Predicted no effect concentration derivation as a significant source of variability in environmental hazard assessments of chemicals in aquatic systems: an international analysis

Freshwater ecotoxicity characterization factors for PMT/vPvM substances

This study addresses the gap in freshwater ecotoxicological characterization factors (CFs) for Persistent, Mobile, and Toxic (PMT) and Very Persistent and Very Mobile (vPvM) substances. These CFs are vital for integrating the ecotoxicity impacts of these chemicals into life cycle assessments. Our goals are twofold: first, to calculate experimental freshwater CFs for PMT/vPvM substances listed by the German Environment Agency (UBA); second, to compare these CFs with those from the USEtox database. The expanded UBA list includes 343 PMT/vPvM substances, each representing a unique chemical structure, and linked to 474 REACH-registered substances. This study successfully computed CFs for 244 substances, with 107 overlapping the USEtox database and 137 being new. However, ecotoxicity data limitations prevented CF determination for 97 substances. This research enhances our understanding of freshwater CFs for PMT/vPvM substances, covering 72% of UBA's 343 PMT/vPvM substances. Data scarcity remains a significant challenge, which invariably impedes CF calculations. Notably, the disparities observed between CF values in the USEtox database and those derived in this research largely stem from variations in ecotoxicity data. Consequently, this research underscores the dynamic nature of CFs for substances, emphasizing the need for regular updates to ensure their accuracy and relevance.

Derivation of species sensitivity distributions and ecotoxicity threshold values for 66 pesticide active ingredients and the hazard and risk they pose to freshwater waterways that discharge to the Great Barrier Reef, Australia

Pesticide active ingredients (PAIs) are one of the main contributors affecting water quality in the Great Barrier Reef Catchment Area (GBRCA). While an extensive list of pesticides is monitored in the GBRCA, only a limited number have water quality guideline values (WQGs), meaning it is not possible to know whether these PAIs are present at concentrations that may pose a hazard to the aquatic environment. In the current study, we derived 66 ecotoxicity threshold values (ETVs) for PAIs, the equivalent of WQGs, with a focus on PAIs applied to sugar cane. The hazard posed by PAIs monitored as part of the Great Barrier Reef Catchment Loads Monitoring Program (GBRCLMP) was assessed by comparing the derived ETVs with monitoring data from 2016/2017 to 2021/2022. The derived ETVs included herbicides, insecticides and fungicides, with the values that should protect 99 or 95 % of aquatic species (PC99 or PC95) spanning nine orders of magnitude. The concentrations of 10 PAIs exceeded their respective ETVs, giving a hazard quotient (HQ) >1. Of particular concern were insecticides chlorpyrifos, diazinon and methomyl, which have maximum HQ values >10. However, joint probability plots indicated that the PAIs generally pose a low risk to the aquatic environment, with most samples below the limit of reporting. As PAIs are predominantly found in mixtures in the GBRCA, the hazard posed by PAI mixtures was assessed by summing all individual HQ values in a sample for all PAIs with an ETV or WQG. On average, the insecticide active ingredient imidacloprid and herbicide active ingredients metolachlor, metsulfuron methyl, diuron and imazepic were the drivers of combined mixture hazard. Methomyl was an important contributor at some sites, suggesting that this pesticide should be considered for inclusion in any future PAI mixture hazard and/or risk assessment of the GBRCA.

Handling concentration data below the analytical limit in environmental mixture risk assessment: A case-study on pesticide river monitoring

Aquatic organisms are exposed to ever-changing complex mixtures of chemicals throughout their lifetime. Component-Based Mixture Risk Assessment (CBMRA) is a well-established methodology for water contaminant-mixture management, the use of which is growing due to improved access to reference ecotoxicity data and extensive monitoring datasets. It enables the translation of measured exposure concentrations of chemicals into biological effect values, and thus to quantitatively estimate the risk of the whole water sample (i.e., as a mixture). However, many factors can bias the final risk decision by impacting the risk metric components; thus, a careful design of the CBMRA is needed, taking into primary consideration the specific features of the dataset and mixture risk assessment assignments. This study systematically addressed the effects of the most common approaches used for handling the concentrations of chemicals below the limit of detection/quantification (LOD/LOQ) in CBMRA. The main results included: i) an informed CBMRA procedure that enables the tracking of the risk decisions triggered by substances below LOD/LOQ, ii) a conceptual map and guidance criteria to support the selection of the most suitable approach for specific scenarios and related interpretation; iii) a guided implementation of the informed CBMRA on dataset of pesticide concentrations in Italian rivers in 2020 (702,097 records).

Revisiting assessment factors for species sensitivity distributions as a function of sample size and variation in species sensitivity

To use species sensitivity distributions (SSDs) for ecological risk assessment, there are various uncertainties, which require applying assessment factors (AFs) accordingly. This study aims to quantify the uncertainty of estimating statistical distributions. Given a management goal of protecting 95% of species, the concentration that affects 5% of the species (HC5) is estimated. Since the true concentration affecting 5% of the species (population HC5) is unknown, the estimated HC5 is divided by an AF to derive the predicted no-effect concentration (PNEC), which is set as the protection goal, to compensate for the deviation in the estimated HC5 from the population HC5. Although the deviation between these two HC5 values depends on the sample size and the variation in sensitivity (standard deviation of the distribution) among species, there has been little discussion of how to quantify the degree of uncertainty. By assuming that toxicity values are a random sample from a lognormal distribution, we mathematically analyzed the SSD to derive the magnitude of AF needed to achieve a given protection goal (as an example, the protection of 95% of species with a probability of 95%). We successfully derived an equation that explicitly relates the magnitude of AF to the sample size and the variation in species sensitivity, providing a new basis to statistically determine the magnitude of AF for ecological risk assessments.

The influence of salinity on the chronic toxicity of shale gas flowback wastewater to freshwater organisms

The potential environmental risk associated with flowback waters generated during hydraulic fracturing of target shale gas formations needs to be assessed to enable management decisions and actions that prevent adverse impacts on aquatic ecosystems. Using direct toxicity assessment (DTA), we determined that the shale gas flowback wastewater (FWW) from two exploration wells (Tanumbirini-1 and Kyalla 117 N2) in the Beetaloo Sub-basin, Northern Territory, Australia were chronically toxic to eight freshwater biota. Salinity in the respective FWWs contributed 16% and 55% of the chronic toxicity at the 50% effect level. The remaining toxicity was attributed to unidentified chemicals and interactive effects from the mixture of identified organics, inorganics and radionuclides. The most sensitive chronic endpoints were the snail (Physa acuta) embryo development (0.08-1.1% EC10), microalga (Chlorella sp. 12) growth rate inhibition (0.23-3.7% EC10) and water flea (Ceriodaphnia cf. dubia) reproduction (0.38-4.9% EC10). No effect and 10% effect concentrations from the DTA were used in a species sensitivity distribution to derive "safe" dilutions of 1 in 300 and 1 in 1140 for the two FWWs. These dilutions would provide site-specific long-term protection to 95% of aquatic biota in the unlikely event of an accidental spill or seepage.

Ecological Thresholds of Toxicological Concern: A Review

The ecological threshold of toxicological concern (ecoTTC) is analogous to traditional human health-based TTCs but with derivation and application to ecological species. An ecoTTC is computed from the probability distribution of predicted no effect concentrations (PNECs) derived from either chronic or extrapolated acute toxicity data for toxicologically or chemically similar groups of chemicals. There has been increasing interest in using ecoTTCs in screening level environmental risk assessments and a computational platform has been developed for derivation with aquatic species toxicity data (https://envirotoxdatabase.org/). Current research and development areas include assessing mode of action-based chemical groupings, conservatism in estimated PNECs and ecoTTCs compared to existing regulatory values, and the influence of taxa (e.g., algae, invertebrates, and fish) composition in the distribution of PNEC values. The ecoTTC continues to develop as a valuable alternative strategy within the toolbox of traditional and new approach methods for ecological chemical assessment. This brief review article describes the ecoTTC concept and potential applications in ecological risk assessment, provides an overview of the ecoTTC workflow and how the values can be derived, and highlights recent developments and ongoing research. Future applications of ecoTTC concept in different disciplines are discussed along with opportunities for its use.

Comparisons of PNEC derivation logic flows under example regulatory schemes and implications for ecoTTC

Derivation of Predicted No Effect Concentrations (PNECs) for aquatic systems is the primary deterministic form of hazard extrapolation used in environmental risk assessment. Depending on the data availability, different regulatory jurisdictions apply application factors (AFs) to the most sensitive measured endpoint to derive the PNEC for a chemical. To assess differences in estimated PNEC values, two PNEC determination methodologies were applied to a curated public database using the EnviroTox Platform (www.EnviroToxdatabase.org). PNECs were derived for 3647 compounds using derivation procedures based on example US EPA and a modified European Union chemical registration procedure to allow for comparisons. Ranked probability distributions of PNEC values were developed and 5th percentile values were calculated for the entire dataset and scenarios where full acute or full chronic data sets were available. The lowest PNEC values indicated categorization based on chemical attributes and modes of action would lead to improved extrapolations. Full acute or chronic datasets gave measurably higher 5th percentile PNEC values. Algae were under-represented in available ecotoxicity data but drove PNECs disproportionately. Including algal inhibition studies will be important in understanding chemical hazards. The PNEC derivation logic flows are embedded in the EnviroTox Platform providing transparent and consistent PNEC derivations and PNEC distribution calculations.

A Novel Approach to Derive the Predicted No-Effect Concentration (PNEC) of Benzophenone-3 (BP-3) Using the Species Sensitivity Distribution (SSD) Method: Suggestion of a New PNEC Value for BP-3

The necessity for the aquatic ecological risk assessment for benzophenone-3 (BP-3) is increasing due to its high toxic potential and high detection frequency in freshwater. The initial step in the ecological risk assessment is to determine predicted no-effect concentration (PNEC). This study derived PNEC of BP-3 in freshwater using a species sensitivity distribution (SSD) approach, whilst existing PNECs are derived using assessment factor (AF) approaches. A total of eight chronic toxicity values, obtained by toxicity testing and a literature survey, covering four taxonomic classes (fish, crustaceans, algae, and cyanobacteria) were used for PNEC derivation. Therefore, the quantity and quality of the toxicity data met the minimum requirements for PNEC derivation using an SSD approach. The PNEC derived in this study (73.3 μg/L) was far higher than the environmental concentration detected in freshwater (up to 10.4 μg/L) as well as existing PNECs (0.67~1.8 μg/L), mainly due to the difference in the PNEC derivation methodology (i.e., AF vs. SSD approach). Since the SSD approach is regarded as more reliable than the AF approach, we recommend applying the PNEC value derived in this study for the aquatic ecological risk assessment of BP-3, as the use of the existing PNEC values seems to unnecessarily overestimate the potential ecological risk of BP-3 in freshwater.

Can We Reasonably Predict Chronic Species Sensitivity Distributions from Acute Species Sensitivity Distributions?

Estimation of species sensitivity distributions (SSDs) is an essential way to estimate the hazardous concentration for 5% of the species (HC5) and thus to derive a "safe" concentration. Here, we examined whether we can reasonably predict SSDs based on chronic no-observed-effect concentration or level (chronic SSDs) from SSDs based on acute median effective/lethal concentration (acute SSDs) by analyzing log-normal SSDs of 150 chemicals. Chronic SSD means were, on average, 10 times lower than acute SSD means. The standard deviations (SDs) of acute and chronic SSDs closely overlapped. Our detailed analysis suggests that the acute SSD SD can be used as an initial estimate of the chronic SSD SD if the number of tested species is ≥10. There were no significant differences in the ratios of chronic to acute SSD means or SDs among three different modes of action. The HC5 of chronic SSDs was, on average, 10 times lower than the acute SSD HC5. We suggest that multiplication of the acute HC5 by a factor of 0.1 is a defensible way to obtain a first approximation of the chronic HC5, particularly when relative ecological risks of chemicals are being evaluated. Further study is needed to develop methods for a more accurate estimation of chronic SSDs.

Extrapolation Factors for Characterizing Freshwater Ecotoxicity Effects

Various environmental and chemical assessment frameworks including ecological risk assessment and life cycle impact assessment aim at evaluating long-term ecotoxicity effects. Chronic test data are reported under the European Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) regulation for various chemicals. However, chronic data are missing for a large fraction of marketed chemicals, for which acute test results are often available. Utilizing acute data requires robust extrapolation factors across effect endpoints, exposure durations, and species groups. We propose a decision tree based on strict criteria for curating and selecting high-quality aquatic ecotoxicity information available in REACH for organic chemicals, to derive a consistent set of generic and species group-specific extrapolation factors. Where ecotoxicity effect data are not available at all, we alternatively provide extrapolations from octanol-water partitioning coefficients as suitable predictor for chemicals with nonpolar narcosis as mode of action. Extrapolation factors range from 0.2 to 7 and are higher when simultaneously extrapolating across effect endpoints and exposure durations. Our results are consistent with previously reported values, while considering more endpoints, providing species group-specific factors, and characterizing uncertainty. Our proposed decision tree can be adapted to curate information from additional data sources as well as data for other environments, such as sediment ecotoxicity. Our approach and robust extrapolation factors help to increase the substance coverage for characterizing ecotoxicity effects across chemical and environmental assessment frameworks. Environ Toxicol Chem 2019;38:2568-2582. © 2019 SETAC.

Revising Environmental Quality Standards: Lessons Learned

An environmental quality standard (EQS) is a threshold value applied in regulatory monitoring for retrospective environmental risk assessment. However, an EQS may vary with time and between countries with shared water bodies, challenging coherent risk management. This study aimed to analyze the underlying reasons for changes in EQS values following a revision of previously derived EQSs for 62 substances. Relevant data were retrieved from publicly accessible databases, available literature, registration dossiers, and, in some cases, provided by manufacturers. Ecotoxicological data were assessed regarding reliability and relevance. As in previous studies, EQS derivation followed the European Union guideline. Overall, 61 annual average EQSs (AA-EQS) and 58 maximum acceptable concentration EQSs (MAC-EQS) were derived. Size and completeness of data sets generally increased due to the revision. AA-EQSs increased in 13 cases and decreased in 21 cases. MAC-EQSs increased in 22 cases and decreased in 11 cases. Most EQSs were derived using the deterministic assessment factor (AF) method. The number of substances for which EQSs were derived probabilistically by reference to the species sensitivity distribution (SSD) method increased from 2 to 5 AA-EQSs and from 6 to 11 MAC-EQSs. For AA-EQS derivation, AFs were reduced in 14 cases and increased in 6 cases. For MAC-EQS derivation, AFs were reduced in 9 cases and increased in 2 cases. Results demonstrate that the revisions did not generally lead to either lower or higher EQSs. The majority of EQSs (>93%) changed less than 10-fold. Clearly, EQSs based on small or incomplete data sets with large AFs were more prone to considerable changes in their numeric values when revised than EQSs based on SSDs. Thus, revision can reduce uncertainty and increase robustness of an EQS. In this study, however, available data continued to be insufficient to construct SSDs for the majority of substances. This was mostly due to a lack of reliable data. Integr Environ Assess Manag 2019;00:1-13. © 2019 SETAC.

How Specific Is Site-Specific? A Review and Guidance for Selecting and Evaluating Approaches for Deriving Local Water Quality Benchmarks

Existing prescriptive guidance on the derivation of local water quality benchmarks (WQBs; e.g., guideline values, criteria, standards) for protecting aquatic ecosystems is limited to only 3 to 4 specific approaches. These approaches do not represent the full suite available for deriving local WQBs for multiple types of water quality-related issues. The general lack of guidance is inconsistent with the need for, and benefits of, local WQBs, and can constrain the appropriate selection and subsequent evaluation of derivation approaches. Consequently, the defensibility of local WQBs may not be commensurate with the nature of the issues for which they are derived. Moreover, where local WQBs are incorporated into regulatory requirements, the lack of guidance presents a potential risk to the derivation of appropriate WQBs and the achievement of desired environmental outcomes. This review addresses the deficiency in guidance by 1) defining local WQBs and outlining initial considerations for deciding if one is required; 2) summarizing the existing regulatory context; 3) summarizing existing guidance and identifying gaps; 4) describing strengths, weaknesses, and potential applications of a range of derivation approaches based on laboratory and/or field data; and 5) presenting a conceptual framework for appropriately selecting and evaluating a derivation approach to best suit the need. The guidance incorporates an existing set of guiding principles for deriving local WQBs and reinforces an existing categorization of site-adapted and site-specific WQBs. The conceptual framework recognizes the need to strike an appropriate balance between effort and ecological risk and, thus, embeds the concept of fit-for-purpose by considering both the significance of the issue being assessed and the extent to which the approach provides confidence that the ecosystem will be appropriately protected. The guidance can be used by industry, regulators, and others for both the a priori selection and the post hoc evaluation of appropriate approaches for deriving local WQBs. Integr Environ Assess Manag 2019;15:683-702. © 2019 The Authors.

On the impact of sample size on median lethal concentration estimation in acute fish toxicity testing: Is n = 7/group enough?

The fish acute toxicity test method is foundational to aquatic toxicity testing strategies, yet the literature lacks a concise sample size assessment. Although various sources address sample size, historical precedent seems to play a larger role than objective measures. We present a novel and comprehensive quantification of the effect of sample size on estimation of the median lethal concentration (LC50), covering a wide range of scenarios. The results put into perspective the practical differences across a range of sample sizes, from n = 5/concentration up to n = 23/concentration. We also provide a framework for setting sample size guidance illustrating ways to quantify the performance of LC50 estimation, which can be used to set sample size guidance given reasonably difficult (or worst-case) scenarios. There is a clear benefit to larger sample size studies: they reduce error in the determination of LC50s, and lead to more robust safe environmental concentration determinations, particularly in cases likely to be called worst-case (shallow slope and true LC50 near the edges of the concentration range). Given that the use of well-justified sample sizes is crucial to reducing uncertainty in toxicity estimates, these results lead us to recommend a reconsideration of the current de minimis 7/concentration sample size for critical studies (e.g., studies needed for a chemical registration, which are being tested for the first time, or involving difficult test substances). Environ Toxicol Chem 2018;37:1565-1578. © 2018 SETAC.

Environmental quality benchmarks-the good, the bad, and the ugly

Environmental quality benchmarks (EQBs) such as water or sediment quality guidelines comprise one line of evidence for assessing the potential harm from chemicals and other stressors (physical, biological). They are useful but not perfect tools, should not always be used, and should never be used alone for final decision-making. The "good" can be designed to be situation-specific and can provide understandable scientific input to decision-makers. The "bad" includes perception that they are absolutes (i.e., definitive binary decision points), no or limited adaptability based on good science or common sense, and protection of individual organisms not populations of organisms. The "ugly" includes benchmarks based on simplistic indices (information loss, misleading results), misuse of biomarkers, and misapplication of EQBs. Other factors to be considered include the following: appropriately deriving EQBs, uncertainty, the laboratory is not the field, contaminant uptake and cause-effect, and specifics regarding sediment quality benchmarks (i.e., their specific "good," "bad," and "ugly" components). EQBs are not always needed or useful.

Defence mechanisms: the role of physiology in current and future environmental protection paradigms

Ecological risk assessments principally rely on simplified metrics of organismal sensitivity that do not consider mechanism or biological traits. As such, they are unable to adequately extrapolate from standard laboratory tests to real-world settings, and largely fail to account for the diversity of organisms and environmental variables that occur in natural environments. However, an understanding of how stressors influence organism health can compensate for these limitations. Mechanistic knowledge can be used to account for species differences in basal biological function and variability in environmental factors, including spatial and temporal changes in the chemical, physical and biological milieu. Consequently, physiological understanding of biological function, and how this is altered by stressor exposure, can facilitate proactive, predictive risk assessment. In this perspective article, existing frameworks that utilize physiological knowledge (e.g. biotic ligand models, adverse outcomes pathways and mechanistic effect models), are outlined, and specific examples of how mechanistic understanding has been used to predict risk are highlighted. Future research approaches and data needs for extending the incorporation of physiological information into ecological risk assessments are discussed. Although the review focuses on chemical toxicants in aquatic systems, physical and biological stressors and terrestrial environments are also briefly considered.

Criteria for assessing the ecological risk of nonylphenol for aquatic life in Chinese surface fresh water

The typical environmental endocrine disruptor nonylphenol is becoming an increasingly common pollutant in both fresh and salt water; it compromises the growth and development of many aquatic organisms. As yet, water quality criteria with respect to nonylphenol pollution have not been established in China. Here, the predicted "no effect concentration" of nonylphenol was derived from an analysis of species sensitivity distribution covering a range of species mainly native to China, as a means of quantifying the ecological risk of nonylphenol in surface fresh water. The resulting model, based on the log-logistic distribution, proved to be robust; the minimum sample sizes required for generating a stable estimate of HC₅ were 12 for acute toxicity and 13 for chronic toxicity. The criteria maximum concentration and criteria continuous concentration were, respectively 18.49 μg L^-1 and 1.85 μg L^-1. Among the 24 sites surveyed, two were associated with a high ecological risk (risk quotient >1) and 12 with a moderate ecological risk (risk quotient >0.1). The potentially affected fraction ranged from 0.008% to 24.600%. The analysis provides a theoretical basis for both short- and long-term risk assessments with respect to nonylphenol, and also a means to quantify the risk to aquatic ecosystems.

Future needs and recommendations in the development of species sensitivity distributions: Estimating toxicity thresholds for aquatic ecological communities and assessing impacts of chemical exposures

A species sensitivity distribution (SSD) is a probability model of the variation of species sensitivities to a stressor, in particular chemical exposure. The SSD approach has been used as a decision support tool in environmental protection and management since the 1980s, and the ecotoxicological, statistical, and regulatory basis and applications continue to evolve. This article summarizes the findings of a 2014 workshop held by the European Centre for Toxicology and Ecotoxicology of Chemicals and the UK Environment Agency in Amsterdam, The Netherlands, on the ecological relevance, statistical basis, and regulatory applications of SSDs. An array of research recommendations categorized under the topical areas of use of SSDs, ecological considerations, guideline considerations, method development and validation, toxicity data, mechanistic understanding, and uncertainty were identified and prioritized. A rationale for the most critical research needs identified in the workshop is provided. The workshop reviewed the technical basis and historical development and application of SSDs, described approaches to estimating generic and scenario-specific SSD-based thresholds, evaluated utility and application of SSDs as diagnostic tools, and presented new statistical approaches to formulate SSDs. Collectively, these address many of the research needs to expand and improve their application. The highest priority work, from a pragmatic regulatory point of view, is to develop a guidance of best practices that could act as a basis for global harmonization and discussions regarding the SSD methodology and tools. Integr Environ Assess Manag 2017;13:664-674. © 2016 SETAC.

Does the Choice of NOEC or EC10 Affect the Hazardous Concentration for 5% of the Species?

We evaluated if the choice of no observed effect concentration (NOEC) or a 10% effect concentration (EC10) affects the hazardous concentrations for 5% of the species (HC5s) estimated from species sensitivity distributions (SSDs). By reviewing available literature reporting NOECs and reanalyzing original toxicity data to estimate EC10s, we developed two SSDs for five chemicals (zinc, lead, nonylphenol, 3,4-dichlorobenzenamine, and lindane) based separately on 9-19 EC10s and NOECs. On average, point estimates of HC5s based on EC10s were 1.2 (range of 0.6-1.9) times higher than those based on NOECs. However, both EC10-based and NOEC-based HC5s estimated for five substances were on the same order of magnitude, and their 95% confidence intervals overlapped considerably. Thus, although EC10 was chosen as a representative of ECx in this study, our results suggest that the choice of ECx (e.g., EC5, EC10, or EC20) or NOEC does not largely affect the resulting HC5s. Therefore, use of NOECs would be acceptable particularly in regulatory contexts, although the NOEC has important shortcomings and should be used with caution.

Critical predicted no effect concentrations (PNECs) should not be based on a single toxicity test

Predicted no-effect concentrations (PNECs), which represent the concentration of a substance below which an unacceptable effect most likely will not occur, are widely used for risk assessment and in environmental policy and regulation. They are typically based on single-species laboratory toxicity tests; often, a single test result for the most sensitive endpoints drives the derivation of a PNEC. In the present study, the authors provide a case study emphasizing the importance of determining the reliability of those most sensitive endpoints. Five 21-d Daphnia magna toxicity tests conducted using the same procedures by 2 laboratories gave 20% inhibitory concentration responses to a specific ionic composition of total dissolved solids that varied from 684 mg/L to more than 1510 mg/L. The concentration-response curve was shallow; thus, these differences could have been attributable to chance alone. The authors strongly recommend that the most sensitive endpoints that determine PNECs not be based on a single toxicity test result but rather on the geometric mean of at least 3 test results to adequately assess and bound test variability, especially when the concentration-response curve is shallow.

Issues to consider in the derivation of water quality benchmarks for the protection of aquatic life

While water quality benchmarks for the protection of aquatic life have been in use in some jurisdictions for several decades (USA, Canada, several European countries), more and more countries are now setting up their own national water quality benchmark development programs. In doing so, they either adopt an existing method from another jurisdiction, update on an existing approach, or develop their own new derivation method. Each approach has its own advantages and disadvantages, and many issues have to be addressed when setting up a water quality benchmark development program or when deriving a water quality benchmark. Each of these tasks requires a special expertise. They may seem simple, but are complex in their details. The intention of this paper was to provide some guidance for this process of water quality benchmark development on the program level, for the derivation methodology development, and in the actual benchmark derivation step, as well as to point out some issues (notably the inclusion of adapted populations and cryptic species and points to consider in the use of the species sensitivity distribution approach) and future opportunities (an international data repository and international collaboration in water quality benchmark development).