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

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.

Towards a surface metric to measure the dustiness of nanomaterial powders

The relevance of dustiness methods is increasingly recognized in the preliminary exposure evaluation of workers handling nanomaterials in powder form, and should also be transposed to the assessment of environmental risk in the future. The methods currently recommended in the European standards are mainly based on determining a mass-based dustiness index [mg kg^-1], whereas surface area is regularly put forward as a more appropriate determinant to assess the pulmonary toxicity of nanoparticles. In this study, we describe an operational methodology leading us to propose a surface metric to determine the dustiness index [m² kg^-1] of nanoparticulate matter. To this end, we demonstrate the equivalence between the external specific surface area of a nanopowder and that of its aerosol with five nanomaterials produced and used on an industrial scale, and covering a range of external specific surface areas from 35 to 230 m² g^-1. Compared to the conventional mass-based dustiness index, the surface-based dustiness index (1) is more discriminating, covering an additional order of magnitude, and (2) has an impact on the powder ranking with potential consequences on the preventive measures to be implemented. Finally, our proposal has the potential to be included in future revisions of European standards for workplace exposure and dustiness measurement, provided that further experimental results on surface-based dustiness indices support these preliminary data.

Risk assessment of consumer spray products using in vitro lung surfactant function inhibition, exposure modelling and chemical analysis

Consumer spray products release aerosols that can potentially be inhaled and reach the deep parts of the lungs. A thin layer of liquid, containing a mixture of proteins and lipids known as lung surfactant, coats the alveoli. Inhibition of lung surfactant function can lead to acute loss of lung function. We focused on two groups of spray products; 8 cleaning and 13 impregnation products, and in the context of risk assessment, used an in vitro method for assessing inhibition of lung surfactant function. Original spray-cans were used to generate aerosols to measure aerodynamic particle size distribution. We recreated a real-life exposure scenario to estimate the alveolar deposited dose. Most impregnation products inhibited lung surfactant function at the lowest aerosolization rate, whereas only two cleaning products inhibited function at the highest rates. We used inhibitory dose and estimated alveolar deposition to calculate the margin of safety (MoS). The MoS for the inhibitory products was ≤1 for the impregnation products, while much larger for the cleaning products (>880). This risk assessment focused on the risk of lung surfactant function disruption and provides knowledge on an endpoint of lung toxicity that is not investigated by the currently available OECD test guidelines.