Improved Decision Making for Water Lead Testing in U.S. Child Care Facilities Using Machine-Learned Bayesian Networks.

Tap water lead testing programs in the U.S. need improved methods for identifying high-risk facilities to optimize limited resources. In this study, machine-learned Bayesian network (BN) models were used to predict building-wide water lead risk in over 4,000 child care facilities in North Carolina according to maximum and 90th percentile lead levels from water lead concentrations at 22,943 taps. The performance of the BN models was compared to common alternative risk factors, or heuristics, used to inform water lead testing programs among child care facilities including building age, water source, and Head Start program status. The BN models identified a range of variables associated with building-wide water lead, with facilities that serve low-income families, rely on groundwater, and have more taps exhibiting greater risk. Models predicting the probability of a single tap exceeding each target concentration performed better than models predicting facilities with clustered high-risk taps. The BN models' Fß-scores outperformed each of the alternative heuristics by 118-213%. This represents up to a 60% increase in the number of high-risk facilities that could be identified and up to a 49% decrease in the number of samples that would need to be collected by using BN model-informed sampling compared to using simple heuristics. Overall, this study demonstrates the value of machine-learning approaches for identifying high water lead risk that could improve lead testing programs nationwide.

A Participatory Science Approach to Evaluating Factors Associated with the Occurrence of Metals and PFAS in Guatemala City Tap Water.

Limited information is available regarding chemical water quality at the tap in Guatemala City, preventing individuals, water utilities, and public health authorities from making data-driven decisions related to water quality. To address this need, 113 participants among households served by a range of water providers across the Guatemala City metropolitan area were recruited as participatory scientists to collect first-draw and flushed tap water samples at their residence. Samples were transported to the U.S. and analyzed for 20 metals and 25 per- and polyfluoroalkyl substances (PFAS). At least one metal exceeded the Guatemalan Maximum Permissible Limit (MPL) for drinking water in 63% of households (n = 71). Arsenic and lead exceeded the MPL in 33.6% (n = 38) and 8.9% (n = 10) of samples, respectively. Arsenic was strongly associated with groundwater while lead occurrence was not associated with location, water source, or provider. One or more PFAS were detected in 19% of samples (n = 21, range 2.1-64.2 ppt). PFAS were significantly associated with the use of plastic water storage tanks but not with location, water source, or provider. Overall, the high prevalence of arsenic above the MPL in Guatemala City tap water represents a potential health risk that current water treatment processes are not optimized to remove. Furthermore, potential contaminants from premise plumbing and storage, including lead and PFAS, represent additional risks requiring further investigation and public engagement.

Arsenic contamination in rainwater harvesting tanks around Lake Poopó in Oruro, Bolivia: An unrecognized health risk.

Drinking water sources used by largely rural and indigenous communities around Lake Poopó in the Bolivian Altiplano are impacted by drought and a combination of natural and anthropogenic mining-related contaminants putting the long-term health and sustainability of these communities at risk. As an alternative drinking water source, 18 rainwater harvesting tanks connected to corrugated iron roofs, each with a first-flush system, were installed in 5 communities around the lake. The water quality of these tanks was monitored over 22 months and compared to alternative unprotected surface and groundwater sources the communities previously relied upon. The rainwater quality was found to be within the Bolivian and World Health Organization (WHO) limits, except for elevated arsenic concentrations two times the recommended health limit (0.01 mg/L). Tracing arsenic concentrations through the rainwater flow-path showed that the elevated arsenic concentrations result from mineral dust particles entering the system when rainwater interacts with the roof catchment, with arsenic leaching out. A leaching test showed that 24 h of contact time between 200 mL of water and <1 g of roof dust is enough to raise the arsenic levels of the water above the Bolivian and WHO limit. Currently, no other research exists evaluating the quality of harvested rainwater in the Bolivian Altiplano for human consumption or the source of arsenic in harvested water. This represents a significant knowledge gap for future development practitioners and programs addressing water security around Lake Poopó and the wider region. As a result, it is strongly recommended to include arsenic as a standard parameter in water quality monitoring of rainwater harvesting projects, especially in active mining regions, and to optimize strategies to minimize roof dust from entering the collection system.

Does Granular Activated Carbon with Chlorination Produce Safer Drinking Water? From Disinfection Byproducts and Total Organic Halogen to Calculated Toxicity.

Granular activated carbon (GAC) adsorption is well-established for controlling regulated disinfection byproducts (DBPs), but its effectiveness for unregulated DBPs and DBP-associated toxicity is unclear. In this study, GAC treatment was evaluated at three full-scale chlorination drinking water treatment plants over different GAC service lives for controlling 61 unregulated DBPs, 9 regulated DBPs, and speciated total organic halogen (total organic chlorine, bromine, and iodine). The plants represented a range of impacts, including algal, agricultural, and industrial wastewater. This study represents the most extensive full-scale study of its kind and seeks to address the question of whether GAC can make drinking water safer from a DBP perspective. Overall, GAC was effective for removing DBP precursors and reducing DBP formation and total organic halogen, even after >22 000 bed volumes of treated water. GAC also effectively removed preformed DBPs at plants using prechlorination, including highly toxic iodoacetic acids and haloacetonitriles. However, 7 DBPs (mostly brominated and nitrogenous) increased in formation after GAC treatment. In one plant, an increase in tribromonitromethane had significant impacts on calculated cytotoxicity, which only had 7-17% reduction following GAC. While these DBPs are highly toxic, the total calculated cytotoxicity and genotoxicity for the GAC treated waters for the other two plants was reduced 32-83% (across young-middle-old GAC). Overall, calculated toxicity was reduced post-GAC, with preoxidation allowing further reductions.

Evaluating Activated Carbon Adsorption of Dissolved Organic Matter and Micropollutants Using Fluorescence Spectroscopy.

Dissolved organic matter (DOM) negatively impacts granular activated carbon (GAC) adsorption of micropollutants and is a disinfection byproduct precursor. DOM from surface waters, wastewater effluent, and 1 kDa size fractions were adsorbed by GAC and characterized using fluorescence spectroscopy, UV-absorption, and size exclusion chromatography (SEC). Fluorescing DOM was preferentially adsorbed relative to UV-absorbing DOM. Humic-like fluorescence (peaks A and C) was selectively adsorbed relative to polyphenol-like fluorescence (peaks T and B) potentially due to size exclusion effects. In the surface waters and size fractions, peak C was preferentially removed relative to peak A, whereas the reverse was found in wastewater effluent, indicating that humic-like fluorescence is associated with different compounds depending on DOM source. Based on specific UV-absorption (SUVA), aromatic DOM was preferentially adsorbed. The fluorescence index (FI), if interpreted as an indicator of aromaticity, indicated the opposite but exhibited a strong relationship with average molecular weight, suggesting that FI might be a better indicator of DOM size than aromaticity. The influence of DOM intermolecular interactions on adsorption were minimal based on SEC analysis. Fluorescence parameters captured the impact of DOM size on the fouling of 2-methylisoborneol and warfarin adsorption and correlated with direct competition and pore blockage indicators.