnerable subgroups. OBJECTIVES: We estimated associations between air pollution exposures and the prevalence of wheeze and shortness of breath using harmonized baseline data from two very large European cohorts, Lifelines (2006-2013) and UK Biobank (2006-2010). Our aim was also to determine whether the relationship between air pollution and respiratory symptom prevalence differed between individuals with different characteristics. METHODS: Cross-sectional analyses explored associations between prevalence of self-reported wheeze and shortness of breath and annual mean particulate matter with aerodynamic diameter

Oxidative potential (OP) of particulate matter (PM) is proposed as a biologically-relevant exposure metric for studies of air pollution and health. We aimed to evaluate the spatial variability of the OP of measured PM

Background/Aim: The potential impact of microwave radiofrequency electromagnetic fields (RF-EMF) emitted by wireless communication devices on neurocognitive functions of adolescents is still discus...

Objectives The World Health Organization has developed ambient air quality guidelines at levels considered to be safe or of acceptable risk for human health. These guidelines are meant to support governments in defining national standards. It is unclear how they are followed. Methods We compiled an inventory of ambient air quality standards for 194 countries worldwide for six air pollutants: PM2.5, PM10, ozone, nitrogen dioxide, sulphur dioxide and carbon monoxide. We conducted literature and internet searches and asked country representatives about national ambient air quality standards. Results We found information on 170 countries including 57 countries that did not set any air quality standards. Levels varied greatly by country and by pollutant. Ambient air quality standards for PM2.5, PM10 and SO2 poorly complied with WHO guideline values. The agreement was higher for CO, SO2 (10-min averaging time) and NO2. Conclusions Regulatory differences mirror the differences in air quality and the related burden of disease around the globe. Governments worldwide should adopt science based air quality standards and clean air management plans to continuously improve air quality locally, nationally, and globally. Electronic supplementary material The online version of this article (doi:10.1007/s00038-017-0952-y) contains supplementary material, which is available to authorized users.

BACKGROUND: Few studies on long-term exposure to air pollution and mortality have been reported from Europe. Within the multicentre European Study of Cohorts for Air Pollution Effects (ESCAPE), we aimed to investigate the association between natural-cause mortality and long-term exposure to several air pollutants. METHODS: We used data from 22 European cohort studies, which created a total study population of 367,251 participants. All cohorts were general population samples, although some were restricted to one sex only. With a strictly standardised protocol, we assessed residential exposure to air pollutants as annual average concentrations of particulate matter (PM) with diameters of less than 2.5 μm (PM2.5), less than 10 μm (PM10), and between 10 μm and 2.5 μm (PMcoarse), PM2.5 absorbance, and annual average concentrations of nitrogen oxides (NO2 and NOx), with land use regression models. We also investigated two traffic intensity variables-traffic intensity on the nearest road (vehicles per day) and total traffic load on all major roads within a 100 m buffer. We did cohort-specific statistical analyses using confounder models with increasing adjustment for confounder variables, and Cox proportional hazards models with a common protocol. We obtained pooled effect estimates through a random-effects meta-analysis. FINDINGS: The total study population consisted of 367,251 participants who contributed 5,118,039 person-years at risk (average follow-up 13.9 years), of whom 29,076 died from a natural cause during follow-up. A significantly increased hazard ratio (HR) for PM2.5 of 1.07 (95% CI 1.02-1.13) per 5 μg/m(3) was recorded. No heterogeneity was noted between individual cohort effect estimates (I(2) p value=0.95). HRs for PM2.5 remained significantly raised even when we included only participants exposed to pollutant concentrations lower than the European annual mean limit value of 25 μg/m(3) (HR 1.06, 95% CI 1.00-1.12) or below 20 μg/m(3) (1.07, 1.01-1.13). INTERPRETATION: Long-term exposure to fine particulate air pollution was associated with natural-cause mortality, even within concentration ranges well below the present European annual mean limit value. FUNDING: European Community's Seventh Framework Program (FP7/2007-2011).

The impact of the introduction and advancement in communication technology in recent years on exposure level of the population is largely unknown. The main aim of this study is to systematically review literature on the distribution of radiofrequency electromagnetic field (RF-EMF) exposure in the everyday environment in Europe and summarize key characteristics of various types of RF-EMF studies conducted in the European countries. We systematically searched the ISI Web of Science for relevant literature published between 1 January 2000 and 30 April 2015, which assessed RF-EMF exposure levels by any of the methods: spot measurements, personal measurement with trained researchers and personal measurement with volunteers. Twenty-one published studies met our eligibility criteria of which 10 were spot measurements studies, 5 were personal measurement studies with trained researchers (microenvironmental), 5 were personal measurement studies with volunteers and 1 was a mixed methods study combining data collected by volunteers and trained researchers. RF-EMF data included in the studies were collected between 2005 and 2013. The mean total RF-EMF exposure for spot measurements in European "Homes" and "Outdoor" microenvironments was 0.29 and 0.54 V/m, respectively. In the personal measurements studies with trained researchers, the mean total RF-EMF exposure was 0.24 V/m in "Home" and 0.76 V/m in "Outdoor". In the personal measurement studies with volunteers, the population weighted mean total RF-EMF exposure was 0.16 V/m in "Homes" and 0.20 V/m in "Outdoor". Among all European microenvironments in "Transportation", the highest mean total RF-EMF 1.96 V/m was found in trains of Belgium during 2007 where more than 95% of exposure was contributed by uplink. Typical RF-EMF exposure levels are substantially below regulatory limits. We found considerable differences between studies according to the type of measurements procedures, which precludes cross-country comparison or evaluating temporal trends. A comparable RF-EMF monitoring concept is needed to accurately identify typical RF-EMF exposure levels in the everyday environment.

In many built-up urban areas, tall buildings along narrow streets obstruct the free flow of air, resulting in higher pollution levels. Input data to account for street configuration in models are difficult to obtain for large numbers of streets. We describe an approach to calculate indicators of this “urban canyon effect” using 3-dimensional building data and evaluated whether these indicators improved spatially resolved land use regression (LUR) models. Concentrations of NO 2 and NO x were available from 132 sites in the Netherlands. We calculated four indicators for canyon effects at each site: (1) the maximum aspect ratio (building height/width of the street) between buildings on opposite sides of the street, (2) the mean building angle, which is the angle between the horizontal street level and the line of sight to the top of surrounding buildings, (3) median building angle and (4) “SkyView Factor” (SVF), a measure of the total fraction of visible sky. Basic LUR models were computed for both pollutants using common predictors such as household density, land-use and nearby traffic intensity. We added each of the four canyon indicators to the basic LUR models and evaluated whether they improved the model. The calculated aspect ratio agreed well ( R 2 = 0.49) with aspect ratios calculated from field observations. Explained variance ( R 2 ) of the basic LUR models without canyon indicators was 80% for NO 2 and 76% for NO x , and increased to 82% and 78% respectively if SVF was included. Despite this small increase in R 2 , contrasts in SVF (10th–90th percentile) resulted in substantial concentration differences of 5.56 μg m −3 in NO 2 and 10.9 μg m −3 in NO x . We demonstrated a GIS based approach to quantify the obstruction of free air flow by buildings, applicable for large numbers of streets. Canyon indicators could be valuable to consider in air pollution models, especially in areas with low- and high-rise canyons.

Background: There is evidence for adverse effects of outdoor air pollution on lung function of children. Quantitative summaries of the effects of air pollution on lung function, however, are lacking due to large differences among studies. Objectives: We aimed to study the association between residential exposure to air pollution and lung function in five European birth cohorts with a standardized exposure assessment following a common protocol. Methods: As part of the European Study of Cohorts for Air Pollution Effects (ESCAPE) we analyzed data from birth cohort studies situated in Germany, Sweden, the Netherlands, and the United Kingdom that measured lung function at 6–8 years of age (n = 5,921). Annual average exposure to air pollution [nitrogen oxides (NO2, NOx), mass concentrations of particulate matter with diameters < 2.5, < 10, and 2.5–10 μm (PM2.5, PM10, and PMcoarse), and PM2.5 absorbance] at the birth address and current address was estimated by land-use regression models. Associations of lung function with estimated air pollution levels and traffic indicators were estimated for each cohort using linear regression analysis, and then combined by random effects meta-analysis. Results: Estimated levels of NO2, NOx, PM2.5 absorbance, and PM2.5 at the current address, but not at the birth address, were associated with small decreases in lung function. For example, changes in forced expiratory volume in 1 sec (FEV1) ranged from –0.86% (95% CI: –1.48, –0.24%) for a 20-μg/m3 increase in NOx to –1.77% (95% CI: –3.34, –0.18%) for a 5-μg/m3 increase in PM2.5. Conclusions: Exposure to air pollution may result in reduced lung function in schoolchildren. Citation: Gehring U, Gruzieva O, Agius RM, Beelen R, Custovic A, Cyrys J, Eeftens M, Flexeder C, Fuertes E, Heinrich J, Hoffmann B, de Jongste JC, Kerkhof M, Klümper C, Korek M, Mölter A, Schultz ES, Simpson A, Sugiri D, Svartengren M, von Berg A, Wijga AH, Pershagen G, Brunekreef B. 2013. Air pollution exposure and lung function in children: the ESCAPE project. Environ Health Perspect 121:1357–1364; http://dx.doi.org/10.1289/ehp.1306770

Introduction Research examining associations between air pollution exposure and respiratory symptoms such as wheezing and shortness of breath in adults has generally been inconclusive. This may in ...

Background Land Use Regression (LUR) is a popular method to explain and predict spatial contrasts in air pollution concentrations, but LUR models for ultrafine particles, such as particle number concentration (PNC) are especially scarce. Moreover, no models have been previously presented for the lung deposited surface area (LDSA) of ultrafine particles. The additional value of ultrafine particle metrics has not been well investigated due to lack of exposure measurements and models. Methods Air pollution measurements were performed in 2011 and 2012 in the eight areas of the Swiss SAPALDIA study at up to 40 sites per area for NO2 and at 20 sites in four areas for markers of particulate air pollution. We developed multi-area LUR models for biannual average concentrations of PM2.5, PM2.5 absorbance, PM10, PMcoarse, PNC and LDSA, as well as alpine, non-alpine and study area specific models for NO2, using predictor variables which were available at a national level. Models were validated using leave-one-out cross-validation, as well as independent external validation with routine monitoring data. Results Model explained variance (R2) was moderate for the various PM mass fractions PM2.5 (0.57), PM10 (0.63) and PMcoarse (0.45), and was high for PM2.5 absorbance (0.81), PNC (0.87) and LDSA (0.91). Study-area specific LUR models for NO2 (R2 range 0.52–0.89) outperformed combined-area alpine (R2 = 0.53) and non-alpine (R2 = 0.65) models in terms of both cross-validation and independent external validation, and were better able to account for between-area variability. Predictor variables related to traffic and national dispersion model estimates were important predictors. Conclusions LUR models for all pollutants captured spatial variability of long-term average concentrations, performed adequately in validation, and could be successfully applied to the SAPALDIA cohort. Dispersion model predictions or area indicators served well to capture the between area variance. For NO2, applying study-area specific models was preferable over applying combined-area alpine/non-alpine models. Correlations between pollutants were higher in the model predictions than in the measurements, so it will remain challenging to disentangle their health effects. Electronic supplementary material The online version of this article (doi:10.1186/s12940-016-0137-9) contains supplementary material, which is available to authorized users.

Satellite-derived (SAT) and chemical transport model (CTM) estimates of PM