Empowering Participatory Research in Urban Health: Wearable Biometric and Environmental Sensors for Activity Recognition

Participatory exposure research, which tracks behaviour and assesses exposure to stressors like air pollution, traditionally relies on time-activity diaries. This study introduces a novel approach, employing machine learning (ML) to empower laypersons in human activity recognition (HAR), aiming to reduce dependence on manual recording by leveraging data from wearable sensors. Recognising complex activities such as smoking and cooking presents unique challenges due to specific environmental conditions. In this research, we combined wearable environment/ambient and wrist-worn activity/biometric sensors for complex activity recognition in an urban stressor exposure study, measuring parameters like particulate matter concentrations, temperature, and humidity. Two groups, Group H (88 individuals) and Group M (18 individuals), wore the devices and manually logged their activities hourly and minutely, respectively. Prioritising accessibility and inclusivity, we selected three classification algorithms: k-nearest neighbours (IBk), decision trees (J48), and random forests (RF), based on: (1) proven efficacy in existing literature, (2) understandability and transparency for laypersons, (3) availability on user-friendly platforms like WEKA, and (4) efficiency on basic devices such as office laptops or smartphones. Accuracy improved with finer temporal resolution and detailed activity categories. However, when compared to other published human activity recognition research, our accuracy rates, particularly for less complex activities, were not as competitive. Misclassifications were higher for vague activities (resting, playing), while well-defined activities (smoking, cooking, running) had few errors. Including environmental sensor data increased accuracy for all activities, especially playing, smoking, and running. Future work should consider exploring other explainable algorithms available on diverse tools and platforms. Our findings underscore ML's potential in exposure studies, emphasising its adaptability and significance for laypersons while also highlighting areas for improvement.

Simulating the impact of particulate matter exposure on health-related behaviour: A comparative study of stochastic modelling and personal monitoring data

Epidemiological and exposure studies concerning particulate matter (PM) often rely on data from sparse governmental stations. While low-cost personal monitors have some drawbacks, recent developments have shown that they can provide fairly accurate and fit-for-purpose data. Comparing a stochastic, i.e., agent-based model (ABM), with environmental, biometric and activity data, collected with personal monitors, could provide insight into how the two approaches assess PM exposure and dose. An ABM was constructed, simulating a PM exposure/dose assessment of 100 agents. Their actions were governed by inherent probabilities of performing an activity, based on population data. Each activity was associated with an intensity level, and a PM pollution level. The ABM results were compared with real-world results. Both approaches had comparable results, showing similar trends and a mean dose. Discrepancies were seen in the activities with the highest mean dose values. A stochastic model, based on population data, does not capture well some specifics of a local population. Combined, personal sensors could provide input for calibration, and an ABM approach can help offset a low number of participants. Implementing a function of agents influencing others transport choice, increased the importance of cycling/walking in the overall dose estimate. Activists, agents with an increased transport influence, did not play an important role at low PM levels. As concentrations rose, higher shares of activists (and their influence) caused the dose to increase. Simulating a person's PM exposure/dose in different scenarios and activities in a virtual environment provides researchers and policymakers with a valuable tool.

HBM4EU-MOM: Prenatal methylmercury-exposure control in five countries through suitable dietary advice for pregnancy - Study design and characteristics of participants

BACKGROUND

Seafood is a major source of vital nutrients for optimal fetal growth, but at the same time is the main source of exposure to methylmercury (MeHg), an established neurodevelopmental toxicant. Pregnant women must be provided with dietary advice so as to include safely fish in their diet for nutrition and mercury control. The aim of this work is to present the design of a multicentre randomized control trial (RCT), which combines human biomonitoring (HBM) with dietary interventions using seafood consumption advice to pregnant women for MeHg control, and to collect information about other possible sources of exposure to mercury. It also presents the materials developed for the implementation of the study and the characteristics of the study participants, which were self-reported in the first trimester of pregnancy.

METHODS

The "HBM4EU-MOM" RCT was performed in the frame of the European Human Biomonitoring Initiative (HBM4EU) in five coastal, high fish-consuming European countries (Cyprus, Greece, Spain, Portugal and Iceland). According to the study design, pregnant women (≥120/country, ≤20 weeks gestational age) provided a hair sample for total mercury assessment (THg) and personal information relevant to the study (e.g., lifestyle, pregnancy status, diet before and during the pregnancy, information on seafood and factors related to possible non-dietary exposures to mercury) during the first trimester of pregnancy. After sampling, participants were randomly assigned to "control" (habitual practices) or "intervention" (received the harmonized HBM4EU-MOM dietary advice for fish consumption during the pregnancy and were encouraged to follow it). Around child delivery, participants provided a second hair sample and completed another tailored questionnaire.

RESULTS

A total of 654 women aged 18-45 years were recruited in 2021 in the five countries, primarily through their health-care providers. The pre-pregnancy BMI of the participants ranged from underweight to obese, but was on average within the healthy range. For 73% of the women, the pregnancy was planned. 26% of the women were active smokers before the pregnancy and 8% continued to smoke during the pregnancy, while 33% were passive smokers before pregnancy and 23% remained passively exposed during the pregnancy. 53% of the women self-reported making dietary changes for their pregnancy, with 74% of these women reporting making the changes upon learning of their pregnancy. Of the 43% who did not change their diet for the pregnancy, 74% reported that their diet was already balanced, 6% found it difficult to make changes and 2% were unsure of what changes to make. Seafood consumption did not change significantly before and during the first trimester of pregnancy (overall average ∼8 times per month), with the highest frequency reported in Portugal (≥15 times per month), followed by Spain (≥7 times per month). During the first-trimester of pregnancy, 89% of the Portuguese women, 85% of the Spanish women and <50% of Greek, Cypriot and Icelandic women reported that they had consumed big oily fish. Relevant to non-dietary exposure sources, most participants (>90%) were unaware of safe procedures for handling spillage from broken thermometers and energy-saving lamps, though >22% experienced such an incident (>1 year ago). 26% of the women had dental amalgams. ∼1% had amalgams placed and ∼2% had amalgams removed during peri-pregnancy. 28% had their hair dyed in the past 3 months and 40% had body tattoos. 8% engaged with gardening involving fertilizers/pesticides and 19% with hobbies involving paints/pigments/dyes.

CONCLUSIONS

The study design materials were fit for the purposes of harmonization and quality-assurance. The harmonized information collected from pregnant women suggests that it is important to raise the awareness of women of reproductive age and pregnant women about how to safely include fish in their diet and to empower them to make proper decisions for nutrition and control of MeHg, as well as other chemical exposures.

Integrated assessment of personal monitor applications for evaluating exposure to urban stressors: A scoping review

Urban stressors pose a health risk, and individual-level assessments provide necessary and fine-grained insight into exposure. An ever-increasing amount of research literature on individual-level exposure to urban stressors using data collected with personal monitors, has called for an integrated assessment approach to identify trends, gaps and needs, and provide recommendations for future research. To this end, a scoping review of the respective literature was performed, as part of the H2020 URBANOME project. Moreover, three specific aims were identified: (i) determine current state of research, (ii) analyse literature according with a waterfall methodological framework and identify gaps and needs, and (iii) provide recommendations for more integrated, inclusive and robust approaches. Knowledge and gaps were extracted based on a systematic approach, e.g., data extraction questionnaires, as well as through the expertise of the researchers performing the review. The findings were assessed through a waterfall methodology of delineating projects into four phases. Studies described in the papers vary in their scope, with most assessing exposure in a single macro domain, though a trend of moving towards multi-domain assessment is evident. Simultaneous measurements of multiple stressors are not common, and papers predominantly assess exposure to air pollution. As urban environments become more diverse, stakeholders from different groups are included in the study designs. Most frequently (per the quadruple helix model), civil society/NGO groups are involved, followed by government and policymakers, while business or private sector stakeholders are less frequently represented. Participants in general function as data collectors and are rarely involved in other phases of the research. While more active involvement is not necessary, more collaborative approaches show higher engagement and motivation of participants to alter their lifestyles based on the research results. The identified trends, gaps and needs can aid future exposure research and provide recommendations on addressing different urban communities and stakeholders.

Quantification and characterization of microplastics in the Thermaic Gulf, in the North Aegean Sea

The abundance and distribution of microplastics has largely increased during last years and the respective implications on the environment and human health is an emerging field in research. In addition, recent studies in the enclosed Mediterranean Sea in Spain and Italy have shown an extended occurrence of microplastics (MPs) in different sediments of environmental samples. This study is focused on the quantification and the characterization of MPs in the Thermaic Gulf in northern Greece. Briefly, samples from different environmental compartments such as seawater, local beaches and seven commercially available fish species collected and analyzed. MPs particles extracted and classified by size, shape, colour and polymer type. A total of 28,523 microplastic particles recorded in the surface water samples, with their numbers ranging from 189 to 7714 particles per sample. The mean concentration of MPs recorded on the surface water was 1.9 ± 2 items/m³ or 750,846 ± 838,029 items/km². Beach sediment sample analysis revealed 14,790 microplastic particles, of which 1825 were large microplastics (LMPs, 1-5 mm) and 12,965 were small microplastics (SMPs, <1 mm). Furthermore, beach sediment samples showed a mean concentration of 733.6 ± 136.6 items/m², with the concentration of LMPs being 90.5 ± 12.4 items/m² and the concentration of SMPs being 643 ± 132 items/m². Concerning fish deposition, microplastics were detected in intestines and mean concentrations per species ranged from 1.3 ± 0.6 to 15.0 ± 1.5 items/individual. The differences in microplastic concentrations between species were statistically significant (p < 0.05) and showed that mesopelagic fish contained the highest concentrations, followed by epipelagic species. The most common size fraction found in the data-set was 1.0-2.5 mm, and polyethylene and polypropylene were the most abundant polymer types recorded. This is the first detailed investigation of MPs in Thermaic Gulf, which raises concerns on their potential negative effects.

Application of AOPs to assist regulatory assessment of chemical risks - Case studies, needs and recommendations

While human regulatory risk assessment (RA) still largely relies on animal studies, new approach methodologies (NAMs) based on in vitro, in silico or non-mammalian alternative models are increasingly used to evaluate chemical hazards. Moreover, human epidemiological studies with biomarkers of effect (BoE) also play an invaluable role in identifying health effects associated with chemical exposures. To move towards the next generation risk assessment (NGRA), it is therefore crucial to establish bridges between NAMs and standard approaches, and to establish processes for increasing mechanistically-based biological plausibility in human studies. The Adverse Outcome Pathway (AOP) framework constitutes an important tool to address these needs but, despite a significant increase in knowledge and awareness, the use of AOPs in chemical RA remains limited. The objective of this paper is to address issues related to using AOPs in a regulatory context from various perspectives as it was discussed in a workshop organized within the European Union partnerships HBM4EU and PARC in spring 2022. The paper presents examples where the AOP framework has been proven useful for the human RA process, particularly in hazard prioritization and characterization, in integrated approaches to testing and assessment (IATA), and in the identification and validation of BoE in epidemiological studies. Nevertheless, several limitations were identified that hinder the optimal usability and acceptance of AOPs by the regulatory community including the lack of quantitative information on response-response relationships and of efficient ways to map chemical data (exposure and toxicity) onto AOPs. The paper summarizes suggestions, ongoing initiatives and third-party tools that may help to overcome these obstacles and thus assure better implementation of AOPs in the NGRA.

PFAS levels and determinants of variability in exposure in European teenagers - Results from the HBM4EU aligned studies (2014-2021)

BACKGROUND

Perfluoroalkyl substances (PFAS) are man-made fluorinated chemicals, widely used in various types of consumer products, resulting in their omnipresence in human populations. The aim of this study was to describe current PFAS levels in European teenagers and to investigate the determinants of serum/plasma concentrations in this specific age group.

METHODS

PFAS concentrations were determined in serum or plasma samples from 1957 teenagers (12-18 years) from 9 European countries as part of the HBM4EU aligned studies (2014-2021). Questionnaire data were post-harmonized by each study and quality checked centrally. Only PFAS with an overall quantification frequency of at least 60% (PFOS, PFOA, PFHxS and PFNA) were included in the analyses. Sociodemographic and lifestyle factors were analysed together with food consumption frequencies to identify determinants of PFAS exposure. The variables study, sex and the highest educational level of household were included as fixed factors in the multivariable linear regression models for all PFAS and each dietary variable was added to the fixed model one by one and for each PFAS separately.

RESULTS

The European exposure values for PFAS were reported as geometric means with 95% confidence intervals (CI): PFOS [2.13 μg/L (1.63-2.78)], PFOA ([0.97 μg/L (0.75-1.26)]), PFNA [0.30 μg/L (0.19-0.45)] and PFHxS [0.41 μg/L (0.33-0.52)]. The estimated geometric mean exposure levels were significantly higher in the North and West versus the South and East of Europe. Boys had significantly higher concentrations of the four PFAS compared to girls and significantly higher PFASs concentrations were found in teenagers from households with a higher education level. Consumption of seafood and fish at least 2 times per week was significantly associated with 21% (95% CI: 12-31%) increase in PFOS concentrations and 20% (95% CI: 10-31%) increase in PFNA concentrations as compared to less frequent consumption of seafood and fish. The same trend was observed for PFOA and PFHxS but not statistically significant. Consumption of eggs at least 2 times per week was associated with 11% (95% CI: 2-22%) and 14% (95% CI: 2-27%) increase in PFOS and PFNA concentrations, respectively, as compared to less frequent consumption of eggs. Significantly higher PFOS concentrations were observed for participants consuming offal (14% (95% CI: 3-26%)), the same trend was observed for the other PFAS but not statistically significant. Local food consumption at least 2 times per week was associated with 40% (95% CI: 19-64%) increase in PFOS levels as compared to those consuming local food less frequently.

CONCLUSION

This work provides information about current levels of PFAS in European teenagers and potential dietary sources of exposure to PFAS in European teenagers. These results can be of use for targeted monitoring of PFAS in food.

Approaches to mixture risk assessment of PFASs in the European population based on human hazard and biomonitoring data

Per- and polyfluoroalkyl substances (PFASs) are a highly persistent, mobile, and bioaccumulative class of chemicals, of which emissions into the environment result in long-lasting contamination with high probability for causing adverse effects to human health and the environment. Within the European Biomonitoring Initiative HBM4EU, samples and data were collected in a harmonized way from human biomonitoring (HBM) studies in Europe to derive current exposure data across a geographic spread. We performed mixture risk assessments based on recent internal exposure data of PFASs in European teenagers generated in the HBM4EU Aligned Studies (dataset with N = 1957, sampling years 2014-2021). Mixture risk assessments were performed based on three hazard-based approaches: the Hazard Index (HI) approach, the sum value approach as used by the European Food Safety Authority (EFSA) and the Relative Potency Factor (RPF) approach. The HI approach resulted in the highest risk estimates, followed by the RPF approach and the sum value approach. The assessments indicate that PFAS exposure may result in a health risk in a considerable fraction of individuals in the HBM4EU teenager study sample, thereby confirming the conclusion drawn in the recent EFSA scientific opinion. This study underlines that HBM data are of added value in assessing the health risks of aggregate and cumulative exposure to PFASs, as such data are able to reflect exposure from different sources and via different routes.

A walk in the PARC: developing and implementing 21st century chemical risk assessment in Europe

Current approaches for the assessment of environmental and human health risks due to exposure to chemical substances have served their purpose reasonably well. Nevertheless, the systems in place for different uses of chemicals are faced with various challenges, ranging from a growing number of chemicals to changes in the types of chemicals and materials produced. This has triggered global awareness of the need for a paradigm shift, which in turn has led to the publication of new concepts for chemical risk assessment and explorations of how to translate these concepts into pragmatic approaches. As a result, next-generation risk assessment (NGRA) is generally seen as the way forward. However, incorporating new scientific insights and innovative approaches into hazard and exposure assessments in such a way that regulatory needs are adequately met has appeared to be challenging. The European Partnership for the Assessment of Risks from Chemicals (PARC) has been designed to address various challenges associated with innovating chemical risk assessment. Its overall goal is to consolidate and strengthen the European research and innovation capacity for chemical risk assessment to protect human health and the environment. With around 200 participating organisations from all over Europe, including three European agencies, and a total budget of over 400 million euro, PARC is one of the largest projects of its kind. It has a duration of seven years and is coordinated by ANSES, the French Agency for Food, Environmental and Occupational Health & Safety.

Assessment of Individual-Level Exposure to Airborne Particulate Matter during Periods of Atmospheric Thermal Inversion

Air pollution exposure is harmful to human health and reducing it at the level of an individual requires measurements and assessments that capture the spatiotemporal variability of different microenvironments and the influence of specific activities. In this paper, activity-specific and general indoor and outdoor exposure during and after a period of high concentrations of particulate matter (PM), e.g., an atmospheric thermal inversion (ATI) in the Ljubljana subalpine basin, Slovenia, was assessed. To this end, personal particulate matter monitors (PPM) were used, worn by participants of the H2020 ICARUS sampling campaigns in spring 2019 who also recorded their hourly activities. ATI period(s) were determined based on data collected from two meteorological stations managed by the Slovenian Environmental Agency (SEA). Results showed that indoor and outdoor exposure to PM was significantly higher during the ATI period, and that the difference between mean indoor and outdoor exposure to PM was much higher during the ATI period (23.0 µg/m3) than after (6.5 µg/m3). Indoor activities generally were associated with smaller differences, with cooking and cleaning even having higher values in the post-ATI period. On the other hand, all outdoor activities had higher PM values during the ATI than after, with larger differences, mostly >30.0 µg/m3. Overall, this work demonstrated that an individual-level approach can provide better spatiotemporal resolution and evaluate the relative importance of specific high-exposure events, and in this way provide an ancillary tool for exposure assessments.

Harmonization and Visualization of Data from a Transnational Multi-Sensor Personal Exposure Campaign

Use of a multi-sensor approach can provide citizens with holistic insights into the air quality of their immediate surroundings and their personal exposure to urban stressors. Our work, as part of the ICARUS H2020 project, which included over 600 participants from seven European cities, discusses the data fusion and harmonization of a diverse set of multi-sensor data streams to provide a comprehensive and understandable report for participants. Harmonizing the data streams identified issues with the sensor devices and protocols, such as non-uniform timestamps, data gaps, difficult data retrieval from commercial devices, and coarse activity data logging. Our process of data fusion and harmonization allowed us to automate visualizations and reports, and consequently provide each participant with a detailed individualized report. Results showed that a key solution was to streamline the code and speed up the process, which necessitated certain compromises in visualizing the data. A thought-out process of data fusion and harmonization of a diverse set of multi-sensor data streams considerably improved the quality and quantity of distilled data that a research participant received. Though automation considerably accelerated the production of the reports, manual and structured double checks are strongly recommended.

Magnetic nanoparticles: An indicator of health risks related to anthropogenic airborne particulate matter

Due to their small dimensions, airborne particles are able to penetrate through inhalation into many human organs, from the lungs to the cardiovascular system and the brain, which can threaten our health. This work establishes a novel approach of collecting quantitative data regarding the fraction, the composition and the size distribution of combustion-emitted particulate matter through the magnetic characterization and analysis of samples received by common air pollution monitoring. To this end, SQUID magnetometry measurements were carried out for samples from urban and suburban areas in Thessaloniki, the second largest city of Greece, taking into consideration the seasonal and weekly variation of airborne particles levels as determined by occurring traffic and meteorological conditions. The level of estimated magnetically-responding atmospheric particulate matter was at least 0.5 % wt. of the collected samples, mostly being present in the form of ultrafine particles with nuclei sizes of approximately 14 nm and their aggregates. The estimated quantities of magnetic particulate matter show maximum values during autumn months (0.8 % wt.) when increased commuting takes place, appearing higher in the city center by up to 50% than those in suburban areas. In combination with high-resolution transmission electron imaging and elemental analysis, it was found that Fe₃O₄ and similar ferrites, some of them attached to heavy metals (Co, Cr), are the dominant magnetic contributors arising from anthropogenic high-temperature processes, e.g. due to traffic emissions. Importantly, nasal cytologic samples collected from residents of both central and suburban areas showed same pattern in what concerns magnetic behavior, thus verifying the critical role of nanosized magnetic particles in the assessment of air pollution threats. Despite the inherent statistical limitations of our study, such findings also indicate the potential transmission of infectious pathogens by means of pollution-derived nanoparticles into the respiratory system of the human body.

Multi-city comparative PM2.5 source apportionment for fifteen sites in Europe: The ICARUS project

PM_2.5 is an air pollution metric widely used to assess air quality, with the European Union having set targets for reduction in PM_2.5 levels and population exposure. A major challenge for the scientific community is to identify, quantify and characterize the sources of atmospheric particles in the aspect of proposing effective control strategies. In the frame of ICARUS EU2020 project, a comprehensive database including PM_2.5 concentration and chemical composition (ions, metals, organic/elemental carbon, Polycyclic Aromatic Hydrocarbons) from three sites (traffic, urban background, rural) of five European cities (Athens, Brno, Ljubljana, Madrid, Thessaloniki) was created. The common and synchronous sampling (two seasons involved) and analysis procedure offered the prospect of a harmonized Positive Matrix Factorization model approach, with the scope of identifying the similarities and differences of PM_2.5 key-source chemical fingerprints across the sampling sites. The results indicated that the average contribution of traffic exhausts to PM_2.5 concentration was 23.3% (traffic sites), 13.3% (urban background sites) and 8.8% (rural sites). The average contribution of traffic non-exhausts was 12.6% (traffic), 13.5% (urban background) and 6.1% (rural sites). The contribution of fuel oil combustion was 3.8% at traffic, 11.6% at urban background and 18.7% at rural sites. Biomass burning contribution was 22% at traffic sites, 30% at urban background sites and 28% at rural sites. Regarding soil dust, the average contribution was 5% and 8% at traffic and urban background sites respectively and 16% at rural sites. Sea salt contribution was low (1-4%) while secondary aerosols corresponded to the 16-34% of PM_2.5. The homogeneity of the chemical profiles as well as their relationship with prevailing meteorological parameters were investigated. The results showed that fuel oil combustion, traffic non-exhausts and soil dust profiles are considered as dissimilar while biomass burning, sea salt and traffic exhaust can be characterized as relatively homogenous among the sites.

Advancing COVID-19 differentiation with a robust preprocessing and integration of multi-institutional open-repository computer tomography datasets for deep learning analysis

The coronavirus pandemic and its unprecedented consequences globally has spurred the interest of the artificial intelligence research community. A plethora of published studies have investigated the role of imaging such as chest X-rays and computer tomography in coronavirus disease 2019 (COVID-19) automated diagnosis. Οpen repositories of medical imaging data can play a significant role by promoting cooperation among institutes in a world-wide scale. However, they may induce limitations related to variable data quality and intrinsic differences due to the wide variety of scanner vendors and imaging parameters. In this study, a state-of-the-art custom U-Net model is presented with a dice similarity coefficient performance of 99.6% along with a transfer learning VGG-19 based model for COVID-19 versus pneumonia differentiation exhibiting an area under curve of 96.1%. The above was significantly improved over the baseline model trained with no segmentation in selected tomographic slices of the same dataset. The presented study highlights the importance of a robust preprocessing protocol for image analysis within a heterogeneous imaging dataset and assesses the potential diagnostic value of the presented COVID-19 model by comparing its performance to the state of the art.

COVID‑19 in Northern Italy: An integrative overview of factors possibly influencing the sharp increase of the outbreak (Review)

Italy is currently one of the countries seriously affected by the COVID‑19 pandemic. As per 10 April 2020, 147,577 people were found positive in a total of 906,864 tests performed and 18,849 people lost their lives. Among all cases, 70.2% of positive, and 79.4% of deaths occurred in the provinces of Northern Italy (Lombardi, Emilia Romagna, Veneto and Piemonte), where the outbreak first started. Originally, it was considered that the high number of positive cases and deaths in Italy resulted from COVID‑19 initially coming to Italy from China, its presumed country of origin. However, an analysis of the factors that played a role in the extent of this outbreak is needed. Evaluating which factors could be specific for a country and which might contribute the most is nevertheless complex, with accompanying high uncertainty. The purpose of this work is to discuss some of the possible contributing factors and their possible role in the relatively high infection and death rates in Northern Italy compared to other areas and countries.

Identification of cement in atmospheric particulate matter using the hybrid method of laser diffraction analysis and Raman spectroscopy

The production of cement is associated with the emissions of dust and particulate matter, nitrogen oxides (NO_x), sulfur dioxide (SO₂), carbon monoxide (CO), heavy metals, and volatile organic compounds into the environment. People living near cement production facilities are potentially exposed to these pollutants, including carcinogens, although at lower doses than the factory workers. In this study we focused on the distribution of fine particulate matter, the composition, size patterns, and spatial distribution of the emissions from Spassk cement plant in Primorsky Krai, Russian Federation. The particulate matter was studied in wash-out from vegetation (conifer needles) using a hybrid method of laser diffraction analysis and Raman spectroscopy. The results showed that fine particulate matter (PM₁₀ fraction) extended to the entire town and its neighbourhood. The percentage of PM₁₀ in different areas of the town and over the course of two seasons ranged from 34.8% to 65% relative to other size fractions of particulate matter. It was further shown that up to 80% of the atmospheric PM content at some sampling points was composed of cement-containing particles. This links the cement production in Spassk-Dalny with overall morbidity of the town population and pollution of the environment.

Comparing Airborne Particulate Matter Intake Dose Assessment Models Using Low-Cost Portable Sensor Data

Low-cost sensors can be used to improve the temporal and spatial resolution of an individual's particulate matter (PM) intake dose assessment. In this work, personal activity monitors were used to measure heart rate (proxy for minute ventilation), and low-cost PM sensors were used to measure concentrations of PM. Intake dose was assessed as a product of PM concentration and minute ventilation, using four models with increasing complexity. The two models that use heart rate as a variable had the most consistent results and showed a good response to variations in PM concentrations and heart rate. On the other hand, the two models using generalized population data of minute ventilation expectably yielded more coarse information on the intake dose. Aggregated weekly intake doses did not vary significantly between the models (6-22%). Propagation of uncertainty was assessed for each model, however, differences in their underlying assumptions made them incomparable. The most complex minute ventilation model, with heart rate as a variable, has shown slightly lower uncertainty than the model using fewer variables. Similarly, among the non-heart rate models, the one using real-time activity data has less uncertainty. Minute ventilation models contribute the most to the overall intake dose model uncertainty, followed closely by the low-cost personal activity monitors. The lack of a common methodology to assess the intake dose and quantifying related uncertainties is evident and should be a subject of further research.

Lifelong exposure to multiple stressors through different environmental pathways for European populations

Traditional exposure studies provide valuable insights for epidemiology, toxicology, and risk assessment. Throughout their lives, individuals are exposed to thousands of stressors in the environment which are not static, but influenced by environmental, temporal, spatial, and even socio-demographic factors. Existing exposure studies have usually focused on specific stressors for a constrained period of time. In response, the concept of the exposome has been raised, which is defined as the totality of exposure experienced from conception until death. The EU FP7-ENVIRONMENT research project HEALS was launched with the aim of incorporating a series of novel technologies, data analysis, and modelling tools to efficiently support exposome studies in Europe. The authors have developed a framework of modelling tools for estimating the long-term external exposure of selected population groups to multiple stressors through different pathways. As the starting point, the stressors, including electromagnetic fields (EMF) and ultraviolet light (UV) through dermal uptake, phthalates (DEHP, DIDP, and DINP) through inhalation, as well as chromium, mercury, and lead through food intake, have been selected. The simulation for multiple stressors has been realised by developing a probabilistic model that integrates the micro-environment approach, time-activity patterns, and a life course trajectory model. The methodology has been applied to a selected sample of subjects enrolled in the Italian Twin Registry (ITR). The results show that long-term exposures to multiple stressors are affected by factors including age, gender, geographical location, and education level. The methods developed in this paper extended the temporal and spatial scales of exposure modelling in Europe. Moreover, the application of our methods provided a novel approach and crucial input data for future work on environment-wide association studies.

A model for estimating the lifelong exposure to PM2.5 and NO2 and the application to population studies

Numerous epidemiological studies have confirmed the negative influences of air pollutants on human health, where fine particles (PM2.5) and nitrogen dioxide (NO₂) cause the highest health risks. However, the traditional studies have only involved the ambient concentration for a short to medium time period, which ignores the influence of indoor sources, the individual time-activity pattern, and the fact that the health status is impacted by the long-term accumulated exposure. The aim of this paper is to develop a methodology to simulate the lifelong exposure (rather than outdoor concentration) to PM2.5 and NO₂ for individuals in Europe. This method is realized by developing a probabilistic model that integrates an outdoor air quality model, a model estimating indoor air pollution, an exposure model, and a life course trajectory model for predicting retrospectively the employment status. This approach has been applied to samples of two population studies in the frame of the European Commission FP7-ENVIRONMENT research project HEALS (Health and Environment-wide Associations based on Large Population Surveys), where socioeconomic data of the participants have been collected. Results show that the simulated exposures to both pollutants for the samples are influenced by socio-demographic characteristics, including age, gender, residential location, employment status and smoking habits. Both outdoor concentrations and indoor sources play an important role in the total exposure. Moreover, large variances have been observed among countries and cities. The application of this methodology provides valuable insights for the exposure modelling, as well as important input data for exploring the correlation between exposure and health impacts.

Assessing and enhancing the utility of low-cost activity and location sensors for exposure studies

Nowadays, the advancement of mobile technology in conjunction with the introduction of the concept of exposome has provided new dynamics to the exposure studies. Since the addressing of health outcomes related to environmental stressors is crucial, the improvement of exposure assessment methodology is of paramount importance. Towards this aim, a pilot study was carried out in the two major cities of Greece (Athens, Thessaloniki), investigating the applicability of commercially available fitness monitors and the Moves App for tracking people's location and activities, as well as for predicting the type of the encountered location, using advanced modeling techniques. Within the frame of the study, 21 individuals were using the Fitbit Flex activity tracker, a temperature logger, and the application Moves App on their smartphones. For the validation of the above equipment, participants were also carrying an Actigraph (activity sensor) and a GPS device. The data collected from Fitbit Flex, the temperature logger, and the GPS (speed) were used as input parameters in an Artificial Neural Network (ANN) model for predicting the type of location. Analysis of the data showed that the Moves App tends to underestimate the daily steps counts in comparison with Fitbit Flex and Actigraph, respectively, while Moves App predicted the movement trajectory of an individual with reasonable accuracy, compared to a dedicated GPS. Finally, the encountered location was successfully predicted by the ANN in most of the cases.

Human biomonitoring data analysis for metals in an Italian adolescents cohort: An exposome approach

The first Italian human biomonitoring survey (PROBE - PROgramme for Biomonitoring general population Exposure) considered a reference population of adolescents, aged 13-15 years, living in urban and rural areas and investigated their exposure to metals. The study was expanded up to 453 adolescents living in the same areas of Latium Region (Italy) and blood samples were analyzed for 19 metals (As, Be, Cd, Co, Cr, Hg, Ir, Mn, Mo, Ni, Pb, Pd, Pt, Rh, Sb, Sn, Tl, V, and W) by sector field inductively coupled plasma mass spectrometry. The exposure assessment was contextualized following an exposome approach that considered several determinants related to the subjects, available environmental parameters and geo-coding of residence address. To assess the influence of exposure determinants and modifiers on children biomarkers levels we used two independent methodologies. The first makes use of the so-called Environment-Wide Association Study (EWAS) methodology while the second was based on the application of a Generalized Liner Model (GLM) capturing co-exposures to pairs of key determinants. Based on our analysis, Hg and As were positively associated with dietary pathways (primarily linked to fish and to a lesser extent to milk consumption) while Cr showed a more complex interaction between co-exposure to different dietary pathways (milk and fish) coupled to proximity of residence to industrial activities. In addition to diet, socio-economic status of the mother revealed robust statistical associations with Cd, Ni and W biomonitoring levels in the respective children.

Development of an assay to assess genotoxicity by particulate matter extract

The current study describes a method for assessing the oxidative potential of common environmental stressors (ambient air particulate matter), using a plasmid relaxation assay where the extract caused single-strand breaks, easily visualised through electrophoresis. This assay utilises a miniscule amount (11 µg) of particulate matter (PM) extract compared to other, cell-based methods (~3,000 µg). The negative impact of air pollution on human health has been extensively recognised. Among the air pollutants, PM plays an eminent role, as reflected in the broad scientific interest. PM toxicity highly depends on its composition (metals and organic compounds), which in turn has been linked to multiple health effects (such as cardiorespiratory diseases and cancer) through multiple toxicity mechanisms; the induction of oxidative stress is considered a major mechanism among these. In this study, the PM levels, oxidative potential, cytotoxicity and genotoxicity of PM in the region of Larissa, Greece were examined using the plasmid relaxation assay. Finally, coffee extracts from different varieties, derived from both green and roasted seeds, were examined for their ability to inhibit PM-induced DNA damage. These extracts also exerted an inhibitory effect on xanthine oxidase and catalase, but had no effect against superoxide dismutase. Overall, this study highlights the importance of assays for assessing the oxidative potential of widespread environmental stressors (PM), as well as the antioxidant capacity of beverages and food items, with the highlight being the development of a plasmid relaxation assay to assess the genotoxicity caused by PM using only a miniscule amount.

Vapor Phase Synthesis of II-IV Semiconductor Nanoparticles in a Counterflow Jet Reactor

The vapor-phase synthesis of polycrystalline ZnSe nanoparticles is reported. The particles were grown at room temperature and at a pressure of 125 torr in a counterflow jet reactor and were collected by impact on a Si watler. The precursors used in this study were vapors of (CH3)2Zn:[N(C2H5)3)]2 and H2Se gas diluted in hydrogen. These precursors have been used in the past for Metalorganic Vapor Phase Epitaxy (MOVPE) of ZnSe thin films. The particles were characterized by Transmission Electron Microscopy (TEM). electron diffraction. and Raman spectroscopy. The reactor was operated in a continuous, steady-state mode using a gas delivery system that is typical flor MOVPII systems.