We used the multimedia chemical fate model BETR Global to evaluate changes in the global distribution of two polychlorinated biphenyls, PCB 28 and PCB 153, under the influence of climate change. This was achieved by defining two climate scenarios based on results from a general circulation model, one scenario representing the last twenty years of the 20th century (20CE scenario) and another representing the global climate under the assumption of strong future greenhouse gas emissions (A2 scenario). The two climate scenarios are defined by four groups of environmental parameters: (1) temperature in the planetary boundary layer and the free atmosphere, (2) wind speeds and directions in the atmosphere, (3) current velocities and directions in the surface mixed layer of the oceans, and (4) rate and geographical pattern of precipitation. As a fifth parameter in our scenarios, we considerthe effect of temperature on primary volatilization emissions of PCBs. Comparison of dynamic model results using environmental parameters from the 20CE scenario against historical long-term monitoring data of concentrations of PCB 28 and PCB 153 in air from 16 different sites shows satisfactory agreement between modeled and measured PCBs concentrations. The 20CE scenario and A2 scenario were compared using steady-state calculations and assuming the same source characteristics of PCBs. Temperature differences between the two scenarios is the dominant factor that determines the difference in PCB concentrations in air. The higher temperatures in the A2 scenario drive increased primary and secondary volatilization emissions of PCBs, and enhance transport from temperate regions to the Arctic. The largest relative increase in concentrations of both PCB congeners in air under the A2 scenario occurs in the high Arctic and the remote Pacific Ocean. Generally, higher wind speeds under the A2 scenario result in more efficient intercontinental transport of PCB 28 and PCB 153 compared to the 20CE scenario. Our modeling indicates that in a future impacted by climate change, we can expectincreased volatilization emissions and increased mobility of persistent organic pollutants with properties similar to those of PCBs.

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The use of non-testing strategies like read-across in the hazard assessment of chemicals and nanomaterials (NMs) is deemed essential to perform the safety assessment of all NMs in due time and at lower costs. The identification of physicochemical (PC) properties affecting the hazard potential of NMs is crucial, as it could enable to predict impacts from similar NMs and outcomes of similar assays, reducing the need for experimental (and in particular animal) testing. This manuscript presents a review of approaches and available case studies on the grouping of NMs to read-across hazard endpoints. We include in this review grouping frameworks aimed at identifying hazard classes depending on PC properties, hazard classification modules in control banding (CB) approaches, and computational methods that can be used for grouping for read-across. The existing frameworks and case studies are systematically reported. Relevant nanospecific PC properties taken into account in the reviewed frameworks to support grouping are shape and surface properties (surface chemistry or reactivity) and hazard classes are identified on the basis of biopersistence, morphology, reactivity, and solubility.

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BackgroundAn increasing number of manufactured nanomaterials (NMs) are being used in industrial products and need to be registered under the REACH legislation. The hazard characterisation of all these forms is not only technically challenging but resource and time demanding. The use of non-testing strategies like read-across is deemed essential to assure the assessment of all NMs in due time and at lower cost. The fact that read-across is based on the structural similarity of substances represents an additional difficulty for NMs as in general their structure is not unequivocally defined. In such a scenario, the identification of physicochemical properties affecting the hazard potential of NMs is crucial to define a grouping hypothesis and predict the toxicological hazards of similar NMs. In order to promote the read-across of NMs, ECHA has recently published “Recommendations for nanomaterials applicable to the guidance on QSARs and Grouping”, but no practical examples were provided in the document. Due to the lack of publicly available data and the inherent difficulties of reading-across NMs, only a few examples of read-across of NMs can be found in the literature. This manuscript presents the first case study of the practical process of grouping and read-across of NMs following the workflow proposed by ECHA.MethodsThe workflow proposed by ECHA was used and slightly modified to present the read-across case study. The Read-Across Assessment Framework (RAAF) was used to evaluate the uncertainties of a read-across within NMs. Chemoinformatic techniques were used to support the grouping hypothesis and identify key physicochemical properties.ResultsA dataset of 6 nanoforms of TiO2 with more than 100 physicochemical properties each was collected. In vitro comet assay result was selected as the endpoint to read-across due to data availability. A correlation between the presence of coating or large amounts of impurities and negative comet assay results was observed.ConclusionThe workflow proposed by ECHA to read-across NMs was applied successfully. Chemoinformatic techniques were shown to provide key evidence for the assessment of the grouping hypothesis and the definition of similar NMs. The RAAF was found to be applicable to NMs.Electronic supplementary materialThe online version of this article (10.1186/s12989-018-0273-1) contains supplementary material, which is available to authorized users.

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