Application of new statistical distribution approaches for environmental mixture risk assessment: A case study

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).

The development and application of a novel hazard scoring tool for assessing impacts of cosmetic ingredients on aquatic ecosystems: A case study of rinse-off cosmetics

The cosmetic industry has been committed to promoting less hazardous products to reduce the environmental impacts of cosmetic ingredients. This requires identifying safer cosmetic ingredients for developing cosmetic formulations that are less harmful to the environment. However, one of the challenges in developing eco-friendly cosmetics relies on integrating all environmental hazard (EH) information of cosmetic ingredients to select the most eco-friendly ones (i.e., ingredients least harmful to the aquatic environment). Thus, we developed a hazard scoring tool (IARA matrix), which integrates data on biodegradation, bioaccumulation, and acute aquatic toxicity, providing a hazard index to classify cosmetic ingredients (raw materials) into categories of EH (low, moderate, high, or very high). The classification of the IARA was based on parameters established by Cradle to Cradle (C2C), the US Environmental Protection Agency (USEPA), and European Regulation 1272/2008, considering the most conservative values of each source. The Leopold matrix was employed as a model for the tool, using a numerical scale from 0 to 6 (lowest to highest EH). According to the IARA, we have successfully demonstrated that ultraviolet (UV) filter ingredients have the highest EH out of 41 cosmetic ingredients commonly used for rinse-off products. In addition to UV filters, triclosan (bactericide) and dimethicone (emollient) presented the second-highest EH for aquatic ecosystems, and humectants presented the lowest hazard index. By applying the IARA in the case study of rinse-off products, we have estimated that the aquatic hazard of cosmetic products can be reduced 46% by identifying less hazardous ingredients and combining them into a cosmetic formulation. In summary, the IARA tool allows the estimation of the EH of cosmetic ingredients, provides safer products, and helps achieve sustainability for cosmetic products. Integr Environ Assess Manag 2023;19:1619-1635. © 2023 SETAC.

Water pollution threats in important bird and biodiversity areas from Spain

Chemical pollution is still an underestimated threat to surface waters from natural areas. This study has analysed the presence and distribution of 59 organic micropollutants (OMPs) including pharmaceuticals, lifestyle compounds, pesticides, organophosphate esters (OPEs), benzophenone and perfluoroalkyl substances (PFASs) in 411 water samples from 140 Important Bird and Biodiversity Areas (IBAs) from Spain, to evaluate the impact of these pollutants in sites of environmental relevance. Lifestyle compounds, pharmaceuticals and OPEs were the most ubiquitous chemical families, while pesticides and PFASs showed a detection frequency below 25% of the samples. The mean concentrations detected ranged from 0.1 to 301 ng/L. According to spatial data, agricultural surface has been identified as the most important source of all OMPs in natural areas. Lifestyle compounds and PFASs have been related to the presence of artificial surface and wastewater treatment plants (WWTPs) discharges, which were also an important source of pharmaceuticals to surface waters. Fifteen out of 59 OMPs have been found at levels posing a high risk for the aquatic IBAs ecosystems, being the insecticide chlorpyrifos, the antidepressant venlafaxine and perfluorooctanesulfonic acid (PFOS) the most concerning compounds. This is the first study to quantify water pollution in IBAs and evidence that OMPs are an emerging threat to freshwater ecosystems that are essential for biodiversity conservation.

Algorithm for environmental risk assessment of cosmetics to reduce their environmental impact

Cosmetics, especially rinse-off personal care products (PCPs), such as shampoo, facial cleanser, and body wash, are composed of various chemicals and are one of the sources of chemicals released into aquatic ecosystems. Therefore, the cosmetic industry strives to reduce the impact of their products on the aquatic environment. In this study, we proposed an algorithm based on persistence, bioaccumulation potential, and toxicity (PBT) for the environmental risk assessment of cosmetics. PBT features are generally used in the evaluation of the environmental impact of chemicals. Based on the PBT assessment, it is possible to predict the short- and long-term effects of chemicals on the environment. Our algorithm derives substance and product scores from PBT features, allowing for the risk assessment of each ingredient in the product. Furthermore, we proposed a criterion for the environmental impact grade through which each component can be classified. We intend to use this grade and factors determined through the algorithm to manufacture products with low environmental impact.

Assessment of a New Approach Method for Grouped Chemical Hazard Estimation: The Toxicity-Normalized Species Sensitivity Distribution (SSDn)

New approach methods are being developed to address the challenges of reducing animal testing and assessing risks to the diversity of species in aquatic environments for the multitude of chemicals with minimal toxicity data. The toxicity-normalized species sensitivity distribution (SSDn) approach is a novel method for developing compound-specific hazard concentrations using data for toxicologically similar chemicals. This approach first develops an SSDn composed of acute toxicity values for multiple related chemicals that have been normalized by the sensitivity of a common species tested with each compound. A toxicity-normalized hazard concentration (HC5n) is then computed from the fifth percentile of the SSDn. Chemical-specific HC5 values are determined by back-calculating the HC5n using the chemical-specific sensitivity of the normalization species. A comparison of the SSDn approach with the single-chemical SSD method was conducted by using data for nine transition metals to generate and compare HC5 values between the two methods. We identified several guiding principles for this method that, when applied, resulted in accurate HC5 values based on comparisons with results from single-metal SSDs. The SSDn approach shows promise for developing statistically robust hazard concentrations when adequate taxonomic representation is not available for a single chemical.

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.

Environmental and human health risk assessment of mixture of Covid-19 treating pharmaceutical drugs in environmental waters

This study identified ecological and human health risks exposure of COVID-19 pharmaceuticals and their metabolites in environmental waters. Environmental concentrations in aquatic species were predicted using surface water concentrations of pharmaceutical compounds. Predicted No-Effect Concentrations (PNEC) in aquatic organisms (green algae, daphnia, and fish) was estimated using EC₅₀/LC₅₀ values of pharmaceutical compounds taken from USEPA ECOSAR database. PNEC for human health risks was calculated using the acceptable daily intake values of drugs. Ecological PNEC revealed comparatively high values in algae (Chronic toxicity PNEC values, high to low: ribavirin (2.65 × 10⁵ μg/L) to ritonavir (2.3 × 10^-1 μg/L)) than daphnia and fish. Risk quotient (RQ) analysis revealed that algae (Avg. = 2.81 × 10⁴) appeared to be the most sensitive species to pharmaceutical drugs followed by daphnia (Avg.: 1.28 × 10⁴) and fish (Avg.: 1.028 × 10³). Amongst the COVID-19 metabolites, lopinavir metabolites posed major risk to aquatic species. Ritonavir (RQ = 6.55) is the major drug responsible for human health risk through consumption of food (in the form fish) grown in pharmaceutically contaminated waters. Mixture toxicity analysis of drugs revealed that algae are the most vulnerable species amongst the three trophic levels. Maximum allowable concentration level for mixture of pharmaceuticals was found to be 0.53 mg/L.

Environmental risk assessment of neonicotinoids in surface water

Neonicotinoids (NNIs) are active substances used as insecticides mainly in plant protection products (PPPs) but also in veterinary applications. The increasing evidence of affecting non-targeted organisms led the European Commission to severely restrict or even ban outdoor uses. To evaluate their current use and their influence in the ecological status of freshwater ecosystem, a total of 19 river water samples were collected to determine the presence of 5 NNIs (acetamiprid, clothianidin, imidacloprid, thiamethoxam and thiacloprid) in the Tagus basin. At least one target analyte was quantified by HPLC-MS/MS analysis in 17 of the 19 water samples, with ∑NNIs ranging from <MDL to 16.8 ng/L. Imidacloprid (2.75 ng/L; mean) and acetamiprid (0.47 ng/L) were quantified in most of the samples. Source identification evidences imidacloprid agricultural use. Risk assessment for different trophic levels was conducted with the data obtained calculating Risk Characterization Ratios (RCR) by two approaches, predicted non effect concentrations (PEC/PNEC) and Toxic Units (TU). RCRs were derived for each NNI and for the mixture of all (RCRmix). Results showed risk for imidacloprid in freshwater organism (RCRfw>1) and for the mix of NNIs (RCRmix (PEC/PNEC) > 1). RCRmix(PEC/PNEC) and the sum of toxic units (STU) showed a risky situation for some locations with different organisms related to agriculture practices. This data arouses concern about NNis (legal or forbidden) use in Tagus basin, and manifest the need of monitoring their presence and effect on the aquatic ecosystem.

Mixture predicted no-effect concentrations derived by independent action model vs concentration addition model based on different species sensitivity distribution models

In the hazard assessment of mixtures, the mixture predicted no-effect concentration (mPNEC) is always derived by the concentration addition (CA) model (mPNEC_CA) to assess the risk of mixtures combined with exposure assessment. However, the independent action (IA) model, which is also widely used as the CA model in the prediction and evaluation of mixture toxicity, is always used to calculate the population fraction showing a predefined effect, not mPNEC, and this limits the application of IA model in the mixture risk assessment. In this study, we explored the process of mPNEC derived by the IA method (mPNEC_IA) based on the species sensitivity distribution (SSD) and compared mPNEC_IA with mPNEC_CA. Taking two common pesticides, dimethoate (DIM) and dichlorvos (DIC), exposed in the actual water environment as an example, their SSD models were constructed separately using nine distribution functions after toxicity data screening and quality testing. For both DIC and DIM, all different nine models had passed the Kolmogorov-Smirnov test. Then, the PNECs of two pesticides were derived based on SSD models. Finally, mPNEC_IA with different concentration ratios was derived and compared to mPNEC_CA based on 81 combinations of nine SSD models. Most mPNEC values derived by IA model were more conservative than those by CA. It is worth noting that the mPNEC_IA is more conservative than mPNEC_CA for the commonly used log-logit distribution (function 7), log-normal distribution (8), and log-Weibull distribution (9). This study provides a new direction for the application of IA in the risk assessment and enriches the framework of mixture risk assessment.

Prioritization and environmental risk assessment of pharmaceuticals mixtures from Brazilian surface waters

The present study provides an environmental risk assessment of the pharmaceutical mixtures detected in Brazilian surface waters, based on Toxic Units and Risk Quotients. Furthermore, the applicability of a previously proposed prioritization methodology was evaluated. The pharmaceuticals were classified according to their properties (occurrence, persistence, bioaccumulation, and toxicity) and the contribution of the prioritized compounds to the mixture risk was determined. The mixture risk quotients, based on acute and chronic toxicity data, often exceed 1, demonstrating a potential risk for the environment. While algae were most affected by acute effects, fish were the most sensitive organism to sublethal effects. The lipid regulator atorvastatin was the main driver for the mixture risk. Despite their lower occurrence, the antibiotics norfloxacin and enrofloxacin were critical compounds for the algae group. The prioritized pharmaceuticals contributed to more than 75% of the mixture risk in most of cases, indicating the applicability of prioritization approaches for risk management.

Cumulative impact assessment of hazardous ionic liquids towards aquatic species using risk assessment methods

In the present research work, a comprehensive tool for cumulative ecotoxicological impact assessment of ionic liquids (ILs) to aquatic life has been constructed. Using the probabilistic tool, impact of individual ILs to a group of aquatic species is assessed by chemical toxicity distributions (CTDs). The impact of group of ILs to individual aquatic species is assessed by species sensitivity distributions (SSDs). Acute toxicity data of imidazolium ILs with chloride (Cl^-), bromide (Br^-), tetrafluoroborate (BF4^-), and hexafluorophosphate (PF6^-) anions are used in CTD and SSD. Allowable concentrations for a group of Imidazolium ILs with the same mode of action (SMOA) to five aquatic species; Daphnia magna, Vibrio fischeri, Algae, Zebrafish, and Escherichia coli are estimated by CTDs. It has been concluded that 1-Butyl-3-methylimidazolium chloride (BMIMCl) possess the lowest risk at an acceptable risk value of 750 × 10^-5 mmol/L which is 12% less than that of OMIMCl. Furthermore, the sensitivities towards the aquatic species reveal that from the studied ILs, BMIMBF4 with an acceptable risk value of 3200 × 10^-5 mmol/L is the most suitable IL towards the selected aquatic species. Hence, current work provides cumulative allowable concentrations and acceptable risk values for ILs which release to aquatic compartment of ecosystem.

Defining the Human-Biota Thresholds of Toxicological Concern for Organic Chemicals in Freshwater: The Proposed Strategy of the LIFE VERMEER Project Using VEGA Tools

Several tons of chemicals are released every year into the environment and it is essential to assess the risk of adverse effects on human health and ecosystems. Risk assessment is expensive and time-consuming and only partial information is available for many compounds. A consolidated approach to overcome this limitation is the Threshold of Toxicological Concern (TTC) for assessment of the potential health impact and, more recently, eco-TTCs for the ecological aspect. The aim is to allow a safe assessment of substances with poor toxicological characterization. Only limited attempts have been made to integrate the human and ecological risk assessment procedures in a "One Health" perspective. We are proposing a strategy to define the Human-Biota TTCs (HB-TTCs) as concentrations of organic chemicals in freshwater preserving both humans and ecological receptors at the same time. Two sets of thresholds were derived: general HB-TTCs as preliminary screening levels for compounds with no eco- and toxicological information, and compound-specific HB-TTCs for chemicals with known hazard assessment, in terms of Predicted No effect Concentration (PNEC) values for freshwater ecosystems and acceptable doses for human health. The proposed strategy is based on freely available public data and tools to characterize and group chemicals according to their toxicological profiles. Five generic HB-TTCs were defined, based on the ecotoxicological profiles reflected by the Verhaar classes, and compound-specific thresholds for more than 400 organic chemicals with complete eco- and toxicological profiles. To complete the strategy, the use of in silico models is proposed to predict the required toxicological properties and suitable models already available on the VEGAHUB platform are listed.

Copula-based exposure risk dynamic simulation of dual heavy metal mixed pollution accidents at the watershed scale

Most heavy metal exposure and pollution results from multiple industrial activities, including metal processing in refineries, and microelectronics. These issues pose a great threat to human health, ecological balance, and even societal stability. During 2012-2017, China, in particular, faced the challenge of 23 heavy metals accidents, six of which were extraordinarily serious accidents. Accidental environmental pollution is rarely caused by a single heavy metal, but rather by heavy metal mixtures. To address the need for a joint exposure risk assessment for heavy metal mixed pollution accidents at the watershed scale, a Copula-based exposure risk dynamic simulation model was proposed. A coupled hydrodynamic and accidental heavy metal exposure model is constructed for an hourly simulation of the exposure fate of heavy metals from each risk source once accidental leakage has occurred. The Copula analysis was introduced to calculate the dual heavy metal joint exposure probability in real time. This method was applied to an acute Cr⁶⁺-Hg²⁺ joint exposure risk assessment for 43 electroplating plants in nine sub-watersheds within the Dongjiang River downstream basin. The results indicated seven risk sources (i.e., S1, S4, H18, H23, H27-H28, and H34) that presented relatively high exposure risk to their surrounding sub-watersheds. Spatially, the acute exposure risk level was highest in the tributary basin (sub-watershed XW) than in the mainstream (sub-watershed DW2) and the river network (sub-watershed RW) of the lower reaches of the Dongjiang River. This research highlights an effective probabilistic approach for performing a joint exposure risk analysis of heavy metal mixed pollution accidents at the watershed scale.

Computational modelling for the sustainable management of chemicals

This commentary explores the contribution of computational toxicology to chemical safety assessment in the context of the broad policy challenges faced by the European Union. The state of the European Environment is considered from the perspective of chemical contributions to the burden of disease and ecosystem damage. This sets the scene for highlighting research and innovation opportunities to further develop computational approaches for assessing the human health and environmental effects of chemicals. Emphasis is placed on focus topics that are particularly relevant to the political priorities of the new European Commission. In particular, two of the six priorities are discussed - “The European Green Deal” and “A Europe fit for a Digital Age”. The former includes the zero pollution ambition for a toxic-free environment, including the need to develop safe and sustainable chemicals, while the latter includes the challenges and opportunities posed by Artificial Intelligence. This commentary is based on a presentation given at the 19th meeting of The Italian Society of Toxicology (SITOX), held in Bologna, Italy, in February 2020.

Submarine groundwater discharge as a source of pharmaceutical and caffeine residues in coastal ecosystem: Bay of Puck, southern Baltic Sea case study

Even though the occurrence of pharmaceuticals in the water environment is thought to be a potential problem for human health and aquatic organisms, the level of knowledge of their sources and presence in the marine ecosystem is still insufficient. Therefore, this study was designed to determine the emergence of sixteen pharmaceuticals and caffeine in groundwater, submarine groundwater discharge (SGD), rivers and coastal seawater in the southern Baltic Sea. It has been recognized that chemical substances load associated with SGD can affect coastal ecosystems equally or even greater than surface runoff. Hence, the Bay of Puck, which is an active groundwater discharge area, has been chosen as a model study site to assess the preliminary risk of pharmaceutical and caffeine residues supply in coastal ecosystem. A special focus was placed on tracing the possible sources of pollution for groundwater and SGD based on the composition of collected samples. Five pharmaceuticals (carbamazepine, sulfapyridine, sulfamethoxazole, ketoprofen and diclofenac) and caffeine were detected in varying concentrations from below the detection limit to 1528.2 ng L^-1. Caffeine and diclofenac were the most widespread compounds. Groundwater was mostly enriched in the analysed compounds and consequently SGD has been recognized as an important source of identified pharmaceutical and caffeine residues to the Bay of Puck. A predicted no-effect concentration (PNEC) was determined in order to perform an environmental risk assessment of five pharmaceuticals and caffeine detected in water samples. Finally, future challenges and potential amendments in monitoring strategies are discussed.

"Modern agriculture" transfers many pesticides to watercourses: a case study of a representative rural catchment of southern Brazil

The total cultivated area in Brazil reached to 62 million ha in 2018, with the predominance of genetically modified soybean and corn (36 and 17 million ha, respectively) in no-tillage systems. In 2018, 5.3 × 10⁵ Mg of active ingredient of pesticides was applied in cropfields, representing about 7.3 L of commercial product by habitant. However, the monitoring of water courses contamination by pesticides remains scarce and is based on traditional grab sampling systems. In this study, we used the grab (water) and passive sampling (Polar Organic Chemical Integrative Sampler-POCIS) to monitor pesticide contamination in the river network of a representative agricultural catchment of southern Brazil. We selected 18 sampling sites located in tributaries and in the main course of the Guaporé River, in Rio Grande do Sul State, with different land use predominance including forest, urban, and agricultural areas. Altogether, 79 and 23 pesticides were, respectively, analyzed in water and POCIS samples. The water of Guaporé River and its tributaries were highly contaminated by many pesticides, especially by four herbicides (2,4-D, atrazine, deethyl-atrazine, and simazine), three fungicides (carbendazim, tebuconazole, and epoxiconazole), and one insecticide (imidacloprid). The amount, type, and concentration of pesticides detected were completely different depending on the sampling technic used. POCIS was effective to discriminate the contamination according to the main land use of each sampling site. The monitored areas with the predominance of soybean cultivation under no-tillage tended to have higher concentrations of fungicide, while in the more diversified region, the herbicides showed higher values. The presence of five herbicides used in corn and grassland forage production was correlated with areas of integrated crop-livestock systems, in contrast to higher contamination by 2,4-D in areas of intensive production of soybean and winter cereals.