Chronic urban hotspots and agricultural drainage drive microbial pollution of karst water resources in rural developing regions

River Sediments Downstream of Villages in a Karstic Watershed Exhibited Increased Numbers and Higher Diversity of Nontuberculous Mycobacteria

The impact of residential villages on the nontuberculous mycobacteria (NTM) in streams flowing through them has not been studied in detail. Water and sediments of streams are highly susceptible to anthropogenic inputs such as surface water flows. This study investigated the impact of seven residential villages in a karst watershed on the prevalence and species spectrum of NTM in water and sediments. Higher NTM species diversity (i.e., 19 out of 28 detected) was recorded downstream of the villages and wastewater treatment plants (WWTPs) compared to sampling sites upstream (i.e., 5). Significantly, higher Zn and lower silicon concentrations were detected in sediments inside the village and downstream of the WWTP's effluents. Higher phosphorus concentration in sediment was downstream of WWTPs compared to other sampling sites. The effluent from the WWTPs had a substantial impact on water quality parameters with significant increases in total phosphorus, anions (Cl-and N-NH3-), and cations (Na+ and K+). The results provide insights into NTM numbers and species diversity distribution in a karst watershed and the impact of urban areas. Although in this report the focus is on the NTM, it is likely that other water and sediment microbes will be influenced as well.

Physiological characteristics, geochemical properties and hydrological variables influencing pathogen migration in subsurface system: What we know or not?

The global outbreak of coronavirus infectious disease-2019 (COVID-19) draws attentions in the transport and spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in aerosols, wastewater, surface water and solid wastes. As pathogens eventually enter the subsurface system, e.g., soils in the vadose zone and groundwater in the aquifers, they might survive for a prolonged period of time owing to the uniqueness of subsurface environment. In addition, pathogens can transport in groundwater and contaminate surrounding drinking water sources, possessing long-term and concealed risks to human society. This work critically reviews the influential factors of pathogen migration, unravelling the impacts of pathogenic characteristics, vadose zone physiochemical properties and hydrological variables on the migration of typical pathogens in subsurface system. An assessment algorithm and two rating/weighting schemes are proposed to evaluate the migration abilities and risks of pathogens in subsurface environment. As there is still no evidence about the presence and distribution of SARS-CoV-2 in the vadose zones and aquifers, this study also discusses the migration potential and behavior of SARS-CoV-2 viruses in subsurface environment, offering prospective clues and suggestions for its potential risks in drinking water and effective prevention and control from hydrogeological points of view.

Seasonal Dynamics in Bacteriological and Physicochemical Water Quality of the Southern Gulf of Lake Tana

Freshwater lakes are important sources of water for domestic, agricultural, and industrial uses. Lake Tana offers a range of ecosystem services to the surrounding communities. However, this lake is facing deterioration in water quality due to pollution caused by anthropogenic influences. Therefore, regular monitoring of key water quality parameters is critical to understanding the water quality status of the lake. This study aimed to assess the seasonal fluctuation of water quality of the Southern Gulf of Lake Tana using indicator bacteria and some physicochemical parameters. A total of 48 water samples were collected in dry and wet seasons from eight sites in the study area. Total coliforms (TC), faecal coliforms (FC), and some physicochemical parameters (pH, temperature, turbidity, electrical conductivity, total dissolved solids, dissolved oxygen, biochemical oxygen demand, ammonium, nitrate, and phosphate) were determined following standard methods. The results revealed that coliform counts were above the permissible level set by Ethiopian Standards and varied significantly among sites (P < 0.05). FC counts ranged from 1 to 1600 MPN/100 ml (with the lowest and highest mean value of 1 at site 8 to 1076.5 ± 3.1 at site 4) and again TC counts ranged from 1 to 1600 MPN/100 ml (with a mean value of 4.8 ± 1.81 at site 6 to 1600 at site 4 and site 8). The findings also confirmed that the highest counts of coliforms were observed during the wet season. The high counts are attributed to the discharge of human excreta and animal wastes during the rainy season from the different anthropogenic activities near the Gulf. Significant variations in most of the physicochemical parameters were also observed between sites and seasons. FC and biochemical oxygen demand (BOD₅₎ in most sites did not meet the EPA standard for surface water. Corrective measures are highly recommended for anthropogenic activities driving high pollution loads in the lake.

Attainment of water and sanitation goals: a review and agenda for research

One-fourth of the global population is without basic drinking water and half of the global population lacks sanitation facilities. The attainment of water and sanitation targets is difficult due to administrative, operational, political, transborder, technical, and policy challenges. Conducted after 5 years from the adoption of sustainable development goals by the United Nations reviews the initiatives for improving access, quality, and affordability of water and sanitation. The bibliometric and thematic analyses are conducted to consolidate the outcomes of scientific papers on sustainable development goal 6 (SDG 6). Africa is struggling in relation with water and sanitation goals, having 17 countries with less than 40% basic drinking water facilities and 16 countries with less than 40% basic sanitation facilities. Globally, the attainment of water and sanitation goals will be depended on economic development, the development of revolutionary measures for wastewater treatment, and creating awareness related to water usage, water recycling, water harvesting, hygiene, and sanitation. Behavioral changes are also required for a new water culture and the attainment of water and sanitation goals by 2030.

Interpreting Self-Potential Signal during Reactive Transport: Application to Calcite Dissolution and Precipitation

Geochemistry and reactive transport play a critical role in many fields. In particular, calcite dissolution and precipitation are chemical processes occurring ubiquitously in the Earth’s subsurface. Therefore, understanding and quantifying them are necessary for various applications (e.g., water resources, reservoirs, geo-engineering). These fundamental geochemical processes can be monitored using the self-potential (SP) method, which is sensitive to pore space changes, water mineralization, and mineral–solution interactions. However, there is a lack of physics-based models linking geochemical processes to the SP response. Thus, in this study, we develop the first geochemical–geophysical fully coupled multi-species numerical workflow to predict the SP electrochemical response. This workflow is based on reactive transport simulation and the computation of a new expression for the electro-diffusive coupling for multiple ionic species. We apply this workflow to calcite dissolution and precipitation experiments, performed for this study and focused on SP monitoring alternating with sample electrical conductivity (EC) measurements. We carried out this experimental part on a column packed with calcite grains, equipped for multichannel SP and EC monitoring and subjected to alternating dissolution or precipitation conditions. From this combined experimental investigation and numerical analysis, the SP method shows clear responses related to ionic concentration gradients, well reproduced with electro-diffusive simulation, and no measurable electrokinetic coupling. This novel coupled approach allows us to determine and predict the location of the reactive zone. The workflow developed for this study opens new perspectives for SP applications to characterize biogeochemical processes in reactive porous media.

Learning hierarchical Bayesian networks to assess the interaction effects of controlling factors on spatiotemporal patterns of fecal pollution in streams

The dynamics of fecal indicator bacteria, such as fecal coliforms (FC) in streams, are influenced by the interactions of a myriad of factors. To predict complex spatiotemporal patterns of FC in streams and assess the relative importance of numerous controlling factors, the adoption of a hierarchical Bayesian network (HBN) was proposed in this study. By introducing latent variables correlated to the observed variables into a Bayesian network, the HBN can represent causal relationships among a large set of variables with a multilevel hierarchy. The study area encompasses 215 sites across the watersheds of the four major rivers in South Korea. The monitoring data collected during the 2012-2019 period included 32 input variables pertaining to meteorology, geography, soil characteristics, land cover, urbanization index, livestock density, and point sources. As model endpoints, the exceedance probability of the FC standard concentration as well as two pollution characteristics (i.e., pollution degree and type), derived from FC load duration curves were used. The probability of exceeding an FC threshold value (200 CFU/100 mL) showed spatiotemporal variations, whereas pollution degree and type showed spatial variations that represent long-term severity and relative dominance of nonpoint and point source fecal pollution, respectively. The conceptual model was validated using structural equation modeling to develop the HBN. The results demonstrate that the HBN effectively simplified the model structure, while showing strong model performance (AUC = 0.81, accuracy = 0.74). The results of the sensitivity analysis indicate that land cover is the most important factor in predicting the probability of exceedance and pollution degree, whereas the urbanization index explains most of the variability in pollution type. Furthermore, the results of the scenario analysis suggest that the HBN provides an interpretable framework in which the interaction of controlling factors has causal relationships at different levels that can be identified and visualized.

Inactivation of waterborne fungal spores by 1-bromo-3-chloro-5,5-dimethylhydantoin: Kinetics, influencing factors and mechanisms

Fungal contamination in drinking water source has become a problem worth studying, as waterborne fungi may cause deterioration of water quality and outbreak of diseases. Various disinfection methods have been explored to control fungal spores in drinking water, such as chlor(am)ination, ozonation, chlorine dioxide treatment, but these methods are not appropriate for remote areas, owing to the difficulties in preparation, carriage and storage. In this study, a powdery disinfectant of 1-bromo-3-chloro-5,5-dimethylhydantoin (BCDMH), which facilitated transportation and preservation, was firstly chosen to inactivate opportunistic pathogens of Aspergillus niger (A. niger) and Penicillium polonicum (P. polonicum). The results revealed that the inactivation kinetics of fungal spores by BCDMH fitted to Chick-Watson model well, with the inactivation rate constant of 0.011 and 0.034 L mg^-1 min^-1 for A. niger and P. polonicum, respectively. Acidic condition and high temperature promoted the inactivation by BCDMH. Compared with chlorine, BCDMH showed relative weaker ability on inactivation of fungal spores. However, it was demonstrated that the inactivation efficiency of BCDMH was obviously enhanced by adding halide ions, with 11 or 36 folds for A. niger and 4 or 15 folds for P. polonicum by adding 40 μM Br^- or I^-. The inactivation mechanisms were detected by flow cytometry and scanning electron microscope. Fungal spores lost their culturability firstly, then membrane integrity was damaged. Meanwhile, the esterase activity and intracellular reactive oxygen species level changed, and finally intracellular adenosine triphosphate released.

Exploration of E. coli contamination drivers in private drinking water wells: An application of machine learning to a large, multivariable, geo-spatio-temporal dataset

Groundwater resources are under increasing threats from contamination and overuse, posing direct threats to human and environmental health. The purpose of this study is to better understand drivers of, and relationships between, well and aquifer characteristics, sampling frequencies, and microbiological contamination indicators (specifically E. coli) as a precursor for improving knowledge and tools to assess aquifer vulnerability and well contamination within Ontario, Canada. A dataset with 795, 023 microbiological testing observations over an eight-year period (2010 to 2017) from 253,136 unique wells across Ontario was employed. Variables in this dataset include date and location of test, test results (E. coli concentration), well characteristics (well depth, location), and hydrogeological characteristics (bottom of well stratigraphy, specific capacity). Association rule analysis, univariate and bivariate analyses, regression analyses, and variable discretization techniques were utilized to identify relationships between E. coli concentration and the other variables in the dataset. These relationships can be used to identify drivers of contamination, their relative importance, and therefore potential public health risks associated with the use of private wells in Ontario. Key findings are that: i) bedrock wells completed in sedimentary or igneous rock are more susceptible to contamination events; ii) while shallow wells pose a greater risk to consumers, deep wells are also subject to contamination events and pose a potentially unanticipated risk to health of well users; and, iii) well testing practices are influenced by results of previous tests. Further, while there is a general correlation between months with the greatest testing frequencies and concentrations of E. coli occurring in samples, an offset in this timing is observed in recent years. Testing remains highest in July while peaks in adverse results occur up to three months later. The realization of these trends prompts a need to further explore the bases for such occurrences.