Tree water uptake patterns across the globe.

Plant water uptake from the soil is a crucial element of the global hydrological cycle and essential for vegetation drought resilience. Yet, knowledge of how the distribution of water uptake depth (WUD) varies across species, climates, and seasons is scarce relative to our knowledge of aboveground plant functions. With a global literature review, we found that average WUD varied more among biomes than plant functional types (i.e. deciduous/evergreen broadleaves and conifers), illustrating the importance of the hydroclimate, especially precipitation seasonality, on WUD. By combining records of rooting depth with WUD, we observed a consistently deeper maximum rooting depth than WUD with the largest differences in arid regions - indicating that deep taproots act as lifelines while not contributing to the majority of water uptake. The most ubiquitous observation across the literature was that woody plants switch water sources to soil layers with the highest water availability within short timescales. Hence, seasonal shifts to deep soil layers occur across the globe when shallow soils are drying out, allowing continued transpiration and hydraulic safety. While there are still significant gaps in our understanding of WUD, the consistency across global ecosystems allows integration of existing knowledge into the next generation of vegetation process models.

A Mine Water Source Prediction Model Based on LIF Technology and BWO-ELM.

The traditional methods for identifying water sources in coal mines lack the ability to quickly detect water sources and are prone to causing secondary pollution of samples. In contrast, laser induced fluorescence (LIF) technology has been introduced for the identification of coal mine water sources due to its high sensitivity and real-time performance. However, extreme learning machine (ELM) have shortcomings in randomly selecting weights and biases. The Beluga Whale Optimization (BWO) algorithm has efficient optimization capability, global search capability, adaptability and parallelism, and can find the optimal weights and biases in a short time. The combination of LIF technology and BWO-ELM model can be applied to quickly identify the welling water source in coal mine. Select sandstone water and old goaf water from the Huainan mining area as experimental samples, and mix them in different proportions to prepare 7 mixed water samples for testing. Utilize LIF technology to obtain spectral curve images, preprocess them with polynomial smoothing algorithm (SG) and spectral multiple scattering correction (MSC), and perform dimensionality reduction using factor analysis (FA) and linear discriminant analysis (LDA) methods. Finally, construct ELM models, Long Short Term Memory (LSTM) models, BWO-ELM models, and Particle Swarm Optimization Extreme Learning Machine(PSO-ELM) models for the dimensionality reduced data. In order to improve the reliability and accuracy of the results, the experimental results were kept to 5 decimal places. From the experimental results, it can be seen that SG-LDA-BWO-ELM has the best fitting effect, with a fitting coefficient of 0.99990, a root mean square error of 0.00041, a mean square error approaching 0, and an average absolute error of 0.00021. It has the best convergence and the smallest absolute error among all models, making it the most suitable for identifying mine water inrush. It is of great significance for preventing and controlling mine water disasters and ensuring coal mine production safety.

Metatranscriptomic data mining together with microfluidic card uncovered the potential pathogens and seasonal RNA viral ecology in a drinking water source.

AIMS: Despite metatranscriptomics becoming an emerging tool for pathogen surveillance, very little is known about the feasibility of this approach for understanding the fate of human-derived pathogens in drinking water sources. METHODS AND RESULTS: We conducted multiplexed microfluidic cards and metatranscriptomic sequencing of the drinking water source in a border city of North Korea in four seasons. Microfluidic card detected norovirus, hepatitis B virus (HBV), enterovirus, and Vibrio cholerae in the water. Phylogenetic analyses showed that environmental-derived sequences from norovirus GII.17, genotype C of HBV, and coxsackievirus A6 (CA6) were genetically related to the local clinical isolates. Meanwhile, metatranscriptomic assembly suggested that several bacterial pathogens, including Acinetobacter johnsonii and V. cholerae might be prevalent in the studied region. Metatranscriptomic analysis recovered 349 species-level groups with substantial viral diversity without detection of norovirus, HBV, and CA6. Seasonally distinct virus communities were also found. Specifically, 126, 73, 126, and 457 types of viruses were identified in spring, summer, autumn, and winter, respectively. The viromes were dominated by the Pisuviricota phylum, including members from Marnaviridae, Dicistroviridae, Luteoviridae, Potyviridae, Picornaviridae, Astroviridae, and Picobirnaviridae families. Further phylogenetic analyses of RNA (Ribonucleic Acid)-dependent RNA polymerase (RdRp) sequences showed a diverse set of picorna-like viruses associated with shellfish, of which several novel picorna-like viruses were also identified. Additionally, potential animal pathogens, including infectious bronchitis virus, Bat dicibavirus, Bat nodavirus, Bat picornavirus 2, infectious bursal disease virus, and Macrobrachium rosenbergii nodavirus were also identified. CONCLUSIONS: Our data illustrate the divergence between microfluidic cards and metatranscriptomics, highlighting that the combination of both methods facilitates the source tracking of human viruses in challenging settings without sufficient clinical surveillance.

Differentiated cognition of the effects of human activities on typical persistent organic pollutants and bacterioplankton community in drinking water source.

Accelerated urbanization in developing countries led to a typical gradient of human activities (low, moderate and high human activities), which affected the pollution characteristics and ecological functions of aquatic environment. However, the occurrence characteristics of typical persistent organic pollutants, including organochlorine pesticides (OCPs) and polycyclic aromatic hydrocarbons (PAHs), and bacterioplankton associated with the gradient of human activities in drinking water sources is still lacking. Our study focused on a representative case - the upper reaches of the Dongjiang River (Pearl River Basin, China), a drinking water source characterized by a gradient of human activities. A comprehensive analysis of PAHs, OCPs and bacterioplankton in the water phase was performed using gas chromatography-mass spectrometry (GC-MS) and the Illumina platform. Moderate human activity could increase the pollution of OCPs and PAHs due to local agricultural activities. The gradient of human activities obviously influenced the bacterioplankton community composition and interaction dynamics, and low human activity resulted in low bacterioplankton diversity. Co-occurrence network analysis indicated that moderate human activity could promote a more modular organization of the bacterioplankton community. Structural equation models showed that nutrients could exert a negative influence on the composition of bacterioplankton, and this phenomenon did not change with the gradient of human activities. OCPs played a negative role in shaping bacterioplankton composition under the low and high human activities, but had a positive effect under the moderate human activity. In contrast, PAHs showed a strong positive effect on bacterioplankton composition under low and high human activities and a weak negative effect under moderate human activity. Overall, these results shed light on the occurrence characteristics of OCPs, PAHs and their ecological effects on bacterioplankton in drinking water sources along the gradient of human activities.

Exploring correlations between microplastics, microorganisms, and water quality in an urban drinking water source.

The microplastic pollution in freshwater system is gradually becoming more severe, which has led to increasing attention on the distribution and potential harmful effects of microplastics. Moreover, microplastics may have an impact on river ecology and pose risks to ecosystems. Therefore, it is important to reveal this process. This study aimed to explore correlations between microplastics and free-living microorganisms in an urban drinking water source of Xiangjiang River by using multivariate statistical analysis. The results indicated that the abundance of microplastics (size 50 µm to 5 mm) in surface water and sediments ranged from 0.72 to 18.6 (mean ± SD: 7.32 ± 2.36) items L-1 and 26.3-302 (150 ± 75.6) items kg-1 dry weight (dw), respectively, suggesting potential microplastic pollution despite the protected status as a drinking water source. Higher microplastic abundances were observed in urban areas and the downstream of wastewater plants, with mostly granular shape, transparent and black color as well as 50-100 µm in size. The multivariate statistical analysis presented that the abundance of microplastics is not significantly correlated with water indicators, due to the complexity of the abundance data. The water indicators showed an obvious correlation with microplastics in colors of transparent and black, and smaller sizes of 50-100 µm. This is also true for microplastics and microorganisms in water and sediment. Proteobacteria was the main prokaryote in water and sediments, being positively correlated with 50-100 µm microplastics; while Chloroplastida was the dominated eukaryotes, presenting a weak correlation with smaller-size microplastics. Overall, when considering the properties of microplastics such as shape, color and size, the potential correlations with water indicators and microorganisms were more evident than abundance. This study provides new insights into the multivariate statistical analysis, explaining the potential correlations among microplastic properties, microorganisms and environmental factors in a river system.

The effect of freeze-thaw action on the dynamic change of supra-permafrost water sources: A stable isotope perspective.

Due to the continuous degradation (gradual thawing) of permafrost, supra-permafrost water has become an important component of runoff that occurs in cold regions. However, current research has only focused on the amount of water provided by permafrost, and little has been reported regarding the source and formation mechanisms of supra-permafrost water. Due to the difficulty of observation and sampling in cold regions and insufficient data accumulation, model simulations face various difficulties in regard to solving problems related to hydrological processes. Considering the advantages of stable isotope tracer methods in hydrology, the source of supra-permafrost water in Qilian Mountain was analyzed based on 1,840 samples, and the source of supra-permafrost water was determined by end-member mixing analysis (EMMA). Negative line-conditioned excess (lc-excess), lower slope, and particularly the negative intercept of the evaporation line (EL) indicates strong evaporation effects on supra-permafrost water. Remarkably, the evolutionary process, influencing factors, and relationship with other water bodies all indicate that supra-permafrost water is replenished by precipitation, ground ice meltwater, and snow meltwater. The results indicated that from May to October, the contributions of precipitation to the supra-permafrost water were 79%, 83%, 90%, 84%, 87%, and 83%, respectively. Snow meltwater contributed 11%, 13%, 10%, 16%, 11%, and 9%, respectively. Permafrost degradation impacts the water cycle and can increase the minimum monthly runoff and increase groundwater storage. To mitigate the effects of this change, monitoring and early warning systems are essential for detecting signs of permafrost degradation in a timely manner so that appropriate measures can be taken. This may involve the use of remote-sensing technologies, sensor networks, and other methods for real-time monitoring. Establishing mechanisms for sharing information with the relevant departments is crucial. The research results provide scientific and technological support and aid in decision-making to mitigate the negative effects of continuous permafrost degradation in a changing environment.

Performance of aerobic denitrifying fungal community for promoting nitrogen reduction and its application in drinking water reservoirs.

The effect of mix-cultured aerobic denitrifying microorganisms on the water remediation has been extensively explored, but little is known about the performance of mix-cultured low efficiency fungi on denitrification. In this study, two kinds of aerobic denitrifying fungi (Trichoderma afroharzianum H1 and Aspergillus niger C1) were isolated from reservoirs, improved the capacity by mix-cultured. The results showed a difference between northern and southern reservoirs, the dominants of genera were Cystobasidium and Acremonium. The removals of total nitrogen (TN) was 12.00%, 7.53% and 69.33% in Trichoderma afroharzianum H1, Aspergillus niger C1 and mix-cultured (C1 and H1) under the denitrification medium. The contents of ATP and electron transport system activity in mix-cultured amendment were increased by 42.54% and 67.52%, 1.72 and 2.91 times, respectively. Besides, the raw water experiment indicated that TN removals were 24.05%, 12.66% and 73.42% in Trichoderma afroharzianum H1, Aspergillus niger C1 and mix-cultured. The removals of dissolved organic carbon in mix-cultured were increased 35.02% and 50.46% compared to Trichoderma afroharzianum H1 and Aspergillus niger C1. Therefore, mix-cultured of two low efficiency aerobic denitrifying fungi has been considered as a novelty perspective for mitigation of drinking water source.

Evaluation of sustainable development capacity of water sources: a case study of China.

The issue of water scarcity has drawn attention from all over the world. The coordination of the interaction between ecological and environmental development of water sources and socio-economic development is currently an essential issue that needs to be solved in order to safeguard the water resources environment for human survival. In this essay, we suggest a paradigm for assessing the sustainable exploitation of water resources. First, three ecological, economic, and social factors are investigated. Twenty essential evaluation indexes are then constructed using the Delphi approach, along with an index system for assessing the potential of water sources for sustainable development. The weights of each evaluation index were then determined using the combination assignment approach, which was then suggested. The coupled degree evaluation model of the capability for sustainable development of water sources was then developed. In order to confirm the viability and validity of the suggested model, the model was used to assess the Liwu River water source's capacity for sustainable growth in the context of the South-North Water Transfer in Shandong, China. It is believed that the aforementioned study would serve as a helpful resource when evaluating the capacity of water sources for sustainable development.

Occurrence, multiphase partition and risk assessment of organic amine pesticides in drinking water source of Xiang River, China.

The extensive use of organic amine pesticides (OAPs) in agricultural practices has resulted in the contamination of water environments, posing threats to ecosystems and human health. This study focused on the Xiang River (XR), a representative drinking water source, as the research area to investigate the occurrence characteristics of 34 OAPs. Diphenylamine emerged as the most prevalent OAP in surface water due to industrial and agricultural activities, while cycloate dominated in sediments due to cumulative effects. Generally, the concentration of OAPs in a mixed tap water sample was lower than those in surface water samples, indicating OAPs can be removed by water plants to a certain extent. The water-sediment distribution coefficients (kd) of ΣOAPs were much less than 1 L/g, the majority of OAPs maintained relatively high concentrations in water samples instead of accumulating in sediments. Furthermore, risk assessment revealed that carbofuran showed a moderate risk to the aquatic environment, with a risk quotient of 0.23, while other OAPs presented minor risks. This study provided crucial insights for regional pesticide management and control in the XR basin, emphasizing the importance of implementing strategies to minimize the release of OAPs into the environment and protect human health.

A critical review on recent research progress on microplastic pollutants in drinking water.

Plastic pollution is an emerging issue in recent days. Persistent plastic particles reach the atmosphere, land and water by multiple pathways. Research has confirmed that the existence of plastic particles is found surprisingly everywhere, from the Artic to the Antarctic region. The probability of ingestion of plastic by all living forms is quite natural, as the whole planet's environment is polluted with microplastic particles. The bioaccumulation of microplastics is a threat and the consequences for living beings are yet to be explored. Microplastics present in different drinking water sources like rivers, lakes, treatment units etc. are studied by several researchers, covering various aspects. Research carried out by various scientists on the microplastics in different drinking water sources is highlighted in this review. In view of the previous research carried out on various aspects of microplastic particles, the necessity of a uniform protocol for qualitative and quantitative analysis of microplastic is ascertained. Microplastic pollution is an ongoing environmental concern, it must be addressed and research should be expanded.

Unimproved source of drinking water and its associated factors: a spatial and multilevel analysis of Ethiopian demographic and health survey.

BACKGROUND: Drinking water quality has been a major public health concern in lower and middle income countries where access to improved water supplies is limited. Ethiopia is thought to have one of the worst drinking water infrastructures in the world. This study aimed to assess the spatial variation and determinants of using unimproved sources of drinking water in Ethiopia using recent nationally representative data. METHODS: A population-based cross-sectional study was employed with the recent EDHS data of 2019. A total of 8663 households were sampled using a stratified two-stage cluster sampling method. Kuldorff's SaTScan version 9.6 software was used to generate spatial scan statistics. ArcGIS version 10.7 software was used to visualize the spatial patterns of unimproved drinking water sources. A multilevel multivariable mixed-effect logistic regression was used to identify factors associated with the use of an unimproved drinking water source. In the multivariable multilevel analysis, those variables with a p-value < 0.05 were considered to be significant predictors of using an unimproved source of drinking water. RESULT: Around 31% (95% CI: 30%, 32%) of the population in Ethiopia uses unimproved sources of drinking water with significant spatial variation across the country. Households aged 41-60 [AOR = 0.69; 95%CI; 0.53, 0.89] as compared to the households aged 10-25, households having middle wealth index [AOR = 0.48; 95%CI; 0.40, 0.59], and households having a rich wealth index [AOR = 0.31; 95%CI; 0.25, 0.39] as compared to the poor households, living in high community literacy level [AOR = 0.36; 95%CI; 0.16, 0.80], living in high-level community poverty [AOR = 3.03; 95%CI; 1.32, 6.98], rural residence [AOR = 7.88; 95%CI; 2.74, 22.67] were significant predictors of use of unimproved source of drinking water. Hot spot areas of use of unimproved drinking water sources were observed in Amhara, Afar, and Somalia regions and some parts of SNNPR and Oromia regions in Ethiopia. The primary clusters were found in Ethiopia's Somalia and Oromia regions. CONCLUSION: Around one third of the Ethiopian population utilizes unimproved source of drinking water and it was distributed non-randomly across regions of Ethiopia. The age of the household head, wealth status of the household, residence, community poverty level, and community literacy level were found to be significantly associated with utilizing unimproved drinking water source. State authorities, non-governmental organizations and local health administrators should work to improve the quality of drinking water particularly for high risk groups such as communities living in high poverty and low literacy, poor households, rural residents, and hot spot areas to decrease the adverse consequences of using unimproved drinking water source.

Antibiotic resistome in groundwater and its association with mountain springs and river.

The distribution of antibiotic resistance genes (ARGs) in water sources potentially threatens drinking water safety. However, the sources of antibiotic resistome in groundwater are still under-investigated. Here, we evaluated the profiles of antibiotic resistome in peri-urban groundwater and its associated water sources (river and mountain spring) to characterize the antibiotic resistome from natural water sources on groundwater resistome. A total of 261 antibiotic resistome were detected in groundwater, mountain spring, and river samples. The relative abundances of ARGs and mobile genetic elements (MGEs) were significantly higher in the river samples than in spring water and groundwater samples. The resistome profiles were similar between groundwater and spring water but differed from the river samples. According to source tracking results, the groundwater resistome was likely to be derived from springs (28.0%-50.0%) and rivers (28.6%-48.6%), which share the same trend for the source tracking of bacterial communities. Bacterial α-diversity, bacterial ß-diversity, and MGEs directly or indirectly affected the ARGs in groundwater samples. Although the abundance of groundwater resistome was not elevated by river and spring water, groundwater resistomes were diverse and may be derived from both river and spring water. We highlight the importance of groundwater resistome and its association with potential water sources, providing a better understanding and basis for the effective control of the ARG proliferation and dissemination in groundwater from exogenous water bodies in the future.

Screening priority pesticides for drinking water quality regulation and monitoring by machine learning: Analysis of factors affecting detectability.

Proper selection of new contaminants to be regulated or monitored prior to implementation is an important issue for regulators and water supply utilities. Herein, we constructed and evaluated machine learning models for predicting the detectability (detection/non-detection) of pesticides in surface water as drinking water sources. Classification and regression models were constructed for Random Forest, XGBoost, and LightGBM, respectively; of these, the LightGBM classification model had the highest prediction accuracy. Furthermore, its prediction performance was superior in all aspects of Recall, Precision, and F-measure compared to the detectability index method, which is based on runoff models from previous studies. Regardless of the type of machine learning model, the number of annual measurements, sales quantity of pesticide for rice-paddy field, and water quality guideline values were the most important model features (explanatory variables). Analysis of the impact of the features suggested the presence of a threshold (or range), above which the detectability increased. In addition, if a feature (e.g., quantity of pesticide sales) acted to increase the likelihood of detection beyond a threshold value, other features also synergistically affected detectability. Proportion of false positives and negatives varied depending on the features used. The superiority of the machine learning models is their ability to represent nonlinear and complex relationships between features and pesticide detectability that cannot be represented by existing risk scoring methods.

Occurrence, sources, and risk assessment of pyrethroid insecticides in surface water and tap water from Taihu Lake, China.

Pyrethroid insecticides are one of the most widely used insecticides globally, posing a severe threat to human health and the environment. In this study, we applied high-throughput organic analysis testing combined with high-volume solid-phase extraction (Hi-throat/Hi-volume SPE) to elucidate the occurrence of 11 pyrethroid insecticides in lake water (n = 37), tributary river water (n = 15), and tap water (n = 6) in the Taihu Lake Basin. Permethrin was found to be the major contributing pyrethroid insecticide (detection rate = 100%). The concentrations of pyrethroid insecticides from different lake regions were revealed in the following descending order: southern > eastern > western > northern. The principal component analysis and multiple linear regression demonstrated that landscape maintenance, agricultural cultivation, and livestock breeding were the main sources of pyrethroid insecticides in the Taihu Lake surface water. Moreover, runoff input plays an important role in their accumulation, while the surrounding rivers contribute 2292 kg of pyrethroid insecticides to Taihu Lake annually. The risk assessment analysis demonstrated that pyrethroid insecticides pose a high risk to both the ecological environment and the surrounding human populations, thereby necessitating effective countermeasures. Furthermore, the pyrethroid insecticides in the Yangtze River Delta region have to be controlled. Overall, this is the first study focused on China that revealed the residue levels in water sources and tap water.

A case-based reasoning tool to recommend drinking water source protection actions.

In response to a need expressed by water actors to support them in identifying appropriate actions for protecting drinking water sources, we modelled, designed, implemented, tested, and validated a prototype case-based reasoning (CBR) system. This required an intensive knowledge acquisition and structuring process which we conducted in collaboration with 102 water management and governance actors in Quebec, Canada. Knowledge was organized in a case base containing nearly 200 past experiences implementing water protection actions at different decision-making scales (local, regional, provincial), by various organizations (government, municipalities, water-related associations), over the last two decades. This paper describes our case engineering process to design case attributes based on content analysis. It presents the case edition, the case retrieval process, and the prototype's implementation and validation, conducted through a rigorous and transparent participatory procedure. This is, to our knowledge, the first successful attempt to apply a CBR approach to support water actors in protecting drinking water sources. It provides empirical evidence of the positive potential of such an approach for knowledge sharing and transfer and can be generalized to other similar contexts.

Significance of the prime factors regulating arsenic toxicity and associated health risk: a hypothesis-based investigation in a critically exposed population of West Bengal, India.

The suffering from arsenic toxicity is a long-standing concern in Asian countries. The role of the key factors (arsenic intake, age and sex) regulating arsenic toxicity is aimed to evaluate for a severely exposed population from Murshidabad district, West Bengal. Mean arsenic concentrations in drinking water supplied through tube well, Sajaldhara treatment plant and pipeline were observed as 208, 27 and 54 µg/l, respectively. Urinary arsenic concentration had been observed as < 3-42.1, < 3-56.2 and < 3-80 µg/l in children, teenagers and adults, respectively. Mean concentrations of hair and nail arsenic were found to be 0.84 and 2.38 mg/kg; 3.07 and 6.18 mg/kg; and 4.41 and 9.07 mg/kg, respectively, for the studied age-groups. Water arsenic was found to be associated with hair and nail (r = 0.57 and 0.60), higher than urine (r = 0.37). Arsenic deposition in biomarkers appeared to be dependent on age; however, it is independent of sex. Principal component analysis showed a direct relationship between dietary intake of arsenic and chronic biomarkers. Nail was proved as the most fitted biomarker of arsenic toxicity by Dunn's post hoc test. Monte Carlo sensitivity analysis and cluster analysis showed that the most significant factor regulating health risk is 'concentration of arsenic' than 'exposure duration', 'body weight' and 'intake rate'. The contribution of arsenic concentration towards calculated health risk was highest in teenagers (45.5-61.2%), followed by adults (47.8-49%) and children (21-27.6%). Regular and sufficient access to arsenic-safe drinking water is an immediate need for the affected population.

Molecular ecological networks reveal the spatial-temporal variation of microbial communities in drinking water distribution systems.

Microbial activity and regrowth in drinking water distribution systems is a major concern for water service companies. However, previous studies have focused on the microbial composition and diversity of the drinking water distribution systems (DWDSs), with little discussion on microbial molecular ecological networks (MENs) in different water supply networks. MEN analysis explores the potential microbial interaction and the impact of environmental stress, to explain the characteristics of microbial community structures. In this study, the random matrix theory-based network analysis was employed to investigate the impact of seasonal variation including water source switching on the networks of three DWDSs that used different disinfection methods. The results showed that microbial interaction varied slightly with the seasons but was significantly influenced by different DWDSs. Proteobacteria, identified as key species, play an important role in the network. Combined UV-chlorine disinfection can effectively reduce the size and complexity of the network compared to chlorine disinfection alone, ignoring seasonal variations, which may affect microbial activity or control microbial regrowth in DWDSs. This study provides new insights for analyzing the dynamics of microbial interactions in DWDSs.

Drinking Water Source and Intake Are Associated with Distinct Gut Microbiota Signatures in US and UK Populations.

BACKGROUND: The microbiome of the digestive tract exerts fundamental roles in host physiology. Extrinsic factors including lifestyle and diet are widely recognized as key drivers of gut and oral microbiome compositions. Although drinking water is among the food items consumed in the largest amount, little is known about its potential impact on the microbiome. OBJECTIVES: We explored the associations of plain drinking water source and intake with gut and oral microbiota compositions in a population-based cohort. METHODS: Microbiota, health, lifestyle, and food intake data were extracted from the American Gut Project public database. Associations of drinking water source (bottled, tap, filtered, or well water) and intake with global microbiota composition were evaluated using linear and logistic models adjusted for anthropometric, diet, and lifestyle factors in 3413 and 3794 individuals, respectively (fecal samples; 56% female, median [IQR] age: 48 [36-59] y; median [IQR] BMI: 23.3 [20.9-26.3] kg/m2), and in 283 and 309 individuals, respectively (oral samples). RESULTS: Drinking water source ranked among the key contributing factors explaining the gut microbiota variation, accounting for 13% [Faith's phylogenetic diversity (Faith's PD)] and 47% (Bray-Curtis dissimilarity) of the age effect size. Drinking water source was associated with differences in gut microbiota signatures, as revealed by ß diversity analyses (P < 0.05; Bray-Curtis dissimilarity, weighted UniFrac distance). Subjects drinking mostly well water had higher fecal α diversity (P < 0.05; Faith's PD, observed amplicon sequence variants), higher Dorea, and lower Bacteroides, Odoribacter, and Streptococcus than the other groups. Low water drinkers also exhibited gut microbiota differences compared with high water drinkers (P < 0.05; Bray-Curtis dissimilarity, unweighted UniFrac distance) and a higher abundance of Campylobacter. No associations were found between oral microbiota composition and drinking water consumption. CONCLUSIONS: Our results indicate that drinking water may be an important factor in shaping the human gut microbiome and that integrating drinking water source and intake as covariates in future microbiome analyses is warranted.

Modeling Exposure to Fecal Contamination in Drinking Water due to Multiple Water Source Use.

The Joint Monitoring Programme estimated that 71% of people globally had access to "safely managed" drinking water in 2017. However, typical data collection practices focus only on a household's primary water source, yet some households in low- and middle-income countries (LMICs) engage in multiple water source use, including supplementing improved water supplies with unimproved water throughout the year. Monte Carlo simulations and previously published data were used to simulate exposure to fecal contamination (as measured by E. coli) along a range of supplemental unimproved source use rates (e.g., 0-100% improved water use, with the remainder made up with unimproved water). The model results revealed a statistically significant increase in annual exposure to E. coli when individuals supplement their improved water with unimproved water just 2 days annually. Additionally, our analysis identified scenarios-realistic for the data set study setting-where supplementing with unimproved water counterintuitively decreases exposure to E. coli. These results highlight the need for evaluating the temporal dynamics in water quality and availability of drinking water sources in LMICs as well as capturing the use of multiple water sources for monitoring global access to safe drinking water.

Determining heavy metal pollution in sediments from the largest impounded lake in the eastern route of China's South-to-North Water Diversion Project: Ecological risks, sources, and implications for lake management.

The eastern route of the South-to-North Water Diversion Project (ER-SNWDP) is a major human health project designed to alleviate the water scarcity in the Beijing-Tianjin-Hebei region in China. Impounded lake water security is directly related to the water diversion project effectiveness. At present, there is not a thorough understanding of the sediment heavy metals in Lake Hongze, the largest impounded lake of the ER-SNWDP. Consequently, this study reports a distribution analysis of Cu, Zn, Pb, Cr, Cd, As, Hg, and Ni in 101 sediment samples from Lake Hongze; we, utilized the enrichment factor, geoaccumulation index, and potential ecological risk index for the are to determine the ecological risk of heavy metals. The heavy metal source was examined with correlation analysis and principal component analysis-multiple linear regressions. The results showed that the average heavy metal content (Cu, Zn, Pb, Cr, Cd, As, Hg, Ni) were 0.03-1.57 times greater than the Jiangsu Province background values. Cd, As, and Hg were the main contributors to the Lake Hongze ecological risk. Spatially, the open water area was the most polluted among the four lake parts, and most of the flushing area had a low ecological risk. Chengzi bay and the western lake area have similar risk profiles, but are lower than the open water area risk. Source analysis showed that nonpoint-source agricultural pollution and industrial production were important pollution sources, while a considerable portion of the heavy metal content came from atmospheric deposition and natural sources. This study identified the main contamination areas and revealed the possible sources of each heavy metal; as such, this study can serve as a reference for the remediation and management of Lake Hongze to ensure the water safety of the ER-SNWDP.