Search

Weather generators (WGs) are tools that create synthetic weather data, which are statistically similar to the observed data. Considering the limitations of most rainfall generators to preserve satisfactorily the fundamental statistical properties (e.g., spatial and temporal coherence) simultaneously, we propose a new framework for multisite rainfall generation. The framework consists of three main components: (1) a spatiotemporal rainfall field, described as spatial modes and their corresponding temporal evolution based on empirical orthogonal function analysis (EOFA). (2) The time series of these spatial modes, decomposed into intrinsic mode functions (IMFs) with characteristic frequencies (periods) using Hilbert-Huang transform (HHT). (3) Stochastic simulation (SS), achieved by assigning random phases for the specific IMFs. The current model, EHS ( E OFA + H HT + S S), is compared with two other typical multi-site rainfall generators, MulGETS (parametric model) and KNN (non-parametric model) for a network of 12 stations in Xiang River basin, China. These three models are assessed based on their ability to simulate sequences with statistical attributes that are similar to those observed. We compare the basic statistics (mean, standard deviation, skewness), extreme value characteristics (95th percentile and maximum), spatial dependence (spatial correlation and spatial continuity ratio), and temporal dependence statistic (autocorrelation, wet/dry spells, and low-frequency variability). The results show that EHS rainfall generator has a similar capacity as KNN model in reproducing the spatial structure of the original rainfall field, and has a greater ability than MulGETS and KNN model to preserve the historical temporal statistics, especially the autocorrelation at various time scales and low-frequency variability. Overall, EHS is a useful model for generating realistic multi-site rainfall field and can be expected to generate plausible scenarios for impact studies.

Polybrominated diphenyl ethers (PBDEs) contained in electronic waste (e-waste) can be released to indoor environments and cause occupational health hazards during the recycling process. TVs, washing machines, refrigerators and printed wiring boar (PWB) represent the main domestic e-wastes. In this study, concentrations of Σ7PBDEs in air and dust samples from recycling workshops handling these four major types of e-wastes were measured, and the occupational exposure risk for workers at the corresponding workshops was evaluated. Concentrations of Σ7PBDEs in air and dust were within the ranges of 55.28–369.66 ng/m3 and 158.07–669.81 μg/g, respectively. The highest concentration of Σ7PBDEs in air was detected in the TV recycling workshop, while the refrigerator recycling workshop had the highest level of Σ7PBDEs in dust. The workers at these two e-waste recycling workshops were the most substantially exposed to BDE-209, which accounted for more than 85% of Σ7PBDEs in both air and dust. Compared to other e-waste recycling workshops, the workers at the PWB recycling workshop were also more exposed to BDE-47 and BDE-99. Occupational exposure levels for inhalation and dust ingestion were within the ranges of 3939 pg/kg/d to 26,271 pg/kg/d and 104,945 pg/kg/d to 444,694 pg/kg/d, respectively. The hazard quotient (HQ) values were calculated based on the RfDs provided by the EPA. Total HQ levels of inhalation exposure and dust ingestion were less than 0.222. The results of the HQ indicated that no adverse health effects were expected for workers in these workshops; however, the exposure risk of workers in the PWB recycling workshop (HQ=0.222) was higher than that in other e-waste recycling workshops (HQ=0.022–0.072). At the PWB recycling workshop, BDE-47 and BDE-99 caused the main occupational exposure risk to the workers, while s in the recycling plants handling other types of domestic e-waste BDE-209 was the major contributor to the risk faced by the workers.

In this study, the effect of biochar (BC) derived from Litchi chinensis Sonn. and its modification, including Ca-biochar (Ca-BC) and Fe–Mn-biochar (Fe–Mn-BC), on the transportation of oestrone (E1) in water and soil was investigated. Fe–Mn-BC showed better adsorption ability than other types of biochar (BC, Ca-BC) under different conditions (humic acid, pH, ionic strength) in an aqueous environment. The maximum mass of sorbent at 298 K increased from 1.12 mg g−1 (BC) to 4.18 mg g−1 (Fe–Mn-BC). Humic acid had a greater impact on aqueous E1 adsorption on these biochars than did the pH and ionic strength. Fe–Mn-BC as a soil amendment had a great control of E1 transport in soil, and no leachate of E1 was observed in the column experiment. E1 mobility showed strong retardation in amended soil with Ca-BC (Rf = 11.2) compared with raw soil (Rf = 7.1). These results suggested that Fe–Mn-BC was more effective in controlling E1 transportation, and Fe–Mn-BC could be used as an alternative and inexpensive adsorbent to reduce E1 contaminants from water and soil.

A quality-assured ecological risk assessment (ERA) requires enormous resources (time and labor) in collection/assessment of hazard data, as well as considerable expertise to interpret the risk. The ERA of chemicals is thereby considered difficult or impossible for those with little assessment experience and cumbersome or complicated for practitioners. To meet the concerns regarding ERA and accelerate the risk assessment and management of chemicals, we developed an all-in-one free tool for multi-purpose ecological risk assessment management (MeRAM) of chemical substances in aquatic environment called the AIST-MeRAM Ver. 2.0.0 (Copyright No: H28PRO-2007). It allows users from beginners to experts to conduct ERA without any preparation because all the necessary ecotoxicity test data and methodologies are available in the system. Approximately 270,000 ecotoxicity test data points for 3900 chemical substances together with the scientific methodologies from traditional simple hazard quotient (HQ) to more ecologically relevant complicated assessments such as species sensitivity distribution (SSD) and population-level assessment are embedded in the AIST-MeRAM. In addition, users can easily understand the Japanese regulatory RA and management of chemical substances due to a special function based on the Japanese Chemical Substance Control Law (CSCL). Here, we demonstrate a tiered ERA using the embedded sample data to evaluate and ensure the functions of AIST-MERAM. We show that the AIST-MeRAM can provide a comprehensive and accurate ERA, suggesting that it is a powerful IT solution for cumbersome ERA.

Growing concerns about the hydrological impacts of climate variability and climate change suggest an imperativeness to generate plausible climate scenarios suitable for the vulnerability assessment studies. A frequency-domain nonstationary framework for multi-site rainfall generation is proposed for decision-centric hydrological impact assessments. The framework has three main components: (1) a spatiotemporal rainfall field, described as spatial modes and their corresponding temporal evolution, based on empirical orthogonal function analysis (EOFA); (2) the time series of these spatial modes, decomposed into intrinsic mode functions (IMFs) with characteristic frequencies (periods) using the Hilbert-Huang transform (HHT); and (3) Stochastic simulation (SS), achieved by assigning random phases to the noise IMFs in combination with adjustments both to the residual series and to the signal IMFs. A synthetic test function is first used to illustrate the power of the EHS (EOFA + HHT + SS) rainfall generator to detect and extract signals (e.g., nonstationary oscillation and trend component) from noisy data. A real application of the EHS model is then presented for the Xiang River basin to demonstrate its ability (reproducibility and adaptivity). The results showed that the EHS rainfall generator has sufficient capacity in reproducing the original spatiotemporal structure, such as the spatial correlation and low-frequency variability. Meanwhile, the EHS model exhibits advantages in terms of perturbing the distribution characteristics of rainfall and altering their behavior according to the intrinsic spatial patterns. These features give the EHS model high feasibility to act as a scenario generator for generating a wide range of possible rainfall scenarios reflecting different aspects of climate variability and climate change, and hence bolster the hydrological impact analysis in the climate change context.

Heavy metal (HM) pollution is a serious and urgent issue in integrated watershed management in China and worldwide. Determining effective management strategies for pollution control requires quantification of input and output metal fluxes and the inherent uncertainties. Process-based metal models can simulate the metal movement on a watershed scale providing essential information for metal budget. However, there has been little effort to quantify the uncertainties in metal flux simulations. In this work, we modified the previously developed SWAT-HM (Soil and Water Assessment Tool – Heavy Metal) model by adding two external model inputs (atmospheric deposition and agricultural-source input) and one process-based module (plant uptake). We then linked the modified model with the SWAT Calibration and Uncertainty Programs SWAT-CUP for stochastic calibration and uncertainty analysis. The modified SWAT-HM was used to model the fluxes of primary inputs and outputs of zinc (Zn) in both uplands (soil) and channel (bed sediment) in the upper Liuyang River watershed in south-central China. To calibrate the model with uncertainty analysis, we used six-years of daily streamflow, daily sediment load, and daily Zn load at monthly frequency at the watershed outlet. In the upland phase, we identified Zn input from atmospheric deposition and Zn output through soil erosion as the most significant fluxes. In the channel phase, bed sediment was the critical Zn sink receiving 5,100 to 42,000 kg yr−1 Zn. The method used in SWAT-HM calibration and uncertainty analysis is general with potential application to similar settings in the world.

Widespread chemical plants render human life more vulnerable to major natural disasters such as earthquakes. Recognizing the potential cascading threats initiated by a devastating earthquake, a general methodology for assessing the life loss risks introduced by airborne hazardous chemical dispersion following seismically induced chemical release (SICR) was proposed. With a 600 km × 600 km region in North China as a demonstrative study area, the dispersion of ammonia released from multiple relevant chemical plants that were supposed to be damaged by a devastating earthquake was simulated in a probabilistic manner. Using an ammonia toxicity-fatality relationship and its toxicity concentration threshold, regional life loss and spatial spread were evaluated. The life loss risk was found to be non-prominent but would be very contingent on unfavorable meteorological conditions. Non-parametric correlation analysis revealed that the respective effects of meteorological mixing parameters on the risk exhibit new features in a disaster context, that is, stronger mixing would cause elevation of risk in a region. This preliminary research implied that the risk of chemical-induced life loss after a devastating earthquake deserves attention and a thorough uncertainty evaluation in the future.

Heavy metal behavior in soil and water requires modeling for a better understanding of the potential adverse impacts on the ecosystem as well as on humans. A heavy metal transport and transformation module is combined with the well-established SWAT (Soil and Water Assessment Tool) model for the purpose of simulating the fate and transport of metals at the watershed scale. The heavy metal module accounts for sorption, complexation and slow reactions among metal species; the heavy metals in the upland are allowed to transport vertically through percolation and evaporation-induced water rising as well as horizontally through soil erosion and surface/subsurface runoff; the heavy metals in the water body, in contrast, are modeled to undergo settling, resuspension, diffusion and burial processes. As a demonstration, the SWAT-laden heavy metal module (SWAT-HM) was calibrated to simulate zinc (Zn) and cadmium (Cd) dynamics in an upstream watershed of the Liuyang River in China, which has been impacted by mining activities for decades. The model simulations were found to agree reasonably well with the monitored results. In particular, the elevation of metal loads in channels with precipitation events was well represented, demonstrating that a considerable amount of Zn and Cd in the waste rock dumps and contaminated soil was released into rivers through rainfall. After a simulation of 6 years (2009–2014), the simulated Zn and Cd concentrations were used as a surrogate for the Predicted Environmental Concentration (PEC), whereby an ecological risk assessment was conducted for the demonstrative mining area. This initiative toward developing a heavy metal module combined with SWAT has high potential for application in environmental risk analysis and pollution control.

Drought disaster management entails not only understanding meteorological drought as a natural hazard but also evaluating the adverse societal impacts related to the economy and human lives. For the purpose of quantifying the drought severity from the perspective of society drought, a drought index, namely “Society Drought Severity Index” (SDSI), was put forward to analyze the drought in Yunnan Province of China. In SDSI for Yunnan, the drought severity was represented by the weighted discrepancy between the “appropriate” water needs and the total available water resources, inspired by the established Palmer Drought Severity Index (PDSI). Technically, the trend in historical water consumption records in agricultural, industrial, and domestic sectors was applied to represent the appropriate water needs; an apparent “runoff” was used to represent the available water resource in Yunnan. The SDSI of Yunnan revealed a trend toward increasing drought severity, which resulted from a combination of meteorological changes and water needs escalation. Moreover, the spatial center of the 2010 drought in Yunnan based on SDSI was different from that identified by PDSI, which exactly reflected the influence of water needs on drought severity. The SDSI was deemed to be a beneficial tool for drought disaster management and drought risk governance.

Free estrogens (estrone, E1; 17β-estradiol, 17β-E2; estriol, E3; and 17α-ethinylestradiol, EE2), their corresponding sulfate and glucuronide conjugates, and bisphenol A (BPA) were investigated in water and sediments in the Fen River catchment, an arid and semiarid area in northwest China. E1 and BPA were frequently detected in the wet and dry sampling seasons. In addition to the sulfate conjugates, other conjugated estrogens were not detected in water and sediments. The concentrations of these compounds in water generally increased from upstream to downstream. The concentrations in water samples of most sites were higher in the wet season than those in the dry season, but concentrations in sediments of most sites were higher in the dry season than those in the wet season. The distributions of these compounds in sediments were positively correlated with the total organic carbon (TOC) contents of sediments (0.3

A six-day static-renewal toxicity test was performed to determine the influences of cadmium on the development of embryos of soldatov's catfish (Silurus soldatovi). The median lethal concentration (LC50) value and median effective concentration (EC50, i.e., the total adverse effects, including developmental defects and mortality) were calculated to be 2740 and 133 μg/L, respectively, when cadmium was prepared in dilution water. The LC50 decreased to 266 μg/L in a subsequent test one month later, thereby suggesting that the sensitivity of this fish to cadmium in the early life stage(1) was largely influenced by the quality of fertilized eggs, which is known to be dependent on the season. The mortality and total adverse effects showed a concentration-dependent relationship at dosages greater than 1000 or 10 μg/L (p

Alcohol ethoxylate (AE) is a widely used household detergent that is ubiquitous in aquatic environments. To assess and manage the risk of AE, its environmental exposure concentrations must be evaluated in rivers nationwide; however, very few AE monitoring data are currently available. Furthermore, developing a rigorous exposure model that would cover rivers nationwide would require a great deal of time, human resources, and money. We developed a new approach to estimate AE concentrations in rivers throughout Japan for screening-level risk assessment. In this approach, five-day biochemical oxygen demand (BOD5) data were used as a surrogate indicator of the AE concentration in river water. The Tama and Nikko Rivers were ranked according to their BOD5 data, and the AE concentrations of the Nikko River were then estimated using the Standardized Hydrology-based Assessment tool for chemical Exposure Load (AIST-SHANEL) model. For each river, the concentrations of AE in its waters were projected based on that riv...

Membrane separation was employed in a novel photocatalytic oxidation slurry reactor to conserve catalyst. This paper reports some critical operational conditions of this reactor. While fine-bubble aeration served to suspend the catalyst, introducing an intermittent coarse bubbling under the membrane during operation was vital to counteract TiO2 catalyst entrapment on membrane surface. Circulation flow in the reactor was also found to have certain effect on counteracting the dropping out of catalyst. A submerged membrane module with a pore size of 0.1 μm successfully conserved the powdered catalysts within the reactor after 2 days’ preluding filtration. As for pollutant removal, membrane filtration and circulation flow had no effect, whereas increase in gas holdup had. Running the reactor to treat model pollutant dissolved in tap water revealed that calcium carbonate both deactivated the catalyst and contributed to membrane fouling, suggesting that water hardness and alkalinity deserves appropriate treatment to warrant a good performance of such a reactor.

Here we report a structured matrix model for wild Japanese medaka (Oryzias latipes) and the use of the model to predict the population-level effects of 4-nonylphenol (4-NP) using a stochastic simulation approach. In the model, the natural fecundity and mortality rates of wild medaka were considered inhibited by 4-NP, based on Weibull dose–response models estimated from a full life-cycle toxicity test. The matrix model was simulated according to three scenarios: (1) stochastic daily growth under optimal conditions, (2) stochastic annual growth under conditions of seasonal variation and (3) population dynamics over 3 years undergoing density-regulation. Accordingly, a finite population growth rate, λ, was applied as an endpoint in the first and second scenarios and a quasi-extinction risk in the third scenario. The median and 95% confidence interval (CI) of 4-NP concentrations corresponding to λ = 1 (Cλ=1) in the first and second scenarios were 27.5 μg/L (CI: [20.2, 33.0] μg/L) and 17.0 μg/L (CI: [16.0, 17.9] μg/L), respectively. The quasi-extinction risks mounted quickly when the exposure concentration approached Cλ=1. The influence of uncertainties was analyzed, and the Cλ=1 was found to be robust against uncertainties in both the mean and the variation of vital rates, whereas the quasi-extinction risk was moderately sensitive to the mean mortality rate. The ignorance of whether the survival of adult madaka should be considered inhibited by 4-NP or not was found to remarkably affect the population-level effects. This study demonstrates an application of Cλ=1 in a stochastic sense as a population-level ecological risk assessment (PLERA) endpoint in chemical risk management.

A novel configuration of a photocatalytic slurry reactor using low-pressure mercury lamps coupled with membrane filtration was proposed, and treatment of polluted river water with a pilot plant of this system was investigated. Both COD and NH+4-N in the river water were simultaneously removed. Under the conditions of a hydraulic retention time of 3.0 h, influent COD strength of 50–80 mg L−1 and NH+4-N of 2–6 mg L−1, 80% COD and 50% NH+4-N were achieved, respectively. The reactor was found to own a higher UV utilization effectiveness than most reported photocatalytic reactors. Intermittent backwash was effective to retard the membrane fouling and enable stable membrane operation for more than 1 month. An adhered catalyst, algae and fungi in the river water were the main contaminants of the membrane, but the membrane permeability could be almost recovered through sequential rinsing by tap water and a sodium hypochlorite solution. After continuous operation for over 1 month, the photocatalytic activity of catalysts was found elevated, which likely resulted from adsorption of hydroxyl-rich alcohols onto the catalyst surfaces.

A six-day static-renewal toxicity test was performed to determine the influences of cadmium on the development of embryos of soldatov's catfish (Silurus soldatovi). The median lethal concentration (LC50) value and median effective concentration (EC50, i.e., the total adverse effects, including developmental defects and mortality) were calculated to be 2740 and 133 μg/L, respectively, when cadmium was prepared in dilution water. The LC50 decreased to 266 μg/L in a subsequent test one month later, thereby suggesting that the sensitivity of this fish to cadmium in the early life stage(1) was largely influenced by the quality of fertilized eggs, which is known to be dependent on the season. The mortality and total adverse effects showed a concentration-dependent relationship at dosages greater than 1000 or 10 μg/L (p0.05), respectively, at pro-larva stage (i.e., 144 hpf) with dilution water. To compare the toxic effects of cadmium under field and experimental conditions, filtered river water was adopted as a solvent simultaneously compared with dilution water. No significant differences were observed in mortality rate, hatching rate and adverse effect prevalence between the two solvents. In comparison to previously published toxicity data for other fish, the pro-larva of soldatov's catfish were less sensitive than established test fish in the early life stage. Therefore, the environmental risks would be overestimated when considering only existing toxicity data for other test fish.

A body length based population model was put forward to depict the dynamics of large icefish (Protosalanx hyalocranius), in the context of ecological risk analysis for northern China waters. The body length of large icefish individual governs its feeding preference to zooplankton, forage fishes, and phytoplankton, as renders body length distribution indispensible for modeling of the large icefish population. A normal distribution and a shifted lognormal distribution were found to fit the body lengths reasonably well for mean length below and above 80mm, respectively. Use of the fitted body length distributions was made to estimate the transition rate from omnivorous juveniles to adults that prey exclusively on forage fishes. With the body length distributions embedded, a large icefish population model was established and parameterized with typical vitality values in Daihai Lake in northern China. The model was simulated along with the modules for phytoplankton, zooplankton, and forage fishes, and the simulated dynamics exhibited consistence with the seasonal fluctuations observed in the field. The large icefish population model was deemed a useful demonstration for ecological risk assessment of populations with short lifecycles.

Ecological risk assessment for chemical management favors multi-species as the protective object. Since different species respond differently, species sensitivity distribution (SSD) is applied to delineate the impact and to infer criterion concentration of a chemical. A SSD is usually established with ecotoxicity test data of different species, usually No-Observed-Effect-Concentrations (NOECs) derived from chronic bioassays. Based on the SSD, the concentration that begets impairment in 5% of the total species in the ecosystem, denoted as HC5, together with its 95% lower limit value, is used for regulation. The dependence of SSD on NOECs entails that the uncertainties in NOEC values will skew the shape of SSD and consequently the HC5, as is of much importance since NOEC value is generally prone to errors. This study demonstrated the bias in HC5 with Monte Carlo simulations by assuming different uncertainty levels in NOECs. With increasing NOEC uncertainty, the HC5 and its lower limit were found to shift downwards substantially, implying underestimation of the ecological risk if NOEC uncertainty is disregarded. By incorporating the NOEC variances during the HC5 inference procedure, the bias could be adequately corrected. However, simulating SSD through Monte Carlo approach is probably indispensable in the case of irregular NOECs uncertainties.

Surface water quality and its natural and anthropogenic controls in the Xiangjiang River were investigated using multivariate statistical approaches and a comprehensive observation dataset collected from 2004 to 2008. Cluster analysis (CA) grouped the 15 different sampling stations into five clusters with similar hydrochemistry characteristics and pollution levels. Four principal components (PCs), nutrients, heavy metals, natural components, and organic components, were extracted from the entire dataset. Comparison of the different regional characteristics of these four PCs revealed a decreasing trend for heavy metals and an increasing trend for organic factor on an annual scale, and the seasonal trend was only observed for natural factor. We also conducted analysis of variance (ANOVA) in combination with principal component analysis (PCA) to quantify the relative contribution of spatial and temporal variations to each of the four PCs. The results revealed that 62% of the contributions from the spatial sites were responsible for variations in heavy metals, while 83% of the contributions from the sampling time were responsible for natural variations observed. However, no significant spatial or temporal contributions were found to be responsible for the nutrient and organic variations. Finally, some suggestions regarding water management were put forward based on the current status and future trends of surface water quality in the Xiangjiang River.

Population-level ecological risk assessment (PLERA) for chemicals has been advocated for broader application in chemicals' risk management. The persistence capability, indicated by the finite growth rate (lambda) of certain population is scientifically soundly founded and is an appropriate risk assessment endpoint. In accordance, the concentration by which a population vitality is so stressed that its lambda value is reduced to be one, can serve as a criterion concentration, denoted as C lambda=1 . Nonetheless, seasonal variation is desirably taken into account when deriving C lambda=1 for better ecological relevance. This paper revisited the algorithm for C lambda=1 derivation and proposed an improved algorithm for faster calculation. Specifically, in the algorithm, the age-structured projection matrix (namely Leslie matrix) was collapsed into a much smaller stage-structured projection matrix. The new algorithm was compared to the normal algorithm with a case study of nonylphenol on Japanese medaka (Oryzias latipes), and the simulation results suggest that the new algorithm can save computation time by around three quarters with a small underestimation of the variance and slight bias. The proposed algorithm is considered useful for a fast or screening stage of PLERA.

A feed-forward artificial neural network (ANN) has been developed for predicting the aquatic ecotoxicity of alcohol ethoxylate (AE), a non-ionic surfactant comprising a variety of homologues. Trained with previously reported ecotoxicity data, the ANN utilizes both molecular characteristics (alkyl chain length, branching extent in alkyl chain, and ethoxylate (EO) number) and exposure features (effect endpoint, test duration, test type, and species taxon) as inputs to predict the ecotoxicity. The ANN predicted an increase in ecotoxicity for homologues with a longer or less-branched alkyl chain, or those with fewer EO units. But for long alkyl chain (>14) homologues, the ecotoxicity increase was predicted by the ANN to level off, which is obscured by existing quantitative structure–activity relationships (QSARs). A “leave-one-out” cross-validation process indicated that the prediction accuracy was within a factor of 5 with 90% probability. This research demonstrated that the current ANN covers a wider application domain with respect to the homologue range and a variety of exposure features without compromising on predictive accuracy.

In order to clarify the dependence of apparent adsorption constant Ks in the Langmuir-Hinshelwood (L-H) model on the incident light intensity, photocatalytic degradation kinetic characteristics were experimentally investigated at different light intensities using para-chlorobenzoate (4-CBA) as a model compound. In all cases 4-CBA initial degradation rates showed dependence on 4-CBA initial concentration, which can be described by the L-H model. However, the adsorption constant Ks and rate constant kr obviously varied with light intensity. To account for the experimental finding, slight modification of the classic kinetic model developed by Turchi and Ollis was tentatively proposed by assuming insufficiency of H2O/OH− available for photo-activated holes' scavenging. Such a kinetic model predicts that both kr and Ks−1 are linearly proportional to the square root of the intensity in a rather large intensity range. The validity of the modified model was proved by fitting it to the experimental data.

An extrapolation approach is proposed using available acute (median lethal or effect concentration) and chronic (no- observed-effect concentration) toxicity test data at the organism level to derive a reference value contributing to the development of predicted-no-effect concentration on population persistence for population-level ecological risk assessment of chemicals. A matrix population model of wild medaka (Oryzias latipes) was employed as the tool to integrate the available organism-level toxicity test data on reproduction and survival into a finite population growth rate () that provides information regarding the status of the population persistence. After demonstrating the approach using the acute and chronic toxicity test data of alcohol ethyxolate on fish to calculate the reference value defined as the concentration at 1( C1), the proposed approach was then evaluated by a comparison of the C1 value derived by the extrapolation approach to those C1 values calculated by two other approaches, in which different amounts of toxicity information contained in the same full life-cycle toxicity test data set on 4-nonylphenol were employed. It was concluded that this extrapolation approach is widely applicable and is promising for performing population-level ecological risk assessment on a more general basis that can support reasonable chemical management. Keywords—Population-level ecological risk assessment Chemical substances Acute/chronic toxicity test data Predicted-no-effect concentration Population growth rate ()