Safe and Sustainable by Design-An Interdisciplinary Challenge for Future-Proof Chemistry.

Advanced materials (such as the TiO2 fibers shown) are important building blocks for a post-fossil circular economy that is fostered by the Horizon Europe research framework programme from 2021 to 2026. Rolf Packroff and Romy Marx outline how this increases the need for scientists in material development to address issues of safe and sustainable design, as well as interdisciplinary cooperation with experts in toxicology, exposure sciences, and chemicals regulation.

Risk Governance of Emerging Technologies Demonstrated in Terms of its Applicability to Nanomaterials.

Nanotechnologies have reached maturity and market penetration that require nano-specific changes in legislation and harmonization among legislation domains, such as the amendments to REACH for nanomaterials (NMs) which came into force in 2020. Thus, an assessment of the components and regulatory boundaries of NMs risk governance is timely, alongside related methods and tools, as part of the global efforts to optimise nanosafety and integrate it into product design processes, via Safe(r)-by-Design (SbD) concepts. This paper provides an overview of the state-of-the-art regarding risk governance of NMs and lays out the theoretical basis for the development and implementation of an effective, trustworthy and transparent risk governance framework for NMs. The proposed framework enables continuous integration of the evolving state of the science, leverages best practice from contiguous disciplines and facilitates responsive re-thinking of nanosafety governance to meet future needs. To achieve and operationalise such framework, a science-based Risk Governance Council (RGC) for NMs is being developed. The framework will provide a toolkit for independent NMs' risk governance and integrates needs and views of stakeholders. An extension of this framework to relevant advanced materials and emerging technologies is also envisaged, in view of future foundations of risk research in Europe and globally.

How safe is control banding? Integrated evaluation by comparing OELs with measurement data and using monte carlo simulation.

The present study aims to explore the protection level that can be achieved by the German control banding (CB) tool Einfaches Massnahmenkonzept Gefahrstoffe, 'Easy-to-use workplace control scheme for hazardous substances'. The rationale of our integrated approach is based on the Bewertungsindex (BWI), which is the quotient of the exposure level and the occupational exposure limit (OEL), with BWI <1 indicating compliance. The frequency distributions of the BWI were calculated in order to reflect statistically the variability of workplace conditions. The corresponding statistical values of the frequency distributions (percentiles etc.) are interpreted as an indicator of the level of protection that is achieved. The occupational exposure data sets used in the calculation of the BWI frequency distribution were mainly collected from Bundesanstalt für Arbeitsschutz und Arbeitsmedizin field studies. The data sets taken into account were selected according to the criteria 'hazard band, exposure potential, control approach'. Such a combination is called the 'control banding scenario' (CBS). Measurement data are only available for two CBS: in the case of the CBS 'hazard band A, EPL3, CS1' the only data that are available (n = 220) relate to propane-2-ol as used in the area of offset printing. Only 0.4 % of the BWI are above 1, this indicating a high level of compliance. In the case of the CBS 'Hazard band B, EPL2, CS1', exposure data are available from screen-printing firms (n = 50), optician workshops (n = 49), and from the area of furniture production (n = 13). The frequency distributions of the BWI reveal almost no instances of values being exceeded in the three branches. In a subsequent step, a Monte Carlo Simulation was employed to explore whether the BWI frequency distributions can be generalized using a probabilistic model. The frequency distributions of the exposure levels and the OELs were used as the input data for the model. The simulation results show that the model distribution, called Modellierter Bewertungsindex distribution, can reproduce the BWI distribution if the data basis is homogeneous (data from one branch) and less correlated. In case of a heterogeneous data set (pooled data from different branches), the simulation results can be interpreted as generic statements about the attainable protection level. It was found that CB does not (at least potentially) guarantee compliance in either case. On the other hand, the generic simulation showed that compliance was high for volatile liquids used in closed systems (CBS: 'hazard band C, EPL3, CS3') and for solids in the presence of local exhaust ventilation (CBS: 'hazard band B, EPS3, CS2').