Simulating behavior of petroleum compounds during refinery effluent treatment using the SimpleTreat model.

Distribution and elimination of petroleum products can be predicted in aerobic wastewater treatment plants (WWTPs) using models such as multimedia fate model SimpleTreat. An advantage of the SimpleTreat model is that it only requires a few basic properties of a chemical in wastewater to calculate partitioning, biodegradation and ultimately emissions to air, surface water and produced sludge. The SimpleTreat model structure reflects a WWTP scheme. However, refinery WWTPs typically incorporate more advanced treatment processes such as dissolved air flotation (DAF), a process that clarifies wastewaters by the removal of suspended matter such as oil or solids. The objective of this work was to develop a WWTP removal model that includes DAF treatment. To understand how including a DAF in the model affects the predicted concentrations of petroleum constituents in effluent, we replaced the primary sedimentation module in SimpleTreat with a module simulating DAF. Subsequently, we compared results from the WWTP-DAF model with results obtained with the original SimpleTreat model for a library of over 1500 representative hydrocarbon constituents. The increased air-water exchange in a WWTP-DAF unit resulted in higher predicted removal of volatile constituents. Predicted removal with DAF was on average 17% larger than removal with primary sedimentation. We compared modelled results with measured removal data from the literature, which supported that this model refinement continues to improve the technical basis of assessment of petroleum products.

Chemical pollution imposes limitations to the ecological status of European surface waters.

Aquatic ecosystems are affected by man-made pressures, often causing combined impacts. The analysis of the impacts of chemical pollution is however commonly separate from that of other pressures and their impacts. This evolved from differences in the data available for applied ecology vis-à-vis applied ecotoxicology, which are field gradients and laboratory toxicity tests, respectively. With this study, we demonstrate that the current approach of chemical impact assessment, consisting of comparing measured concentrations to protective environmental quality standards for individual chemicals, is not optimal. In reply, and preparing for a method that would enable the comprehensive assessment and management of water quality pressures, we evaluate various quantitative chemical pollution pressure metrics for mixtures of chemicals in a case study with 24 priority substances of Europe-wide concern. We demonstrate why current methods are sub-optimal for water quality management prioritization and that chemical pollution currently imposes limitations to the ecological status of European surface waters. We discuss why management efforts may currently fail to restore a good ecological status, given that to date only 0.2% of the compounds in trade are considered in European water quality assessment and management.

Screening-Level Estimates of Environmental Release Rates, Predicted Exposures, and Toxic Pressures of Currently Used Chemicals.

We describe a procedure to quantify emissions of chemicals for environmental protection, assessment, and management purposes. The procedure uses production and use volumes from registration dossiers and combines these with Specific Environmental Release Category data. The procedure was applied in a case study. Emission estimations were made for chemicals registered under the European Union chemicals regulations for industrial chemicals (Registration, Evaluation, Authorisation and Restriction of Chemicals [REACH]) and for the active ingredients of medicines and crop protection products. Emissions themselves cannot be validated. Instead, emission estimates were followed by multimedia fate modeling and mixture toxic pressure modeling to arrive at predicted environmental concentrations (PECs) and toxic pressures for a typical European water body at steady state, which were compared with other such data. The results show that screening-level assessments could be performed, and yielded estimates of emissions, PECs, and mixture toxic pressures of chemicals used in Europe. Steady-state PECs agreed fairly well with measured concentrations. The mixture toxic pressure at steady state suggests the presence of effects in aquatic species assemblages, whereby few compounds dominate the predicted impact. The study shows that our screening-level emission estimation procedure is sufficiently accurate and precise to serve as a basis for assessment of chemical pollution in aquatic ecosystems at the scale of river catchments. Given a recognized societal need to develop methods for realistic, cumulative exposures, the emission assessment procedure can assist in the prioritization of chemicals in safety policies (such as the European Union REACH regulation), where "possibility to be used safely" needs to be demonstrated, and environmental quality policies (such as the European Union Water Framework Directive), where "good environmental quality" needs to be reached. Environ Toxicol Chem 2020;39:1839-1851. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Computational material flow analysis for thousands of chemicals of emerging concern in European waters.

Knowledge of exposure to a wide range of chemicals, and the spatio-temporal variability thereof, is urgently needed in the context of protecting and restoring aquatic ecosystems. This paper discusses a computational material flow analysis to predict the occurrence of thousands of man-made organic chemicals on a European scale, based on a novel temporally and spatially resolved modelling framework. The goal was to increase understanding of pressures by emerging chemicals and to complement surface water monitoring data. The ambition was to provide a first step towards a "real-life" mixture exposure situation accounting for as many chemicals as possible. Comparison of simulated concentrations and chemical monitoring data for 226 substance/basin combinations showed that the simulated concentrations were accurate on average. For 65% and 90% of substance/basin combinations the error was within one and two orders of magnitude respectively. An analysis of the relative importance of uncertainties revealed that inaccuracies in use volume or use type information contributed most to the error for individual substances. To resolve this, we suggest better registration of use types of industrial chemicals, investigation of presence/absence of industrial chemicals in wastewater and runoff samples and more scientific information exchange.

Chemical fate of persistent organic pollutants in the arctic: Evaluation of simplebox.

Persistent organic pollutants (POPs) are of great concern for decades due to their persistence, bioaccumulation and long-range transport potential. Multimedia fate models are useful scientific and decision-support tools for predicting the chemical fate in the environment. The SimpleBox multimedia fate model (v4.0) was used in this study to estimate the impact of POP emissions from the European and North American mainland on POP contamination in the Arctic. The purpose of the study was to evaluate the performance of SimpleBox by comparing estimations to measurements. Model performance for the air compartment was reasonable as estimated concentrations were generally within a factor of five of measured concentrations. SimpleBox suggested higher POP concentrations in Arctic oceans than in temperate oceans, contrary to the few measured data. Discrepancies between estimations and measurements may be attributed to the variability in emission estimates and degradation rates of POPs, representativeness of monitoring data, and a missing snow and ice environmental compartment in SimpleBox. Emission rates and degradation rate constants were the most influential input parameters in SimpleBox based on sensitivity analysis. Suggestions for improvements of SimpleBox refining POP risk assessment are provided.

QSAR-Based Estimation of Species Sensitivity Distribution Parameters: An Exploratory Investigation.

Ecological risk assessments are hampered by limited availability of ecotoxicity data. The present study aimed to explore the possibility of deriving species sensitivity distribution (SSD) parameters for nontested compounds, based on simple physicochemical characteristics, known SSDs for data-rich compounds, and a quantitative structure-activity relationship (QSAR)-type approach. The median toxicity of a data-poor chemical for species assemblages significantly varies with values of the physicochemical descriptors, especially when based on high-quality SSD data (from either acute median effect concentrations or chronic no-observed-effect concentrations). Beyond exploratory uses, we discuss how the precision of QSAR-based SSDs can be improved to construct models that accurately predict the SSD parameters of data-poor chemicals. The current models show that the concept of QSAR-based SSDs supports screening-level evaluations of the potential ecotoxicity of compounds for which data are lacking. Environ Toxicol Chem 2019;38:2764-2770. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Species sensitivity distributions for use in environmental protection, assessment, and management of aquatic ecosystems for 12 386 chemicals.

The present study considers the collection and use of ecotoxicity data for risk assessment with species sensitivity distributions (SSDs) of chemical pollution in surface water, which are used to quantify the likelihood that critical effect levels are exceeded. This fits the European Water Framework Directive, which suggests using models to assess the likelihood that chemicals affect water quality for management prioritization. We derived SSDs based on chronic and acute ecotoxicity test data for 12 386 compounds. The log-normal SSDs are characterized by the median and the standard deviation of log-transformed ecotoxicity data and by a quality score. A case study illustrates the utility of SSDs for water quality assessment and management prioritization. We quantified the chronic and acute mixture toxic pressure of mixture exposures for >22 000 water bodies in Europe for 1760 chemicals for which we had both exposure and hazard data. The results show the likelihood of mixture exposures exceeding a negligible effect level and increasing species loss. The SSDs in the present study represent a versatile and comprehensive approach to prevent, assess, and manage chemical pollution problems. Environ Toxicol Chem 2019;38:905-917. © 2019 SETAC.

Time-Integrative Passive sampling combined with TOxicity Profiling (TIPTOP): an effect-based strategy for cost-effective chemical water quality assessment.

This study aimed at demonstrating that effect-based monitoring with passive sampling followed by toxicity profiling is more protective and cost-effective than the current chemical water quality assessment strategy consisting of compound-by-compound chemical analysis of selected substances in grab samples. Passive samplers were deployed in the Dutch river delta and in WWTP effluents. Their extracts were tested in a battery of bioassays and chemically analyzed to obtain toxicity and chemical profiles, respectively. Chemical concentrations in water were retrieved from publicly available databases. Seven different strategies were used to interpret the chemical and toxicity profiles in terms of ecological risk. They all indicated that the river sampling locations were relatively clean. Chemical-based monitoring resulted for many substances in measurements below detection limit and could only explain <20% of the observed in vitro toxicity. Effect-based monitoring yielded more informative conclusions as it allowed for ranking the sampling sites and for estimating a margin-of-exposure towards chronic effect ranges. Effect-based monitoring was also cheaper and more cost-effective (i.e. yielding more information per euro spent). Based on its identified strengths, weaknesses, opportunities, and threats (SWOT), a future strategy for effect-based monitoring has been proposed.

A chemical activity approach to exposure and risk assessment of chemicals: Focus articles are part of a regular series intended to sharpen understanding of current and emerging topics of interest to the scientific community.

To support the goals articulated in the vision for exposure and risk assessment in the twenty-first century, we highlight the application of a thermodynamic chemical activity approach for the exposure and risk assessment of chemicals in the environment. The present article describes the chemical activity approach, its strengths and limitations, and provides examples of how this concept may be applied to the management of single chemicals and chemical mixtures. The examples demonstrate that the chemical activity approach provides a useful framework for 1) compiling and evaluating exposure and toxicity information obtained from many different sources, 2) expressing the toxicity of single and multiple chemicals, 3) conducting hazard and risk assessments of single and multiple chemicals, 4) identifying environmental exposure pathways, and 5) reducing error and characterizing uncertainty in risk assessment. The article further illustrates that the chemical activity approach can support an adaptive management strategy for environmental stewardship of chemicals where "safe" chemical activities are established based on toxicological studies and presented as guidelines for environmental quality in various environmental media that can be monitored by passive sampling and other techniques. Environ Toxicol Chem 2018;37:1235-1251. © 2018 The Authors. Published by Wiley Periodicals, Inc. on behalf of SETAC.

Quantitative structure-activity relationships for green algae growth inhibition by polymer particles.

After use and disposal of chemical products, many types of polymer particles end up in the aquatic environment with potential toxic effects to primary producers like green algae. In this study, we have developed Quantitative Structure-Activity Relationships (QSARs) for a set of highly structural diverse polymers which are capable to estimate green algae growth inhibition (EC50). The model (N = 43, R2 = 0.73, RMSE = 0.28) is a regression-based decision tree using one structural descriptor for each of three polymer classes separated based on charge. The QSAR is applicable to linear homo polymers as well as copolymers and does not require information on the size of the polymer particle or underlying core material. Highly branched polymers, non-nitrogen cationic polymers and polymeric surfactants are not included in the model and thus cannot be evaluated. The model works best for cationic and non-ionic polymers for which cellular adsorption, disruption of the cell wall and photosynthesis inhibition were the mechanisms of action. For anionic polymers, specific properties of the polymer and test characteristics need to be known for detailed assessment. The data and QSAR results for anionic polymers, when combined with molecular dynamics simulations indicated that nutrient depletion is likely the dominant mode of toxicity. Nutrient depletion in turn, is determined by the non-linear interplay between polymer charge density and backbone flexibility.

The toxicity of plastic nanoparticles to green algae as influenced by surface modification, medium hardness and cellular adsorption.

To investigate processes possibly underlying accumulation and ecological effects of plastic nano-particles we have characterized their interaction with the cell wall of green algae. More specifically, we have investigated the influence of particle surface functionality and water hardness (Ca2+ concentration) on particle adsorption to algae cell walls. Polystyrene nanoparticles with different functional groups (non-functionalized, -COOH and -NH2) as well as coated (starch and PEG) gold nanoparticles were applied in these studies. Depletion measurements and atomic force microscopy (AFM) showed that adsorption of neutral and positively charged plastic nanoparticles onto the cell wall of P. subcapitata was stronger than that of negatively charged plastic particles. Results indicated that binding affinity is a function of both inter-particle and particle-cell wall interactions which are in turn influenced by the medium hardness and particle concentration. Physicochemical modelling using DLVO theory was used to interpret the experimental data, using also values for interfacial surface free energies. Our study shows that material properties and medium conditions play a crucial role in the rate and state of nanoparticle bio-adsorption for green algae. The results show that the toxicity of nanoparticles can be better described and assessed by using appropriate dose metrics including material properties, complexation/agglomeration behavior and cellular attachment and adsorption. The applied methodology provides an efficient and feasible approach for evaluating potential accumulation and hazardous effects of nanoparticles to algae caused by particle interactions with the algae cell walls.

Towards the review of the European Union Water Framework Directive: Recommendations for more efficient assessment and management of chemical contamination in European surface water resources.

Water is a vital resource for natural ecosystems and human life, and assuring a high quality of water and protecting it from chemical contamination is a major societal goal in the European Union. The Water Framework Directive (WFD) and its daughter directives are the major body of legislation for the protection and sustainable use of European freshwater resources. The practical implementation of the WFD with regard to chemical pollution has faced some challenges. In support of the upcoming WFD review in 2019 the research project SOLUTIONS and the European monitoring network NORMAN has analyzed these challenges, evaluated the state-of-the-art of the science and suggested possible solutions. We give 10 recommendations to improve monitoring and to strengthen comprehensive prioritization, to foster consistent assessment and to support solution-oriented management of surface waters. The integration of effect-based tools, the application of passive sampling for bioaccumulative chemicals and an integrated strategy for prioritization of contaminants, accounting for knowledge gaps, are seen as important approaches to advance monitoring. Including all relevant chemical contaminants in more holistic "chemical status" assessment, using effect-based trigger values to address priority mixtures of chemicals, to better consider historical burdens accumulated in sediments and to use models to fill data gaps are recommended for a consistent assessment of contamination. Solution-oriented management should apply a tiered approach in investigative monitoring to identify toxicity drivers, strengthen consistent legislative frameworks and apply solutions-oriented approaches that explore risk reduction scenarios before and along with risk assessment.

Combining exposure and effect modeling into an integrated probabilistic environmental risk assessment for nanoparticles.

There is a growing need for good environmental risk assessment of engineered nanoparticles (ENPs). Environmental risk assessment of ENPs has been hampered by lack of data and knowledge about ENPs, their environmental fate, and their toxicity. This leads to uncertainty in the risk assessment. To deal with uncertainty in the risk assessment effectively, probabilistic methods are advantageous. In the present study, the authors developed a method to model both the variability and the uncertainty in environmental risk assessment of ENPs. This method is based on the concentration ratio and the ratio of the exposure concentration to the critical effect concentration, both considered to be random. In this method, variability and uncertainty are modeled separately so as to allow the user to see which part of the total variation in the concentration ratio is attributable to uncertainty and which part is attributable to variability. The authors illustrate the use of the method with a simplified aquatic risk assessment of nano-titanium dioxide. The authors' method allows a more transparent risk assessment and can also direct further environmental and toxicological research to the areas in which it is most needed. Environ Toxicol Chem 2016;35:2958-2967. © 2016 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

SimpleBox 4.0: Improving the model while keeping it simple .

Chemical behavior in the environment is often modeled with multimedia fate models. SimpleBox is one often-used multimedia fate model, firstly developed in 1986. Since then, two updated versions were published. Based on recent scientific developments and experience with SimpleBox 3.0, a new version of SimpleBox was developed and is made public here: SimpleBox 4.0. In this new model, eight major changes were implemented: removal of the local scale and vegetation compartments, addition of lake compartments and deep ocean compartments (including the thermohaline circulation), implementation of intermittent rain instead of drizzle and of depth dependent soil concentrations, adjustment of the partitioning behavior for organic acids and bases as well as of the value for enthalpy of vaporization. In this paper, the effects of the model changes in SimpleBox 4.0 on the predicted steady-state concentrations of chemical substances were explored for different substance groups (neutral organic substances, acids, bases, metals) in a standard emission scenario. In general, the largest differences between the predicted concentrations in the new and the old model are caused by the implementation of layered ocean compartments. Undesirable high model complexity caused by vegetation compartments and a local scale were removed to enlarge the simplicity and user friendliness of the model.

Hierarchical Bayesian Approach To Reduce Uncertainty in the Aquatic Effect Assessment of Realistic Chemical Mixtures.

Species in the aquatic environment differ in their toxicological sensitivity to the various chemicals they encounter. In aquatic risk assessment, this interspecies variation is often quantified via species sensitivity distributions. Because the information available for the characterization of these distributions is typically limited, optimal use of information is essential to reduce uncertainty involved in the assessment. In the present study, we show that the credibility intervals on the estimated potentially affected fraction of species after exposure to a mixture of chemicals at environmentally relevant surface water concentrations can be extremely wide if a classical approach is followed, in which each chemical in the mixture is considered in isolation. As an alternative, we propose a hierarchical Bayesian approach, in which knowledge on the toxicity of chemicals other than those assessed is incorporated. A case study with a mixture of 13 pharmaceuticals demonstrates that this hierarchical approach results in more realistic estimations of the potentially affected fraction, as a result of reduced uncertainty in species sensitivity distributions for data-poor chemicals.

A semi-empirical model for transport of inorganic nanoparticles across a lipid bilayer: implications for uptake by living cells.

Due to increasing application, release of nanoparticles (NPs) and nanomaterials into the environment becomes likely. Knowledge about NP uptake in organisms is crucial for risk assessment including estimations on the behavior of NPs based on their physicochemical properties. In the present study, the authors have applied current scientific knowledge to construct a mathematical model, which estimates the transport of NPs through a model biological membrane. The semi-empirical model developed showed all parameters studied to substantially affect the agglomeration of the NPs in suspension, thereby also affecting passive transport. The authors quantified the effects of pH, ionic strength, organic matter concentration of medium, and NP size of several inorganic NPs on the permeation through the lipid membrane. Model outcomes and experimental results described in literature were strongly correlated for several metal oxide NPs. With caution, the model may be used to explain some of the existing variance in nano-uptake and toxicity experiments.

Definition and applications of a versatile chemical pollution footprint methodology.

Because of the great variety in behavior and modes of action of chemicals, impact assessment of multiple substances is complex, as is the communication of its results. Given calls for cumulative impact assessments, we developed a methodology that is aimed at expressing the expected cumulative impacts of mixtures of chemicals on aquatic ecosystems for a region and subsequently allows to present these results as a chemical pollution footprint, in short: a chemical footprint. Setting and using a boundary for chemical pollution is part of the methodology. Two case studies were executed to test and illustrate the methodology. The first case illustrates that the production and use of organic substances in Europe, judged with the European water volume, stays within the currently set policy boundaries for chemical pollution. The second case shows that the use of pesticides in Northwestern Europe, judged with the regional water volume, has exceeded the set boundaries, while showing a declining trend over time. The impact of mixtures of substances in the environment could be expressed as a chemical footprint, and the relative contribution of substances to that footprint could be evaluated. These features are a novel type of information to support risk management, by helping prioritization of management among chemicals and environmental compartments.