The importance of over-the-counter-sales and product format in the environmental exposure assessment of active pharmaceutical ingredients.

When assessing the environmental exposure of active pharmaceutical ingredients (APIs), the mass contributed from over the counter (OTC) sales are often not included due to difficulty obtaining this data and topical formats are overlooked completely. This study presents a comprehensive approach, investigating the significance of OTC and topical applications as sources of API releases to wastewater, in addition to temporal and subnational variations in use in the UK. The study provides methods to obtain and make use of OTC sales data which can be applied widely. The calculated releases to wastewater compared well with influent concentrations measured at several UK wastewater treatment plants (WWTPs). Consistent overestimation was observed, attributed to a number of factors, including in-sewer removal. OTC sales were found to make up a large proportion of the mass of ibuprofen (76%) and diclofenac (35%) consumed and topical formats were also found to be vital, contributing disproportionately to wastewater loadings per unit mass of ibuprofen and diclofenac used (43% and 99% of the total mass released, respectively). Releases of the APIs investigated did not vary temporally, but regional variation was significant and where possible should be considered for the most accurate exposure assessment of pharmaceuticals.

Bioenergetics modelling to analyse and predict the joint effects of multiple stressors: Meta-analysis and model corroboration.

Understanding the consequences of the combined effects of multiple stressors-including stress from man-made chemicals-is important for conservation management, the ecological risk assessment of chemicals, and many other ecological applications. Our current ability to predict and analyse the joint effects of multiple stressors is insufficient to make the prospective risk assessment of chemicals more ecologically relevant because we lack a full understanding of how organisms respond to stress factors alone and in combination. Here, we describe a Dynamic Energy Budget (DEB) based bioenergetics model that predicts the potential effects of single or multiple natural and chemical stressors on life history traits. We demonstrate the plausibility of the model using a meta-analysis of 128 existing studies on freshwater invertebrates. We then validate our model by comparing its predictions for a combination of three stressors (i.e. chemical, temperature, and food availability) with new, independent experimental data on life history traits in the daphnid Ceriodaphnia dubia. We found that the model predictions are in agreement with observed growth curves and reproductive traits. To the best of our knowledge, this is the first time that the combined effects of three stress factors on life history traits observed in laboratory studies have been predicted successfully in invertebrates. We suggest that a re-analysis of existing studies on multiple stressors within the modelling framework outlined here will provide a robust null model for identifying stressor interactions, and expect that a better understanding of the underlying mechanisms will arise from these new analyses. Bioenergetics modelling could be applied more broadly to support environmental management decision making.

Drivers of contaminant levels in surface water of China during 2000-2030: Relative importance for illustrative home and personal care product chemicals.

Water pollution are among the most critical problems in China and emerging contaminants in surface water have attracted rising attentions in recent years. There is great interest in China's future environmental quality as the national government has committed to a major action plan to improve surface water quality. This study presents methodologies to rank the importance of socioeconomic and environmental drivers to the chemical concentration in surface water during 2000-2030. A case study is conducted on triclosan, a home and personal care product (HPCP) ingredient. Different economic and discharge flow scenarios are considered. Urbanization and wastewater treatment connection rates in rural and urban areas are collected or projected for 2000-2030 for counties across China. The estimated usage increases from ca. 86 to 340 t. However, emissions decreases from 76 to 52 t during 2000-2030 under a modelled Organisation for Economic Co-operation (OECD) economic scenario because of the urbanization, migration and development of wastewater treatment plants/facilities (WWTPs). The estimated national median concentration of triclosan ranges 1.5-8.2 ng/L during 2000-2030 for different scenarios. It peaks in 2009 under the OECD and three of the Intergovernmental Panel on Climate Change (IPCC), A2, B1 and B2 economic scenarios, but in 2025 under A1 economic scenario. Population distribution and surface water discharge flow rates are ranked as the top two drivers to triclosan levels in surface water over the 30 years. The development of urban WWTPs was the most important driver during 2000-2010 and the development of rural works is projected to be the most important in 2011-2030. Projections suggest discharges of ingredients in HPCPs - controlled by economic growth - should be balanced by the major expenditure programme on wastewater treatment in China.

Effects of triclosan on aquatic invertebrates in tropics and the influence of pH on its toxicity on microalgae.

The antimicrobial triclosan (TCS) has been detected in household wastewaters (untreated and treated) and receiving environments across the globe. The toxic effects of TCS on temperate standard aquatic test organisms have been widely reported with microalgae being the most sensitive. However, environmental differences between tropical and temperate regions may have selected different trait compositions between these two regions, which in turn may lead to a difference in species sensitivity. Therefore, additional information is required to better characterize risks to organisms in tropics and ensure biodiversity in these regions is not adversely impacted. This study aims to supplement existing TCS toxicity data with five aquatic invertebrates found in tropics and to compare the sensitivity between aquatic invertebrate species from tropical and temperate regions. In addition, the effect of pH on the toxicity of neutral and ionized forms of TCS to microalgae (Chlorella ellipsoidea) was investigated. The reported 96-h LC50 values for the studied invertebrate species ranged from 72 to 962 µg/L. There was no significant difference between the sensitivity of aquatic invertebrate species from tropical and temperate regions. EC50 values for C. ellipsoidea, with and without pH buffer, were significantly different. The findings of this study can be used to support site-specific water quality criteria and environmental risk assessment for TCS in tropical regions. However, further chronic and semi-field experiments with TCS could potentially enable a refined assessment of direct and indirect effects on tropical aquatic communities and further explore functional endpoints of tropical ecosystems.

Application of a spatially resolved model to contextualise monitoring data for risk assessment of down-the-drain chemicals over large scales.

Many regulatory screening level exposure assessments are based on simple large scale conceptual scenarios. However, exposure, and therefore risks associated with chemicals, are characterised by high spatial variability. The Scenario assembly tool (ScenAT) is a global screening level model to enable spatially resolved local predictions of environmental concentrations of home and personal care chemicals. It uses the European Union Technical Guidance Document (TGD) equation to predict local scale freshwater concentrations (predicted environmental concentrations - PECs) of chemicals discharged via wastewater. ScenAT uses Geographic Information System (GIS) layers for the underlying socio-economic (population) and environmental parameters (per capita water use, sewage treatment plant connectivity, dilution factor). Using a probabilistic approach, we incorporate sources of uncertainty in the input data (tonnage estimation, removal in sewage treatment plants and seasonal variability in dilution factors) for two case-study chemicals: the antimicrobial triclosan (TCS) and the anionic surfactant linear alkylbenzene sulphonate (LAS). We then compare model estimates of wastewater and freshwater concentrations of TCS and LAS to UK monitoring data. Comparison showed that modeled PECs were on average higher than mean measured data for TCS and LAS by a factor 1.8 and 1.4, respectively. Considering the uncertainty associated with both model and monitoring data, the use of a probabilistic approach using the ScenAT model for screening assessment is reasonable. The combination of modelled and monitoring data enables the contextualisation of monitoring data. Spatial PECs can be used to identify areas of elevated concentration for further refined assessment.

Toward refined environmental scenarios for ecological risk assessment of down-the-drain chemicals in freshwater environments.

Current regulatory practice for chemical risk assessment suffers from the lack of realism in conventional frameworks. Despite significant advances in exposure and ecological effect modeling, the implementation of novel approaches as high-tier options for prospective regulatory risk assessment remains limited, particularly among general chemicals such as down-the-drain ingredients. While reviewing the current state of the art in environmental exposure and ecological effect modeling, we propose a scenario-based framework that enables a better integration of exposure and effect assessments in a tiered approach. Global- to catchment-scale spatially explicit exposure models can be used to identify areas of higher exposure and to generate ecologically relevant exposure information for input into effect models. Numerous examples of mechanistic ecological effect models demonstrate that it is technically feasible to extrapolate from individual-level effects to effects at higher levels of biological organization and from laboratory to environmental conditions. However, the data required to parameterize effect models that can embrace the complexity of ecosystems are large and require a targeted approach. Experimental efforts should, therefore, focus on vulnerable species and/or traits and ecological conditions of relevance. We outline key research needs to address the challenges that currently hinder the practical application of advanced model-based approaches to risk assessment of down-the-drain chemicals. Integr Environ Assess Manag 2017;13:233-248. © 2016 SETAC.

Integrated presentation of ecological risk from multiple stressors.

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

Spatial and temporal variability in the potential of river water biofilms to degrade p-nitrophenol.

In order to predict the fate of chemicals in the environment, a range of regulatory tests are performed with microbial inocula collected from environmental compartments to investigate the potential for biodegradation. The abundance and distribution of microbes in the environment is affected by a range of variables, hence diversity and biomass of inocula used in biodegradation tests can be highly variable in space and time. The use of artificial or natural biofilms in regulatory tests could enable more consistent microbial communities be used as inocula, in order to increase test consistency. We investigated spatial and temporal variation in composition, biomass and chemical biodegradation potential of bacterial biofilms formed in river water. Sampling time and sampling location impacted the capacity of biofilms to degrade p-nitrophenol (PNP). Biofilm bacterial community structure varied across sampling times, but was not affected by sampling location. Degradation of PNP was associated with increased relative abundance of Pseudomonas syringae. Partitioning of the bacterial metacommunity into core and satellite taxa revealed that the P. syringae could be either a satellite or core member of the community across sampling times, but this had no impact on PNP degradation. Quantitative PCR analysis of the pnpA gene showed that it was present in all samples irrespective of their ability to degrade PNP. River biofilms showed seasonal variation in biomass, microbial community composition and PNP biodegradation potential, which resulted in inconsistent biodegradation test results. We discuss the results in the context of the mechanisms underlying variation in regulatory chemical degradation tests.

Simultaneous determination of 20 trace organic chemicals in waters by solid-phase extraction (SPE) with triple-quadrupole mass spectrometer (QqQ-MS) and hybrid quadrupole Orbitrap high resolution MS (Q-Orbitrap-HRMS).

A sensitive method for simultaneous determination of 20 trace organic chemicals (TOrCs, including preservatives, antioxidants, disinfectants, oestrogens, alkyl-phenols and bisphenol-A) in surface water and wastewater has been developed and validated based on the optimisation of solid-phase extraction (SPE) followed by liquid chromatography-mass spectrometry (LC-MS) analysis. 500 mL acidified (pH = 2.5) water samples were pre-concentrated by Supel-Select HLB cartridge (200 mg, 6 mL) and eluted with 12 mL mixture of acetonitrile and ethyl acetate (50:50, v/v). This optimised SPE procedure could provide >75% recoveries for the majority of TOrCs. The instrumental methods were developed using two different LC-MS systems: a triple-quadrupole MS (QqQ-MS) and a hybrid quadrupole Orbitrap high resolution MS (Q-Orbitrap-HRMS). Both showed good performance data, but the former system provided better linearity and method precision, with the latter system providing 2-33 times lower detection limits. Different matrix effects were observed for both systems: No remarkable matrix effects were observed for Q-Orbitrap-HRMS but significant matrix effects were found in influent and river water samples for the QqQ-MS. This analytical method was subsequently employed to analyse the TOrCs in river waters and wastewaters from China successfully, which confirmed its applicability to environmental samples.

A Multimedia Fate Model to Support Chemical Management in China: A Case Study for Selected Trace Organics.

SESAMe v3.3, a spatially explicit multimedia fate model for China, is a tool suggested to support quantitative risk assessment for national scale chemical management. The key advantage over the previous version SESAMe v3.0 is consideration of spatially varied environmental pH. We evaluate the model performance using estimates of emission from total industry usage of three UV filters (benzophenone-3, octocrylene, and octyl methoxycinnamate) and three antimicrobials (triclosan, triclocarban, and climbazole). The model generally performs well for the six case study chemicals as shown by the comparison between predictions and measurements. The importance of accounting for chemical ionization is demonstrated with the fate and partitioning of both triclosan and climbazole sensitivity to environmental pH. The model predicts ionizable chemicals (triclosan, climbazole, benzophenone-3) to primarily partition into soils at steady state, despite hypothetically only being released to freshwaters, as a result of agricultural irrigation by freshwater. However, further model calibration is needed when more field data becomes available for soils and sediments and for larger areas of water. As an example, accounting for the effect of pH in the environmental risk assessment of triclosan, limited freshwater areas (0.03% or ca. 55 km(2)) in mainland China are modeled to exceed its conservative environmental no-effect threshold. SESAMe v3.3 can be used to support the development of chemical risk assessment methodologies with the spatial aspects of the model providing a guide to the identification regions of interest in which to focus monitoring campaigns or develop a refined risk assessment.

Ecological risks of home and personal care products in the riverine environment of a rural region in South China without domestic wastewater treatment facilities.

Home and personal care products (HPCPs) including biocides, benzotriazoles (BTs) and ultraviolet (UV) filters are widely used in our daily life. After use, they are discharged with domestic wastewater into the receiving environment. This study investigated the occurrence of 29 representative HPCPs, including biocides, BTs and UV filters, in the riverine environment of a rural region of South China where no wastewater treatment plants were present, and assessed their potential ecological risks to aquatic organisms. The results showed the detection of 11 biocides and 4 BTs in surface water, and 9 biocides, 3 BTs and 4 UV filters in sediment. In surface water, methylparaben (MeP), triclocarban (TCC), and triclosan (TCS) were detected at all sites with median concentrations of 9.23 ng/L, 2.64 ng/L and 5.39 ng/L, respectively. However, the highest median concentrations were found for clotrimazole (CLOT), 5-methyl-1H-benzotriazole (MBT) and carbendazim (CARB) at 55.6 ng/L, 33.7 ng/L and 13.8 ng/L, respectively. In sediment, TCC, TCS, and UV-326 were detected with their maximum concentrations up to 353 ng/g, 155 ng/g, and 133 ng/g, respectively. The concentrations for those detected HPCPs in surface water and sediment were generally lower in the upper reach (rural area) of Sha River than in the lower reach of Sha River with close proximity to Dongjiang River (Pt-test<0.05), indicating other input sources of HPCPs in the lower reach. Biocides showed significantly higher levels in surface water in the wet season than in the dry and intermediate seasons. Preliminary risk assessment demonstrated that the majority of HPCPs monitored represented low risk in surface waters. There are potentially greater risks to aquatic organisms from the use of TCS and TCC in the wet season than in dry and intermediate seasons in surface waters. This preliminary assessment also indicates potential concerns associated with TCC, TCS, DEET, CARB, and CLOT in sediments, although additional data should be generated to assess this fully. Thus future research is needed to investigate ecological effects of these HPCPs on benthic organisms in sediment of rural rivers receiving untreated wastewater discharge.

Characterization of para-Nitrophenol-Degrading Bacterial Communities in River Water by Using Functional Markers and Stable Isotope Probing.

Microbial degradation is a major determinant of the fate of pollutants in the environment. para-Nitrophenol (PNP) is an EPA-listed priority pollutant with a wide environmental distribution, but little is known about the microorganisms that degrade it in the environment. We studied the diversity of active PNP-degrading bacterial populations in river water using a novel functional marker approach coupled with [(13)C6]PNP stable isotope probing (SIP). Culturing together with culture-independent terminal restriction fragment length polymorphism analysis of 16S rRNA gene amplicons identified Pseudomonas syringae to be the major driver of PNP degradation in river water microcosms. This was confirmed by SIP-pyrosequencing of amplified 16S rRNA. Similarly, functional gene analysis showed that degradation followed the Gram-negative bacterial pathway and involved pnpA from Pseudomonas spp. However, analysis of maleylacetate reductase (encoded by mar), an enzyme common to late stages of both Gram-negative and Gram-positive bacterial PNP degradation pathways, identified a diverse assemblage of bacteria associated with PNP degradation, suggesting that mar has limited use as a specific marker of PNP biodegradation. Both the pnpA and mar genes were detected in a PNP-degrading isolate, P. syringae AKHD2, which was isolated from river water. Our results suggest that PNP-degrading cultures of Pseudomonas spp. are representative of environmental PNP-degrading populations.

Environmental Distributions of Benzo[a]pyrene in China: Current and Future Emission Reduction Scenarios Explored Using a Spatially Explicit Multimedia Fate Model.

SESAMe v3.0, a spatially explicit multimedia fate model with 50 × 50 km(2) resolution, has been developed for China to predict environmental concentrations of benzo[a]pyrene (BaP) using an atmospheric emission inventory for 2007. Model predictions are compared with environmental monitoring data obtained from an extensive review of the literature. The model performs well in predicting multimedia concentrations and distributions. Predicted concentrations are compared with guideline values; highest values with some exceedances occur mainly in the North China Plain, Mid Inner Mongolia, and parts of three northeast provinces, Xi'an, Shanghai, and south of Jiangsu province, East Sichuan Basin, middle of Guizhou and Guangzhou. Two potential future scenarios have been assessed using SESAMe v3.0 for 2030 as BaP emission is reduced by (1) technological improvement for coal consumption in energy production and industry sectors in Scenario 1 (Sc1) and (2) technological improvement and control of indoor biomass burning for cooking and indoor space heating and prohibition of open burning of biomass in 2030 in Scenario 2 (Sc2). Sc2 is more efficient in reducing the areas with exceedance of guideline values. Use of SESAMe v3.0 provides insights on future research needs and can inform decision making on options for source reduction.

Accounting for dissociation and photolysis: a review of the algal toxicity of triclosan.

Triclosan, an antimicrobial agent commonly used in down-the-drain consumer products, is toxic to freshwater microalgae. However, the rapid photolysis and pH-dependent dissociation of this compound may give rise to uncertainty in growth inhibition tests with freshwater microalgae, if these are not well characterized. Methods are presented to minimize these uncertainties by stabilizing pH with an organic buffering agent (Bis-Tris) and by the application of ultraviolet (UV) covers to remove UV wavelengths. Toxicity tests with these methods were in compliance with the validity criteria of the Organisation for Economic Co-operation and Development test 201, and no negative effects were seen in controls relative to the unmodified method. The methods were used for toxicity tests with triclosan at pH levels of 7.0, 8.0, and 8.5, yielding effective concentration, 10% values of 0.5 µg/L, 0.6 µg/L, and 12.1 µg/L, respectively. The observed change in toxicity with pH was proportional to the change in bioconcentration factor (BCF) as calculated using the cell model (a dynamic flux model based on the Fick-Nernst-Planck equations, in this case parameterized for an algal cell). Effect concentrations produced with the methods presented in the present study offer robust data on which to base risk assessment, and it is suggested that similar approaches be used to minimize uncertainty when other compounds that dissociate and photolyse are tested.

A new multimedia contaminant fate model for China: how important are environmental parameters in influencing chemical persistence and long-range transport potential?

We present a new multimedia chemical fate model (SESAMe) which was developed to assess chemical fate and behaviour across China. We apply the model to quantify the influence of environmental parameters on chemical overall persistence (POV) and long-range transport potential (LRTP) in China, which has extreme diversity in environmental conditions. Sobol sensitivity analysis was used to identify the relative importance of input parameters. Physicochemical properties were identified as more influential than environmental parameters on model output. Interactive effects of environmental parameters on POV and LRTP occur mainly in combination with chemical properties. Hypothetical chemicals and emission data were used to model POV and LRTP for neutral and acidic chemicals with different KOW/DOW, vapour pressure and pKa under different precipitation, wind speed, temperature and soil organic carbon contents (fOC). Generally for POV, precipitation was more influential than the other environmental parameters, whilst temperature and wind speed did not contribute significantly to POV variation; for LRTP, wind speed was more influential than the other environmental parameters, whilst the effects of other environmental parameters relied on specific chemical properties. fOC had a slight effect on POV and LRTP, and higher fOC always increased POV and decreased LRTP. Example case studies were performed on real test chemicals using SESAMe to explore the spatial variability of model output and how environmental properties affect POV and LRTP. Dibenzofuran released to multiple media had higher POV in northwest of Xinjiang, part of Gansu, northeast of Inner Mongolia, Heilongjiang and Jilin. Benzo[a]pyrene released to the air had higher LRTP in south Xinjiang and west Inner Mongolia, whilst acenaphthene had higher LRTP in Tibet and west Inner Mongolia. TCS released into water had higher LRTP in Yellow River and Yangtze River catchments. The initial case studies demonstrated that SESAMe performed well on comparing POV and LRTP of chemicals in different regions across China in order to potentially identify the most sensitive regions. This model should not only be used to estimate POV and LRTP for screening and risk assessments of chemicals, but could potentially be used to help design chemical monitoring programmes across China in the future.

Evolution of the sewage treatment plant model SimpleTreat: use of realistic biodegradability tests in probabilistic model simulations.

Given the large number of chemicals under regulatory scrutiny, models play a crucial role in the screening phase of the environmental risk assessment. The sewage treatment plant (STP) model SimpleTreat 3.1 is routinely applied as part of the European Union System for the Evaluation of Substances to estimate the fate and elimination of organic chemicals discharged via sewage. SimpleTreat estimates tend to be conservative and therefore only useful for lower-tier assessments. A probabilistic version of SimpleTreat was built on the updated version of the model (SimpleTreat 3.2, presented in a parallel article in this issue), embracing likeliest as well as worst-case conditions in a statistically robust way. Probabilistic parameters representing the variability of sewage characteristics, STP design, and operational parameters were based on actual STP conditions for activated sludge plants in Europe. An evaluation study was carried out for 4 chemicals with distinct sorption and biodegradability profiles: tonalide, triclosan, trimethoprim, and linear alkylbenzene sulfonate. Simulations incorporated information on biodegradability simulation studies with activated sludge (OECD 314B and OECD 303A tests). Good agreement for both median values and variability ranges was observed between model estimates and monitoring data. The uncertainty analysis highlighted the importance of refined data on partitioning and biodegradability in activated sludge to achieve realistic estimates. The study indicates that the best strategy to refine the exposure assessment of down-the-drain chemicals is by integrating higher-tier laboratory data with probabilistic STP simulations and, if possible, by comparing them with monitoring data for validation.

Evolution of the sewage treatment plant model SimpleTreat: applicability domain and data requirements.

SimpleTreat 3.1 is the sewage treatment plant (STP) model implemented in the European Union (EU) framework for the environmental risk assessment of chemicals. The model was originally designed for neutral hydrophobic chemicals, whereas many substances currently under regulatory scrutiny, are ionizable at environmental pH. Although the model has been adapted to describe ionization (SimpleTreat 3.1), the fate of organic ions is limited to the unbound aqueous phase, which seriously restricts the applicability domain. New regressions were implemented to estimate the sludge-water partition coefficient normalized to organic carbon (KOC ) of monovalent acids and bases from the octanol-water partition coefficient (KOW ), the dissociation constant (pKa) and the pH. We evaluated the updated model (SimpleTreat 3.2) with 10 test chemicals by comparing predictions with monitoring data collected from the literature. Test chemicals were specifically selected to challenge the applicability domain and to cover a wide range of functionality and physical-chemical properties. Although predicted effluent concentrations are generally conservative, SimpleTreat 3.2 provides reasonable estimates for use in lower-tier risk assessment for neutral and monovalent ionizable chemicals. The accuracy of the new KOC regressions is acceptable for monovalent acid but is lower for bases, for which measured sludge KOC is highly recommended. Measured KOC are also recommended for ionic surfactants and necessary for organic ligands, which may limit the applicability of SimpleTreat using a basic input data set. The conservative nature of model estimates reflects the default worst case, non-numerical parameterization of biodegradation rates and the assumption that biodegradation is limited to the unbound aqueous phase. The potential of refining the description of biodegradation using higher tier simulation tests is explored in a parallel article (Franco et al. this issue).

Prioritising chemicals used in personal care products in China for environmental risk assessment: application of the RAIDAR model.

China represents a significant market for the sale of personal care products (PCPs). Given the continuous emission of hundreds of chemicals used in PCPs to waste water and the aquatic environment after regular use, methods for prioritising the environmental risk assessment for China are needed. In an effort to assess the prioritisation of chemicals used in PCPs in China, we have identified the chemical ingredients used in 2500 PCPs released to the Chinese market in 2009, and estimated the annual emission of these chemicals. The physical-chemical property data for these substances have been estimated and used as model inputs in the RAIDAR model. In general, the RAIDAR model provides an overall assessment of the multimedia fate of chemicals, and provides a holistic approach for prioritising chemical ingredients. The prioritisation exercise conducted in this study is shown to be strongly influenced by loss processes, such as the removal efficiencies of WWT plants and biotransformation.