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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.

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.

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.

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