Spatiotemporal modeling of occupational particulate matter using personal low-cost sensor and indoor location tracking data.

Occupational exposure to particulate matter (PM) can result in multiple adverse health effects and should be minimized to protect workers' health. PM exposure at the workplace can be complex with many potential sources and fluctuations over time, making it difficult to control. Dynamic maps that visualize how PM is distributed throughout a workplace over time can help in gaining better insights into when and where exposure occurs. This study explored the use of spatiotemporal modeling followed by kriging for the development of dynamic PM concentration maps in an experimental setting and a workplace setting. Data was collected using personal low-cost PM sensors and an indoor location tracking system, mounted on a moving robot or worker. Maps were generated for an experimental study with one simulated robot worker and a workplace study with four workers. Cross-validation was performed to evaluate the performance and robustness of three types of spatiotemporal models (metric, separable, and summetric) and, as an additional external validation, model estimates were compared with measurements from sensors that were placed stationary in the laboratory or workplace. Spatiotemporal models and maps were generated for both the experimental and workplace studies, with average root mean squared error (RMSE) from 10-fold cross-validation ranging from 7-12 and 73-127 µg/m3, respectively. Workplace models were relatively more robust compared to the experimental study (relative SD ranging from 8-14% of the average RMSE vs. 27-56%, respectively), presumably due to the larger number of parallel measurements. Model estimates showed low to moderate fits compared to stationary sensor measurements (R2 ranging from 0.1-0.5), indicating maps should be interpreted with caution and only used indicatively. Together, these findings show the feasibility of using spatiotemporal modeling for generating dynamic concentration maps based on personal data. The described method could be applied for exposure characterization within comparable study designs or can be expanded further, for example by developing real-time, location-based worker feedback systems, as efficient tools to visualize and communicate exposure risks.

Neighbourhood and path-based greenspace in three European countries: associations with objective physical activity.

BACKGROUND: Greenspace has been associated with health benefits in many contexts. An important pathway may be through outdoor physical activity. We use a novel approach to examine the link between greenspace microenvironments and outdoor physical activity levels in the HEALS study conducted in Edinburgh (UK), the Netherlands, and Athens and Thessaloniki (Greece). METHODS: Using physical activity tracker recordings, 118 HEALS participants with young children were classified with regard to daily minutes of moderate to vigorous physical activity (MVPA); 60 were classified with regard to the metabolic equivalent task (MET)-minutes for each of the 1014 active trips they made. Greenspace indicators were generated for Normalised Difference Vegetation Index (NDVI), tree cover density (TCD), and green land use (GLU). We employed linear mixed-effects models to analyse (1) daily MVPA in relation to greenspace within 300 m and 1000 m of residential addresses and (2) trip MET-minutes in relation to average greenspace within a 50 m buffer of walking/cycling routes. Models were adjusted for activity, walkability, bluespace, age, sex, car ownership, dog ownership, season, weekday/weekend day, and local meteorology. RESULTS: There was no clear association between MVPA-minutes and any residential greenspace measure. For example, in fully adjusted models, a 10 percentage point increase in NDVI within 300 m of home was associated with a daily increase of 1.14 (95% CI - 0.41 to 2.70) minutes of MVPA. However, we did find evidence to indicate greenspace markers were positively linked to intensity and duration of activity: in fully adjusted models, 10 percentage point increases in trip NDVI, TCD, and GLU were associated with increases of 10.4 (95% CI: 4.43 to 16.4), 10.6 (95% CI: 4.96 to 16.3), and 3.36 (95% CI: 0.00 to 6.72) MET-minutes, respectively. The magnitude of associations with greenspace tended to be greater for cycling. CONCLUSIONS: More strenuous or longer walking and cycling trips occurred in environments with more greenspace, but levels of residential greenspace did not have a clear link with outdoor MVPA. To build on our research, we suggest future work examine larger, more diverse populations and investigate the influence of greenspace for trip purpose and route preference.

Urban greenspace and the indoor environment: Pathways to health via indoor particulate matter, noise, and road noise annoyance.

BACKGROUND/AIM: The exposome includes urban greenspace, which may affect health via a complex set of pathways, including reducing exposure to particulate matter (PM) and noise. We assessed these pathways using indoor exposure monitoring data from the HEALS study in four European urban areas (Edinburgh, UK; Utrecht, Netherlands; Athens and Thessaloniki, Greece). METHODS: We quantified three metrics of residential greenspace at 50 m and 100 m buffers: Normalised Difference Vegetation Index (NDVI), annual tree cover density, and surrounding green land use. NDVI values were generated for both summer and the season during which the monitoring took place. Indoor PM2.5 and noise levels were measured by Dylos and Netatmo sensors, respectively, and subjective noise annoyance was collected by questionnaire on an 11-point scale. We used random-effects generalised least squares regression models to assess associations between greenspace and indoor PM2.5 and noise, and an ordinal logistic regression to model the relationship between greenspace and road noise annoyance. RESULTS: We identified a significant inverse relationship between summer NDVI and indoor PM2.5 (-1.27 µg/m3 per 0.1 unit increase [95% CI -2.38 to -0.15]) using a 100 m residential buffer. Reduced (i.e., <1.0) odds ratios (OR) of road noise annoyance were associated with increasing summer (OR = 0.55 [0.31 to 0.98]) and season-specific (OR = 0.55 [0.32 to 0.94]) NDVI levels, and tree cover density (OR = 0.54 [0.31 to 0.93] per 10 percentage point increase), also at a 100 m buffer. In contrast to these findings, we did not identify any significant associations between greenspace and indoor noise in fully adjusted models. CONCLUSIONS: We identified reduced indoor levels of PM2.5 and noise annoyance, but not overall noise, with increasing outdoor levels of certain greenspace indicators. To corroborate our findings, future research should examine the effect of enhanced temporal resolution of greenspace metrics during different seasons, characterise the configuration and composition of green areas, and explore mechanisms through mediation modelling.

Comparison of methods for converting Dylos particle number concentrations to PM2.5 mass concentrations.

The aim of this study was to (a) develop a method for converting particle number concentrations (PNC) obtained by Dylos to PM2.5 mass concentrations, (b) compare this conversion with similar methods available in the literature, and (c) compare Dylos PM2.5 obtained using all available conversion methods with gravimetric samples. Data were collected in multiple residences in three European countries using the Dylos and an Aerodynamic Particle Sizer (APS, TSI) in the Netherlands or an optical particle counter (OPC, GRIMM) in Greece. Two statistical fitted curves were developed based on Dylos PNC and either an APS or an OPC particle mass concentrations (PMC). In addition, at the homes of 16 volunteers (UK and Netherlands), Dylos measurements were collected along with gravimetric samples. The Dylos PNC were transformed to PMC using all the fitted curves obtained during this study (and three found in the literature) and were compared with gravimetric samples. The method developed in the present study using an OPC showed the highest correlation (Pearson (R) = 0.63, Concordance (ρc ) = 0.61) with gravimetric data. The other methods resulted in an underestimation of PMC compared to gravimetric measurements (R = 0.65-0.55, ρc  = 0.51-0.24). In conclusion, estimation of PM2.5 concentrations using the Dylos is acceptable for indicative purposes.

Cardiovascular effects among workers exposed to multiwalled carbon nanotubes.

OBJECTIVES: The increase in production of multiwalled carbon nanotubes (MWCNTs) has led to growing concerns about health risks. In this study, we assessed the association between occupational exposure to MWCNTs and cardiovascular biomarkers. METHODS: A cross-sectional study was performed among 22 workers of a company commercially producing MWCNTs (subdivided into lab personnel with low or high exposure and operators), and a gender and age-matched unexposed population (n=42). Exposure to MWCNTs and 12 cardiovascular markers were measured in participants' blood (phase I). In a subpopulation of 13 exposed workers and six unexposed workers, these measures were repeated after 5 months (phase II). We analysed associations between MWCNT exposure and biomarkers of cardiovascular risk, adjusted for age, body mass index, sex and smoking. RESULTS: We observed an upward trend in the concentration of endothelial damage marker intercellular adhesion molecule-1 (ICAM-1), with increasing exposure to MWCNTs in both phases. The operator category showed significantly elevated ICAM-1 geometric mean ratios (GMRs) compared with the controls (phase I: GMR=1.40, P=1.30E-3; phase II: GMR=1.37, P=0.03). The trends were significant both across worker categories (phase I: P=1.50E-3; phase II: P=0.01) and across measured GM MWCNT concentrations (phase I: P=3.00E-3; phase II: P=0.01). No consistent significant associations were found for the other cardiovascular markers. CONCLUSION: The associations between MWCNT exposure and ICAM-1 indicate endothelial activation and an increased inflammatory state in workers with MWCNT exposure.

Comparative Human Health Impact Assessment of Engineered Nanomaterials in the Framework of Life Cycle Assessment.

For safe innovation, knowledge on potential human health impacts is essential. Ideally, these impacts are considered within a larger life-cycle-based context to support sustainable development of new applications and products. A methodological framework that accounts for human health impacts caused by inhalation of engineered nanomaterials (ENMs) in an indoor air environment has been previously developed. The objectives of this study are as follows: (i) evaluate the feasibility of applying the CF framework for NP exposure in the workplace based on currently available data; and (ii) supplement any resulting knowledge gaps with methods and data from the life cycle approach and human risk assessment (LICARA) project to develop a modified case-specific version of the framework that will enable near-term inclusion of NP human health impacts in life cycle assessment (LCA) using a case study involving nanoscale titanium dioxide (nanoTiO2 ). The intent is to enhance typical LCA with elements of regulatory risk assessment, including its more detailed measure of uncertainty. The proof-of-principle demonstration of the framework highlighted the lack of available data for both the workplace emissions and human health effects of ENMs that is needed to calculate generalizable characterization factors using common human health impact assessment practices in LCA. The alternative approach of using intake fractions derived from workplace air concentration measurements and effect factors based on best-available toxicity data supported the current case-by-case approach for assessing the human health life cycle impacts of ENMs. Ultimately, the proposed framework and calculations demonstrate the potential utility of integrating elements of risk assessment with LCA for ENMs once the data are available.

Occupational Exposure to Multi-Walled Carbon Nanotubes During Commercial Production Synthesis and Handling.

The world-wide production of carbon nanotubes (CNTs) has increased substantially in the last decade, leading to occupational exposures. There is a paucity of exposure data of workers involved in the commercial production of CNTs. The goals of this study were to assess personal exposure to multi-walled carbon nanotubes (MWCNTs) during the synthesis and handling of MWCNTs in a commercial production facility and to link these exposure levels to specific activities. Personal full-shift filter-based samples were collected, during commercial production and handling of MWCNTs, R&D activities, and office work. The concentrations of MWCNT were evaluated on the basis of EC concentrations. Associations were studied between observed MWCNT exposure levels and location and activities. SEM analyses showed MWCNTs, present as agglomerates ranging between 200 nm and 100 µm. Exposure levels of MWCNTs observed in the production area during the full scale synthesis of MWCNTs (N = 23) were comparable to levels observed during further handling of MWCNTs (N = 19): (GM (95% lower confidence limit-95% upper confidence limit)) 41 µg m(-3) (20-88) versus 43 µg m(-3) (22-86), respectively. In the R&D area (N = 11) and the office (N = 5), exposure levels of MWCNTs were significantly (P < 0.05) lower: 5 µg m(-3) (2-11) and 7 µg m(-3) (2-28), respectively. Bagging, maintenance of the reactor, and powder conditioning were associated with higher exposure levels in the production area, whereas increased exposure levels in the R&D area were related to handling of MWCNTs powder.

Occupational Exposure to Nano-Objects and Their Agglomerates and Aggregates Across Various Life Cycle Stages; A Broad-Scale Exposure Study.

BACKGROUND: Occupational exposure to manufactured nano-objects and their agglomerates, and aggregates (NOAA) has been described in several workplace air monitoring studies. However, data pooling for general conclusions and exposure estimates are hampered by limited exposure data across the occupational life cycle of NOAA and a lack in comparability between the methods of collecting and analysing the data. By applying a consistent method of collecting and analysing the workplace exposure data, this study aimed to provide information about the occupational NOAA exposure levels across various life cycle stages of NOAA in the Netherlands which can also be used for multi-purpose use. METHODS: Personal/near field task-based exposure data was collected using a multi-source exposure assessment method collecting real time particle number concentration, particle size distribution (PSD), filter-based samples for morphological, and elemental analysis and detailed contextual information. A decision logic was followed allowing a consistent and objective way of analysing the exposure data. RESULTS: In total, 46 measurement surveys were conducted at 15 companies covering 18 different exposure situations across various occupational life cycle stages of NOAA. Highest activity-effect levels were found during replacement of big bags (<1000-76000 # cm(-3)), mixing/dumping of powders manually (<1000-52000 # cm(-3)) and mechanically (<1000-100000 # cm(-3)), and spraying of liquid (2000-800000 # cm(-3)) showing a high variability between and within the various exposure situations. In general, a limited change in PSD was found during the activity compared to the background. CONCLUSIONS: This broad-scale exposure study gives a comprehensive overview of the NOAA exposure situations in the Netherlands and an indication of the levels of occupational exposure to NOAA across various life cycle of NOAA. The collected workplace exposure data and contextual information will serve as basis for future pooling of data and modelling of worker exposure.

Worker perspectives on improving occupational health and safety using wearable sensors: a cross-sectional survey.

Workplace exposure is an important source of ill health. The use of wearable sensors and sensing technologies may help improve and maintain worker health, safety, and wellbeing. Input from workers should inform the integration of these sensors into workplaces. We developed an online survey to understand the acceptability of wearable sensor technologies for occupational health and safety (OSH) management. The survey was disseminated to members of OSH-related organizations, mainly in the United Kingdom and the Netherlands. There were 158 respondents, with over half (n = 91, 58%) reporting current use of wearable sensors, including physical hazards (n = 57, 36%), air quality (n = 53, 34%), and location tracking (n = 36, 23%), although this prevalence likely also captures traditional monitoring equipment. There were no clear distinctions in wearable sensor use between the reported demographic and occupational characteristics, with the exception that hygienists were more likely than non-hygienists (e.g. safety professionals) to use wearable sensors (66% versus 34%). Overall, there was an interest in how sensors can help OSH professionals understand patterns of exposure and improve exposure management practices. Some wariness was expressed primarily around environmental and physical constraints, the quality of the data, and privacy concerns. This survey identified a need to better identify occupational situations that would benefit from wearable sensors and to evaluate existing devices that could be used for occupational hygiene. Further, this work underscores the importance of clearly defining "sensor" according to the occupational setting and context.

Supporting the working life exposome: Annotating occupational exposure for enhanced literature search.

An individual's likelihood of developing non-communicable diseases is often influenced by the types, intensities and duration of exposures at work. Job exposure matrices provide exposure estimates associated with different occupations. However, due to their time-consuming expert curation process, job exposure matrices currently cover only a subset of possible workplace exposures and may not be regularly updated. Scientific literature articles describing exposure studies provide important supporting evidence for developing and updating job exposure matrices, since they report on exposures in a variety of occupational scenarios. However, the constant growth of scientific literature is increasing the challenges of efficiently identifying relevant articles and important content within them. Natural language processing methods emulate the human process of reading and understanding texts, but in a fraction of the time. Such methods can increase the efficiency of both finding relevant documents and pinpointing specific information within them, which could streamline the process of developing and updating job exposure matrices. Named entity recognition is a fundamental natural language processing method for language understanding, which automatically identifies mentions of domain-specific concepts (named entities) in documents, e.g., exposures, occupations and job tasks. State-of-the-art machine learning models typically use evidence from an annotated corpus, i.e., a set of documents in which named entities are manually marked up (annotated) by experts, to learn how to detect named entities automatically in new documents. We have developed a novel annotated corpus of scientific articles to support machine learning based named entity recognition relevant to occupational substance exposures. Through incremental refinements to the annotation process, we demonstrate that expert annotators can attain high levels of agreement, and that the corpus can be used to train high-performance named entity recognition models. The corpus thus constitutes an important foundation for the wider development of natural language processing tools to support the study of occupational exposures.

Limited Health Risks in Performing Drug Reconstitution and Handling Tasks in Pharmacies-Results of an Occupational Risk Assessment Study.

OBJECTIVE: Some drugs need processing before they can be administered or dispensed. We measured airborne exposure of pharmacy staff to small particles when performing these tasks. METHODS: Reconstitution of powdered drugs in vials; crushing, splitting, and counting of tablets; and opening of capsules, using different ventilation strategies, were investigated in five pharmacies after in a worst-case approach. Airborne particulate matter was determined for a range of particles sizes. RESULTS: Mean particle concentrations ranged from not detectable to 1.03 µg/m 3 (<1 µm) and 589.7 µg/m 3 (<10 µm). Dust exhaust made tasks safer. Most hazardous was pouring out tablets from a bulk supply, and least hazardous was reconstitution of a powder for injection. CONCLUSIONS: Occupational exposure during routine handling of drugs can occur, but the risks vary greatly with the nature and duration of the tasks.

Exposure Monitoring Strategies for Applying Low-Cost PM Sensors to Assess Flour Dust in Industrial Bakeries.

Low-cost particulate matter (PM) sensors provide new methods for monitoring occupational exposure to hazardous substances, such as flour dust. These devices have many possible benefits, but much remains unknown about their performance for different exposure monitoring strategies in the workplace. We explored the performance of PM sensors for four different monitoring strategies (time-weighted average and high time resolution, each quantitative and semi-quantitative) for assessing occupational exposure using low-cost PM sensors in a field study in the industrial bakery sector. Measurements were collected using four types of sensor (PATS+, Isensit, Airbeam2, and Munisense) and two reference devices (respirable gravimetric samplers and an established time-resolved device) at two large-scale bakeries, spread over 11 participants and 6 measurement days. Average PM2.5 concentrations of the low-cost sensors were compared with gravimetric respirable concentrations for 8-h shift periods and 1-min PM2.5 concentrations of the low-cost sensors were compared with time-resolved PM2.5 data from the reference device (quantitative monitoring strategy). Low-cost sensors were also ranked in terms of exposure for 8-h shifts and for 15-min periods with a shift (semi-quantitative monitoring strategy). Environmental factors and methodological variables, which can affect sensor performance, were investigated. Semi-quantitative monitoring strategies only showed more accurate results compared with quantitative strategies when these were based on shift-average exposures. The main factors that influenced sensor performance were the type of placement (positioning the devices stationary versus personal) and the company or workstation where measurements were collected. Together, these findings provide an overview of common strengths and drawbacks of low-cost sensors and different ways these can be applied in the workplace. This can be used as a starting point for further investigations and the development of guidance documents and data analysis methods.

Applying the exposome concept to working life health: The EU EPHOR project.

Exposures at work have a major impact on noncommunicable diseases (NCDs). Current risk reduction policies and strategies are informed by existing scientific evidence, which is limited due to the challenges of studying the complex relationship between exposure at work and outside work and health. We define the working life exposome as all occupational and related nonoccupational exposures. The latter includes nonoccupational exposures that may be directly or indirectly influenced by or interact with the working life of the individual in their relation to health. The Exposome Project for Health and Occupational Research aims to advance knowledge on the complex working life exposures in relation to disease beyond the single high exposure-single health outcome paradigm, mapping and relating interrelated exposures to inherent biological pathways, key body functions, and health. This will be achieved by combining (1) large-scale harmonization and pooling of existing European cohorts systematically looking at multiple exposures and diseases, with (2) the collection of new high-resolution external and internal exposure data. Methods and tools to characterize the working life exposome will be developed and applied, including sensors, wearables, a harmonized job exposure matrix (EuroJEM), noninvasive biomonitoring, omics, data mining, and (bio)statistics. The toolbox of developed methods and knowledge will be made available to policy makers, occupational health practitioners, and scientists. Advanced knowledge on working life exposures in relation to NCDs will serve as a basis for evidence-based and cost-effective preventive policies and actions. The toolbox will also enable future scientists to further expand the working life exposome knowledge base.

Ethics and Privacy Considerations Before Deploying Sensor Technologies for Exposure Assessment in the Workplace: Results of a Structured Discussion Amongst Dutch Stakeholders.

Will sensor-based exposure assessment be the future in workplace settings? Static instruments with embedded sensors are already applied to monitor levels of dangerous substances-in the context of acute health effects-at critical locations. However, with wearable, lightweight, miniaturized (low-cost) sensors developing quickly, much more is possible with sensors in relation to exposure assessment. Sensors can be applied in the work environment, on machines, or on employees and may include sensors that measure chemical exposures, but also sensors or other technologies that collect contextual information to support the exposure measurements. Like every technology it also has downsides. Sensors collect data on individuals that, depending on the purpose, need to be shared with others (e.g. health, safety and environment manager). One can imagine that people are afraid of misuse. To explore possible ethical and privacy issues that may come along with the introduction of sensors in the workplace, we organized a workshop with stakeholders (n = 32) to discuss three possible sensor-based scenarios in a structured way around five themes: purpose, efficacy, intrusiveness, proportionality, and fairness. The main conclusion of the discussions was that stakeholders currently see benefits in using sensors for applied targeted studies (short periods, clear reasons). In order to find acceptance for the implementation of sensors, all individuals affected by the sensors or its data need to be involved in the decisions on the purpose and application of sensors. Possible negative side effects need to be discussed and addressed. Continuous sensor-based monitoring of workers currently appears to be a bridge too far for the participants of this workshop.

Stakeholders' Perceptions of Environmental and Public Health Risks Associated with Hydrocarbon Activities in and around the Vasilikos Energy Center, Cyprus.

The Vasilikos Energy Center (VEC) is a large hydrocarbon industrial hub actively operating in Cyprus. There is strong public interest by the communities surrounding VEC to engage with all stakeholders towards the sustainable development of hydrocarbon in the region. The methodological framework of the exposome concept would allow for the holistic identification of all relevant environmental exposures by engaging the most relevant stakeholders in industrially contaminated sites. The main objectives of this study were to: (i) evaluate the stakeholders' perceptions of the environmental and public health risks and recommended actions associated with the VEC hydrocarbon activities, and (ii) assess the stakeholders' understanding and interest towards exposome-based technologies for use in oil and gas applications. Methods: Six major groups of stakeholders were identified: local authorities, small-medium industries (SMIs) (including multi-national companies), small-medium enterprises (SMEs), academia/professional associations, government, and the general public residing in the communities surrounding the VEC. During 2019-2021, a suite of stakeholder engagement initiatives was deployed, including semi-structured interviews (n = 32), a community survey for the general public (n = 309), technical meetings, and workshops (n = 4). Results from the semi-structured interviews, technical meetings and workshops were analyzed through thematic analysis and results from the community survey were analyzed using descriptive statistics. Results: Almost all stakeholders expressed the need for the implementation of a systematic health monitoring system for the VEC broader area and its surrounding residential communities, including frequent measurements of air pollutant emissions. Moreover, stricter policies by the government about licensing and monitoring of hydrocarbon activities and proper communication to the public and the mass media emerged as important needs. The exposome concept was not practiced by the SMEs, but SMIs showed willingness to use it in the future as part of their research and development activities. Conclusions: The sustainable development of hydrocarbon exploitation and processing prospects for Cyprus involves the VEC. Continuous and active collaboration and mutual feedback among all stakeholders involved with the VEC is essential, as this may allow future environmental and occupational health initiatives to be formalized.

A Scoping Review of Technologies and Their Applicability for Exposome-Based Risk Assessment in the Oil and Gas Industry.

INTRODUCTION: Oil and gas workers have been shown to be at increased risk of chronic diseases including cancer, asthma, chronic obstructive pulmonary disease, and hearing loss, among others. Technological advances may be used to assess the external (e.g. personal sensors, smartphone apps and online platforms, exposure models) and internal exposome (e.g. physiologically based kinetic modeling (PBK), biomonitoring, omics), offering numerous possibilities for chronic disease prevention strategies and risk management measures. The objective of this study was to review the literature on these technologies, by focusing on: (i) evaluating their applicability for exposome research in the oil and gas industry, and (ii) identifying key challenges that may hamper the successful application of such technologies in the oil and gas industry. METHOD: A scoping review was conducted by identifying peer-reviewed literature with searches in MEDLINE/PubMed and SciVerse Scopus. Two assessors trained on the search strategy screened retrieved articles on title and abstract. The inclusion criteria used for this review were: application of the aforementioned technologies at a workplace in the oil and gas industry or, application of these technologies for an exposure relevant to the oil and gas industry but in another occupational sector, English language and publication period 2005-end of 2019. RESULTS: In total, 72 articles were included in this scoping review with most articles focused on omics and bioinformatics (N = 22), followed by biomonitoring and biomarkers (N = 20), external exposure modeling (N = 11), PBK modeling (N = 10), and personal sensors (N = 9). Several studies were identified in the oil and gas industry on the application of PBK models and biomarkers, mainly focusing on workers exposed to benzene. The application of personal sensors, new types of exposure models, and omics technology are still in their infancy with respect to the oil and gas industry. Nevertheless, applications of these technologies in other occupational sectors showed the potential for application in this sector. DISCUSSION AND CONCLUSION: New exposome technologies offer great promise for personal monitoring of workers in the oil and gas industry, but more applied research is needed in collaboration with the industry. Current challenges hindering a successful application of such technologies include (i) the technological readiness of sensors, (ii) the availability of data, (iii) the absence of standardized and validated methods, and (iv) the need for new study designs to study the development of disease during working life.

Future Prospects of Occupational Exposure Modelling of Substances in the Context of Time-Resolved Sensor Data.

This commentary explores the use of high-resolution data from new, miniature sensors to enrich models that predict exposures to chemical substances in the workplace. To optimally apply these sensors, one can expect an increased need for new models that will facilitate the interpretation and extrapolation of the acquired time-resolved data. We identified three key modelling approaches in the context of sensor data, namely (i) enrichment of existing time-integrated exposure models, (ii) (new) high-resolution (in time and space) empirical models, and (iii) new 'occupational dispersion' models. Each approach was evaluated in terms of their application in research, practice, and for policy purposes. It is expected that substance-specific sensor data will have the potential to transform workplace modelling by re-calibrating, refining, and validating existing (time-integrated) models. An increased shift towards 'sensor-driven' models is expected. It will allow for high-resolution modelling in time and space to identify peak exposures and will be beneficial for more individualized exposure assessment and real-time risk management. New 'occupational dispersion models' such as interpolation, computational fluid dynamic models, and assimilation techniques, together with sensor data, will be specifically useful. These techniques can be applied to develop site-specific concentration maps which calculate personal exposures and mitigate worker exposure through early warning systems, source finding and improved control design and control strategies. Critical development and investment needs for sensor data linked to (new) model development were identified such as (i) the generation of more sensor data with reliable sensor technologies (achieved by improved specificity, sensitivity, and accuracy of sensors), (ii) investing in statistical and new model developments, (iii) ensuring that we comply with privacy and security issues of concern, and (iv) acceptance by relevant target groups (such as employers and employees) and stimulation of these new technologies by policymakers and technology developers.

Exploring the Effects of Environmental Factors on the Development of 0-4-Year Old Children in The Netherlands.

Air pollution, noise, and green space are important environmental exposures, having been linked to a variety of specific health outcomes. However, there are few studies addressing overall early life development. To assess their effects, associations between developmental milestones for a large population of 0-4-year old children in The Netherlands and environmental exposures were explored. Developmental milestones and background characteristics were provided by Preventive Child Health Care (PCHC) and supplemented with data from Statistics Netherlands. Milestones were summarized and standardized into an aggregate score measuring global development. Four age groups were selected. Environmental exposures were assigned to geocoded addresses using publicly available maps for PM2.5, PM10, PMcoarse, NO2, EC, road traffic noise, and green space. Associations were investigated using single and multiple-exposure logistic regression models. 43,916 PCHC visits by 29,524 children were available. No consistent associations were found for air pollution and road traffic noise. Green space was positively associated in single and multiple-exposure models although it was not significant in all age groups (OR 1.01 (0.95; 1.08) (1 year) to 1.07 (1.01; 1.14) (2 years)). No consistent associations were found between air pollution, road traffic noise, and global child development. A positive association of green space was indicated.

Increased telomere length and mtDNA copy number induced by multi-walled carbon nanotube exposure in the workplace.

Carbon nanotubes (CNTs) except MWCNT-7 have been classified as Group 3 ["Not classifiable as to its carcinogenicity to humans"] by the IARC. Despite considerable mechanistic evidence in vitro/in vivo, the classification highlights a general lack of data, especially among humans. In our previous study, we reported epigenetic changes in the MWCNT exposed workers. Here, we evaluated whether MWCNT can also cause alterations in aging related features including relative telomere length (TL) and/or mitochondrial copy number (mtDNAcn). Relative TL and mtDNAcn were measured on extracted DNA from peripheral blood from MWCNT exposed workers (N = 24) and non-exposed controls (N = 43) using a qPCR method. A higher mtDNAcn and longer TL were observed in MWCNT exposed workers when compared to controls. Independent of age, sex, smoking behavior, alcohol consumption and BMI, MWCNT-exposure was associated with an 18.30 % increase in blood TL (95 % CI: 7.15-30.62 %; p = 0.001) and 35.21 % increase in mtDNAcn (95 % CI: 19.12-53.46 %). Our results suggest that exposure to MWCNT can induce an increase in the mtDNAcn and TL; however, the mechanistic basis or consequence of such change requires further experimental studies.

Exploring Evaluation Variables for Low-Cost Particulate Matter Monitors to Assess Occupational Exposure.

(1) Background: Small, lightweight, low-cost optical particulate matter (PM) monitors are becoming popular in the field of occupational exposure monitoring, because these devices allow for real-time static measurements to be collected at multiple locations throughout a work site as well as being used as wearables providing personal exposure estimates. Prior to deployment, devices should be evaluated to optimize and quantify measurement accuracy. However, this can turn out to be difficult, as no standardized methods are yet available and different deployments may require different evaluation procedures. To gain insight in the relevance of different variables that may affect the monitor readings, six PM monitors were selected based on current availability and evaluated in the laboratory; (2) Methods: Existing strategies that were judged appropriate for the evaluation of PM monitors were reviewed and seven evaluation variables were selected, namely the type of dust, within- and between-device variations, nature of the power supply, temperature, relative humidity, and exposure pattern (peak and constant). Each variable was tested and analyzed individually and, if found to affect the readings significantly, included in a final correction model specific to each monitor. Finally, the accuracy for each monitor after correction was calculated; (3) Results: The reference materials and exposure patterns were found to be main factors needing correction for most monitors. One PM monitor was found to be sufficiently accurate at concentrations up to 2000 µg/m3 PM2.5, with other monitors appropriate at lower concentrations. The average accuracy increased by up to three-fold compared to when the correction model did not include evaluation variables; (4) Conclusions: Laboratory evaluation and readings correction can greatly increase the accuracy of PM monitors and set boundaries for appropriate use. However, this requires identifying the relevant evaluation variables, which are heavily reliant on how the monitors are used in the workplace. This, together with the lack of current consensus on standardized procedures, shows the need for harmonized PM monitor evaluation methods for occupational exposure monitoring.