Freshwater Water-Quality Criteria for Chloride and Guidance for the Revision of the Water-Quality Standard in China

Placental and fetal enrichment of microplastics from disposable paper cups: implications for metabolic and reproductive health during pregnancy

The disposable paper cups (DPCs) release millions of microplastics (MPs) when used for hot beverages. However, the tissue-specific deposition and toxic effects of MPs and associated toxins remain largely unexplored, especially at daily consumption levels. We administered MPs and associated toxins extracted from leading brand DPCs to pregnant mice, revealing dose-responsive harmful effects on fetal development and maternal physiology. MPs were detected in all 13 examined tissues, with preferred depositions in the fetus, placenta, kidney, spleen, lung, and heart, contributing to impaired phenotypes. Brain tissues had the smallest MPs (90.35 % < 10 µm). A dose-responsive shift in the cecal microbiome from Firmicutes to Bacteroidetes was observed, coupled with enhanced biosynthesis of microbial fatty acids. A moderate consumption of 3.3 cups daily was sufficient to alter the cecal microbiome, global metabolic functions, and immune health, as reflected by tissue-specific transcriptomic analyses in maternal blood, placenta, and mammary glands, leading to neurodegenerative and miscarriage risks. Gene-based benchmark dose framework analysis suggested a safe exposure limit of 2 to 4 cups/day in pregnant mice. Our results highlight tissue-specific accumulation and metabolic and reproductive toxicities in mice at DPC consumption levels presumed non-hazardous, with potential health implications for pregnant women and fetuses.

Groundwater geochemistry using modified integrated water quality index (IWQI) and health indices with special emphasis on nitrates and heavy metals in southern parts of Tirupati, South India

Groundwater is particularly vulnerable to pollution in places with a high population density and extensive human usage of the land, especially in southern parts of Tirupati, India. To assess this, 60 bore-well samples were obtained and assessed for physical specifications, ion chemistry, and heavy metals during the pre- and post-monsoon seasons 2022. The current investigation employed a modified integrated water quality index (IWQI), conventional graphical and human health risk assessment (HHRA) of nitrates and heavy metals to know the groundwater chemistry and its detrimental health effects on humans. The major ions were analyzed using American public health association (APHA) standards, whereas heavy metals were analyzed using inductively coupled plasma optical emission spectrometry (ICP-OES). Additionally, pH Redox Equilibrium and C (PHREEQC), a geochemical model written in C programming language was employed to determine the saturation indices of mineral facies and ArcGIS 10.3.1 was used for spatial distribution patterns of IWQI. Then, the HHRA of nitrates and heavy metals was performed using United States environmental protection agency (US EPA) guidelines. The noteworthy outcomes include elevated levels of Ca2+, Mg2+, Cl-, NO3-, Cu, Fe, Mn, and Pb, demonstrating rock-water interaction, silicate weathering, Ca-Mg-HCO3 followed by mixed water facies, dissolution/precipitation, reverse exchange, and anthropogenic contamination are the major controlling processes in groundwater of southern Tirupati, India. The modified IWQI reveals that most groundwater samples (38%) fall under the bad quality class, with (47%) in the poor quality class and only (15%) classified as medium quality class in pre- and post-monsoon seasons. Elevated IWQI were observed in all directions except in the east, which is suitable for drinking. Moreover, the major hazard quotient (HQ) and hazard index (HI) for nitrates (NO3-) and heavy metals like copper (Cu), iron (Fe), manganese (Mn), lead (Pb) and zinc (Zn) are above the critical value of 1, revealing potential risk to humans, especially infants, followed by children and adults, entailing the instantaneous implementation of proper remedial measures and stringent policies to reduce the risk associated with groundwater pollution in the southern parts of Tirupati.

Novel Discrete and Imprinted Fluoride-Selective Sensors: Bridging the Gap from DMSO to Aqueous Samples

Fluoride in drinking water has beneficial or harmful health effects depending on its concentration. This highlights the need for new low-cost and portable sensors capable of in situ monitoring of F- ions. Unfortunately, achieving high levels of water compatibility and fluoride specificity remains a challenge. Here, four new urea-based discrete sensors are prepared and characterized. The sensors containing anthracenyl- (5) and 9H-fluorenyl- (7) signaling units exhibit intense luminescent emissions in dimethyl sulfoxide, the former being particularly sensitive and selective to fluoride. In water, 5 displays a superior sensitivity (871 M-1) and a detection limit (8 µm) below international guidelines, albeit with cross-sensitivity to H2PO4‾. To enhance the performance, 5 and 7 are embedded into a fluoride-imprinted polymeric matrix to give solid-state sensors (5P and 7P, respectively). 5P shows good sensitivity (360 M-1) and specificity in water. Besides, it has a low detection limit (35 µm) and a response linear range (118-6300 µm) encompassing the limit established by the Environmental Protection Agency (211 µm). Furthermore, 5P also displays good reusability and adequate recovery values in real-sample testing (102 ± 2%), constituting the first example of a low-cost anion-imprinted polymeric probe tailored for the selective sensing of fluoride in aqueous samples.

Groundwater Hardness and Alkalinity As Risk Factors for Kidney Stone Disease in Alwar, India: An Ecological Study

INTRODUCTION

Rajasthan is a semi-arid state in India where people still use groundwater for drinking purposes. However, the quality of groundwater as compared to standards have not been studied in any details. This ecological study was done to study the groundwater quality parameters in the stone-belt states, compare the quality of groundwater in Alwar with the rest of Rajasthan, and study the morbidity profile of surgical in-patients in the same district, with special emphasis on kidney stone disease (KSDs).

METHODS

The morbidity profile of patients coming to the surgery department of a tertiary teaching hospital between January 2002 and June 2023 was obtained from the medical records department, and water quality data was obtained from the publicly available Water Resources Information System (WRIS) groundwater dataset for the year 2023. The dataset provided detailed information on the chemical parameters of water samples throughout the country that were evaluated to estimate the quality of groundwater.

RESULTS

It was found that the groundwater in Alwar is non-potable due to the presence of iron, alkalinity, magnesium, and total dissolved solids (TDS). Iron was estimated to be much higher than the acceptable limit of the Bureau of Indian Standards (BIS) drinking-water quality guidelines (0.3 mg/L). Similarly, most of the chemical parameters in the groundwaters of Rajasthan significantly exceeded the national average. The median electrical conductivity, fluoride, magnesium, sodium, hardness, alkalinity, and turbidity were found to be 1680 μS/cm, 1.05 parts per million (PPM), 41 PPM, 233 PPM, 330 PPM, 310 PPM, 988 PPM, respectively, which are above the WHO recommendations for drinking water guidelines.

CONCLUSIONS

The levels of iron and total alkalinity were significantly higher in the study district as compared to the rest of the state. Also, magnesium hardness and TDS levels were very high in the groundwater of the entire state of Rajasthan, making the population vulnerable to KSDs in the long run.

Systematic tracking of nitrogen sources in complex river catchments: Machine learning approach based on microbial metagenomics

Tracking nitrogen pollution sources is crucial for the effective management of water quality; however, it is a challenging task due to the complex contaminative scenarios in the freshwater systems. The contaminative pattern variations can induce quick responses of aquatic microorganisms, making them sensitive indicators of pollution origins. In this study, the soil and water assessment tool, accompanied by a detailed pollution source database, was used to detect the main nitrogen pollution sources in each sub-basin of the Liuyang River watershed. Thus, each sub-basin was assigned to a known class according to SWAT outputs, including point source pollution-dominated area, crop cultivation pollution-dominated area, and the septic tank pollution-dominated area. Based on these outputs, the random forest (RF) model was developed to predict the main pollution sources from different river ecosystems using a series of input variable groups (e.g., natural macroscopic characteristics, river physicochemical properties, 16S rRNA microbial taxonomic composition, microbial metagenomic data containing taxonomic and functional information, and their combination). The accuracy and the Kappa coefficient were used as the performance metrics for the RF model. Compared with the prediction performance among all the input variable groups, the prediction performance of the RF model was significantly improved using metagenomic indices as inputs. Among the metagenomic data-based models, the combination of the taxonomic information with functional information of all the species achieved the highest accuracy (0.84) and increased median Kappa coefficient (0.70). Feature importance analysis was used to identify key features that could serve as indicators for sudden pollution accidents and contribute to the overall function of the river system. The bacteria Rhabdochromatium marinum, Frankia, Actinomycetia, and Competibacteraceae were the most important species, whose mean decrease Gini indices were 0.0023, 0.0021, 0.0019, and 0.0018, respectively, although their relative abundances ranged only from 0.0004 to 0.1 %. Among the top 30 important variables, functional variables constituted more than half, demonstrating the remarkable variation in the microbial functions among sites with distinct pollution sources and the key role of functionality in predicting pollution sources. Many functional indicators related to the metabolism of Mycobacterium tuberculosis, such as K24693, K25621, K16048, and K14952, emerged as significant important factors in distinguishing nitrogen pollution origins. With the shortage of pollution source data in developing regions, this suggested approach offers an economical, quick, and accurate solution to locate the origins of water nitrogen pollution using the metagenomic data of microbial communities.

Elucidating potential bioindicators from insights in the diversity and assembly processes of prokaryotic and eukaryotic communities in the Mekong River

Drivers for spatio-temporal distribution patterns of overall planktonic prokaryotes and eukaryotes in riverine ecosystems are generally not fully understood. This study employed amplicon metabarcoding to investigate the distributions and assembly mechanisms of bacterial and eukaryotic communities in the Mekong River. The prevailing bacteria taxa were found to be Betaproteobacteria, Actinobacteria, and Bacteroidetes, while the dominant eukaryotic organisms were cryptophytes, chlorophytes, and diatoms. The community assemblages were influenced by a combination of stochastic and deterministic processes. Drift (DR) and dispersal limitation (DL), signifying the stochastic mechanism, were the main processes shaping the overall prokaryotic and eukaryotic communities. However, homogeneous selection (HoS), indicating deterministic mechanism, played a major role in the assembly process of core prokaryotic communities, especially in the wet season. In contrast, the core eukaryotic communities including Opisthokonta, Sar, and Chlorophyta were dominated by stochastic processes. The significance of HoS within prokaryotic communities was also found to exhibit a decreasing trend from the upstream sampling sites (Chiang Saen and Chiang Khan, Nong Khai) towards the downstream sites (Mukdahan, and Khong Chiam) of the Mekong River. The environmental gradients resulting from the site-specific variations and the gradual decrease in elevation along the river may have a potential influence on the role of HoS in community assembly. Crucial environmental factors that shape the phylogenetic structure within distinct bins of the core prokaryotic communities including water depth, temperature, chloride, sodium, and sulphate were identified, as inferred by their correlation with the beta Net Relatedness Index (betaNRI) during the wet season. Overall, these findings enhance understanding of the complex mechanisms governing the spatio-temporal dynamics of prokaryotic and eukaryotic communities in the Mekong River. Finally, insights gained from this study could provide information on further use of specific core bacteria as microbial-based bioindicators that are effective for the assessment and conservation of the Mekong River ecosystem.

Advancements, Challenges, and Future Directions in Aquatic Life Criteria Research in China

Aquatic life criteria (ALC) serve as the scientific foundation for establishing water quality standards, and in China, significant strides have been made in the development of freshwater ALC. This comprehensive review traces the evolution of China's WQC, focusing on the methodological advancements and challenges in priority pollutants selection, test organism screening, and standardized ecotoxicity testing protocols. It also provides a critical evaluation of quality assurance measures, data validation techniques, and minimum data requirements essential for ALC assessments. The paper highlights China's technical guidelines for deriving ALC, and reviews the published values for typical pollutants, assessing their impact on environmental quality standards. Emerging trends and future research avenues are discussed, including the incorporation of molecular toxicology data and the development of predictive models for pollutant toxicity. The review concludes by advocating for a tiered WQC system that accommodates China's diverse ecological regions, thereby offering a robust scientific basis for enhanced water quality management.