Nitrogen and phosphorus adsorption in aqueous solutions by humic acids from weathered coal: isotherm, kinetics and thermodynamic analysis.

The aim of this study was to reveal the mechanism of nitrogen and phosphorus adsorption by humic acids (HAs). HAs were extracted from weathered coal and used as adsorbents of urea-N and phosphate-P in water. The effect of different factors was considered, such as the initial concentration of urea-N and phosphate-P, temperature, and pH. The surface characteristics of the HAs were analyzed by X-ray diffraction, scanning electron microscopy, energy dispersive X-ray spectroscopy, and Fourier transform infrared spectrometry. The results of batch adsorption experiments showed high effectiveness for nitrogen adsorption, the kinetics fitted with the pseudo-second-order model, and the isotherm followed the Langmuir model. For phosphorus adsorption, the data fitted well with the Weber and Morris model and the adsorption isotherms followed both the Langmuir and Freundlich isotherm models. The experimental results indicated that the adsorption behavior of HAs was both an endothermic and spontaneous process. These findings can be used as a reference for the mitigation of non-point source pollution and the application of fertilizer in agriculture.

The application of human-derived cell lines in neurotoxicity studies of environmental pollutants.

As industrial and societal advancements progress, an increasing number of environmental pollutants linked to human existence have been substantiated to elicit neurotoxicity and developmental neural toxicity. For research in this field, human-derived neural cell lines have become excellent in vitro models. This study examines the utilization of immortalized cell lines, specifically the SH-SY5Y human neuroblastoma cell line, and neural cells derived from human pluripotent stem cells, in the investigation of neurotoxicity and developmental neural toxicity caused by environmental pollutants. The study also explores the culturing techniques employed for these cell lines and provides an overview of the standardized assays used to assess various biological endpoints. The environmental pollutants involved include a variety of organic compounds, heavy metals, and microplastics. The utilization of cell lines derived from human sources holds significant significance in elucidating the neurotoxic effects of environmental pollutants and the underlying mechanisms. Finally, we propose the possibility of improving the in vitro model of the human nervous system and the toxicity detection methods.

Health risk assessment and development of human health ambient water quality criteria for PCBs in Taihu Basin, China.

Polychlorinated biphenyls (PCBs) are a class of typical persistent organic pollutants (POPs) with carcinogenicity and extensively found in diverse environmental mediums. The Taihu Basin is one of the most economically developed regions in China, and it has also caused a lot of historical legacy and unconscious emissions of PCBs, posing a threat to the health of people in the region. This study counted the concentrations of PCBs in five environmental media (water, soil, air, dust, and food) in the Taihu Basin from 2000 to 2020 and used Monte Carlo simulation to simulate the multi-channel exposure of PCBs in people of different ages (children, teenagers, and adults), and evaluated their noncarcinogenic and carcinogenic health risks. Finally, the human health ambient water quality standards (AWQC) for PCBs were obtained using regional exposure parameters and bioaccumulation factors. The results showed that the pollution of PCBs in the Taihu Basin was relatively serious in China. The concentration of PCBs in dust is higher than other environmental media. And exposure to water and food is the main exposure pathway for PCBs in the population of the region. Besides, PCBs pose no noncarcinogenic risk to people in this region, but their carcinogenic risk to residents exceeds the safety threshold. Among the three population groups, adults have the highest risk of cancer, and prevention measures need to be taken by controlling the intake of related foods and the concentration of PCBs in water. The following human health AWQC values of the PCBs in Taihu Basin is 3.2 × 10-9 mg/L.

QSAR-QSIIR-based prediction of bioconcentration factor using machine learning and preliminary application.

Bioconcentration factor (BCF) is one of the important parameters for developing human health ambient water quality criteria (HHAWQC) for chemical pollutants. Traditional experimental method to obtain BCF is time-consuming and costly. Therefore, prediction of BCF by modeling has attracted much attention. QSAR (Quantitative Structure-Activity Relationship) model based on molecular descriptor is often used to predict BCF, however, in order to improve the accuracy of prediction, previous models are only applicable for prediction for a single category of substance and a single species, and cannot meet the needs of BCF prediction of pollutants lacing toxicity data. In this study, optimized 17 traditional molecular descriptor and five kinds of bioactivity descriptor were selected from more than 200 molecular descriptor and 25 kinds of biological activity descriptors. A QSAR-QSIIR (Quantitative Structure In vitro-In vivo Relationship) model suitable for multiple chemical substances and whole species is constructed by using optimized 4-MLP machine learning algorithm with selected molecular and bioactivity descriptors. The constructed model significantly improves the prediction accuracy of BCF. The R2 of verification set and test set are 0.8575 and 0.7924, respectively, and the difference between predicted BCF and measured BCF is mostly less than 1.5 times. Then, BCF of BTEX in Chinese common aquatic products is predicted using the constructed QSAR-QSIIR model, and the HHAWQC of BTEX in China are derived using the predicted BCF, which provides a valuable reference for establishment of China's BTEX water quality standards.

The Application of Reference Dose Prediction Model to Human Health Water Quality Criteria and Risk Assessment.

Oral reference dose (RfD) is a key parameter for deriving the human health ambient water quality criteria (AWQC) for non-carcinogenic substances. In this study, a non-experimental approach was used to calculate the RfD values, which explore the potential correlation between toxicity and physicochemical characteristics and the chemical structure of pesticides. The molecular descriptors of contaminants were calculated using T.E.S.T software from EPA, and a prediction model was developed using a stepwise multiple linear regression (MLR) approaches. Approximately 95% and 85% of the data points differ by less than 10-fold and 5-fold between predicted values and true values, respectively, which improves the efficiency of RfD calculation. The model prediction values have certain reference values in the absence of experimental data, which is beneficial to the advancement of contaminant health risk assessment. In addition, using the prediction model constructed in this manuscript, the RfD values of two pesticide substances in the list of priority pollutants are calculated to derive human health water quality criteria. Furthermore, an initial assessment of the health risk was performed by the quotient value method based on the human health water quality criteria calculated by the prediction model.

Chinese Technical Guideline for Deriving Water Quality Criteria for Protection of Freshwater Organisms.

In recent years, China has determined the national goal of "developing national environmental criteria", thereby promoting the rapid development of environmental quality criteria research in China. In 2017, the Ministry of Ecology and Environment of China (MEEC, formerly the Ministry of Environmental Protection of China) issued the technical guideline for deriving water quality criteria (WQC) for protection of freshwater organisms (HJ 831-2017), and in 2022, they organized the guideline revision and issued an updated version (HJ 831-2022). The primary contents of the revision included the following. The minimum toxicity data requirements were upgraded from 6 to 10, and the species mean toxicity value was replaced by the same effect toxicity value for the criteria calculation. It is now required that the tested organisms must be distributed in China's natural fresh waters, and the toxicity data of non-native model species will no longer be used. The list of freshwater invasive species in China that cannot be used as test species was added into the guideline. The acute/chronic ratio (ACR) method for the criteria derivation and the extreme value model were deleted, and the provisions for testing the toxicity data distribution were also deleted. The exposure time of the toxicity test of various tested organisms was refined, and the priority of the toxicity data was clearly specified. This paper introduces the framework and specific technical requirements of HJ 831-2022 in detail, including data collection, pre-processing of toxicity data, criteria derivation, fitting models, and quality control. This introduction is helpful for international peers to understand the latest research progress of China's WQC.

Reference dose prediction by using CDK molecular descriptors: A non-experimental method.

Reference dose (RfD) is an estimate of a daily dose that individual can be exposed chronically without obvious deleterious effects during a lifetime. In the area of toxicology, researchers always use the traditional approach by employing NOAEL/LOAEL or the benchmark dose (BMD) and other dose-response approaches to estimate RfD. These methods have, despite their typicalness, certain limitations. In this study, we present a novel method of the estimation of reference dose without experiments. The information of the organic chemicals is available from the Integrated Risk Information System (IRIS) of USEPA. Molecular descriptors for each molecular structure were calculated by an integrated platform, and the chemicals were classified into four categories based on molecular similarity: 128 contained benzene rings, 47 were heteroaromatics, 104 contained halogen substituents and 44 were halogenated aliphatic hydrocarbons. The predictive model of RfD was constructed by the multiple linear stepwise regression (MLR) method. Approximately 95% and 82% of the data points differ by less than 10-fold and 5-fold between the predicted values and the true values respectively. The non-experimental method improves the estimation efficiency and has a certain reference value to predict.

Health risk assessment and development of human health ambient water quality criteria for PBDEs in China.

Polybrominated diphenyl ethers (PBDEs) are not only a class of highly efficient brominated flame retardants (BFRs) but also a class of typical persistent organic pollutants (POPs) that are persistent and widely distributed in various environmental media. This study examined the concentrations of PBDEs in five environmental media (water, soil, air, dust, and food) and two human body media (human milk and blood) in China from 2010 to 2020. In addition, this study conducted multi-pathway exposure health risk assessments of populations of different ages in urban, rural, key regions, and industrial factories using the Monte-Carlo simulation. Finally, the human health ambient water quality criteria (AWQC) of eight PBDEs were derived using Chinese exposure parameters and bioaccumulation factors (BAFs). The results showed that the eastern and southeastern coastal regions of China were heavily polluted by PBDEs, and the variation trends of the ΣPBDEs concentrations in the different exposure media were not consistent. PBDEs did not pose a risk to urban and rural residents in ordinary regions, but the hazard indexes (HIs) for residents in key regions and occupational workers exceeded the safety threshold. Dust exposure was the primary exposure pathway for urban and rural residents in ordinary regions, but for residents in key regions and occupational workers, dietary exposure was the primary exposure pathway. BDE-209 was found to be the most serious individual PBDE congener in China. The following human health AWQC values of the PBDEs were derived: drinking water exposure: 0.233-65.2 µg·L-1; and drinking water and aquatic products exposure: 8.51 × 10-4-1.10 µg·L-1.

Responses of Low-Quality Soil Microbial Community Structure and Activities to Application of a Mixed Material of Humic Acid, Biochar, and Super Absorbent Polymer.

Low-quality soil for land reuse is a crucial problem in vegetation quality and especially to waste disposal sites in mining areas. It is necessary to find suitable materials to improve the soil quality and especially to increase soil microbial diversity and activity. In this study, pot experiments were conducted to investigate the effect of a mixed material of humic acid, super absorbent polymer and biochar on low-quality soil indexes and the microbial community response. The indexes included soil physicochemical properties and the corresponding plant growth. The results showed that the mixed material could improve chemical properties and physical structure of soil by increasing the bulk density, porosity, macro aggregate, and promote the mineralization of nutrient elements in soil. The best performance was achieved by adding 3 g·kg-1 super absorbent polymer, 3 g·kg-1 humic acid, and 10 g·kg-1 biochar to soil with plant total nitrogen, dry weight and height increased by 85.18%, 266.41% and 74.06%, respectively. Physicochemical properties caused changes in soil microbial diversity. Acidobacteria, Bacteroidetes, Chloroflexi, Cyanobacteria, Firmicutes, Nitrospirae, Planctomycetes, and Proteobacteria were significantly positively correlated with most of the physical, chemical and plant indicators. Actinobacteria and Armatimonadetes were significantly negatively correlated with most measurement factors. Therefore, this study can contribute to improving the understanding of low-quality soil and how it affects soil microbial functions and sustainability.

Heavy metals and metalloids in the surface sediments of the Xiangjiang River, Hunan, China: distribution, contamination, and ecological risk assessment.

Here, we aim to determine the distribution, ecological risk and sources of heavy metals and metalloids in the surface sediments of the Xiangjiang River, Hunan Province, China. Sixty-four surface sediment samples were collected in 16 sites of the Xiangjiang River, and the concentrations of ten heavy metals and metalloids (Mn, Zn, Cr, V, Pb, Cu, As, Ni, Co, and Cd) in the sediment samples were investigated using an inductively coupled plasma mass spectrometer (ICP-MS) and an atomic fluorescence spectrophotometer (AFS), respectively. The results showed that the mean concentrations of the ten heavy metals and metalloids in the sediment samples followed the order Mn > Zn > Cr > V > Pb > Cu > As ≈ Ni >Co > Cd. The geoaccumulation index (I geo), enrichment factor (EF), modified degree of contamination (mCd), and potential ecological risk index (RI) revealed that Cd, followed by Pb, Zn, and Cu, caused severely contaminated and posed very highly potential ecological risk in the Xiangjiang River, especially in Shuikoushan of Hengyang, Xiawan of Zhuzhou, and Yijiawan of Xiangtan. The Pearson's correlation coefficient (PCC) analysis, principal component analysis (PCA), and hierarchical cluster analysis (HCA) indicated that the ten heavy metals and metalloids in the sampling sediments of the Xiangjiang River were classified into three groups: (1) Cd, Pb, Zn, and Cu which possibly originated from Shuikoushan, Xiawan, and Yijiawan clustering Pb-Zn mining and smelting industries; (2) Co, V, Ni, Cr, and Al from natural resources; and (3) Mn and As. Therefore, our results suggest that anthropogenic activities, especially mining and smelting, have caused severe contamination of Cd, Pb, Zn, and Cu and posed very high potential ecological risk in the Xiangjiang River.