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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.

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.

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.

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.

Background/AimThe 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).MethodsWe 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.ResultsWe 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., ConclusionsWe 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.

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.

This review describes an evaluation of the effectiveness of Risk Management Measures (RMM) for nanomaterials in the workplace. Our aim was to review the effectiveness of workplace RMM for nanomaterials and to determine whether established effectiveness values of conventional chemical substances applied for modelling purposes should be adopted or revised based on available evidence. A literature review was conducted to collate nano-specific data on workplace RMM. Besides the quantitative efficacy values, the library was populated with important covariables such as the study design, measurement type, size of particles or agglomerates/aggregates, and metrics applied. In total 770 records were retrieved from 41 studies for three general types of RMM (engineering controls, respiratory equipment and skin protective equipment: gloves and clothing). Records were found for various sub-categories of the different types of RMM although the number of records for each was generally limited. Significant variation in efficacy values was observed within RMM categories while also considering the respective covariables. Based on a comparative evaluation with efficacy values applied for conventional substances, adapted efficacy values are proposed for various RMM sub-categories (e.g. containment, fume cupboards, FFP2 respirators). It is concluded that RMM efficacy data for nanomaterials are limited and often inconclusive to propose effectiveness values. This review also shed some light on the current knowledge gaps for nanomaterials related to RMM effectiveness (e.g. ventilated walk-in enclosures and clean rooms) and the challenges foreseen to derive reliable RMM efficacy values from aggregated data in the future.

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.

Fume hoods are one of the most common types of equipment applied to reduce the potential of particle exposure in laboratory environments. A number of previous studies have shown particle release during work with nanomaterials under fume hoods. Here, we assessed laboratory workers’ inhalation exposure during synthesis and handling of CuO, TiO2 and ZnO in a fume hood. In addition, we tested the capacity of a fume hood to prevent particle release to laboratory air during simulated spillage of different powders (silica fume, zirconia TZ-3Y and TiO2). Airborne particle concentrations were measured in near field, far field, and in the breathing zone of the worker. Handling CuO nanoparticles increased the concentration of small particles (

Exposure assessment for nano-objects, and their aggregates and agglomerates (NOAA), has evolved from explorative research toward more comprehensive exposure assessment, providing data to further develop currently used conservative control banding (CB) tools for risk assessment. This study aims to provide an overview of current knowledge on emission potential of NOAA across the occupational life cycle stages by a systematic review and subsequently use the results in a data analysis. Relevant parameters that influence emission were collected from peer-reviewed literature with a focus on the four source domains (SD) in the source-receptor conceptual framework for NOAA. To make the reviewed exposure data comparable, we applied an approach to normalize for workplace circumstances and measurement location, resulting in comparable "surrogate" emission levels. Finally, descriptive statistics were performed. During the synthesis of nanoparticles (SD1), mechanical reduction and gas phase synthesis resulted in the highest emission compared to wet chemistry and chemical vapor condensation. For the handling and transfer of bulk manufactured nanomaterial powders (SD2) the emission could be differentiated for five activity classes: (1) harvesting; (2) dumping; (3); mixing; (4) cleaning of a reactor; and (5) transferring. Additionally, SD2 was subdivided by the handled amount with cleaning further subdivided by energy level. Harvesting and dumping resulted in the highest emissions. Regarding processes with liquids (SD3b), it was possible to distinguish emissions for spraying (propellant gas, (high) pressure and pump), sonication and brushing/rolling. The highest emissions observed in SD3b were for propellant gas spraying and pressure spraying. The highest emissions for the handling of nano-articles (SD4) were found to nano-sized particles (including NOAA) for grinding. This study provides a valuable overview of emission assessments performed in the workplace during the occupational handling of NOAA. Analyses were made per source domain to derive emission levels which can be used for models to quantitatively predict the exposure.

The advent of the exposome concept, the advancement of mobile technology, sensors, and the “internet of things” bring exciting opportunities to exposure science. Smartphone apps, wireless devices, the downsizing of monitoring technologies, along with lower costs for such equipment makes it possible for various aspects of exposure to be measured more easily and frequently. We discuss possibilities and lay out several criteria for using smart technologies for external exposome studies. Smart technologies are evolving quickly, and while they provide great promise for advancing exposure science, many are still in developmental stages and their use in epidemiology and risk studies must be carefully considered. The most useable technologies for exposure studies at this time relate to gathering exposure-factor data, such as location and activities. Development of some environmental sensors (e.g., for some air pollutants, noise, UV) is moving towards making the use of these more reliable and accessible to research studies. The possibility of accessing such an unprecedented amount of personal data also comes with various limitations and challenges, which are discussed. The advantage of improving the collection of long term exposure factor data is that this can be combined with more “traditional” measurement data to model exposures to numerous environmental factors. © 2017 by the authors. Licensee MDPI, Basel, Switzerland.

Dustiness is not an intrinsic physically defined property of a powder, but the tendency of particles to become airborne in response to mechanical and/or aerodynamic stimuli. The present study considers a set of 10 physical properties to which the powder dustiness can be attributed. Through a preliminary investigation of a standardized continuous drop test scenario, we present first set of results on the varying degrees or weights of influence of these properties on the aerosolization tendency of powder particles. The inter-particle distance is found to be the most dominant property controlling the particle aerosolization, followed by the ability of powder particles to get electrostatically charged. We observe the kinetics involved during powder aerosolization to be governed by two ratios: drag force/cohesive force and drag force/gravitational force. The converging tendencies in these initial results indicate that these physical properties can be used to model dustiness of falling powder, which can eventually be used in risk assessment tools for an efficient exposure estimation of the powders.