A prospective ecological risk assessment of high-efficiency III-V/silicon tandem solar cells.

III-V/Silicon tandem solar cells offer one of the most promising avenues for high-efficiency, high-stability photovoltaics. However, a key concern is the potential environmental release of group III-V elements, especially arsenic. To inform long-term policies on the energy transition and energy security, we develop and implement a framework that fully integrates future PV demand scenarios with dynamic stock, emission, and fate models in a probabilistic ecological risk assessment. We examine three geographical scales: local (including a floating utility-scale PV and waste treatment), regional (city-wide), and continental (Europe). Our probabilistic assessment considers a wide range of possible values for over one hundred uncertain technical, environmental, and regulatory parameters. We find that III-V/silicon PV integration in energy grids at all scales presents low-to-negligible risks to soil and freshwater organisms. Risks are further abated if recycling of III-V materials is considered at the panels' end-of-life.

A multimedia model to estimate the environmental fate of microplastic particles.

Nano- and microplastic (NMP) is a diverse and challenging contaminant and data on NMP concentrations are therefore not fully available for all environmental compartments. For environmental assessments of NMP, screening-level multimedia models can fill this gap, but such models are not available. Here, we present SimpleBox4Plastic (SB4P) as the first multimedia 'unit world' model capable of addressing the full NMP continuum, explore its validity, and evaluate it based on a case study for microbeads and by comparisons with (limited) concentration data. SB4P links NMP transport and concentrations in and across air, surface water, sediment, and soil, taking into account processes such as attachment, aggregation, and fragmentation, by solving mass balance equations using matrix algebra. These link all concentrations and processes known to be relevant for NMP using first-order rate constants, which are obtained from the literature. The SB4P model, as applied to microbeads, provided mass or number concentrations of NMP as the total of 'free' particles, heteroaggregates with natural colloids, and larger natural particles in each compartment at steady state. Processes most relevant in explaining observed Predicted Exposure Concentrations (PECs) were determined using rank correlation analysis. Although the predicted PECs remained uncertain due to the propagating uncertainty, inferences regarding these processes and relative distribution across compartments can be considered robust.

FAIR assessment tools: evaluating use and performance.

Publishing research data using a findable, accessible, interoperable, and reusable (FAIR) approach is paramount to further innovation in many areas of research. In particular in developing innovative approaches to predict (eco)toxicological risks in (nano or advanced) material design where efficient use of existing data is essential. The use of tools assessing the FAIRness of data helps the future improvement of data FAIRness and therefore their re-use. This paper reviews ten FAIR assessment tools that have been evaluated and characterized using two datasets from the nanomaterials and microplastics risk assessment domain. The tools were grouped into four categories: online and offline self-assessment survey based, online (semi-) automated and other tools. We found that the online self-assessment tools can be used for a quick scan of a user's dataset due to their ease of use, little need for experience and short time investment. When a user is looking to assess full databases, and not just datasets, for their FAIRness, (semi-)automated tools are more practical. The offline assessment tools were found to be limited and unreliable due to a lack of guidance and an under-developed state. To further characterize the usability, two datasets were run through all tools to check the similarity in the tools' results. As most of the tools differ in their implementation of the FAIR principles, a large variety in outcomes was obtained. Furthermore, it was observed that only one tool gives recommendations to the user on how to improve the FAIRness of the evaluated dataset. This paper gives clear recommendations for both the user and the developer of FAIR assessment tools.

Genotoxic effects in the Eastern mudminnow (Umbra pygmaea L.) after exposure to Rhine water, as assessed by use of the SCE and Comet assays: a comparison between 1978 and 2005.

Surface water used for drinking-water preparation requires continuous monitoring for the presence of toxic compounds. For monitoring of genotoxic compounds fish models have been developed, such as the Eastern mudminnow (Umbra pygmaea L.) because of its clearly visible 22 meta-centric chromosomes. It was demonstrated in the late seventies that Rhine water was able to induce chromosome aberrations and sister chromatid exchange in this fish species. Although in vitro mutagenicity studies of the RIWA (Rhine Water Works, The Netherlands) have shown that the genotoxicity of the river Rhine steadily decreased during the last decades, there is still concern about the presence of some residual mutagenicity. In addition, in most studies the water samples have been tested only in in vitro test systems such as the Salmonella-microsome test. For this reason, and in order to be able to make a comparison with the water quality 27 years ago, a study was performed with the same experimental design as before in order to measure the effect of Rhine water on the induction of SCE in the Eastern mudminnow. As a new test system the single cell gel electrophoresis assay (Comet assay) was performed. Fish were exposed to Rhine water or to groundwater for 3 and 11 days in flow-through aquaria. Fish exposed for 11 days to Rhine water had a significantly higher number of SCE and an increased comet tail-length compared with control fish exposed to groundwater. After exposure for three days to Rhine water there was no difference in SCE and a slightly increased comet tail-length compared with the control. It was concluded that genotoxins are still present in the river Rhine, but that the genotoxic potential has markedly decreased compared with 27 years ago. Furthermore, the Comet assay appears to be a sensitive assay to measure the genotoxic potential of surface waters in fish.

Lake retention of manufactured nanoparticles.

For twenty-five world lakes and three engineered nanoparticles (ENP), lake retention was calculated using a uniformly mixed lake mass balance model. This follows similar approaches traditionally used in water quality management. Lakes were selected such that lake residence times, depths and areal hydraulic loadings covered the widest possible range among existing lakes. Sedimentation accounted for natural colloid as well as suspended solid settling regimes. An ENP-specific mixed sedimentation regime is proposed. This regime combines ENP sedimentation through slow settling with natural colloids from the water column, with faster settling with suspended solids from a selected part of the water column. Although sedimentation data and hydrodynamic concepts as such were not new, their first time combination or application to ENPs shows in which cases lake retention is important for these particles. In combination with ENP emission data, lake retention translates directly into potential risks of ENPs for lake benthic communities.

Guidance for the prognostic risk assessment of nanomaterials in aquatic ecosystems.

Our understanding of the environmental fate and effects of engineered nanomaterials (ENMs) is in a state of fast transition. Recent scientific developments open new and powerful perspectives to define a framework for the prognostic risk assessment of ENMs in aquatic ecosystems. This requires abandoning the reductionist's approach of mechanistic analysis on particle or cellular scales and calls for engineering solutions that deal with uncertainties by applying assessment factors and probabilistic approaches. An ecological risk assessment (ERA) framework for ENMs is similar to that for other classes of substances, in that it requires clear protection goals based on ecosystem services, evidence-based concepts that link exposure to effects, and a transparent tiered effect assessment. Here, we discuss approaches to assess exposure and effects of ENMs. This includes recent developments in ENP fate modeling that greatly expanded the potential of prognostic exposure assessments. For the effect assessment, we advise a cost-effective screening based on principles of read-across as a conservative first tier. The feasibility of using species sensitivity distributions as a higher tier option is discussed. Controlled model ecosystem field experiments are proposed as a highest experimental tier, and are required for the calibration of the lower tiers. An outlook to unify information from various tiers by experimental work, fate modeling, and effect modeling as cost-effective prognostic tools for the ERA of ENMs is provided.

Heteroaggregation and sedimentation rates for nanomaterials in natural waters.

Exposure modeling of engineered nanomaterials requires input parameters such as sedimentation rates and heteroaggregation rates. Here, we estimate these rates using quiescent settling experiments under environmentally relevant conditions. We investigated 4 different nanomaterials (C60, CeO2, SiO2-Ag and PVP-Ag) in 6 different water types ranging from a small stream to seawater. In the presence of natural colloids, sedimentation rates ranged from 0.0001 m d(-1) for SiO2-Ag to 0.14 m d(-1) for C60. The apparent rates of heteroaggregation between nanomaterials and natural colloids were estimated using a novel method that separates heteroaggregation from homoaggregation using a simplified Smoluchowski-based aggregation-settling equation applied to data from unfiltered and filtered waters. The heteroaggregation rates ranged between 0.007 and 0.6 L mg(-1) day(-1), with the highest values observed in seawater. We argue that such system specific parameters are key to the development of dedicated water quality models for ENMs.