Conflicting results of ecological and health risk assessment of perfluorinated compounds in major river basins in China.

Environmental exposure and ecological risk of perfluorinated substances (PFASs) in the Shaying River Basin, China

Chapter 8 - Development of species sensitivity distribution (SSD) models for setting up the management priority with water quality criteria of toxic chemicals

Tiered ecological risk assessment of nonylphenol and tetrabromobisphenol A in the surface waters of China based on the augmented species sensitivity distribution models

Per- and polyfluoroalkyl substances (PFASs) are a class of highly fluorinated aliphatic compounds that are persistent and bioaccumulate, posing a potential threat to the aquatic environment. The electroplating industry is considered to be an important source of PFASs. Due to emerging PFASs and many alternatives, the acute toxicity data for PFASs and their alternatives are relatively limited. In this study, a QSAR–ICE–SSD composite model was constructed by combining quantitative structure-activity relationship (QSAR), interspecies correlation estimation (ICE), and species sensitivity distribution (SSD) models in order to obtain the predicted no-effect concentrations (PNECs) of selected PFASs. The PNECs for the selected PFASs ranged from 0.254 to 6.27 mg/L. The ΣPFAS concentrations ranged from 177 to 983 ng/L in a river close to an electroplating industry in Shenzhen. The ecological risks associated with PFASs in the river were below 2.97 × 10−4.

Phthalate esters (PAEs) are typical industrial and agricultural chemicals that are readily released into the environment. Due to their endocrine-disrupting properties, PAEs pose considerable ecological risks in different environmental matrices. However, current standards for evaluating the ecological risks of PAEs focus primarily on environmental quality thresholds and do not account for criteria based on native species. This study integrated species sensitivity distribution modeling, interspecies correlation estimation, and acute-chronic ratio calculations using toxicity data for seven representative PAEs from native species in freshwater: dimethyl phthalate (DMP), diethyl phthalate (DEP), dibutyl phthalate (DnBP), butyl benzyl phthalate (BBP), dis(2-ethylhexyl) phthalate (DEHP), diisodecyl phthalate (DIDP), and dihexyl phthalate (DnHP). Short- and long-term predicted no-effect concentrations (PNECs) were estimated and applied to the ecological risk assessment (ERA) for these PAEs in freshwater and sediment across major basins of China. The PNECs for DIDP and DnHP were derived for the first time. The values of PNECs for the remaining PAEs were generally lower than or similar with previously reported values. The freshwater ERAresults indicated a consistent risk ranking of DEHP > DnBP > BBP > DEP > DMP (DnHP) for acute and chronic exposure. For sediment, the short- and long-term risk rankings differed, with acute risks following DnBP > DEP (DMP) > DEHP > BBP > DnHP and chronic risks following DEHP > DnBP > DEP > DMP > BBP > DnHP. The DEHP should be warranted as a particular concern in sediments, as its ecological risk increased over time.

The eco-safety of plasticizer alternative di-isobutyl phthalate (DiBP) has received continued concerns owing to its large usage as a plasticizer and high detection frequency in environments. The concentrations of dibutyl phthalate (DBP) and DiBP in the surface waters ranged from ng/L to μg/L. However, the accurate ecological risk assessment of alternatives is limited by data on toxic effects and potencies. The interspecies correlation estimation (ICE) model combined with the species sensitivity distribution (SSD) model was used to assess the ecological risk of DBP and DiBP. The acute and reproductive predicted no-effect concentrations (PNECs) were derived as 0.05 mg/L and 1.23 μg/L for DBP and 0.16 mg/L and 0.51 μg/L for DiBP based on ICE-SSD models. Our results showed that acute risks (risk quotient (RQ) < 0.1) in mainland China waterbodies, except Hangzhou Bay, were acceptable. The risk quotients indicated that Yangtze River (RQ = 1.55 and 0.48), Hun River (RQ = 1.74 and 6.03), and Hangzhou Bay (RQ = 7.33 and 13.49) had relatively high ecological risk levels based on the reproductive PNECs of DBP and DiBP. Furthermore, the joint probability curves showed that the ecological risks in Hangzhou Bay needed further concern. Thus, the ICE-SSD model could effectively compensate for the lack of toxicity data in risk assessment.

Management principles for heavy metal contaminated farmland based on ecological risk—A case study in the pilot area of Hunan province, China

Mixture predicted no-effect concentrations of surfactants and antibiotics: Modeling based on experimental testing.

Nonylphenol (NP) is a typical type of persistent organic pollutants (POPs) with endocrine-disrupting effect. Its ecological risk has caused increasing concerns owing to its degradation-resistance, bioaccumulation, and widespread distribution in the environment. The species sensitivity distribution (SSD) method has been widely used for establishing water quality criteria (WQC) and performing ecological risk assessment (ERA) of the water environment. However, the selected sensitive species may exhibit different toxicity sensitivity in different geographical regions, which would affect the results of WQC and ERA. In this study, SSD was applied to calculate the predicted no effect concentrations (PNECs) based on the acute and chronic toxicity data of the general sensitive species and native sensitive species in China. The results showed that there was little difference between the PNECs derived from the general sensitive species and native sensitive species based on the acute toxicity data, which indicated that the sensitivity of native species towards the acute toxicity effect of NP is similar to that of general species. However, the PNECs based on the chronic toxicity data were quite different, and the Chinese native species appeared to be more sensitive than general species to the chronic toxicity effect of NP. As a result, direct use of the PNECs derived from non-local species may lead to insufficient protection of Chinese native species. Based on the PNECs derived from the acute and chronic toxicity data, the risk quotient (RQ) method was used to characterize the ecological risk of NP in the surface waters of Yangtze River Delta. The results showed that the RQ based on PNECs derived from the acute data and chronic data of general sensitive species may lead to an underestimation of the ecological risk. The mean RQ values based on the PNECs derived from the chronic data of Chinese native sensitive species ranged from 0.23 to 1.55. Luoma Lake was found at a high risk, and the maximum RQ values of Taihu Lake and Yangtze River (Nanjing) exceeded 1, indicating the high risk of the individual areas which deserve further attentions. In conclusion, the chronic toxic effect of NP on Chinese native aquatic organisms can be identified, and continuous attention should be paid to the long-term adverse effect of NP, for which actions should be taken to ensure the health of the aquatic ecosystem.

When assessing the socio‐economic impacts of climate change, it is sensible to make targeted climate projections for regions of high population density and economy activity. Much of human activity is concentrated at river basins, yet it has been difficult to resolve the complex boundaries of these basins in coarse resolution global climate models. The latest high‐resolution observation and climate projection datasets enable such basin‐based evaluations now, and this study assesses the historical and projected climate changes over three major river basins in China—the Yellow, Yangtze and Pearl River basins. Based on CN05.1 dataset, the Yellow River basin has significantly warmed by about 1.8°C over the past five decades, far more than the other two basins. The change in temperature extremes has been as severe, with the annual maxima of daily maximum temperatures (TXx) increasing by 1.5°C, and the annual minima of daily minimum temperatures (TNn) increasing by 2.5°C. Precipitation over the Yangtze River has significantly increased by about 0.2 mm·day−1, while changes over the other two basins were not statistically significant. The uncertainty in the change of precipitation was greater than that of temperature. A selection of simulations from the Fifth and Sixth Coupled Model Intercomparison Projects (CMIP5 and CMIP6) were validated against the CN05.1 dataset for the historical period of 1961–2018. Changes in temperature indices were well‐reproduced, but changes in precipitation indices poorly so. CMIP6 models performed better than the CMIP5 models. Both CMIP5 and CMIP6 multi‐model ensembles (MMEs) projected about 1.0–2.0°C warming over China and the three river basins by 2015–2050. Both MMEs projected wetting trends over most parts of China and the three river basins. Both warming and wetting were projected to accelerate with time, particularly warming over the Yellow River basin, and wetting over the Pearl River basin.

Antibiotics have been recognized as emerging pollutants due to their ecological and human health risks. This paper aims to enhance the ecological risk assessment (ERA) framework for antibiotics, to illustrate the distribution of these risks across different locations and seasons, and to identify the antibiotics that pose high ecological risk. This paper focuses on 52 antibiotics in seven major basins of China. Relying on the optimized approach of ERA and antibiotic monitoring data published from 2017 to 2021, the results of ERA are presented in multilevel. Across the study area, there are marked variations in the spatial distribution of antibiotics' ecological risks. The Huaihe River Basin, the Haihe River Basin, and the Liaohe River Basin are the top three in the ranking of present ecological risks. The research results also reveal significant differences in temporal variation, underscoring the need for increased attention during certain seasons. Ten antibiotics with high contribution rates to ecological risk are identified, which is an important reference to formulate an antibiotic control list. The multilevel results provided both risk values and their ubiquities across a broad study region, which is a powerful support for developing ecological risk management of antibiotics.

Deriving predicted no-effect concentrations (PNECs) for emerging contaminants in the river Po, Italy, using three approaches: Assessment factor, species sensitivity distribution and AQUATOX ecosystem modelling

PBDEs, PCBs and PCDD/Fs in the sediments from seven major river basins in China: Occurrence, congener profile and spatial tendency

This study presents an analysis of the changes in extreme temperatures over major river basins in China under different shared socioeconomic pathway (SSP) scenarios based on a set of dynamical downscaling over CORDEX East Asia, performed with the regional climate model RegCM4 at a resolution of 25 km, driven by the global climate model FGOALS‐g3. The results indicated that the dynamical downscaling tended to reduce the warm (cold) biases of the present‐day daily maximum (TXx) and minimum temperatures (TNn) simulated by FGOALS‐g3. Under the SSP scenarios, substantial increases in TXx and TNn and the number of warm days and warm nights throughout China were projected by both models. The average increase in TXx in most of the river basins ranged from 1 to 2°C under the SSP1‐2.6 scenario, from 2 to 3°C under the SSP2‐4.5 scenario, and from 3 to 5°C under the SSP5‐8.5 scenario. Reductions in the number of cold days and cold nights were projected across China, but these reductions were smaller than the increases in the number of warm days and warm nights. The interregional variability in the increases in TXx and TNn was more pronounced in the SSP5‐8.5 scenario and the RegCM4 model than in the other SSP scenarios and the FGOALS‐g3 model, respectively. Larger percentages of the land area and population of China would be affected by greater increases in extreme high temperatures and TNn. Under the SSP2‐4.5 (SSP1‐2.6) scenario, 20–65% (50–95%) of the impacts of extreme temperatures under the SSP5‐8.5 scenario could be avoided across most regions in China. The avoided impacts of warm days and warm nights were greater than those of the other extreme temperature indices. More of the impacts of extreme temperatures could be avoided in the Huai River basin, Yellow River basin, Hai River basin, and Northwest Interior River basin than in the other river basins in China.

Combining species sensitivity distribution (SSD) model and thermodynamic index (exergy) for system-level ecological risk assessment of contaminates in aquatic ecosystems