Chronic Toxicity Data Research Articles

Toxicity prediction and risk assessment of per- and polyfluoroalkyl substances for threatened and endangered fishes

Per- and polyfluoroalkyl substances (PFASs) are severely polluted in aquatic environments and can harm aquatic organisms. Due to the limitation of conducting toxicity experiments directly on threatened and endangered (T&E) species, their toxicity data is scarce, hindering accurate risk assessments. The development of computational toxicology makes it possible to assess the risk of pollutants to T&E fishes. This study innovatively combined machine learning models, including random forest (RF), artificial neural network (ANN), and XGBoost, and the QSAR-ICE model to predict chronic developmental toxicity data of PFASs to T&E fishes. Among these, the XGBoost model exhibited superior performance, with R2 of 0.95 and 0.81 for the training and testing sets, respectively. Internal and external validation further confirmed that the XGBoost model is robust and reliable. Subsequently, it was used to predict chronic developmental toxicity data for seven priority PFASs to T&E fishes in the Yangtze River. Acipenseridae fishes (e.g., Acipenser dabryanus and Acipenser sinensis) showed high sensitivity to PFASs, possibly due to their unique lifestyle and physiological characteristics. Based on these data, the predicted no-effect concentration (PNEC) of individual PFASs was calculated, and the risk for T&E fishes in the Yangtze River was assessed. The results indicated that the risk of PFASs to T&E fishes is low (3.85 × 10−9∼8.20 × 10−4), with perfluorohexanoic acid (PFHxA) and perfluorooctanoic acid (PFOA) as the high-risk pollutants. The risk in the middle and lower reaches of the river is higher than in the upper reaches. This study provides a new approach for obtaining chronic toxicity data and conducting risk assessments for T&E species, advancing the protection of T&E species worldwide.

Determining high priority disinfection byproducts based on experimental aquatic toxicity data and predictive models: Virtual screening and in vivo study

Only about 100 disinfection byproducts (DBPs) have been tested for their potential aquatic toxicity. It is not known which specific DBPs, DBP main groups, and DBP subgroups are more toxic due to the lack of experimental toxicity data. Herein, high priority specific DBPs, DBP main groups, DBP subgroups, most sensitive model aquatic species, potential PBT and PMT (persistent, bioaccumulative/mobile, and toxic) DBPs were virtually screened for 1187 updated DBPs inventory. Priority setting based on experimental and predicted acute and chronic aquatic toxicity data found that the aromatic and alicyclic DBPs in four DBPs main groups showed high priority because larger proportions of aromatic and alicyclic DBPs are in high hazard categories (i.e. Acute and/or Chronic Toxic-1 or Toxic-2) according to the criteria in GHS system compared to the aliphatic and heterocyclic DBPs. The halophenols, estrogen-DBPs, nonhalogenated esters, and nonhalogenated aldehydes were recognized as high priority DBPs subgroups. For specific DBPs, 19 and 31 DBPs should be highly concerned in the future study because both acute and chronic toxicity of those DBPs to all of the three aquatic life (algae, Daphnia magna, fish) were classified as Toxic-1 and Toxic-2, respectively. The Daphnia magna and algae were sensitive to the acute toxicity of DBPs, while the fish and Daphnia magna were sensitive to the chronic toxicity of DBPs. One potential PBT (Tetrachlorobisphenol A) and four potential PMT DBPs were identified. For verification, the acute toxicity of four DBPs on three aquatic organism were performed, and their tested acute toxicity data to three aquatic organisms were consistent with the predictions. Our results could be beneficial to government regulators to adopt effective measures to limit the discharge of high priority DBPs and help the scientific community to develop or improve disinfection processes to reduce the production of high priority DBPs.

Pollution level and ecological risk assessment of triazine herbicides in Laizhou Bay and derivation of seawater quality criteria

Triazine herbicides are widely used in agriculture and have become common pollutants in marine environments. However, the spatiotemporal distribution characteristics and water quality criteria (WQC) of triazine herbicides are still unclear. This study found that triazine herbicides had a high detection rate of 100 % in surface seawater of Laizhou Bay, China, with average concentrations of 217.61, 225.13, 21.97, and 1296.72 ng/L in March, May, August, and October, respectively. Moreover, estuaries were important sources, and especially the Yellow River estuary exhibited the highest concentrations of 16,115.86 ng/L in October. The 10 triazine herbicides were detected in the sediments of Laizhou Bay, with a concentration ranging from 0.14−1.68 μg/kg. Atrazine and prometryn accounted for 33.41 %−59.10 % and 28.93 %−50.06 % of the total triazine herbicides in the seawater, and prometryn had the highest proportion (63.50 %) in the sediments. Correlation analysis revealed that triazine herbicides led to the loss of plankton biodiversity, which further decreased the dissolved oxygen. In addition, this study collected 45 acute toxicity data and 22 chronic toxicity data of atrazine, 16 acute toxicity data of prometryn, and supplemented with toxicity experiments of prometryn on marine organisms. Based on the toxicity database, the WQCs of atrazine and prometryn were derived using species sensitivity distribution. The overall risk probability of atrazine and prometryn were both less than 1.75 % in the Laizhou Bay, indicating an acceptable risk. This study not only clarified the pollution status and ecological risk of triazine herbicides, but also provided scientific basis for their environmental management standards.

Assessment of potential environmental and human risks for Bisphenol AF contaminant

Bisphenol AF (BPAF) is found in high concentrations in aquatic environments due to the increased use of thermal paper and food packaging. However, there have been relatively few toxicological studies and potential risk assessments of BPAF. In this study, the risk quotient (RQ) and hazard quotient (HQ) of BPAF were derived to present the safety standards for environmental risk management and protection in lakes, rivers, bays, and Italian regions. We applied the species sensitivity distribution (SSD) method based on the previous ecotoxicological data and the results of supplementary toxicity tests on BPAF. From the SSD curves, the hazardous concentration for 5 % of the species (HC5) values for the acute and chronic toxicity data were 464.75 µg/L and 3.59 µg/L, respectively, and the acute- and chronic-based predicted no-effect concentration were derived as 154.92 µg/L and 1.20 µg/L, respectively. The acute-based RQ (RQA)values of BPAF in all regions were negligible (RQ < 0.1). The chronic-based RQ (RQC) in the Xitang River (XR) and the Central Italy (CI) showed a considerably high ecological risk (12.77 and 1.29) and the Hangzhou Bay (0.21), the South and North Italy (0.79 and 0.27), and the Tamagawa River (0.13) had a medium ecological risk (0.1 < RQ < 1.0). However, the HQ values based on the tolerable daily intake for BPAF over all age groups in these regions was < 0.1, indicating the low health risk. Nonetheless, the result of this study indicates that BPAF contamination is serious in XR and CI, and their use and emissions require continuous monitoring.

Ecological risk assessment of heavy metals in desulfurized seawater discharged from a coal-fired power plant in Qingdao.

Despite the prevalence of discharge of large volumes of heavy-metal-bearing seawater from coal-fired power plants into adjacent seas, studies on the associated ecological risks remain limited. This study continuously monitored concentrations of seven heavy metals (i.e. As, Cd, Cr, Cu, Hg, Pb, and Zn) in surface seawater near the outfall of a coal-fired power plant in Qingdao, China over three years. The results showed average concentrations of As, Cd, Cr, Cu, Hg, Pb, and Zn of 2.63, 0.33, 2.97, 4.63, 0.008, 0.85, and 25.00 μg/L, respectively. Given the lack of data on metal toxicity to local species, this study investigated species composition and biomass near discharge outfalls and constructed species sensitivity distribution (SSD) curves with biological flora characteristics. Hazardous concentrations for 5% of species (HC5) for As, Cd, Cr, Cu, Hg, Pb, and Zn derived from SSDs constructed from chronic toxicity data for native species were 3.23, 2.22, 0.06, 2.83, 0.66, 4.70, and 11.07 μg/L, respectively. This study further assessed ecological risk of heavy metals by applying the Hazard Quotient (HQ) and Joint Probability Curve (JPC) based on long-term heavy metal exposure data and chronic toxicity data for local species. The results revealed acceptable levels of ecological risk for As, Cd, Hg, and Pb, but unacceptable levels for Cr, Cu, and Zn. The order of studied heavy metals in terms of ecological risk was Cr > Cu ≈ Zn > As > Cd ≈ Pb > Hg. The results of this study can guide the assessment of ecological risk at heavy metal contaminated sites characterized by relatively low heavy metal concentrations and high discharge volumes, such as receiving waters of coal-fired power plant effluents.

First report on pesticide sub-chronic and chronic toxicities against dogs using QSAR and chemical read-across

ABSTRACT Excessive use of chemicals is the outcome of the industrialization of agricultural sectors which leads to disturbance of ecological balance. Various agrochemicals are widely used in agricultural fields, urban green areas, and to protect from various pest-associated diseases. Due to their long-term health and environmental hazards, chronic toxicity assessment is crucial. Since in vivo and in vitro toxicity assessments are costly, lengthy, and require a large number of animal experiments, in silico toxicity approaches are better alternatives to save time, cost, and animal experimentation. We have developed the first regression-based 2D-QSAR models using different sub-chronic and chronic toxicity data of pesticides against dogs employing 2D descriptors. From the statistical results ( n train = 53 − 62 , r 2 = 0.614 to 0.754, Q L O O 2 = 0.501 to 0.703 and Q F 1 2 = 0.531 to 0.718, Q F 2 2 = 0.523 − 0.713 ), it was concluded that the models are robust, reliable, interpretable, and predictive. Similarity-based read-across algorithm was also used to improve the predictivity ( Q F 1 2 = 0.595 − 0.813 , Q F 2 2 = 0.573 − 0.809 ) of the models. 5132 chemicals obtained from the CPDat and 1694 pesticides obtained from the PPDB database were also screened using the developed models, and their predictivity and reliability were checked. Thus, these models will be helpful for eco-toxicological data-gap filling, toxicity prediction of untested pesticides, and development of novel, safer & eco-friendly pesticides.

Ecological risk assessment for typical organophosphorus pesticides in surface water of China based on a species sensitivity distribution model

The ecological risks posed by widespread organophosphorus pesticide (OPs) pollution in the surface waters of China remain unclear. In this study, species sensitivity distribution (SSD) parametric statistical approaches were coupled with fully acute and chronic toxicity data to fit the sensitivity distributions of different aquatic species to five typical OPs: dimethoate, malathion, parathion-methyl, trichlorfon, and dichlorvos. Crustaceans exhibit the highest sensitivity to OPs, whereas algae are the least sensitive. The acute hazardous concentrations that affected 5 % of the species (HC5) were 0.112, 0.001, 0.001, 0.001, and 0.001 mg/L for dimethoate, malathion, parathion-methyl, trichlorfon, and dichlorvos, respectively, whereas their chronic HC5 values were 0.004, 0.004, 0.053, 0.001, and 0.0005 mg/L, respectively. Hence, dichlorvos is highly toxic and poses greater risk to non-target aquatic species. The evaluation data revealed varying geographical distribution characteristics of the ecological risks from OPs in 15 freshwater aquatic systems across different regions of China. Dichlorvos posed the highest risk in the basins of Zhejiang and Guangdong Provinces, with the highest chronic Risk Quotient (RQ) and Hazard Index (HI) at 9.34 and 9.92, respectively. This is much higher than what was collected and evaluated for foreign rivers (the highest chronic RQ and HI in foreign rivers were 1.65 and 2.24, respectively). Thus, dichlorvos in the surface waters of China poses a substantial ecological risk to aquatic organisms, and may endanger human health.

New insight into the spatiotemporal distribution and ecological risk assessment of endocrine-disrupting chemicals in the Minjiang and Tuojiang rivers: perspective of watershed landscape patterns.

This study evaluated the pollution characteristics, spatiotemporal distribution, and ecological risks of eight endocrine-disrupting chemicals (EDCs) in the Minjiang and Tuojiang rivers. Utilizing 3S technology (ArcGIS, remote sensing, GPS) and Fragstats, the research calculated eight landscape pattern indices related to land use types along the Minjiang river and established correlations between landscape factors and EDC distribution through stepwise multiple regression. The results indicated that bisphenol A (BPA) and nonylphenol (NP) were the most concerning EDCs, with detection frequencies of 97-100% and peak concentrations up to 63.35 ng L-1, primarily located in the middle and lower reaches of the Minjiang river and the upper reaches of the Tuojiang river. There was a significant correlation between the spatial distribution of pollutants and landscape patterns, where increased fragmentation, a higher number of patches, and complex patch shapes within a 10-kilometer buffer zone were associated with elevated levels of river pollution. By integrating four classical mathematical models to fit curves for acute and chronic toxicity data of BPA and NP, the findings suggested that BPA posed a higher ecological risk. This interdisciplinary research provided essential theoretical insights for investigating river pollution and its influencing factors, offering a new perspective on simultaneous river pollution control, urban functional zoning, and adjustment of watershed landscape spatial patterns from an urban planning standpoint.

Advancing chronic toxicity risk assessment in freshwater ecology by molecular characterization-based machine learning

The continuously increased production of various chemicals and their release into environments have raised potential negative effects on ecological health. However, traditional labor-intensive assessment methods cannot effectively and rapidly evaluate these hazards, especially for chronic risk. In this study, machine learning (ML) was employed to construct quantitative structure-activity relationship (QSAR) models, enabling the prediction of chronic toxicity to aquatic organisms by leveraging the molecular characteristics of pollutants, namely, the molecular descriptors, fingerprints, and graphs. The limited dataset size hindered the notable advantages of the graph attention network (GAT) model for the molecular graphs. Considering computational efficiency and performance (R2 = 0.78; RMSE = 0.77), XGBoost (XGB) was used for reliable QSAR-ML models predicting chronic toxicity using small- or medium-sized tabular data and the molecular descriptors. Further kernel density estimation analysis confirmed the high accuracy of the model for pollutant concentrations ranging from 10−3 to 102 mg/L, effectively aligning with most environmental scenarios. Model interpretation showed SlogP and exposure duration as the primary influential factors. SlogP, representing the distribution coefficient of a molecule between lipophilic and hydrophilic environments, had a negative effect on the toxicity outcomes. Additionally, the exposure duration played a crucial role in determining the chronic toxicity. Finally, the chronic toxicity data of bisphenol A validated the robustness and reliability of the model established in this research. Our study provided a robust and feasible methodology for chronic ecological risk evaluation of various types of pollutants and could facilitate and increase the use of ML applications in environmental fields.

Water quality criteria derivation and ecological risk assessment for ibuprofen, a common antifever drug in China

Ibuprofen, an extensively consumed antifever drug, has been inevitably recorded in various aquatic environments in China. However, water quality criteria (WQC) are rarely derived, thereby hindering the ecological risk assessment for this emerging pollutant. This study, therefore, aims to determine the WQC for IBU by screening toxicity data of freshwater and seawater species residing in China and simulating the species sensitivity distribution curves. The ecological risk of IBU in the aquatic environment of China was subsequently assessed through hazard quotient and margin of safety at 10% methods. A total of 15 acute and 9 chronic toxicity data were collected from the literature, and the acute and chronic WQC for IBU were derived as 7.6 mg/L and 2.9 μg/L, respectively. The ecological risk of IBU was generally negligible, with 21.4% of the waters in China at low chronic risk. The long-term effects and environmental existence of IBU, however, warrant further concern considering the shortage of ecotoxicology data and the popularity of usage for this well-known pharmaceutical.

Deriving seawater quality criteria of tris(2-chloroethyl) phosphate for ecological risk assessment in China seas through species sensitivity distributions

Tris(2-chloroethyl) phosphate (TCEP), one of the widely used organophosphorus flame retardants (OPFRs), has been frequently detected in the marine environment in the seas off China. The existing freshwater biotoxicity data are not suited to derivation of the seawater quality criteria of TCEP and evaluating the associated ecological risks. This study aimed at deriving water quality criteria (WQC) of TCEP for marine organisms based on species sensitivity distribution (SSD) approach using the acute toxicity data generated from multispecies bioassays and chronic toxicity data by converting acute data with the acute-to-chronic ratios (ACRs); the derived WQC were then used to evaluate the ecological risk for TCEP in China Seas. According to median effective concentration (EC50) and median lethal concentration (LC50), TCEP had a moderate or low toxicity to eight marine species selected, among which mysid Neomysis awatschensis (96h-LC50 of 39.65 mg/L) and green alga Platymonas subcordiformis (96-h EC50 of 395.42 mg/L) were the most sensitive and the most tolerant, respectively. The acute and chronic hazardous concentrations of TCEP for 5% of marine species (HC5) were estimated to be 29.55 and 2.68 mg/L, respectively. The short-term and long-term WQC were derived to be 9.85 and 0.89 mg/L, respectively. The risk quotient (RQ) values indicated that TECP at current levels poses a negligible risk to marine ecosystems in China. These results will provide valuable reference for the government to establish a seawater quality standard for TCEP.

Deriving aquatic PNECs of endocrine disruption effects for PFOS and PFOA by combining species sensitivity weighted distributions and adverse outcome pathway networks

Perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA), as emerging endocrine-disrupting chemicals (EDCs), pose adverse effects on aquatic organisms. Conventional ecological risk assessment (ERA) not fully considering the mode of toxicity action of PFOS and PFOA, may result in an underestimation of risks and confuse decision-makers. In the study, we developed species sensitivity weighted distribution (SSWD) models based on adverse outcome pathway (AOP) networks for deriving predicted no-effect concentrations (PNECs). Three kinds of weighting criteria (intraspecies variation, trophic level abundance, and data quality) and weighted log-normal distribution methods were adopted. The developed models considered the inter/intraspecies variation and integrated nontraditional endpoints of endocrine-disrupting effects. The PNECs of endocrine disruption effects were derived as 2.52 μg/L (95% confidence intervals 0.667–9.85 μg/L) for PFOS and 18.7 μg/L (5.40–71.0 μg/L) for PFOA, which were more conservative than those derived from the SSD method and were comparable with the values in the literature based on the chronic toxicity data. For PFOS, the effect of growth and development was the most sensitive; however, for PFOA, the effect of reproduction was the most sensitive in the effects of growth and development, reproduction, biochemistry and genetics, and survival. The endocrine-disrupting effects of PFOS and PFOA are significant and need to be fully recognized in the ERA. This study provided an ERA framework that can improve the ecological relevance and reduce the uncertainty of PNECs of EDCs.

The Taxon-Specific Species Sensitivity and Aquatic Ecological Risk Assessment of Three Heavy Metals in Songhua River Water, China

Copper (Cu), zinc (Zn), and nickel (Ni) are essential micronutrients for aquatic life, but they produce adverse effects on aquatic organisms when environmental concentrations exceed a certain threshold. The objective of this study was to analyze the taxon-specific sensitivities of aquatic life to the three metals and assess ecological risks at exposure levels prevalent in the Songhua River, China. The results showed that sensitivities to these metals varied among different taxonomic groups, with intra-taxon sensitivities being lower than inter-taxa sensitivities, and the consistency of intra-taxon sensitivity increased from phylum to order. The maximum detected concentrations of Cu, Zn, and Ni in the Songhua River were 52.7, 166.0, and 65.3 μg/L, respectively, which met the water quality standards set by China but exceeded the chronic criteria established by the USA. A probabilistic risk assessment based on chronic toxicity data revealed that these three metals posed an intermediate to high risk to aquatic animals, with maximum risk products of 36.4% for Cu, 14.3% for Ni, and 6.2% for Zn, respectively. These results indicate that the ecological damage of heavy metals in the Songhua River cannot be ignored.

The pollution of microplastics in sediments of the Yangtze River Basin: Occurrence, distribution characteristics, and basin-scale multilevel ecological risk assessment.

Microplastics (MPs) pollution in the Yangtze River Basin (YRB) of China has grown to be a serious issue, yet there is a lack of understanding of the environmental risks of MPs in the sediment of the entire basin. This work revealed the spatial distribution characteristics of MPs in YRB sediments, and it methodically assessed the ecological risks of MPs by taking into consideration their abundance, toxic effects, and polymer types. The results showed a high heterogeneity in the abundance of MPs in YRB sediments, with an average of 611 particles/kg dry weight (DW) sediment. Small-sized MPs (<1mm), fibrous, transparent-colored and polypropylene (PP) accounted for the majority with 71.6%, 68%, 37% and 30.8%, respectively. Correlation analysis indicated significant influences of human activities such as population, industrial structure, and urban wastewater discharge on the abundance and morphological types of MPs in sediments. Based on chronic toxicity data exposed to sediments, a predicted no-effect concentration (PNEC) of 539 particles/kg DW was calculated using the species susceptibility distribution (SSD). Multiple deterministic risk assessment indices indicated that MPs in YRB sediments exhibited primarily low pollution load levels, moderate-to-low potential ecological risk levels, and high levels of polymer pollution. However, probabilistic risk assessment revealed an overall low risk of MPs in YRB sediments. Monte Carlo simulation results demonstrated that polyvinyl chloride (PVC) and polycarbonate (PC) made a great contribution to ecological risk and should be considered as priority control pollutants in MPs. In addition, various assessments showed that the ecological risk of MPs in river sediments was higher than that in lake reservoir sediments. This is the first study to comprehensively assess the ecological risk of MPs in sediments of the YRB, which improves the understanding of the basin-wide occurrence characteristics and environmental risks of MPs in freshwater systems.

Acute and chronic toxicity of manganese to tropical adult coral (Acropora millepora) to support the derivation of marine manganese water quality guideline values

Adult corals are among the most sensitive marine organisms to dissolved manganese and experience tissue sloughing without bleaching (i.e., no loss of Symbiodinium spp.) but there are no chronic toxicity data for this sensitive endpoint. We exposed adult Acropora millepora to manganese in 2-d acute and 14-d chronic experiments using tissue sloughing as the toxicity endpoint. The acute tissue sloughing median effect concentration (EC50) was 2560 μg Mn/L. There was no chronic toxicity to A. millepora at concentrations up to and including the highest concentration of 1090 μg Mn/L i.e., the chronic no observed effect concentration (NOEC). A coral-specific acute-to-chronic ratio (ACR) (EC50/NOEC) of 2.3 was derived. These data were combined with chronic toxicity data for other marine organisms in a species sensitivity distribution (SSD). Marine manganese guidelines were 190, 300, 390 and 570 μg Mn/L to provide long-term protection of 99, 95, 90, and 80 % of marine species, respectively.

Environmental Risk Assessment of Drugs in Tropical Freshwaters Using Ceriodaphnia silvestrii as Test Organism.

In this study we evaluated the acute (immobility/mortality) and chronic (survival and reproduction) effects of the drugs caffeine, diclofenac sodium salt, ketoprofen, paracetamol and salicylic acid on the cladoceran Ceriodaphnia silvestrii. The environmental risks of these substances for tropical freshwaters were estimated from the risk quotient MEC/PNEC. Sensitivity in acute exposures varied up on the drug as follows: salicylic acid (EC50 = 69.15mg L- 1) < caffeine (EC50 = 45.94mg L- 1) < paracetamol (EC50 = 34.49mg L- 1) < ketoprofen (EC50 = 24.84mg L- 1) < diclofenac sodium salt (EC50 = 14.59mg L- 1). Chronic toxicity data showed negative effects of the drugs on reproduction. Paracetamol and salicylic acid caused reduction in fecundity in concentrations starting from 10mg L- 1 and 35mg L- 1, respectively. Ketoprofen caused total inhibition at 5mg L- 1. MEC/PNEC values were relatively low for all drugs. The risk was estimated as low or insignificant, except for caffeine, whose MEC/PNEC value was greater than 1 (moderate risk).

Understanding hazardous concentrations of microplastics in fresh water using non-traditional toxicity data

Microplastic pollution has become a major environmental problem, indicating the need to implement quantitative governance standards in combination with reducing or banning single-use plastic. Previous studies have predicted no-effect concentrations for limited microplastic-based toxicity data but have not considered environmentally relevant sizes, shapes, or polymers. To provide high quantity and quality data for microplastics of different sizes, shapes, or polymer compositions, non-traditional and traditional toxicity data may need to be considered in combination. In this study, we reviewed toxicity data for microplastics in freshwaters from 2018 to 2022 and analyzed the toxicity data using traditional and non-traditional methods. Based on 166 chronic traditional toxicity data points, the hazard concentration (HC) values calculated from non-traditional toxicity endpoints or all toxicity endpoints were lower than those calculated from traditional toxicity endpoints. Based on 398 chronic traditional plus non-traditional toxicity data points, the HC values calculated from traditional plus non-traditional values were higher than those calculated from traditional toxicity values. With these results, we developed a new framework for deriving microplastic-specific hazardous concentrations, one that especially considers non-traditional toxicity endpoints and values for microplastics. Overall, this study offers a basis for future management strategies and associated frameworks for mitigating microplastic toxicity.

Derivation of predicted no-effect concentrations for thirty-five pharmaceuticals and personal care products in freshwater ecosystem

Pharmaceuticals and personal care products (PPCPs) are contaminants of emerging concern. PPCPs have been detected in various environmental matrices, posing potential threat to human health and environment quality. Thus far, there are no water quality guidelines (WQGs) established for PPCPs for the protection of freshwater organisms and ecosystems. In this study, we used the species sensitivity distribution (SSD) and assessment factor (AF) approaches to derive the 5% hazardous concentrations (HC5) of 35 selected PPCPs using acute and chronic toxicity data. The predicted no-effect concentrations (PNECs) and the acute-to-chronic ratios (ACRs) of chemicals were inherently computed to support the derivation of WQGs and for ecological risk assessment. Among these, endocrine-disrupting chemicals and antipsychotics were shown to pose a greater threat to the freshwater environment and organisms. The highest PNEC was recorded for chloramphenicol (3,620 μg/L) and the lowest for fluoxetine (0.0000291 μg/L), which could have significant ecological risks. In addition, the commonly used default ACRs do not seem to provide adequate support for the prediction of chronic toxicity thresholds and WQGs, as the highest ACRs of these drugs reached 39,100 (e.g., chloramphenicol). The findings of this study provide critical scientific information regarding the development of WQGs for environmental management and the risk control of PPCPs.

Occurrence and ecological risk assessment of 2,2′,4,4′-tetrabromodiphenyl ether and decabromodiphenyl ether in surface waters across China

Polybrominated diphenyl ethers (PBDEs) are efficient brominated flame retardants and are released into various environmental media via usage, recycling and disposal. This study investigated the concentrations and ecological risks of two typical PBDEs, 2,2′,4,4′-tetrabromodiphenyl ether (BDE-47) and decabromodiphenyl ether (BDE-209), in surface waters across China from 2011 to 2018. The results showed that the concentration of BDE-209 (8.25 ng L−1) was higher than that of BDE-47 (1.02 ng L−1), and the concentrations of BDE-47 and BDE-209 in the lakes (2.56 ng L−1 and 22.19 ng L−1, respectively) were higher than those in the rivers (0.58 ng L−1 and 7.05 ng L−1, respectively). In addition, the concentration of BDE-209 in the wet season (2.61 ng L−1) was lower than that in the dry season (10.83 ng L−1), whereas the concentration of BDE-47 in the wet season (0.24 ng L−1) was a little lower than that in the dry season (0.99 ng L−1). BDE-47 and BDE-209 concentrations showed a gradual decrease in surface waters across China during the eight-year period. Based on the species sensitivity distribution (SSD) models, the 5% hazardous concentration (HC5) and predicted no-effect concentration (PNEC) values were derived using the acute and chronic toxicity data of BDE-47 and BDE-209. Results showed that the PNEC values based on the acute and chronic toxicity data were 2.08 μg L−1 and 0.52 μg L−1 for BDE-47, respectively and 370 μg L−1 and 0.34 μg L−1 for BDE-209, respectively. The risk quotient (RQ) values of BDE-47 in surface waters across China were far smaller than 0.1 (low ecological risk). Similarly, the RQ values of BDE-209 were also smaller than 0.1, except for those at Baiyangdian Lake and Chaohu Lake, where the probability of 0.1 ≤ RQ < 1.0 (medium ecological risk) was approximately 10% based on 10,000 Monte Carlo simulations.

Monitoring and ecological risk assessment of contaminants in freshwater bodies by bioindicators in China: a proposed framework.

Bioindicators can provide pollution information with longer temporal duration and larger spatial scale. It is an ideal strategy for long-term monitoring of bioaccumulative contaminants. Bioindicator monitoring has been widely used; however, there were seldom detailed studies about bioindicator methodology in literature. The present study proposed a bioindicator framework suitable for the local conditions of China, including selection of bioindicator species, evaluation of impact factors, and derivation of threshold values using per- and polyfluoroalkyl substances (PFASs) as an example. The criteria that proper bioindicator species should meet and the procedure how the bioindicator species is selected were proposed, under which crucian carp (Carassius auratus) was selected as the local bioindicator for studied PFASs. Several factors which may affect accumulation of contaminants in bioindicators were suggested to produce reliable and comparable results. Derivation method of bioindicator thresholds for ecological risk assessment of aquatic ecosystems was firstly developed. The long-term and short-term ecological thresholds of perfluorooctanesulfonate using crucian carp as bioindicator are 3.329 and 1.402μg/g wet weight respectively. Using the long-term thresholds derived from chronic toxicity data and the accumulative concentrations of contaminants obtained by bioindicator results, the bioindicator monitoring can be used for long-term ecological risk surveillance. The threshold derivation method can extend the application of bioindicator monitoring from the occurrence study to ecological risk surveillance, which is especially important for China who has made progresses on regular contaminant control and starts to be concerned about the ecological risks of the emerging contaminants. The framework can be used to create national and regional long-term freshwater bioindicator monitoring programs, with the purposes of ecological risk assessment, occurrence and temporal trend study, pollution source identification, international convention fulfillment, retrospective study, etc. The bioindicator framework will benefit the aquatic environmental safety and the hazardous chemical management in China.