Suchergebnisse

Abstract
Nanotechnology is a growing megatrend in industrial production and innovations. Many applications utilize engineered nanomaterials (ENMs) that are potentially released into the atmospheric environment, e.g., via direct stack emissions from production facilities, and may have adverse effects on human health and the environment. Previous modeling approaches have focused on large regional compartments, into which the released ENMs are evenly mixed. However, due to the localization of the ENM release and removal processes, potentially higher airborne concentrations and deposition fluxes are obtained around the production facilities. Therefore, we compare the ENM concentrations from a dispersion model to those from the uniformly mixed compartment approach. For realistic release scenarios, we based the modeling on the case study measurement data from two ENM handling facilities. In addition, we calculated the distances, at which 50% of the ENMs are deposited, serving as a physically relevant metric to separate the local scale from the regional scale, thus indicating the size of the high exposure and risk region near the facility. As a result, we suggest a local scale compartment to be implemented in the multicompartment nanomaterial exposure models. We also present a computational tool for local exposure assessment that could be included to regulatory guidance and existing risk governance networks. A related research article is currently under peer-review (Poikkimäki et al. 2022, submitted).

Abstract
This study aims at achieving a better picture of the spatial and temporal distribution of industrial pollutants in the working environment. We explore the utilization of this information in occupational hygiene practice by developing and building a low-cost sensor network in multiple real working environments. Sensor networks were installed in different scenarios: in- and outdoors of a steel factory and on a cruise ship's car deck. The stationary sensor networks are composed of multiple custom sensing nodes. Each node is equipped with various low-cost sensors to assess gaseous components, dust particles, temperature, and humidity. Additionally, measurements using validated traditional occupational hygiene methods and high end portable direct-reading instruments (DRIs) are performed stationary and mobile. Mobile devices carried by the workers in the breathing zone complement the measurements by the stationary sensor network. The results consist of evaluations carried out through combining the sensor data, contextual information and the results obtained with traditional occupational methods. Can this data fusion be used to assess exposure, and target risk management measures? In this work, we discuss the feasibility of the available sensors for industrial measurements and further explore the suitability of pollutant concentration maps for exposure assessment and for planning control measures.

Nanomaterial risk governance requires models to estimate the material flow, fate and transport as well as uptake/bioavailability, hazard and risk in the environment. This study assesses the fit of such available models to different stages during the innovation of nano-enabled products. Through stakeholder consultations, criteria were identified for each innovation stage from idea conception to market launch and monitoring. In total, 38 models were scored against 41 criteria concerning model features, applicability, resource demands and outcome parameters. A scoring scheme was developed to determine how the models fit the criteria of each innovation stage. For each model, the individual criteria scores were added, yielding an overall fit score to each innovation stage. Three criteria were critical to stakeholders and incorporated as multipliers in the scoring scheme; the required time/costs and level of expertise needed to use the model, and for risk assessment models only, the option to compare PEC and PNEC. Regulatory compliance was also identified as critical, but could not be incorporated, as a nanomaterial risk assessment framework has yet to be developed and adopted by legislators. In conclusion, the scoring approach underlined similar scoring profiles across stages within model categories. As most models are research tools designed for use by experts, their score generally increased for later stages where most resources and expertise are committed. In contrast, stakeholders need relatively simple models to identify potential hazards and risk management measures at early product development stages to ensure safe use of nanomaterials without costs and resource needs hindering innovation. ; acceptedVersion ; Peer reviewed

Nanomaterial risk governance requires models to estimate the material flow, fate and transport as well as uptake/bioavailability, hazard and risk in the environment. This study assesses the fit of such available models to different stages during the innovation of nano-enabled products. Through stakeholder consultations, criteria were identified for each innovation stage from idea conception to market launch and monitoring. In total, 38 models were scored against 41 criteria concerning model features, applicability, resource demands and outcome parameters. A scoring scheme was developed to determine how the models fit the criteria of each innovation stage. For each model, the individual criteria scores were added, yielding an overall fit score to each innovation stage. Three criteria were critical to stakeholders and incorporated as multipliers in the scoring scheme; the required time/costs and level of expertise needed to use the model, and for risk assessment models only, the option to compare PEC and PNEC. Regulatory compliance was also identified as critical, but could not be incorporated, as a nanomaterial risk assessment framework has yet to be developed and adopted by legislators. In conclusion, the scoring approach underlined similar scoring profiles across stages within model categories. As most models are research tools designed for use by experts, their score generally increased for later stages where most resources and expertise are committed. In contrast, stakeholders need relatively simple models to identify potential hazards and risk management measures at early product development stages to ensure safe use of nanomaterials without costs and resource needs hindering innovation.

Advanced material development, including at the nanoscale, comprises costly and complex challenges coupled to ensuring human and environmental safety. Governmental agencies regulating safety have announced interest toward acceptance of safety data generated under the collective term New Approach Methodologies (NAMs), as such technologies/approaches offer marked potential to progress the integration of safety testing measures during innovation from idea to product launch of nanomaterials. Divided in overall eight main categories, searchable databases for grouping and read across purposes, exposure assessment and modeling, in silico modeling of physicochemical structure and hazard data, in vitro high-throughput and high-content screening assays, dose-response assessments and modeling, analyses of biological processes and toxicity pathways, kinetics and dose extrapolation, consideration of relevant exposure levels and biomarker endpoints typify such useful NAMs. Their application generally agrees with articulated stakeholder needs for improvement of safety testing procedures. They further fit for inclusion and add value in nanomaterials risk assessment tools. Overall 37 of 50 evaluated NAMs and tiered workflows applying NAMs are recommended for considering safer-by-design innovation, including guidance to the selection of specific NAMs in the eight categories. An innovation funnel enriched with safety methods is ultimately proposed under the central aim of promoting rigorous nanomaterials innovation. ; acceptedVersion ; Peer reviewed