Source and drinking water organic and total iodine and correlation with water quality parameters

Sayess, Rassil; Eyring, Adam M.; Reckhow, David A.

doi:10.1016/j.watres.2020.116686

Cited by 17 publications

(7 citation statements)

References 73 publications

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“…A recent study of three river basins in northeast US noted that I T exhibited seasonal patterns characterized by elevated concentrations in low flow conditions (spring-summer) and reduced concentrations during high flow seasons (fall-winter). 64 Similar findings were noted in river basins sampled in our study, where I T varied inversely with streamflow conditions and proportionally to Br − . I − concentrations were <2 μg/L for the majority of the river-based source waters.…”

Section: Seasonal Variation Insupporting

confidence: 90%

“…IO 3 – was detected in only two of the rivers sampled (utilities 12 and 20). 20–80% of DOI may take part in the iodine species cycling in lakes or may be associated with varying influx of dissolved organic carbon due to seasonality . For GW sources, I-species variability was not observed across two sampling events typically 4–6 months apart (Figure S8b,d).…”

Section: Resultsmentioning

confidence: 98%

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Co-Occurrence of Bromine and Iodine Species in US Drinking Water Sources That Can Impact Disinfection Byproduct Formation

Sharma

Zeng

Eaton

et al. 2023

Environ. Sci. Technol.

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Bromine and iodine species are precursors for forming disinfection byproducts in finished drinking waters. Our study incorporates spatial and temporal data to quantify concentrations of inorganic (bromide (Br − ), iodide (I − ), and iodate (IO 3 − )), organic, and total bromine (Br T ) and iodine (I T ) species from 286 drinking water sources and 7 wastewater effluents across the United States. Br − ranged from <5−7800 μg/L (median of 62 μg/L in surface water (SW) and 95 μg/L in groundwater (GW)). I − was detected in 41% of SW (1−72 μg/L, median = <1 μg/L) and 62% of GW (<1−250 μg/L, median = 3 μg/L) samples. The median Br − /I − ratio in SW and GW was 22 μg/μg and 16 μg/μg, respectively, in paired samples with detect Br − and I − . Br T existed primarily as Br − , while I T was present as I − , IO 3 − , and/or total organic iodine (TOI). Inorganic iodine species (I − and IO 3 − ) were predominant in GW samples, accounting for 60−100% of I T ; however, they contributed to only 20−50% of I T in SW samples. The unknown fraction of I T was attributed to TOI. In lakes, seasonal cycling of I-species was observed and was presumably due to algal productivity. Finally, Spearman Rank Correlation tests revealed a strong correlation between Br − and I T in SW (R Br − ,IT = 0.83) following the log 10 (Br − , μg/L) = 0.65 × log 10 (I T , μg/L) − 0.17 relationship. Br − and I − in treated wastewater effluents (median Br − = 234 μg/L, median I − = 5 μg/L) were higher than drinking water sources.

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Section: Seasonal Variation Insupporting

confidence: 90%

Section: Resultsmentioning

confidence: 98%

Co-Occurrence of Bromine and Iodine Species in US Drinking Water Sources That Can Impact Disinfection Byproduct Formation

Sharma

Zeng

Eaton

et al. 2023

Environ. Sci. Technol.

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“…Tobit regression uses independent variables to estimate both the linear coefficients of interest and the probability an observation is equal to or less than a censored threshold. Tobit regression has been used successfully in other water quality domains that demonstrated censoring. , Tobit models were evaluated using the coefficient of determination or R 2 . Binary logistic regression was used to predict service line material, where model performance was measured using the area under the receiving operator curve (AUROC) and precision (or share of correct predictions of lead service lines).…”

Section: Methodsmentioning

confidence: 99%

Identifying Lead Service Lines with Field Tap Water Sampling

Blackhurst

2021

ACS EST Water

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Cross-sectional associations between tap water lead levels and service line materials are not fully understood. As a result, stakeholders are unable to make use of routinely collected tap water samples for myriad decisions. This analysis leverages a novel data set associating field tap water observations with service line materials under varying seasonal and sampling conditions. The analysis demonstrates a staged approach that leverages interpretable model results to strategically filter the sample to boost material diagnoses. Predicted precisions guided by interpretable model results easily exceed those from an incumbent black box, Random Forest model. For example, precisions of 94% were achieved for samples collected between July and October, when lead more naturally leaches. Precisions for the 7% of households with the highest predicted probabilities exceed 96%, which could help municipalities locate lead service lines. Models were also used to inform customers about their risks, predicting lead with a 95% probability when either a single sample exceeds 20 ppb or multiple samples exceed detection thresholds. These results should help stakeholders make better use of tap water samples for risk mitigation and regulatory compliance. Similarly, the staged approach, using interpretable model results to guide classification, can support other water research domains.

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“…7 It was reported that the concentrations of iodide and iodate in source water vary greatly, ranging from 0.5 to 20.0 μg L −1 and from <0.3 μg L −1 to 3.4 μg L −1 , respectively, 7 while the concentration of total organic iodine was lower than 18 μg L −1 in general. 9,10 The species of disinfectant can impact the formation of I-DBPs too. Compared with chloramine, chlorine can form fewer iodinated trihalomethanes (I-THMs), but it can form more chlorine-iodine mixed trihalomethanes (THMs) and form organic chloramines with organic amines in water.…”

Section: Introductionmentioning

confidence: 99%

Comparison of iodinated disinfection by-product formation from the reaction of chlorine, monochloramine, and organic chloramine with seaweed salt during a simulated household cooking process

Ding

et al. 2022

Environ. Sci.: Water Res. Technol.

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Source and drinking water organic and total iodine and correlation with water quality parameters

Cited by 17 publications

References 73 publications

Co-Occurrence of Bromine and Iodine Species in US Drinking Water Sources That Can Impact Disinfection Byproduct Formation

Co-Occurrence of Bromine and Iodine Species in US Drinking Water Sources That Can Impact Disinfection Byproduct Formation

Identifying Lead Service Lines with Field Tap Water Sampling

Comparison of iodinated disinfection by-product formation from the reaction of chlorine, monochloramine, and organic chloramine with seaweed salt during a simulated household cooking process

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