Lead substances selection using GHS approach for the classification of mixtures: Case study of painting in the work environment.

We developed a lead substances selection approach based on the concept of mixture classification of UN GHS for the purpose of efficient risk assessment of mixtures consisting of multiple components. Lead substances selection methods are being actively developed in Europe, but these methods are predicated on the regulations and information sources available within Europe and are therefore not readily applicable to countries outside Europe. In this study, the features of the GHS-based approach and the risk assessment results for outdoor painting work as a specific utilization example of the GHS-based approach were described. Comparison with the DPD + method and the CCA method proposed in Europe revealed that the GHS-based approach resulted in the selection of the safest lead substances. The GHS method, like the DPD + method, is a classification-based approach. We believe that a classification-based approach based on the GHS method can be an appropriate tool to efficiently implement risk assessment of mixtures for countries outside Europe. Some tools for business operators to conduct the management of chemicals using the GHS classification have been established in Japan. We plan to propose the GHS-based approach as a standardized assessment tool.

Geo-referenced multimedia environmental fate model (G-CIEMS): model formulation and comparison to the generic model and monitoring approaches.

A spatially resolved and geo-referenced dynamic multimedia environmental fate model, G-CIEMS (Grid-Catchment Integrated Environmental Modeling System) was developed on a geographical information system (GIS). The case study for Japan based on the air grid cells of 5 x 5 km resolution and catchments with an average area of 9.3 km2, which corresponds to about 40,000 air grid cells and 38,000 river segments/catchment polygons, were performed for dioxins, benzene, 1,3-butadiene, and di-(2-ethyhexyl)phthalate. The averaged concentration of the model and monitoring output were within a factor of 2-3 for all the media. Outputs from G-CIEMS and the generic model were essentially comparable when identical parameters were employed, whereas the G-CIEMS model gave explicit information of distribution of chemicals in the environment. Exposure-weighted averaged concentrations (EWAC) in air were calculated to estimate the exposure ofthe population, based on the results of generic, G-CIEMS, and monitoring approaches. The G-CIEMS approach showed significantly better agreement with the monitoring-derived EWAC than the generic model approach. Implication for the use of a geo-referenced modeling approach in the risk assessment scheme is discussed as a generic-spatial approach, which can be used to provide more accurate exposure estimation with distribution information, using generally available data sources for a wide range of chemicals.