Fadri Gottschalk

Modeled environmental concentrations of engineered nanomaterials (TiO2, ZnO, Ag, CNT, fullerenes) for different regions.

Engineered nanomaterials (ENM) are already used in many products and consequently released into environmental compartments. In this study, we calculated predicted environmental concentrations (PEC) based on a probabilistic material flow analysis from a life-cycle perspective of ENM-containing products. We modeled nano-TiO(2), nano-ZnO, nano-Ag, carbon nanotubes (CNT), and fullerenes for the U.S., Europe and Switzerland. The environmental concentrations were calculated as probabilistic density functions and were compared to data from ecotoxicological studies. The simulated modes (most frequent values) range from 0.003 ng L(-1) (fullerenes) to 21 ng L(-1) (nano-TiO(2)) for surface waters and from 4 ng L(-1) (fullerenes) to 4 microg L(-1) (nano-TiO(2)) for sewage treatment effluents. For Europe and the U.S., the annual increase of ENMs on sludge-treated soil ranges from 1 ng kg(-1) for fullerenes to 89 microg kg(-1) for nano-TiO(2). The results of this study indicate that risks to aquatic organisms may currently emanate from nano-Ag, nano-TiO(2), and nano-ZnO in sewage treatment effluents for all considered regions and for nano-Ag in surface waters. For the other environmental compartments for which ecotoxicological data were available, no risks to organisms are presently expected.

Possibilities and limitations of modeling environmental exposure to engineered nanomaterials by probabilistic material flow analysis

Information on environmental concentrations is needed to assess the risks that engineered nanomaterials (ENM) may pose to the environment. In this study, predicted environmental concentrations (PEC) were modeled for nano-TiO2, carbon nanotubes (CNT) and nano-Ag for Switzerland. Based on a life-cycle perspective, the model considered as input parameters the production volumes of the ENMs, the manufacturing and consumption quantities of products containing those materials, and the fate and pathways of ENMs in natural and technical environments. Faced with a distinct scarcity of data, we used a probabilistic material flow analysis model, treating all parameters as probability distributions. The modeling included Monte Carlo and Markov Chain Monte Carlo simulations as well as a sensitivity and uncertainty analysis. The PEC values of the ENMs in the different environmental compartments vary widely due to different ENM production volumes and different life cycles of the nanoproducts. The use of ENM in products with high water relevance leads to higher water and sediment concentrations for nano-TiO2 and nano-Ag, compared to CNTs, where smaller amounts of ENM reach the aquatic compartments. This study also presents a sensitivity analysis and a comprehensive discussion of the uncertainties of the simulation results and the limitations of the used approach. To estimate potential risks, the PEC values were compared to the predicted-no-effect concentrations (PNEC) derived from published data. The risk quotients (PEC/PNEC) for nano-TiO2 and nano-Ag were larger than one for treated wastewater and much smaller for all other environmental compartments (e.g., water, sediments, soils). We conclude that probabilistic modeling is very useful for predicting environmental concentrations of ENMs given the current lack of substantiated data.

Modeling Flows and Concentrations of Nine Engineered Nanomaterials in the Danish Environment

Predictions of environmental concentrations of engineered nanomaterials (ENM) are needed for their environmental risk assessment. Because analytical data on ENM-concentrations in the environment are not yet available, exposure modeling represents the only source of information on ENM exposure in the environment. This work provides material flow data and environmental concentrations of nine ENM in Denmark. It represents the first study that distinguishes between photostable TiO2 (as used in sunscreens) and photocatalytic TiO2 (as used in self-cleaning surfaces). It also provides first exposure estimates for quantum dots, carbon black and CuCO3. Other ENM that are covered are ZnO, Ag, CNT and CeO2. The modeling is based for all ENM on probability distributions of production, use, environmental release and transfer between compartments, always considering the complete life-cycle of products containing the ENM. The magnitude of flows and concentrations of the various ENM depends on the one hand on the production volume but also on the type of products they are used in and the life-cycles of these products and their potential for release. The results reveal that in aquatic systems the highest concentrations are expected for carbon black and photostable TiO2, followed by CuCO3 (under the assumption that the use as wood preservative becomes important). In sludge-treated soil highest concentrations are expected for CeO2 and TiO2. Transformation during water treatments results in extremely low concentrations of ZnO and Ag in the environment. The results of this study provide valuable environmental exposure information for future risk assessments of these ENM.

Probabilistic environmental risk assessment of five nanomaterials (nano-TiO2, nano-Ag, nano-ZnO, CNT, and fullerenes).

Abstract The environmental risks of five engineered nanomaterials (nano-TiO2, nano-Ag, nano-ZnO, CNT, and fullerenes) were quantified in water, soils, and sediments using probabilistic Species Sensitivity Distributions (pSSDs) and probabilistic predicted environmental concentrations (PECs). For water and soil, enough ecotoxicological endpoints were found for a full risk characterization (between 17 and 73 data points per nanomaterial for water and between 4 and 20 for soil) whereas for sediments, the data availability was not sufficient. Predicted No Effect Concentrations (PNECs) were obtained from the pSSD and used to calculate risk characterization ratios (PEC/PNEC). For most materials and environmental compartments, exposure and effect concentrations were separated by several orders of magnitude. Nano-ZnO in freshwaters and nano-TiO2 in soils were the combinations where the risk characterization ratio was closest to one, meaning that these are compartment/ENM combinations to be studied in more depth with the highest priority. The probabilistic risk quantification allows us to consider the large variability of observed effects in different ecotoxicological studies and the uncertainty in modeled exposure concentrations. The risk characterization results presented in this work allows for a more focused investigation of environmental risks of nanomaterials by consideration of material/compartment combinations where the highest probability for effects with predicted environmental concentrations is likely.

Life cycle assessment of facade coating systems containing manufactured nanomaterials

Nanotechnologies are expected to hold considerable potential for the development of new materials in the construction sector. Up to now the environmental benefits and risks of products containing manufactured nanomaterials (MNM) have been quantified only to a limited extent. This study aims to assess the potential environmental, health and safety impacts of coatings containing MNM using Life-cycle assessment: Do paints containing MNM result in a better environmental performance than paints not containing MNM? The study shows that the results depend on a number of factors: (i) The MNM have to substitute an (active) ingredient of the initial paint composition and not simply be an additional ingredient. (ii) The new composition has to extend the lifetime of the paint for such a time period that the consumption of paint along the life cycle of a building is reduced. (iii) Releases of MNM have to be reduced to the lowest level possible (in particular by dumping unused paint together with the packaging). Only when all these boundary conditions are fulfilled, which is the case only for one of the three paint systems examined, is an improved environmental performance of the MNM-containing paint possible for the paint compositions examined in this study.

Chapter 12:Modeling the Environmental Release and Exposure of Engineered Nanomaterials

Engineered nanomaterials (ENMs) are used in a broad spectrum of consumer products. The particle size at the nano-range gives ENMs particular physicochemical properties that may lead to exceptional performance regarding parameters such as e.g. surface reactivity, conductivity, porosity, solubility, c...