Size-specific, dynamic, probabilistic material flow analysis of titanium dioxide releases into the environment

Abstract

Most of the existing exposure models for engineered nanomaterials (ENMs) do not consider particle size, crystalline forms, and coating materials that all may influence the material's fate, transport, and toxicity. Our work aimed to incorporate particle size distributions into a material flow analysis (MFA) to develop a sizespecif ic, dynamic, probabilistic MFA model (ss-DPMFA). Using titanium dioxide (TiO2) as a first case study, we aimed to determine the contribution of conventional TiO2pigments to the total amount of nanoscale TiO2released into the environment. Besides providing information on mass flows, the new model used particle size distributions and crystalline forms to describe the stocks and flows of TiO2. The most striking modeling result to emerge was that before TiO2ENMs came onto the market as such in 2000, 22, 400 tons of nanosized (<100 nm) TiO2 particles had already been released into the environment, originating from conventional TiO2pigments. Even in 2016, 50% of the nanosized TiO2particles released into wastewater came from the nanosized fraction of TiO2particles in pigments. Quantitative data on the particle size distribution of TiO2particles released into the environment can be used as input for environmental fate models. Our new ss-DPMFA model's additional insights about crystalline forms and coatings could pave the way for advanced size- and form-specific hazard and risk assessments for other nanomaterials in ecological systems.