Lung cancer mortality in the European cohort of titanium dioxide workers: a reanalysis of the exposure-response relationship.

OBJECTIVES: Animal bioassays have demonstrated convincing evidence of the potential carcinogenicity to humans of titanium dioxide (TiO2), but limitations in cohort studies have been identified, among which is the healthy worker survivor effect (HWSE). We aimed to address this bias in a pooled study of four cohorts of TiO2 workers. METHODS: We reanalysed data on respirable TiO2 dust exposure and lung cancer mortality among 7341 male workers employed in TiO2 production in Finland, France, UK and Italy using the parametric g-formula, considering three hypothetical interventions: setting annual exposures at 2.4 (U.S. occupational exposure limit), 0.3 (German limit) and 0 mg/m3 for 25 and 35 years. RESULTS: The HWSE was evidenced. Taking this into account, we observed a positive association between lagged cumulative exposure to TiO2 and lung cancer mortality. The estimated number of lung cancer deaths at each age group decreased across increasingly stringent intervention levels. At age 70 years, the estimated number of lung cancer deaths expected in the cohort after 35-year exposure was 293 for exposure set at 2.4 mg/m3, 235 for exposure set at 0.3 mg/m3, and 211 for exposure set at 0 mg/m3. CONCLUSION: This analysis shows that HWSE can hide an exposure-response relationship. It also shows that TiO2 epidemiological data could demonstrate an exposure-effects relationship if analysed appropriately. More epidemiological studies and similar reanalyses of existing cohort studies are warranted to corroborate the human carcinogenicity of TiO2. This human evidence, when combined with the animal evidence, strengthens the overall evidence of carcinogenicity of TiO2.

rbioacc: An R-package to analyze toxicokinetic data.

The R-package rbioacc allows to analyse experimental data from bioaccumulation tests where organisms are exposed to a chemical (exposure) then put into clean media (depuration). Internal concentrations are measured over time during the experiment. rbioacc provides turnkey functions to visualise and analyse such data. Under a Bayesian framework, rbioacc fits a generic one-compartment toxicokinetic model built from the data. It provides TK parameter estimates (uptake and elimination rates) and standard bioaccumulation metrics. All parameter estimates, bioaccumulation metrics and predictions of internal concentrations are delivered with their uncertainty. Bioaccumulation metrics are provided in support of environmental risk assessment, in full compliance with regulatory requirements required to approve market release of chemical substances. This paper provides worked examples of the use of rbioacc from data collected through standard bioaccumulation tests, publicly available within the scientific literature. These examples constitute step-by-step user-guides to analyse any new data set, uploaded in the right format.

Improvements in Estimating Bioaccumulation Metrics in the Light of Toxicokinetic Models and Bayesian Inference.

The surveillance of chemical substances in the scope of Environmental Risk Assessment (ERA) is classically performed through bio-assays from which data are collected and then analysed and/or modelled. Some analysis are based on the fitting of toxicokinetic (TK) models to assess the bioaccumulation capacity of chemical substances via the estimation of bioaccumulation metrics as required by regulatory documents. Given that bio-assays are particularly expensive and time consuming, it is of crucial importance to deeply benefit from all information contained in the data. By revisiting the calculation of bioaccumulation metrics under a Bayesian framework, this paper suggests changes in the way of characterising the bioaccumulation capacity of chemical substances. For this purpose, a meta-analysis of a data-rich TK database was performed, considering uncertainties around bioaccumulation metrics. Our results were statistically robust enough to suggest an additional criterion to the single median estimate of bioaccumulation metrics to assign a chemical substance to a given bioaccumulation capacity. Our proposal is to use the 75th percentile of the uncertainty interval of the bioaccumulation metrics, which revealed an appropriate complement for the classification of chemical substances (e.g. PBT (persistent, bioaccumulative and toxic) and vPvB (very persistent and very bioaccumulative) under the EU chemicals legislation). The 75% quantile proved its efficiency, similarly classifying 90% of the chemical substances as the conventional method.

New Insights to Compare and Choose TKTD Models for Survival Based on an Interlaboratory Study for Lymnaea stagnalis Exposed to Cd.

Toxicokinetic-toxicodynamic (TKTD) models, as the General Unified Threshold model of Survival (GUTS), provide a consistent process-based framework compared to classical dose-response models to analyze both time and concentration-dependent data sets. However, the extent to which GUTS models (Stochastic Death (SD) and Individual Tolerance (IT)) lead to a better fitting than classical dose-response model at a given target time (TT) has poorly been investigated. Our paper highlights that GUTS estimates are generally more conservative and have a reduced uncertainty through smaller credible intervals for the studied data sets than classical TT approaches. Also, GUTS models enable estimating any x% lethal concentration at any time (LCx,t), and provide biological information on the internal processes occurring during the experiments. While both GUTS-SD and GUTS-IT models outcompete classical TT approaches, choosing one preferentially to the other is still challenging. Indeed, the estimates of survival rate over time and LCx,t are very close between both models, but our study also points out that the joint posterior distributions of SD model parameters are sometimes bimodal, while two parameters of the IT model seems strongly correlated. Therefore, the selection between these two models has to be supported by the experimental design and the biological objectives, and this paper provides some insights to drive this choice.

Optimizing the design of a reproduction toxicity test with the pond snail Lymnaea stagnalis.

This paper presents the results from two ring-tests addressing the feasibility, robustness and reproducibility of a reproduction toxicity test with the freshwater gastropod Lymnaea stagnalis (RENILYS strain). Sixteen laboratories (from inexperienced to expert laboratories in mollusc testing) from nine countries participated in these ring-tests. Survival and reproduction were evaluated in L. stagnalis exposed to cadmium, tributyltin, prochloraz and trenbolone according to an OECD draft Test Guideline. In total, 49 datasets were analysed to assess the practicability of the proposed experimental protocol, and to estimate the between-laboratory reproducibility of toxicity endpoint values. The statistical analysis of count data (number of clutches or eggs per individual-day) leading to ECx estimation was specifically developed and automated through a free web-interface. Based on a complementary statistical analysis, the optimal test duration was established and the most sensitive and cost-effective reproduction toxicity endpoint was identified, to be used as the core endpoint. This validation process and the resulting optimized protocol were used to consolidate the OECD Test Guideline for the evaluation of reproductive effects of chemicals in L. stagnalis.

Modelling algae-duckweed interaction under chemical pressure within a laboratory microcosm.

Contaminant effects on species are generally assessed with single-species bioassays. As a consequence, interactions between species that occur in ecosystems are not taken into account. To investigate the effects of contaminants on interacting species dynamics, our study describes the functioning of a 2-L laboratory microcosm with two species, the duckweed Lemna minor and the microalgae Pseudokirchneriella subcapitata, exposed to cadmium contamination. We modelled the dynamics of both species and their interactions using a mechanistic model based on coupled ordinary differential equations. The main processes occurring in this two-species microcosm were thus formalised, including growth and settling of algae, growth of duckweeds, interspecific competition between the two species and cadmium effects. We estimated model parameters by Bayesian inference, using simultaneously all the data issued from multiple laboratory experiments specifically conducted for this study. Cadmium concentrations ranged between 0 and 50 µg·L(-1). For all parameters of our model, we obtained biologically realistic values and reasonable uncertainties. Only duckweed dynamics was affected by interspecific competition, while algal dynamics was not impaired. Growth rate of both species decreased with cadmium concentration, as well as competition intensity showing that the interspecific competition pressure on duckweed decreased with cadmium concentration. This innovative combination of mechanistic modelling and model-guided experiments was successful to understand the algae-duckweed microcosm functioning without and with contaminant. This approach appears promising to include interactions between species when studying contaminant effects on ecosystem functioning.

Constructing Time-Resolved Species Sensitivity Distributions Using a Hierarchical Toxico-Dynamic Model.

Classical species sensitivity distribution (SSD) is used to assess the threat to ecological communities posed by a contaminant and derive a safe concentration. It suffers from several well-documented weaknesses regarding its ecological realism and statistical soundness. Criticism includes that SSD does not take time-dependence of the data into account, that safe concentrations obtained from SSD might not be entirely protective of the target communities, and that there are issues of statistical representativity and of uncertainty propagation from the experimental data. We present a hierarchical toxico-dynamic (TD) model to simultaneously address these weaknesses: TD models incorporate time-dependence and allow improvement of the ecological relevance of safe concentrations, while the hierarchical approach affords appropriate propagation of uncertainty from the original data. We develop this model on a published data set containing the salinity tolerance over 72 h of 217 macroinvertebrate taxa, obtained through rapid toxicity testing (RTT). The shrinkage properties of the hierarchical model prove particularly adequate for modeling inhomogeneous RTT data. Taking into account the large variability in the species response, the model fits the whole data set well. Moreover, the model predicts a time-independent safe concentration below that obtained with classical SSD at 72 h, demonstrating under-protectiveness of the classical approach.

Hierarchical modelling of species sensitivity distribution: development and application to the case of diatoms exposed to several herbicides.

The species sensitivity distribution (SSD) is a key tool to assess the ecotoxicological threat of contaminants to biodiversity. For a contaminant, it predicts which concentration is safe for a community of species. Widely used, this approach suffers from several drawbacks: (i) summarizing the sensitivity of each species by a single value entails a loss of valuable information about the other parameters characterizing the concentration-effect curves; (ii) it does not propagate the uncertainty on estimated sensitivities into the SSD; (iii) the hazardous concentration estimated with SSD only indicates the threat to biodiversity, without any insight about a global response of the community related to the measured endpoint. To remedy these drawbacks, we built a global hierarchical model including the concentration-effect model together with the distribution law of the SSD. We revisited the current SSD approach to account for more sources of variability and uncertainty into the prediction than the traditional analysis and to assess a global response for the community. Working within a Bayesian framework, we were able to compute an SSD taking into account the uncertainty from the original raw data. We also developed a quantitative indicator of a global response of the community to the contaminant. We applied this methodology to study the toxicity and the risk of six herbicides to benthic diatoms from Lake Geneva, based on the biomass endpoint. Our approach highlighted a wide variability within the set of diatom species for all the parameters of the concentration-effect model and a potential correlation between them. Remarkably, variability of the shape parameter of the model and correlation had not been considered before. Comparison between the SSD and the global response of the community revealed that protecting 95% of the species might preserve only 80-86% of the global response. Finally, propagating the uncertainty on the estimated sensitivity showed that building an SSD on a low level of effect, such as EC10, might be unreasonable as it induces a large uncertainty on the result.

Statistical handling of reproduction data for exposure-response modeling.

Reproduction data collected through standard bioassays are classically analyzed by regression in order to fit exposure-response curves and estimate ECx values (x% effective concentration). But regression is often misused on such data, ignoring statistical issues related to (i) the special nature of reproduction data (count data), (ii) a potential inter-replicate variability, and (iii) a possible concomitant mortality. This paper offers new insights in dealing with those issues. Concerning mortality, particular attention was paid not to waste any valuable data-by dropping all the replicates with mortality-or to bias ECx values. For that purpose we defined a new covariate summing the observation periods during which each individual contributes to the reproduction process. This covariate was then used to quantify reproduction-for each replicate at each concentration-as a number of offspring per individual-day. We formulated three exposure-response models differing by their stochastic part. Those models were fitted to four data sets and compared using a Bayesian framework. The individual-day unit proved to be a suitable approach to use all the available data and prevent bias in the estimation of ECx values. Furthermore, a nonclassical negative-binomial model was shown to correctly describe the inter-replicate variability observed in the studied data sets.

Ecological modeling for the extrapolation of ecotoxicological effects measured during in situ assays in Gammarus.

Evaluating the effects of chemical contamination on populations and ecological communities still constitutes a challenging necessity in environmental management. However, the toxic effects of contaminants are commonly measured by means of organism-level responses. Linking such effects measures with ecological models is a promising way to determine population-level impacts. In this way, population models are currently increasingly used in predictive risk assessment procedures, but their use in environmental diagnostic framework remains limited due to their lack of ecological realism. The present study with the crustacean Gammarus fossarum, a sentinel species in freshwater monitoring, combines a dual field and laboratory experimental approach with a population modeling framework. In this way, we developed an ecologically relevant periodic matrix population model for Gammarus. This model allowed us to capture the population dynamics in the field, and to understand the particular pattern of demographic sensitivities induced by Gammarus life-history phenology. The model we developed provided a robust population-level assessment of in situ-based effects measures recorded during a biomonitoring program on a French watershed impacted by past mining activities. Thus, our study illustrates the potential of population modeling when seeking to decipher the role of environmental toxic contamination in ecological perturbations.

Development and validation of an OECD reproductive toxicity test guideline with the pond snail Lymnaea stagnalis (Mollusca, Gastropoda).

The OECD test guideline development program has been extended in 2011 to establish a partial life-cycle protocol for assessing the reproductive toxicity of chemicals to several mollusk species, including the great pond snail Lymnaea stagnalis. In this paper, we summarize the standard draft protocol for a reproduction test with this species, and present inter-comparison results obtained in a 56-day prevalidation ring-test using this protocol. Seven European laboratories performed semi-static tests with cultured snails of the strain Renilys® exposed to nominal concentrations of cadmium chloride (from 53 to 608µgCdL(-1)). Cd concentrations in test solutions were analytically determined to confirm accuracy in the metal exposure concentrations in all laboratories. Physico-chemical and biological validity criteria (namely dissolved oxygen content >60% ASV, water temperature 20±1°C, control snail survival >80% and control snail fecundity >8 egg-masses per snail over the test period) were met in all laboratories which consistently demonstrated the reproductive toxicity of Cd in snails using the proposed draft protocol. Effect concentrations for fecundity after 56days were reproducible between laboratories (68

Mechanistic analysis of the sub chronic toxicity of La and Gd in Daphnia magna based on TKTD modelling and synchrotron X-ray fluorescence imaging.

The release of lanthanides (Ln) into the environment has increased in recent decades due to their expanding applications in society. Studying their toxicity in aquatic ecosystems is urgent and challenging, with contradictory evidence presented in the literature. This study compared the biodistribution of La and Gd in Daphnia magna exposed to sub-chronic conditions and developed the first Toxicokinetic-Toxicodynamic (TKTD) model for these lanthanides with this model crustacean. D. magna were initially exposed for 7 days to concentrations close to the LC50 of La (2.10 mg L-1) and Gd (1.70 mg L-1). After exposure, half of the live daphnids were introduced in a clean media to allow depuration over 24 h, while the other organisms were directly prepared for synchrotron imaging measurements. Synchrotron X-ray fluorescence analysis revealed that metal distribution in the organisms was similar for both La and Gd, predominantly localized in the intestinal tract, even after the depuration process. These results indicate that ingested metal can adversely affect organisms under sub-chronic exposure conditions, highlighting the importance of using nominal concentrations as a more suitable indicator of metal bioavailability for risk assessment. The General Unified Threshold Model of Survival (GUTS) TKTD framework, in its reduced form (GUTS-RED), was developed for La and Gd using dissolved and nominal concentrations. D. magna were exposed for 7 days to concentrations from 0.5 to 5 mg L-1 of La or Gd and mortality monitored daily. The mechanistic model revealed a faster toxicokinetics for La than Gd and a higher toxicity for Gd than La in the organism. This study confirmed, despite similar chemical properties, the variation in both toxicity and toxicokinetics between these two metals.

Editorial trend: adverse outcome pathway (AOP) and computational strategy - towards new perspectives in ecotoxicology.

The adverse outcome pathway (AOP) has been conceptualized in 2010 as an analytical construct to describe a sequential chain of causal links between key events, from a molecular initiating event leading to an adverse outcome (AO), considering several levels of biological organization. An AOP aims to identify and organize available knowledge about toxic effects of chemicals and drugs, either in ecotoxicology or toxicology, and it can be helpful in both basic and applied research and serve as a decision-making tool in support of regulatory risk assessment. The AOP concept has evolved since its introduction, and recent research in toxicology, based on integrative systems biology and artificial intelligence, gave it a new dimension. This innovative in silico strategy can help to decipher mechanisms of action and AOP and offers new perspectives in AOP development. However, to date, this strategy has not yet been applied to ecotoxicology. In this context, the main objective of this short article is to discuss the relevance and feasibility of transferring this strategy to ecotoxicology. One of the challenges to be discussed is the level of organisation that is relevant to address for the AO (population/community). This strategy also offers many advantages that could be fruitful in ecotoxicology and overcome the lack of time, such as the rapid identification of data available at a time t, or the identification of "data gaps". Finally, this article proposes a step forward with suggested priority topics in ecotoxicology that could benefit from this strategy.

The molecular signal for the adaptation to cold temperature during early life on Earth.

Several lines of evidence such as the basal location of thermophilic lineages in large-scale phylogenetic trees and the ancestral sequence reconstruction of single enzymes or large protein concatenations support the conclusion that the ancestors of the bacterial and archaeal domains were thermophilic organisms which were adapted to hot environments during the early stages of the Earth. A parsimonious reasoning would therefore suggest that the last universal common ancestor (LUCA) was also thermophilic. Various authors have used branch-wise non-homogeneous evolutionary models that better capture the variation of molecular compositions among lineages to accurately reconstruct the ancestral G + C contents of ribosomal RNAs and the ancestral amino acid composition of highly conserved proteins. They confirmed the thermophilic nature of the ancestors of Bacteria and Archaea but concluded that LUCA, their last common ancestor, was a mesophilic organism having a moderate optimal growth temperature. In this letter, we investigate the unknown nature of the phylogenetic signal that informs ancestral sequence reconstruction to support this non-parsimonious scenario. We find that rate variation across sites of molecular sequences provides information at different time scales by recording the oldest adaptation to temperature in slow-evolving regions and subsequent adaptations in fast-evolving ones.

hb or not hb - When and why accounting for background mortality in toxicological survival models matters?

Decisions in Environmental Risk Assessment (ERA) about impacts of chemical compounds on different species are based on critical effect indicators such as the 50% lethal concentration (LC50). Regulatory documents recommend concentration-response (or concentration-effect) model fitting on standard toxicity test data to get LC50 values. However, toxicokinetic-toxicodynamic (TKTD) models proved their efficiency to better exploit toxicity test data, at Tier-2 but also at Tier-1, delivering time-independent indicators. In particular, LC50 values can be obtained from the reduced General Unified Threshold model of Survival (GUTS-RED) with both variants, Stochastic Death and Individual Tolerance, that include parameter hb, the background mortality. Estimating hb during the fitting process or not depends on studies and fitting habits, while it may strongly influence the other GUTS-RED parameters, and consequently the LC50 estimate. We hypothesized that estimating hb from all data in all replicates over time should provide more precise LC50 estimates. We then explored how estimating hb impacted: (i) GUTS-RED model parameters; (ii) goodness-of-fit criteria (fitting plot, posterior predictive check, parameter correlations); (iii) LC50 accuracy and precision. We finally show that estimating hb does not impact the LC50 precision while providing more accurate and precise GUTS parameter estimates. Hence, estimating hb would lead to a more protective ERA.

The ATTAC guiding principles to openly and collaboratively share wildlife ecotoxicology data.

The inability to quantitatively integrate scattered data regarding potential threats posed by the increasing total amount and diversity of chemical substances in our environment limits our ability to understand whether existing regulations and management actions sufficiently protect wildlife. Systematic literature reviews and meta-analyses are great scientific tools to build upon the current push for accessibility under the Open Science and FAIR movements. Despite the potential of such integrative analyses, the emergence of innovative findings in wildlife ecology and ecotoxicology is still too rare relative to the potential that is hidden within the entirety of the available scattered data. To promote the reuse of wildlife ecotoxicology data, we propose the ATTAC workflow which comprises five key steps (Access, Transparency, Transferability, Add-ons, and Conservation sensitivity) along the chain of collecting, homogenizing, and integrating data for subsequent meta-analyses. The ATTAC workflow brings together guidelines supporting both the data prime movers and re-users. As such, the ATTAC workflow could promote an open and collaborative wildlife ecotoxicology able to reach a major objective in this applied field, namely, providing strong scientific support for regulations and management actions to protect and preserve wildlife species.

Uptake, distribution, and elimination of selenite in earthworm Eisenia fetida at sublethal concentrations based on toxicokinetic model.

Natural and anthropogenic causes have promoted the rapid increase in environmental selenium (Se) levels, and the complex Se metabolism and dynamic in organisms make it challenging to evaluate the toxicity and ecological risks. In this study, the kinetics of selenite in earthworm Eisenia fetida were investigated based on toxicokinetic (TK) model (uptake-elimination phases: 14-14 days). The results showed the highest sub-tissue Se concentrations in pre-clitellum (PC), post-clitellum (PoC) parts, and total earthworms were 95.71, 70.40, and 79.94 mg/kg, respectively, which indicates the distinctive Se uptake capacities of E. fetida. Se kinetic rates in PCs were faster than that of the total E. fetida for both uptake (Kus = 0.30-0.80 mg/kg/day) and elimination phases (Kee = 0.024-0.056 mg/kg/day). Longer half-life times (LT1/2) were observed in the total earthworms (17.85-47.15 d) than PCs (12.28-29.22 d), while non-significant difference was found for the kinetic Se bioaccumulation factor (BAFk) in PC and total earthworms (12-19), which demonstrates that Se can be efficiently bioaccumulated and eliminated in earthworm PC part. Besides, the significant increase Se concentration in PoC with rapid elimination in PC also illustrates that earthworms can alleviate the Se stress by the transformation strategy of Se from the head to tail tissues. In conclusion, the investigation of Se kinetic accumulation and elimination characteristics in this study is helpful for understanding the metabolism and detoxification processes of Se in earthworms, and also providing a theoretical basis for further Se risk assessment using TK model.

The use of new approach methodologies for the environmental risk assessment of food and feed chemicals.

New Approach Methodologies (NAMs) provide tools for supporting both human and environmental risk assessment (HRA and ERA). This short review provides recent insights regarding the use of NAMs in ERA of food and feed chemicals. We highlight the usefulness of tiered methods supporting weight-of-evidence approaches in relation to problem formulation (i.e., data availability, time, and resource availability). In silico models, including quantitative structure activity relationship models, support filling data gaps when no chemical property or ecotoxicological data are available, and biologically-based models (e.g., toxicokinetic-toxicodynamic models, dynamic energy models, physiologically-based models and species sensitivity distributions) are applicable in more data rich situations, including landscape-based modelling approaches. Particular attention is given to provide practical examples to apply the approaches described in real-world settings. We conclude with future perspectives, with regards to the need for addressing complex challenges such as chemical mixtures and multiple stressors in a wide range of organisms and ecosystems.

Impacts of neonicotinoids on biodiversity: a critical review.

Neonicotinoids are the most widely used class of insecticides in the world, but they have raised numerous concerns regarding their effects on biodiversity. Thus, the objective of this work was to do a critical review of the contamination of the environment (soil, water, air, biota) by neonicotinoids (acetamiprid, clothianidin, imidacloprid, thiacloprid, thiamethoxam) and of their impacts on terrestrial and aquatic biodiversity. Neonicotinoids are very frequently detected in soils and in freshwater, and they are also found in the air. They have only been recently monitored in coastal and marine environments, but some studies already reported the presence of imidacloprid and thiamethoxam in transitional or semi-enclosed ecosystems (lagoons, bays, and estuaries). The contamination of the environment leads to the exposure and to the contamination of non-target organisms and to negative effects on biodiversity. Direct impacts of neonicotinoids are mainly reported on terrestrial invertebrates (e.g., pollinators, natural enemies, earthworms) and vertebrates (e.g., birds) and on aquatic invertebrates (e.g., arthropods). Impacts on aquatic vertebrate populations and communities, as well as on microorganisms, are less documented. In addition to their toxicity to directly exposed organisms, neonicotinoid induce indirect effects via trophic cascades as demonstrated in several species (terrestrial and aquatic invertebrates). However, more data are needed to reach firmer conclusions and to get a clearer picture of such indirect effects. Finally, we identified specific knowledge gaps that need to be filled to better understand the effects of neonicotinoids on terrestrial, freshwater, and marine organisms, as well as on ecosystem services associated with these biotas.

Main conclusions and perspectives from the collective scientific assessment of the effects of plant protection products on biodiversity and ecosystem services along the land-sea continuum in France and French overseas territories.

Preservation of biodiversity and ecosystem services is critical for sustainable development and human well-being. However, an unprecedented erosion of biodiversity is observed and the use of plant protection products (PPP) has been identified as one of its main causes. In this context, at the request of the French Ministries responsible for the Environment, for Agriculture and for Research, a panel of 46 scientific experts ran a nearly 2-year-long (2020-2022) collective scientific assessment (CSA) of international scientific knowledge relating to the impacts of PPP on biodiversity and ecosystem services. The scope of this CSA covered the terrestrial, atmospheric, freshwater, and marine environments (with the exception of groundwater) in their continuity from the site of PPP application to the ocean, in France and French overseas territories, based on international knowledge produced on or transposable to this type of context (climate, PPP used, biodiversity present, etc.). Here, we provide a brief summary of the CSA's main conclusions, which were drawn from about 4500 international publications. Our analysis finds that PPP contaminate all environmental matrices, including biota, and cause direct and indirect ecotoxicological effects that unequivocally contribute to the decline of certain biological groups and alter certain ecosystem functions and services. Levers for action to limit PPP-driven pollution and effects on environmental compartments include local measures from plot to landscape scales and regulatory improvements. However, there are still significant gaps in knowledge regarding environmental contamination by PPPs and its effect on biodiversity and ecosystem functions and services. Perspectives and research needs are proposed to address these gaps.