A template wizard for the cocreation of machine-readable data-reporting to harmonize the evaluation of (nano)materials.

Making research data findable, accessible, interoperable and reusable (FAIR) is typically hampered by a lack of skills in technical aspects of data management by data generators and a lack of resources. We developed a Template Wizard for researchers to easily create templates suitable for consistently capturing data and metadata from their experiments. The templates are easy to use and enable the compilation of machine-readable metadata to accompany data generation and align them to existing community standards and databases, such as eNanoMapper, streamlining the adoption of the FAIR principles. These templates are citable objects and are available as online tools. The Template Wizard is designed to be user friendly and facilitates using and reusing existing templates for new projects or project extensions. The wizard is accompanied by an online template validator, which allows self-evaluation of the template (to ensure mapping to the data schema and machine readability of the captured data) and transformation by an open-source parser into machine-readable formats, compliant with the FAIR principles. The templates are based on extensive collective experience in nanosafety data collection and include over 60 harmonized data entry templates for physicochemical characterization and hazard assessment (cell viability, genotoxicity, environmental organism dose-response tests, omics), as well as exposure and release studies. The templates are generalizable across fields and have already been extended and adapted for microplastics and advanced materials research. The harmonized templates improve the reliability of interlaboratory comparisons, data reuse and meta-analyses and can facilitate the safety evaluation and regulation process for (nano) materials.

Development of handling energy factors for use of dustiness data in exposure assessment modelling.

Several exposure assessment models use dustiness as an input parameter for scaling or estimating exposure during powder handling. Use of different dustiness methods will result in considerable differences in the dustiness values as they are based on different emission generation principles. EN17199:2019 offers 4 different dustiness test methods considering different dust release scenarios (e.g. powder pouring, mixing and gentle agitation, and vibration). Conceptually, the dustiness value by a given method can be multiplied with a scenario-specific modifier, called a handling energy factor (Hi), that allows conversion of a dustiness value to a release constant. Therefore, a Hi, scaling the effective mechanical energy in the process to the energy supplied in the specific dustiness test, needs to be applied. To improve the accuracy in predictive exposure modelling, we derived experimental Hi to be used in exposure algorithms considering both the mass- and number-based dust release fraction determined by the EN17199-3 continuous drop (CD) and the EN17199-4 small rotating drum (SRD) test methods. Three materials were used to evaluate the relationship between dustiness and dust levels during pouring powder from different heights in a controlled environment. The results showed increasing scatter and difference between the Hi derived for the 2 test methods with increasing pouring height. Nearly all the Hi values obtained for both SRD and CD were <1 indicating that the dustiness tests involved more energy input than the simulated pouring activity and consequently de-agglomeration and dust generation were higher. This effect was most pronounced in CD method showing that SRD mechanistically resembles more closely the powder pouring.

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.

Historical Asbestos Measurements in Denmark-A National Database.

OBJECTIVES: Due to the long lag-time for health outcomes, historical asbestos exposure measurements are valuable to support assessments of associated occupational health effects, and also to assess time trends and effects of preventive measures. METHODS: Different sources of stored data were collated, assessed and refined to create a harmonized database on historical asbestos fibre concentrations measured in specific work tasks and different industries. The final database contains 9236 asbestos measurements from Danish workplaces collected from 1971 to 1997. RESULTS: The geometric mean of asbestos concentrations in different occupations and tasks ranged from 0.003 to 35 fibres cm-3. Highest concentrations were registered during handling of asbestos products in the construction services during the period 1981-1997. Although all the measured asbestos exposures without the use of respiratory equipment by the worker in the period of 1971-1997 exceeded the current 8-h time-weighted average exposure limit of 0.1 fibres cm-3, the majority of samples collected in the earlier period of 1971 to 1980 did not exceed the exposure limit of 2 fibres cm-3, which was in place at the time. All exposure data obtained from 1980 and onwards were found to be one seventh of the mean fibre concentrations in the previous measurement period. The impact of time shows a clear exponentially decreasing trend-line. CONCLUSIONS: Despite limitations in coverage of different occupations and tasks associated with the inventoried historical asbestos measurements, the data are helpful to identify specific work scenarios within an industry, where relatively high asbestos exposure levels may still occur or have occurred from 1971 to 1997.

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.

Occupational Exposure and Environmental Release: The Case Study of Pouring TiO2 and Filler Materials for Paint Production.

Pulmonary exposure to micro- and nanoscaled particles has been widely linked to adverse health effects and high concentrations of respirable particles are expected to occur within and around many industrial settings. In this study, a field-measurement campaign was performed at an industrial manufacturer, during the production of paints. Spatial and personal measurements were conducted and results were used to estimate the mass flows in the facility and the airborne particle release to the outdoor environment. Airborne particle number concentration (1 × 103-1.0 × 104 cm-3), respirable mass (0.06-0.6 mg m-3), and PM10 (0.3-6.5 mg m-3) were measured during pouring activities. In overall; emissions from pouring activities were found to be dominated by coarser particles >300 nm. Even though the raw materials were not identified as nanomaterials by the manufacturers, handling of TiO2 and clays resulted in release of nanometric particles to both workplace air and outdoor environment, which was confirmed by TEM analysis of indoor and stack emission samples. During the measurement period, none of the existing exposure limits in force were exceeded. Particle release to the outdoor environment varied from 6 to 20 g ton-1 at concentrations between 0.6 and 9.7 mg m-3 of total suspended dust depending on the powder. The estimated release of TiO2 to outdoors was 0.9 kg per year. Particle release to the environment is not expected to cause any major impact due to atmospheric dilution.

Importance of the number emission factor of combustion-generated aerosols from nano-enabled products.

Accidental or open waste burning and incineration of nano-enabled products (NEPs) might lead to the release of incidental aerosols in the nano size range into the environment resulting in harmful effects on humans. We have investigated combustion-generated aerosol release during accidental burning for several real-life NEPs such as paints with silica (SiO2) and spruce wood panels containing SiO2 and Fe2O3 nanomaterials (NMs), paper with SiO2 and Fe2O3 NMs and polymeric composites with CuPhthtalocyanine NMs in poly lactic acid (PLA), polyamide 6 (PA6) and thermoplastic pol-urethane (TPU) matrices. Chemical compositions, aerosols number emission factors (nefs) and concentrations of the signature elements of the NMs of the combustion-generated aerosols were investigated. In addition, the residual ash was analyzed. The outcomes of this study shed light on how NM and matrix types influenced the properties of the released aerosols. Based on our results it was established that the combustion-generated aerosols were composed of transformed NMs with modified physical-chemical characteristics compared to the pristine NMs. In addition to aerosols with transformed NMs, there were also particles due to incomplete combustion of the matrix. Types of the pristine NMs and matrices affected the characteristics of the released aerosols. Since the effect of the aerosols is related to the inhaled aerosol number concentration, the nef is an important parameter. Our results showed that the nefs in the size range of 5.6 to 560 nm depended strongly on the type of combusted NEP, which indicated that the NEPs could be categorized according to their potential to release aerosols in this size range when they were burnt. The generated release data facilitate the assessment of human and environmental exposure and the associated risk assessment of combustion-generated aerosols from NEPs.

Health effects of exposure to diesel exhaust in diesel-powered trains.

BACKGROUND: Short-term controlled exposure to diesel exhaust (DE) in chamber studies have shown mixed results on lung and systemic effects. There is a paucity of studies on well-characterized real-life DE exposure in humans. In the present study, 29 healthy volunteers were exposed to DE while sitting as passengers in diesel-powered trains. Exposure in electric trains was used as control scenario. Each train scenario consisted of three consecutive days (6 h/day) ending with biomarker samplings. RESULTS: Combustion-derived air pollutants were considerably higher in the passenger carriages of diesel trains compared with electric trains. The concentrations of black carbon and ultrafine particles were 8.5 µg/m3 and 1.2-1.8 × 105 particles/cm3 higher, respectively, in diesel as compared to electric trains. Net increases of NOx and NO2 concentrations were 317 µg/m3 and 36 µg/m3. Exposure to DE was associated with reduced lung function and increased levels of DNA strand breaks in peripheral blood mononuclear cells (PBMCs), whereas there were unaltered levels of oxidatively damaged DNA, soluble cell adhesion molecules, acute phase proteins in blood and urinary excretion of metabolites of polycyclic aromatic hydrocarbons. Also the microvascular function was unaltered. An increase in the low frequency of heart rate variability measures was observed, whereas time-domain measures were unaltered. CONCLUSION: Exposure to DE inside diesel-powered trains for 3 days was associated with reduced lung function and systemic effects in terms of altered heart rate variability and increased levels of DNA strand breaks in PBMCs compared with electric trains. TRIAL REGISTRATION: ClinicalTrials.Gov ( NCT03104387 ). Registered on March 23rd 2017.

Exposure to Air Pollution inside Electric and Diesel-Powered Passenger Trains.

Diesel-powered trains are used worldwide for passenger transport. The present study aimed to assess air pollution concentrations in passenger cars from diesel and electric trains. Personal exposure monitoring (6-7 h per day) was carried out for 49 days on diesel and 22 days on electric trains. Diesel trains had higher concentrations of all the assessed air pollution components. Average increases (and fold differences) in passenger cars of diesel trains compared with electric trains were for ultrafine particles 212 000 particles/cm3 (35-fold), black carbon 8.3 µg/m3 (6-fold), NO x 316 µg/m3 (8-fold), NO2 38 µg/m3 (3-fold), PM2.5 34 µg/m3 (2-fold), and benzo( a)pyrene 0.14 ng/m3 (6-fold). From time-series data, the pull and push movement modes, the engine in use, and the distance to the locomotive influenced the concentrations inside the diesel trains. In conclusion, concentrations of all air pollutants were significantly elevated in passenger cars in diesel trains compared to electric trains.

Source specific exposure and risk assessment for indoor aerosols.

Poor air quality is a leading contributor to the global disease burden and total number of deaths worldwide. Humans spend most of their time in built environments where the majority of the inhalation exposure occurs. Indoor Air Quality (IAQ) is challenged by outdoor air pollution entering indoors through ventilation and infiltration and by indoor emission sources. The aim of this study was to understand the current knowledge level and gaps regarding effective approaches to improve IAQ. Emission regulations currently focus on outdoor emissions, whereas quantitative understanding of emissions from indoor sources is generally lacking. Therefore, specific indoor sources need to be identified, characterized, and quantified according to their environmental and human health impact. The emission sources should be stored in terms of relevant metrics and statistics in an easily accessible format that is applicable for source specific exposure assessment by using mathematical mass balance modelings. This forms a foundation for comprehensive risk assessment and efficient interventions. For such a general exposure assessment model we need 1) systematic methods for indoor aerosol emission source assessment, 2) source emission documentation in terms of relevant a) aerosol metrics and b) biological metrics, 3) default model parameterization for predictive exposure modeling, 4) other needs related to aerosol characterization techniques and modeling methods. Such a general exposure assessment model can be applicable for private, public, and occupational indoor exposure assessment, making it a valuable tool for public health professionals, product safety designers, industrial hygienists, building scientists, and environmental consultants working in the field of IAQ and health.

Dip coating of air purifier ceramic honeycombs with photocatalytic TiO2 nanoparticles: A case study for occupational exposure.

Nanoscale TiO2 (nTiO2) is manufactured in high volumes and is of potential concern in occupational health. Here, we measured workers exposure levels while ceramic honeycombs were dip coated with liquid photoactive nanoparticle suspension and dried with an air blade. The measured nTiO2 concentration levels were used to assess process specific emission rates using a convolution theorem and to calculate inhalation dose rates of deposited nTiO2 particles. Dip coating did not result in detectable release of particles but air blade drying released fine-sized TiO2 and nTiO2 particles. nTiO2 was found in pure nTiO2 agglomerates and as individual particles deposited onto background particles. Total particle emission rates were 420×109min-1, 1.33×109µm2min-1, and 3.5mgmin-1 respirable mass. During a continued repeated process, the average exposure level was 2.5×104cm-3, 30.3µm2cm-3, <116µgm-3 for particulate matter. The TiO2 average exposure level was 4.2µgm-3, which is well below the maximum recommended exposure limit of 300µgm-3 for nTiO2 proposed by the US National Institute for Occupational Safety and Health. During an 8-hour exposure, the observed concentrations would result in a lung deposited surface area of 4.3×10-3cm2g-1 of lung tissue and 13µg of TiO2 to the trachea-bronchi, and alveolar regions. The dose levels were well below the one hundredth of the no observed effect level (NOEL1/100) of 0.11cm2g-1 for granular biodurable particles and a daily no significant risk dose level of 44µgday-1. These emission rates can be used in a mass flow model to predict the impact of process emissions on personal and environmental exposure levels.

Characterization of exposure to carbon nanotubes in an industrial setting.

While production and use of carbon nanotubes (CNTs) is increasing, workers exposure to CNTs is expected to increase as well, with inhalation being potentially the main pathway for uptake. However, there have been few studies reporting results about workers' personal exposure to CNTs. In this study, worker exposure to single-walled CNTs (SWCNTs) during the production of conductive films in a modern up-scaling factory was assessed. Particulate matter concentrations (2.5-10 µm) and concentrations of CO and CO2 were monitored by using real-time instruments. Workers' exposure levels to SWCNTs were qualitatively estimated by analyzing particle samples by transmission electron microscopy (TEM). TEM samples identified high aspect ratio (length/width > 500) SWCNTs in workplace air. SWCNT concentrations estimated from micrographs varied during normal operation, reactor use without local exhaust ventilation (LEV), and cleaning between 1.7×10(-3), 5.6 and 6.0×10(-3) SWCNT cm(-3), respectively. However, during cleaning it was unclear whether the SWCNTs originated from the cleaning itself or from other reactor openings. We were unable to quantify the SWCNT emissions with online particle instrumentation due to the SWCNT low concentrations compared to background particle concentrations, which were on average 2.6±1.1×10(3)cm(-3). However, CO concentrations were verified as a good indicator of fugitive emissions of SWCNTs. During normal operation, exposure levels were well below proposed limit values (1.0×10(-2) fibers cm(-3) and 1 µg m(-3)) when LEV was used. Based on the results in this study, the analysis of TEM grids seems to be the only direct method to detect SWCNTs in workplace air.