Assessment of exposure determinants and exposure levels by using stationary concentration measurements and a probabilistic near-field/far-field exposure model

A generic approach to estimate airborne concentrations of substances released by indoor spray processes using a deterministic 2-box model

Sprays are used both in workplace and consumer settings. Although spraying has advantages, such as uniform distribution of substances on surfaces in a highly efficient manner, it is often associated with a high inhalation burden. For an adequate risk assessment, this exposure has to be reliably quantified. Exposure models of varying complexity are available, which are applicable to spray applications. However, a need for improvement has been identified. In this contribution, a simple 2-box approach is suggested for the assessment of the time-weighted averaged exposure concentration (TWA) using a minimum of input data. At the moment, the model is restricted to binary spray liquids composed of a non-volatile fraction and volatile solvents. The model output can be refined by introducing correction factors based on the classification and categorization of two key parameters, the droplet size class and the vapor pressure class of the solvent, or by using a data set of experimentally determined airborne release fractions related to the used spray equipment. A comparison of model results with measured data collected at real workplaces showed that this simple model based on readily available input parameters is very useful for screening purposes. The generic 2-box spray model without refinement overestimates the measurements of the considered scenarios in approximately 50% of the cases by more than a factor of 100. The generic 2-box model performs better for room spraying than for surface spraying, as the airborne fraction in the latter case is clearly overestimated. This conservatism of the prediction was significantly reduced when correction factors or experimentally determined airborne release fractions were used in addition to the generic input parameters. The resulting predictions still overestimate the exposure (ratio tool estimate to measured TWA > 10) or they are accurate (ratio 0.5-10). If the available information on boundary conditions (application type, equipment) does not justify the usage of airborne release fraction, room spraying should be used resulting in the highest exposure estimate. The model scope may be extended to (semi)volatile substances. However, acceptance may be compromised by the limited availability of measured data for this group of substances and thus may have limited potency to evaluate the model prediction.

Use of the dustiness index in combination with the handling energy factor for exposure modelling of nanomaterials

The use of modelling tools in the occupational hygiene community has increased in the last years to comply with the different existing regulations. However, limitations still exist mainly due to the difficulty to obtain certain key parameters such as the emission rate, which in the case of powder handling can be estimated using the dustiness index (DI). The goal of this work is to explore the applicability and usability of the DI for emission source characterization and occupational exposure prediction to particles during nanomaterial powder handling. Modelling of occupational exposure concentrations of 13 case scenarios was performed using a two-box model as well as three nano-specific tools (Stoffenmanager nano, NanoSafer and GUIDEnano). The improvement of modelling performance by using a derived handling energy factor (H) was explored. Results show the usability of the DI for emission source characterization and respirable mass exposure modelling of powder handling scenarios of nanomaterials. A clear improvement in modelling outcome was obtained when using derived quartile-3 H factors with, 1) Pearson correlations of 0.88 vs. 0.52 (not using H), and 2) ratio of modelled/measured concentrations ranging from 0.9 to 10 in 75% cases vs. 16.7% of the cases when not using H. Particle number concentrations were generally underpredicted. Using the most conservative H values, predictions with ratios modelled/measured concentrations of 0.4-3.6 were obtained.

Effects of air pollution on telomere length: Evidence from in vitro to clinical studies

Air pollution remains the major environmental problem globally. There is extensive evidence showing that the variety of air pollutants from environmental and occupational exposures cause adverse effects to our health. The clinical symptoms of those effects may present at a late stage, so surveillance is difficult to manage. Several biomarkers have been used for the early detection of health issues following exposure to air pollution, including the use of telomere length which indicates cellular senescence in response to oxidative stress. Oxidative stress is one of the most plausible mechanisms associated with exposure to air pollutants. Some specific contexts including age groups, gender, ethnicity, occupations, and health conditions, showed significant alterations in telomere length after exposure to air pollutants. Several reports demonstrated both negative and positive associations between telomere length and air pollution, the studies using different concentrations and exposure times to air pollution on the study of telomere lengths. Surprisingly, some studies reported that low levels of exposure to air pollutants (lower than regulated levels) caused the alterations in telomere length. Those findings suggest that telomere length could be one of most practical biomarkers in air pollution surveillance. Therefore, this review aimed to summarize and discuss the relationship between telomere length and exposure to air pollution. The knowledge from this review will be beneficial for the planning of public health to reduce health problems in the general population, particularly in vulnerable people, who still live in areas with high air pollution.

Quantifying Emission Factors and Setting Conditions of Use According to ECHA Chapter R.14 for a Spray Process Designed for Nanocoatings—A Case Study

Spray coatings’ emissions impact to the environmental and occupational exposure were studied in a pilot-plant. Concentrations were measured inside the spray chamber and at the work room in Near-Field (NF) and Far-Field (FF) and mass flows were analyzed using a mechanistic model. The coating was performed in a ventilated chamber by spraying titanium dioxide doped with nitrogen (TiO2N) and silver capped by hydroxyethylcellulose (Ag-HEC) nanoparticles (NPs). Process emission rates to workplace, air, and outdoor air were characterized according to process parameters, which were used to assess emission factors. Full-scale production exposure potential was estimated under reasonable worst-case (RWC) conditions. The measured TiO2-N and Ag-HEC concentrations were 40.9 TiO2-μg/m3 and 0.4 Ag-μg/m3 at NF (total fraction). Under simulated RWC conditions with precautionary emission rate estimates, the worker’s 95th percentile 8-h exposure was ≤171 TiO2 and ≤1.9 Ag-μg/m3 (total fraction). Environmental emissions via local ventilation (LEV) exhaust were ca. 35 and 140 mg-NP/g-NP, for TiO2-N and Ag-HEC, respectively. Under current situation, the exposure was adequately controlled. However, under full scale production with continuous process workers exposure should be evaluated with personal sampling if recommended occupational exposure levels for nanosized TiO2 and Ag are followed for risk management.

ASINA Project: Towards a Methodological Data-Driven Sustainable and Safe-by-Design Approach for the Development of Nanomaterials

The novel chemical strategy for sustainability calls for a Sustainable and Safe-by-Design (SSbD) holistic approach to achieve protection of public health and the environment, industrial relevance, societal empowerment, and regulatory preparedness. Based on it, the ASINA project expands a data-driven Management Methodology (ASINA-SMM) capturing quality, safety, and sustainability criteria across the Nano-Enabled Products’ (NEPs) life cycle. We base the development of this methodology through value chains of highly representative classes of NEPs in the market, namely, (i) self-cleaning/air-purifying/antimicrobial coatings and (ii) nano-structured capsules delivering active phases in cosmetics. These NEPs improve environmental quality and human health/wellness and have innovative competence to industrial sectors such as healthcare, textiles, cosmetics, and medical devices. The purpose of this article is to visually exhibit and explain the ASINA approach, which allows identifying, combining, and addressing the following pillars: environmental impact, techno-economic performance, functionality, and human and environmental safety when developing novel NEPs, at an early stage. A metamodel supports the above by utilizing quality data collected throughout the NEPs’ life cycle, for maximization of functionality (to meet stakeholders needs) and nano-safety (regulatory obligations) and for the minimization of costs (to meet business requirements) and environmental impacts (to achieve sustainability). Furthermore, ASINA explores digitalization opportunities (digital twins) to speed the nano-industry translation into automatic progress towards economic, social, environmental, and governance sustainability.

Evaluation of One- and Two-Box Models as Particle Exposure Prediction Tools at Industrial Scale

One- and two-box models have been pointed out as useful tools for modelling indoor particle exposure. However, model performance still needs further testing if they are to be implemented as trustworthy tools for exposure assessment. The objective of this work is to evaluate the performance, applicability and reproducibility of one- and two-box models on real-world industrial scenarios. A study on filling of seven materials in three filling lines with different levels of energy and mitigation strategies was used. Inhalable and respirable mass concentrations were calculated with one- and two-box models. The continuous drop and rotating drum methods were used for emission rate calculation, and ranges from a one-at-a-time methodology were applied for local exhaust ventilation efficiency and inter-zonal air flows. When using both dustiness methods, large differences were observed for modelled inhalable concentrations but not for respirable, which showed the importance to study the linkage between dustiness and processes. Higher model accuracy (ratio modelled vs. measured concentrations 0.5-5) was obtained for the two- (87%) than the one-box model (53%). Large effects on modelled concentrations were seen when local exhausts ventilation and inter-zonal variations where parametrized in the models. However, a certain degree of variation (10-20%) seems acceptable, as similar conclusions are reached.

Data Shepherding in Nanotechnology. The Exposure Field Campaign Template

In this paper, we demonstrate the realization process of a pragmatic approach on developing a template for capturing field monitoring data in nanomanufacturing processes. The template serves the fundamental principles which make data scientifically Findable, Accessible, Interoperable and Reusable (FAIR principles), as well as encouraging individuals to reuse it. In our case, the data shepherds' (the guider of data) template creation workflow consists of the following steps: (1) Identify relevant stakeholders, (2) Distribute questionnaires to capture a general description of the data to be generated, (3) Understand the needs and requirements of each stakeholder, (4) Interactive simple communication with the stakeholders for variables/descriptors selection, and (5) Design of the template and annotation of descriptors. We provide an annotated template for capturing exposure field campaign monitoring data, and increase their interoperability, while comparing it with existing templates. This paper enables the data creators of exposure field campaign data to store data in a FAIR way and helps the scientific community, such as data shepherds, by avoiding extensive steps for template creation and by utilizing the pragmatic structure and/or the template proposed herein, in the case of a nanotechnology project (Anticipating Safety Issues at the Design of Nano Product Development, ASINA).