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An organometallic dye, europium tetrakis dibenzoylmethide triethylammonium (EuD 4 TEA) and gold nanoparticles (Au NPs) impregnated paper based sensor platform have been utilized for development of fluorescence turn-on cyanide assay in aqueous media. The ordinary filter paper with 6 μ m pore size were employed as solid support that facilitates impregnation of EuD 4 TEA and gold nanoparticles and provides durability. Detection mechanism relying on two processes (i) dissolution of gold nanoparticles causing fluorescence recovery and (ii) ligand exchange of triethyl amine with CN group stimulating cyanide specific fluorescence enhancement. The paper platform exhibit naked eye distinguishable color transition upon CN − addition from 10 −2 to 10 −12 M. To standardize the methodology a homemade image processing algorithm has been developed that enabling calibration of color change and quantify CN − concentration. The described algorithm is applicable to Android smart phones and facilitate transforming these devices into a quantitative cyanide detector. The overall methodology provides instrument free cyanide detection and therefore rapid control of water quality and safety at off-field conditions. [ABSTRACT FROM AUTHOR]

Abstract Over the past 29 years there have been myriad research efforts into the catalytic removal of nitrates from drinking water. In this work, 147 papers published during that period have been examined from the point of view of the ability of catalysis to produce water that is suitable for human consumption as well as amenable to industrial scale-up at reasonable working conditions of temperature and residence time. After close examination of the aforementioned articles, it is evident that this methodology has fulfilled only half its aims: it is able to reduce the nitrate concentration to guideline levels for human consumption, but it inevitably produces concentrations of ammonia and nitrites that are beyond the accepted limits for safe consumption of water. It is sometimes recommended that catalysis be combined with an ancillary technique, such as adsorption, in order to eliminate the undesirable byproducts mentioned above. However, this implies resorting to extra treatment units at the industrial scale, thus making the whole treatment process more complex and expensive. Our conclusion is that the effective catalytic removal of nitrates from drinking water is a very difficult problem. Highlights • 147 papers on catalytic removal of nitrates from drinking water have been examined. • No catalyst has been found to simultaneously decrease nitrate, nitrite and ammonia. • To transfer this lab technique to purify water to a realistic situation, is difficult. • The catalytic removal of nitrates from drinking water is still an unresolved problem. [ABSTRACT FROM AUTHOR]

A number of physical, chemical and biological water quality parameters are measured to understand quality conditions of a riverine environment. Various aggregation techniques have been used to reflect the combined effect of the existing or proposed quality levels. Water Quality Index (WQI) has been developed primarily for fresh water environments. Organic pollutants are not considered in many WQIs because analyses of organics are rather expensive. In general, fecal coliform and total coliform counts are measured to reflect biological contamination of water. With growing consensus on considering rivers as ecological entity, rather than merely a source of water for human consumptions, the emphasis is changing from water quality index (WQI) to River Health Index (RHI). As benthic macroinvertebrate species are differentially sensitive to many biotic and abiotic factors in river environment, macroinvertebrate community structure has commonly been used as indicator of stream water condition. A number of river health assessment methodologies have been proposed in past and several indices such as Ecological Health Index (EHI), Ecological Quality Index (EQI), Overall Index of Pollution (OIP) and River Pollution Index (RPI) have been developed using water quality variables and aquatic species for evaluating the ecological health of river systems. This paper attempts to review and summarize some of these indices with particular emphasis on measurable parameters included in such formulations. The analyses suggest that with sufficient scientific experience and understanding in this area, it is possible to define a River Health Index (RHI) by including algae, macroinvertebrates and fish species as measurable parameters along with routine physico-chemical characteristics of river water. One such formulation on RHI has been proposed by the authors in this paper. The novelty of the proposed formulation include simple calculations and presentation of RHI value on 0–100 scale. The biological indices used in ACEDP (2011) requires biological expertise which is not normally available with water resource managers. Hence species identification and counting based simple biotic indices have been proposed so that it can be easily done by non experts also. River Health Level (RHL) can be categorized as ‘critical’ or ‘excellent’ based on RHI value <=20 or >80. Thus RHI values can be used to identify the healthy or unhealthy stretches of the river. RHI can serve as scientific tool to assess the current status, need and effectiveness of any intervention required to improve the condition of the river. Application of this RHI formulation on main stream of river Ganga (India) is under study. [ABSTRACT FROM AUTHOR]

The paper presents results of a follow-up to an earlier study which established a geospatial link between naturally elevated uranium (U) levels in borehole water and haematological abnormalities in local residents serving as a proxy for leukaemia prevalent in the area. While the original study focussed on drinking water only, this paper also explores alternative exposure pathways including the inhalation of dust and the food chain. U-levels in grass and tissue of sheep generally reflect U-levels in nearby borehole water and exceed background concentrations by 20 to nearly 500 times. U-levels in sheep tissue increase with age of the animal. Wool showed the highest U-concentration followed by other non-consumable tissue such as hooves, teeth and bones. Lower levels occur in edible parts such as meat and inner organs. The U-deposition rate in wool is several orders of magnitudes higher than in bone as a known target organ. Wool is an easy-to-sample non-invasive bioindicator for U-levels in meat. Depending on the original water content, dried samples show up to 5 times higher U-levels than identical fresh material. Contaminated drinking water is the main exposure pathway for farm residents resulting in U-uptake rates exceeding the WHO's tolerable daily intake (TDI) limit by up to 900%. This is somewhat mitigated by the fact that U-speciation is dominated by a neutral calcium-uranyl-carbonate complex of relatively low toxicity. Commercially available household filters are able to significantly reduce U-levels in well water and are thus recommended as a short-term intervention. Based on average consumption rates sheep meat, as local staple food, accounts for 34% of the TDI for U. Indoor levels of radon should be monitored, too, since it is linked to both, U and leukaemia. With elevated U-levels being present in other geological formations across South Africa boreholes in these areas should be surveyed. [ABSTRACT FROM AUTHOR]

In nature, arsenic is mostly found in the form of inorganic compounds. Inorganic arsenic compounds have a variety of uses and are currently used in the manufacture of pesticides, preservatives, pharmaceuticals, etc. While inorganic arsenic is widely used, arsenic pollution is increasing worldwide. Public hazards caused by arsenic contamination of drinking water and soil are becoming increasingly evident. Epidemiological and experimental studies have linked inorganic arsenic exposure to the development of many diseases, including cognitive impairment, cardiovascular failure, cancer, etc. Several mechanisms have been proposed to explain the effects caused by arsenic, such as oxidative damage, DNA methylation, and protein misfolding. Understanding the toxicology and potential molecular mechanisms of arsenic can help mitigate its harmful effects. Therefore, this paper reviews the multiple organ toxicity of inorganic arsenic in animals, focusing on the various toxicity mechanisms of arsenic-induced diseases in animals. In addition, we have summarized several drugs that can have therapeutic effects on arsenic poisoning in pursuit of reducing the harm of arsenic contamination from different pathways. • Inorganic arsenic exposure can cause toxic damage to multiple organ systems in animals. • Oxidative stress, DNA damage, cell cycle disruption, inflammation and immune imbalance are the main toxic mechanisms of arsenic. • Curcumin, selenium, N -acetylcysteine, melatonin, and propolis are all effective against arsenic toxicity. [ABSTRACT FROM AUTHOR]

Municipal solid waste management (MSWM) has always been a typical issue in India. The rapid population growth, impetuous adoption of modern lifestyle, and fast urbanization resulted in India's swift generation of complicated municipal solid waste (MSW). Consequently, municipalities of different cities in India face various difficulties in MSW collection, treatment and disposal methodology. Inefficient or poorly managed MSW causes numerous troubles, including air pollution, soil fouling, contamination in drinking water and health hazard, and it also impacts socio-economic deterioration. MSWM technique selection is based on several criteria, which are generally imprecise, uncertain, and vague. This paper uses the cubic Pythagorean fuzzy number to comprise the fuzzy characteristics of the criteria value concerning the five alternatives (Thermochemical methods in MSW treatment and disposal). The best MSW treatment and disposal method is selected amongst the five alternatives under the novel multi-criteria group decision-making (MCGDM) approach, the cubic Pythagorean fuzzy EDAS (Evaluation based on Distance from Average Solution) in the Indian context. The weight information of the criteria has yet to be wholly known. A non-linear optimization scheme is proposed to determine the criteria weights that are partially known to maximize the generalized total distance measure between alternatives corresponding to all criteria. The present method is explained with a case study. Finally, a comparative analysis is drawn between the present and some existing methods, showing that the present method is consistent and robust enough to apply in practice. • CuPyF extended EDAS approach is developed for solving MCGDM problems. • Optimization model is applied for computing incomplete weights. • Create an algorithm for MCGDM problems using the CuP-EDAS technique. • A case study for municipal solid waste management is considered for recycling. • Sensitivity and comparative analysis are verified to validate the results. [ABSTRACT FROM AUTHOR]

While infrastructure is often understood to operate 'in the background', scholars have increasingly attended to the labour that enables urban material flows. Drawing on empirical material collected through fieldwork and document analysis in Lilongwe, this paper explores how different residents of the city experience and respond to the regular failures of infrastructure. We examine sanitation in one middle- and two low-income areas, considering the contamination of drinking water and the collapse of latrines. Attending to the gendered, embodied, affective, and intimate dimensions of maintenance and repair labours, we develop three interrelated arguments. First, we frame incidents of failure not as individual accidents but as part of persistently fragile infrastructures. Second, we contribute to extending the gaze of infrastructural labours beyond manual work and 'expert' knowledge to consider a range of unpaid practices and their role in preventing, responding to, and being impacted by failure. Finally, we show that both the labour and impacts of infrastructural failure disproportionally fall on (low-income) women. Emphasising the ongoing, gendered struggles of keeping sanitation infrastructures functional helps us to see the limits of scholarship that centres clearly identifiable jobs associated with infrastructure's construction, maintenance and repair. We conclude with reflections on the implications of these arguments for our understanding of the knowledges and labours that keep infrastructures working, and the conditions in which these are performed. [ABSTRACT FROM AUTHOR]

In order to counter growing shortages in water supply, there has been an increasing adoption of non-conventional sources, such as desalination. As a matter of fact, the marginal costs of water ( i.e. , production) or, in a different perspective, the potential and limitations of different technologies, make the use of particular types of desalination methods an increasing possibility. The growing use of hybrid systems highlights the acknowledgment of those technologies as accepted opportunities to diversify water sources, and from a different perspective, render desalination solutions more efficient and effective. Thus, the study of cost determinants which confer a dynamic importance to such technologies is paramount and policy relevant. For that purpose, cost structures and cost determinants were standardized in order to provide guidelines, or a basis, for a suitable cost perception. This paper provides relevant insights of desalination projects’ key factors, and to such an extent, this is a significant contribution. In this analysis, the results achieved compare possible energy solutions, mainly targeting renewable prospects, due to their impact on the total cost of produced water. The economic feasibility of different desalination technologies and energy solutions is also assessed, with a significant focus on possible hybrid possibilities and the site-specificity of such projects, due to their importance and impact on future technology trends and their cost variations. [ABSTRACT FROM AUTHOR]

The continuously increasing presence of micro- and nanoplastics contamination in numerous food products for human consumption is threatening and their potential health effects towards humans remain uncertain. At present, investigations on packaged beverages (e.g. bottled drinking water, beer, milk and refreshments) have received scientific attention and represent an important part of microplastic research as humans are orally exposed to these anthropogenic contaminants every day. Rapid and effective detection methods are important to quantify micro- and nanoplastic particles with a great accuracy as well as to identify their sources and characteristics. A number of methods are currently in use to assess microplastics in packaged beverages; however, the great variations in methods and data acquisition render difficulties when comparing the results and developing the protocols. Based on the challenges, this paper aims to provide a comprehensive understanding of emerging technological approaches, points out the current limitations from sample preparation to quantification and present recommendations. From the results of our analysis, we postulate an example framework that can be applied to different types of drinking products for investigating micro- and nanoplastics. Overall, this review will serve as a first step towards harmonization of micro- and nanoplastic monitoring efforts and a point of reference to help direct future researches focusing on drinking products intended for human consumption. Image 1 • Analytical methods for detecting microplastics in commercial drinking products are critically reviewed. • Methods vary greatly with respect to the type of drinking products and of geographical region. • Microplastics were most studied in bottled water, followed by beer, milk and refreshments. • Illustrated example workflow provides a first step towards harmonization of methods to investigate micro- and nanoplastics. This paper focuses on adopting a unified approach towards determination and characterization of micro (nano)plastics on packaged beverages by critically summarizing the available literature information of detection, analysis and methods regarding microplastic contamination including; drinking water, beer, milk and other refreshments, along with describing an example framework to provide a guideline for further research. [ABSTRACT FROM AUTHOR]

Since Flint returned to its pre-crisis source of drinking water close to 25,000 water samples have been collected and tested for lead and copper in > 10,000 residences. This paper presents the first analysis and time trend modeling of lead data, providing new insights about the impact of this intervention. The analysis started with geocoding all water lead levels (WLL) measured during an 11-month period following the return to the Detroit water supply. Each data was allocated to the corresponding tax parcel unit and linked to secondary datasets, such as the composition of service lines, year built, or census tract poverty level. Only data collected on residential parcels within the City limits were used in the analysis. One key feature of Flint data is their collection through two different sampling initiatives: (i) voluntary or homeowner-driven sampling whereby concerned citizens decided to acquire a testing kit and conduct sampling on their own (non-sentinel sites), and (ii) State-controlled sampling where data were collected bi-weekly at selected sites after training of residents by technical teams (sentinel sites). Temporal trends modeled from these two datasets were found to be statistically different with fewer sentinel data exceeding WLL thresholds ranging from 10 to 50 μg/L. Even after adjusting for housing characteristics the odds ratio (OR) of measuring WLL above 15 μg/L at non-sentinel sites is significantly > 1 (OR = 1.480) and it increases with the threshold (OR = 2.055 for 50 μg/L). Joinpoint regression showed that the city-wide percentage of WLL data above 15 μg/L displayed four successive trends since the return to Detroit Water System. Despite the recent improvement in water quality, the culprit for differences between sampling programs needs to be identified as it impacts exposure assessment and might influence whether there is compliance or not with the Lead and Copper Rule. [ABSTRACT FROM AUTHOR]

Studies have yet to evaluate the effects of water improvement on fluoride concentrations in drinking water and the corresponding health risks to Chinese residents in endemic fluorosis areas (EFAs) at a national level. This paper summarized available data in the published literature (2008–2016) on water fluoride from the EFAs in China before and after water quality was improved. Based on these obtained data, health risk assessment of Chinese residents' exposure to fluoride in improved drinking water was performed by means of a probabilistic approach. The uncertainties in the risk estimates were quantified using Monte Carlo simulation and sensitivity analysis. Our results showed that in general, the average fluoride levels (0.10–2.24 mg/L) in the improved drinking water in the EFAs of China were lower than the pre-intervention levels (0.30–15.24 mg/L). The highest fluoride levels were detected in North and Southwest China. The mean non-carcinogenic risks associated with consumption of the improved drinking water for Chinese residents were mostly accepted (hazard quotient < 1), but the non-carcinogenic risk of children in most of the EFAs at the 95th percentile exceeded the safe level of 1, indicating the potential non-cancer-causing health effects on this fluoride-exposed population. Sensitivity analyses indicated that fluoride concentration in drinking water, ingestion rate of water, and the exposure time in the shower were the most relevant variables in the model, therefore, efforts should focus mainly on the definition of their probability distributions for a more accurate risk assessment. [ABSTRACT FROM AUTHOR]

Waterborne outbreaks of gastrointestinal diseases are of great concern to drinking water producers and can give rise to substantial costs to the society. The World Health Organisation promotes an approach where the emphasis is on mitigating risks close to the contamination source. In order to handle microbial risks efficiently, there is a need for systematic risk management. In this paper we present a framework for microbial risk management of drinking water systems. The framework incorporates cost-benefit analysis as a decision support method. The hydrological Soil and Water Assessment Tool (SWAT) model, which was set up for the Stäket catchment area in Sweden, was used to simulate the effects of four different mitigation measures on microbial concentrations. The modelling results showed that the two mitigation measures that resulted in a significant (p < 0.05) reduction of Cryptosporidium spp. and Escherichia coli concentrations were a vegetative filter strip linked to cropland and improved treatment (by one Log10 unit) at the wastewater treatment plants. The mitigation measure with a vegetative filter strip linked to grazing areas resulted in a significant reduction of Cryptosporidium spp., but not of E. coli concentrations. The mitigation measure with enhancing the removal efficiency of all on-site wastewater treatment systems (total removal of 2 Log10 units) did not achieve any significant reduction of E. coli or Cryptosporidiu m spp. concentrations. The SWAT model was useful when characterising the effect of different mitigation measures on microbial concentrations. Hydrological modelling implemented within an appropriate risk management framework is a key decision support element as it identifies the most efficient alternative for microbial risk reduction. [ABSTRACT FROM AUTHOR]

[Display omitted] • HFPNM undergoes fluorescence quenching upon contact with Cu2+. • HFPNM is capable of accurately detecting 100–1000 nmol/L of Cu2+. • HFPNM can still be used as a Cu2+ sensor after 5 cycles of use. • HFPNM have the advantages of high detection sensitivity and environmental friendliness for recycling compared to other Cu2+ sensors. Cu2+ contamination in drinking water poses a threat to humans and the environment, and high concentrations of Cu2+ in human blood can induce disease. In recent years, fluorescence sensing of Cu2+ prepared from rare earth elements has been widely used for the accurate detection and quantification of Cu2+. In this paper, we report that europium (Eu), 4,4′,4-trimethyltriphenylamine (TTA), and 1,10-phenanthroline (Phen) undergo a complexation reaction to form the Eu(TTA) 3 Phen complex, which is loaded on SiO 2 nanoparticle to form SiO 2 @Eu3+. We use electrospinning of SiO 2 @Eu3+ and polyacrylonitrile (PAN) co-blended solutions to prepare PAN fluorescent nanofiber membranes (FPNM). FPNM are hydrolyzed hydrolysis to obtain Cu2+ sensors (HFPNM). The super hydrophilic surface of HFPNM undergoes fluorescence quenching upon contact with Cu2+. HFPNM is capable of accurately detecting 100–1000 nmol/L of Cu2+. Moreover, EDTA can be used as a reversible on/off switch for detection, and HFPNM can still be used as a Cu2+ sensor after 5 cycles of use. The HFPNM have the advantages of high detection sensitivity and environmental friendliness for recycling compared to other Cu2+ sensors. Fluorescent nanofibers can be combined with bio-nanotechnology allowing for promising future applications in Cu2+ detection and wearable smart fabrics. [ABSTRACT FROM AUTHOR]

Per- and polyfluoroalkyl substances (PFAS) are persistent, mobile, and toxic chemicals that are hazardous to human health and the environment. Several countries, including the United States, plan to set an enforceable maximum contamination level for certain PFAS compounds in drinking water sources. Among the available treatment options, photocatalytic treatment is promising for PFAS degradation and mineralization in the aqueous solution. In this review, recent advances in the abatement of PFAS from water using photo-oxidation and photo-reduction are systematically reviewed. Degradation mechanisms of PFAS by photo-oxidation involving the holes (h vb + ) and oxidative radicals and photo-reduction using the electrons (e cb - ) and hydrated electrons (e aq - ) are integrated. The recent development of innovative heterogeneous photocatalysts and photolysis systems for enhanced degradation of PFAS is highlighted. Photodegradation mechanisms of alternative compounds, such as hexafluoropropylene oxide dimer acid (GenX) and chlorinated polyfluorinated ether sulfonate (F-53B), are also critically evaluated. This paper concludes by identifying major knowledge gaps and some of the challenges that lie ahead in the scalability and adaptability issues of photocatalysis for natural water treatment. Development made in photocatalysts design and system optimization forges a path toward sustainable treatment of PFAS-contaminated water through photodegradation technologies. [Display omitted] • Degradation mechanisms of PFAS by photo-oxidation and photo-reduction processes are discussed in detail. • Innovative heterogeneous photocatalysts and photolysis systems for enhanced degradation of PFAS are highlighted. • Advancements on the photodegradation of PFAS alternatives are emphasized. • Major knowledge gaps in the PFAS photodegradation are identified. [ABSTRACT FROM AUTHOR]

Galvanic corrosion is one of the main reasons for pipe degradation and lead contamination in drinking water systems. The electrical connection of dissimilar metals in corrosive tap water accelerates the dissolution rate of lead from leaded materials. This paper reports an electrochemistry based model to predict lead leaching from a copper pipe fitted with leaded connections. The corrosion of lead at the metal-electrolyte interface depends on the charge transfer and the electric field across the interface. The electric potential field and the mass transport process are dynamically coupled for corrosion propagation in stagnant water; they are respectively governed by the conservation of charge and reactant mass. Using polarization parameters for the electrodes as a function of concentration of oxidizing agents, a dynamic electrochemical model is developed to predict lead leaching from galvanic corrosion. The predicted lead and copper leaching curves are in good agreement with the experimental data for a lead-soldered coupled copper pipe, a brass valve coupled copper pipe, and a pure copper pipe. The findings offer a quantitative understanding on galvanic corrosion in drinking water supply systems and a practical modeling framework for prediction of lead leaching in tap water as a function of stagnation time. [Display omitted] • Time evolution of 3d (axisymmetric) electric potential and reactant concentration fields. • Prediction of lead leaching curve in drinking water pipe from basic electrochemical principles. • Determination of polarization parameters of galvanic pairs. [ABSTRACT FROM AUTHOR]

Best practice in regulating contaminants of emerging concern (CEC) must involve the integration of science and policy, be defensible and accepted by diverse stakeholders. Key elements of CEC frameworks include identification and prioritisation of emerging contaminants, evaluation of health and environmental impacts from key matrices such as soil, groundwater, surface waters and sediment, assessments of available data, methods and technologies (and limitations), and mechanisms to take cognisance of diverse interests. This paper discusses one of the few frameworks designed for emerging contaminants, the Minnesota Department of Health (MDH) Drinking Water Contaminants of Emerging Concern (CEC) program. Further review of mechanisms for CECs in other jurisdictions reveals that there is only a small number of regulatory and guidance regimes globally. There is also merit in a formal mechanism for the global exchange of knowledge and outcomes associated with CECs of global interest. [ABSTRACT FROM AUTHOR]

The security of drinking water is increasingly being recognized as a major challenge for municipalities and water utilities. In the event of a contamination, water spreads rapidly before the problem is detected. Contaminated drinking water can induce major epidemics, disrupt economic life and create mass panics. SAFEWATER is an EU-funded project that aims at developing a comprehensive event detection and event management solution for drinking water security management. The implemented solution will rely on new and currently existing sensors. A number of innovative software components will capture and analyze the data collected by the sensors, trigger alerts when anomalies are detected, and enable prediction of the contamination spread and its source. A web-based decision support tool will facilitate situation awareness and support the execution of mitigation measures. This paper focuses on the software architecture that enables coordinated operation of the event detection, simulation modules and the decision support application. [ABSTRACT FROM AUTHOR]

Inconsistent use of household water treatment and safe storage (HWTS) systems reduces their potential health benefits. Ultraviolet (UV) disinfection is more convenient than some existing HWTS systems, but it does not provide post-treatment residual disinfectant, which could leave drinking water vulnerable to recontamination. In this paper, using as-treated analyses, we report on the field efficacy of a UV disinfection system at improving household drinking water quality in rural Mexico. We further assess the risk of post-treatment contamination from the UV system, and develop a process-based model to better understand household risk factors for recontamination. This study was part of a larger cluster-randomized stepped wedge trial, and the results complement previously published population-level results of the intervention on diarrheal prevalence and water quality. Based on the presence of Escherichia coli (proportion of households with ≥1 E. coli /100 mL), we estimated a risk difference of −28.0% (95% confidence interval (CI): −33.9%, −22.1%) when comparing intervention to control households; −38.6% (CI: −48.9%, −28.2%) when comparing post- and pre-intervention results; and −37.1% (CI: −45.2%, −28.9%) when comparing UV disinfected water to alternatives within the household. We found substantial increases in post-treatment E. coli contamination when comparing samples from the UV system effluent (5.0%) to samples taken from the storage container (21.1%) and drinking glasses (26.0%). We found that improved household infrastructure, additional extractions from the storage container, additional time from when the storage container was filled, and increased experience of the UV system operator were associated with reductions in post-treatment contamination. Our results suggest that the UV system is efficacious at improving household water quality when used as intended. Promoting safe storage habits is essential for an effective UV system dissemination. The drinking glass appears to represent a small but significant source of recontamination that is likely to impact all HWTS systems. [ABSTRACT FROM AUTHOR]

Addressing the issue of agricultural pollution in water protection areas (WPA) requires assessing the impact of agricultural activities at regional scales. However, current water quality modeling studies often neglect the agronomic concept of a cropping system and interactions with soils. This paper presents a participatory assessment framework involving local experts in building a shared diagnosis of nitrate losses from cropping systems in a WPA. It includes a co-designed typology of landscape units and participatory assessment of nitrate losses with the modeling software Syst'N. Results show that characteristics of cropping systems depended on soils and that nitrate losses were highest in shallow soils. Intercrop periods were identified as critical periods for nitrate leaching, which demonstrates the importance of considering pluri-annual crop rotations rather than individual crops. The framework is generic for a modeling approach based on the involvement of local experts, who define their functional system in an agronomically sound way. [ABSTRACT FROM AUTHOR]

Arsenic contamination of drinking water is a major problem for many people worldwide, especially the inhabitants of Bangladesh and Nepal. Through Dartmouth Humanitarian Engineering (DHE) at Dartmouth College, we are working to create a home-based arsenic filtration system. The ultimate goal of this project is to provide highly effective, reliable and affordable filters for the people affected by this problem in Nepal and other countries. This paper illustrates the purpose of the project, reports results obtained while creating various components of the filer, and discusses future plans to create a fully assembled, deployable prototype. Our current working prototype can get arsenic concentration below the WHO safe drinking limit of 10ppb – specifically to 2.58ppb starting from 260 ppb. [ABSTRACT FROM AUTHOR]

• The Bayesian Evidential Learning framework is extended for experimental design. • Wellhead protection areas are delineated using the Traveling Salesman Problem. • Wellhead protection areas are predicted from tracer's breakthrough curves. • The prediction procedure comes at low computational cost. • The experimental design does not require any mathematical model simplification. Groundwater management practices, such as sustainable drinking water extraction or contamination protection, can have significant socioeconomic impacts. A complete uncertainty analysis should ideally be performed to anticipate all possible outcomes and assess any risk. Uncertainties arise as a result of our limited understanding of the physical processes involved, as well as a scarcity of measurement data, whether directly or indirectly related to the physical parameters of interest. In this paper, we use a small number of tracing experiments (predictor) to predict the wellhead protection area (WHPA, target), the shape and extent of which are influenced by the distribution of hydraulic conductivity (K). Our first goal is to make stochastic predictions of the WHPA within the Bayesian Evidential Learning (BEL) framework, which uses machine learning to find a direct relationship between predictor and target. This relationship is learned using a small number of training models (400) drawn from the prior distribution of K. Forward modelling is used to obtain the 400 pairs of simulated predictors and targets. Newly collected field data can then be used directly to predict the approximate posterior distribution of the corresponding WHPA, obviating the need for the traditional step of data inversion. The number and location of data sources (injection wells) influence the posterior WHPA distribution's uncertainty range. Our second goal is to extend BEL to determine the optimal design of data source locations that minimises the WHPA's posterior uncertainty. Because the BEL model, once trained, allows the computation of the posterior uncertainty corresponding to any new input data, experimental design can be done explicitly, without averaging or approximating. We estimate the WHPA's posterior uncertainty range using the Modified Hausdorff Distance (MHD) and Structural Similarity (SSIM) index metrics. Because the breakthrough curves store information on a large area of the K field surrounding the pumping well, increasing the number of injection wells reduces the derived posterior WHPA uncertainty. Our method can also estimate which injection wells are more informative than others, as demonstrated by a k-fold cross-validation procedure. Overall, the application of BEL to experimental design allows for identifying data sources that maximise the information content of any measurement data while keeping budget constraints and computational costs to a minimum. [ABSTRACT FROM AUTHOR]

Carbon capture and sequestration (carbon capture and storage or CCS) represents a unique potential strategy that can minimize CO2 emissions in the atmosphere, and it creates a pathway toward a neutral carbon balance, which cannot be solely achieved by combining energy efficiency and other forms of low carbon energy. To contribute to the decision-making process and ensure that CCS is successful and safe, an adequate monitoring program must be implemented to prevent storage reservoir leakage and contamination of drinking water in groundwater aquifers. In this paper, we propose an approach to perform value of information (VOI) analyses to address sequential decision problems in reservoir management in the context of monitoring the geological storage of CO2 operations. These sequential decision problems are often solved and modeled by approximate dynamic programming (ADP), which is a powerful technique for handling complex large-scale problems and finding a near-optimal solution for intractable sequential decision-making. In this study, we tested machine learning techniques that fall within ADP to estimate the VOI and determine the optimal time to stop CO2 injections into the reservoir based on information from seismic surveys. This ADP approach accounts for both the effect of the information obtained before a decision and the effect of the information that might be obtained to support future decisions while significantly improving the timing, value of the decision, and uncertainty of the CO2 plume behavior, thereby significantly increasing economic performance. The Utsira saline aquifer west of Norway was used to exemplify ADP's ability to improve decision support regarding CO2 storage projects. • The only way to create value is through good decision making. • A good decision does not always imply good outcomes unless if it is consistent with alternatives, uncertainty, and information. • We provide a framework to quantify the VOI of 4D seismic data in a CCS project. • Approximate dynamic programming is used to provide better reservoir management decisions. [ABSTRACT FROM AUTHOR]

• Distribution network as an indirect PFASs contamination and exposure risks source. • Mechanistic model for predicting PFOA fate and transport in the distribution system. • PFASs exposure risks by comparing the simulated PFOA levels with guideline values. • Child population group was found susceptible to PFOA exposure beyond 3 ng/kg/day. • Reducing chlorine dose decreased the PFOA exposure risks in the distribution network. Recent studies identified fluoroalkyl amides (FAs) transformation to perfluorooctanoic acid (PFOA) during disinfection as an indirect source of PFASs contamination of drinking water. This paper discerns the position of water disinfection systems (WDSs) as a PFOA exposure pathway. A new mechanistic model incorporating the derived knowledge about the zwitterionic/cationic FAs transformation to PFOA with the unsteady-state hydraulic characteristics of WDSs was developed. The simulation outputs from model application to a WDS from the USA established the significant role of delivery via distribution network in the PFOA formation in drinking water. PFOA exposure risk assessment studies predicted >95% of the system nodes to be at high risk when the existing stringent health-based guideline values are adopted. The 1 to 3 years and 4 to 8 years old age groups were found susceptible to PFOA exposure through drinking water beyond the tolerable limit of 3 ng/kg/day. The model predicted that reducing the chlorine dose from 2±0.2 to 1±0.1 mg/L at the treatment units drops the share of 1 to 3 years old and 4 to 8 years old consumers falling to PFOA exposure from 4.32 to 0.45% and 0.32 to <0.01%, respectively. Besides, 24.9% more, including ∼x223C10% of the consumers of 1 to 3 years old age group, were found exposed to PFOA risks when the organic loading of water was reduced by 60%. [Display omitted] [ABSTRACT FROM AUTHOR]

Rapid and portable analysis of arsenic (As) contamination in drinking water is very important due to its adverse health effects on humans. Available commercial detection kits have shown low sensitivity and selectivity in analysis, and also they can generate harmful by-products. Microfluidic-based approaches allow portable analysis with gold nanoparticles (AuNPs) as labels. However, they need complex surface modification steps that complicate detection protocols. Due to the lack of precise sensing and affordable solution, we focused on developing a microfluidic platform that uses a push-and-pull pumping method for sensitive detection of As. In this detection principle, a sample is introduced in the microfluidic channel modified with -SH functional groups where As can bind. Then, AuNPs are given in the channel and AuNPs bind on free -SH functional groups which are not allocated with As. Absorbance measurements are conducted to detect AuNPs absorbed on the surfaces and the resulting absorbance value is inversely proportional with As concentration. The method enables detection of As down to 2.2 μg/L concentration levels in drinking water, which is well-below the allowed maximum As concentration of 10 μg/L in the drinking waters by the World Health Organization (WHO). The paper reveals that multiple push-and-pull pumping of fixed volume of sample and AuNPs with a syringe pump can improve the binding efficiency in the microfluidic channel. With this technique, low amounts of sample (1 mL) and short total assay time (25 min) are sufficient to detect As. [Display omitted] • Microfluidic channels functionalized with thiol groups are used to capture Arsenic • Bare gold nanoparticles are used for covering thiol groups not occupied with Arsenic • Absorbance measurements are conducted on the channels for Arsenic detection • Arsenic in drinking water can be detected below 10 μg/L levels • Push-and-pull pumping strategy reduces sample consumptions and total assay time [ABSTRACT FROM AUTHOR]