Literature DB >> 18486990

Distribution and variability of redox zones controlling spatial variability of arsenic in the Mississippi River Valley alluvial aquifer, southeastern Arkansas.

M U Sharif1, R K Davis, K F Steele, B Kim, P D Hays, T M Kresse, J A Fazio.   

Abstract

Twenty one of 118 irrigation water wells in the shallow (25-30 m thick) Mississippi River Valley alluvial aquifer in the Bayou Bartholomew watershed, southeastern Arkansas had arsenic (As) concentrations (<0.5 to 77 microg/L) exceeding 10 microg/L. Sediment and groundwater samples were collected and analyzed from the sites of the highest, median, and lowest concentrations of As in groundwater in the alluvial aquifers located at Jefferson County, Arkansas. A traditional five-step sequential extraction was performed to differentiate the exchangeable, carbonate, amorphous Fe and Mn oxide, organic, and hot HNO(3)-leachable fraction of As and other compounds in sediments. The Chao reagent (0.25 M hydroxylamine hydrochloride in 0.25 M HCl) removes amorphous Fe and Mn oxides and oxyhydroxides (present as coatings on grains and amorphous minerals) by reductive dissolution and is a measure of reducible Fe and Mn in sediments. The hot HNO(3) extraction removes mostly crystalline metal oxides and all other labile forms of As. Significant total As (20%) is complexed with amorphous Fe and Mn oxides in sediments. Arsenic abundance is not significant in carbonates or organic matter. Significant (40-70 microg/kg) exchangeable As is only present at shallow depth (0-1 m below ground surface). Arsenic is positively correlated to Fe extracted by Chao reagent (r=0.83) and hot HNO(3) (r=0.85). Arsenic extracted by Chao reagent decreases significantly with depth as compared to As extracted by hot HNO(3). Fe (II)/Fe (the ratio of Fe concentration in the extracts of Chao reagent and hot HNO(3)) is positively correlated (r=0.76) to As extracted from Chao reagent. Although Fe (II)/Fe increases with depth, the relative abundance of reducible Fe decreases noticeably with depth. The amount of reducible Fe, as well as As complexed to amorphous Fe and Mn oxides and oxyhydroxides decreases with depth. Possible explanations for the decrease in reducible Fe and its complexed As with depth include historic flushing of As and Fe from hydrous ferric oxides (HFO) by microbially-mediated reductive dissolution and aging of HFO to crystalline phases. Hydrogeochemical data suggests that the groundwater in the area falls in the mildly reducing (suboxic) to relatively highly reducing (anoxic) zone, and points to reductive dissolution of HFO as the dominant As release mechanism. Spatial variability of gypsum solubility and simultaneous SO(4)(2-) reduction with co-precipitation of As and sulfide is an important limiting process controlling the concentration of As in groundwater in the area.

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Year:  2008        PMID: 18486990     DOI: 10.1016/j.jconhyd.2008.03.001

Source DB:  PubMed          Journal:  J Contam Hydrol        ISSN: 0169-7722            Impact factor:   3.188


  5 in total

1.  Predicting arsenic concentrations in groundwater of San Luis Valley, Colorado: implications for individual-level lifetime exposure assessment.

Authors:  Katherine A James; Jaymie R Meliker; Barbara E Buttenfield; Tim Byers; Gary O Zerbe; John E Hokanson; Julie A Marshall
Journal:  Environ Geochem Health       Date:  2014-01-16       Impact factor: 4.609

2.  Risk assessment for arsenic-contaminated groundwater along River Indus in Pakistan.

Authors:  Unaib Rabbani; Gohar Mahar; Azhar Siddique; Zafar Fatmi
Journal:  Environ Geochem Health       Date:  2016-03-24       Impact factor: 4.609

3.  Natural and Anthropogenic Processes Affecting Domestic Groundwater Quality within the Northwestern Appalachian Basin.

Authors:  H G Siegel; M A Soriano; C J Clark; N P Johnson; H G Wulsin; N C Deziel; D L Plata; T H Darrah; J E Saiers
Journal:  Environ Sci Technol       Date:  2022-09-21       Impact factor: 11.357

4.  Geochemical modeling of arsenic release from a deep natural solid matrix under alternated redox conditions.

Authors:  A Molinari; C Ayora; M Marcaccio; L Guadagnini; X Sanchez-Vila; A Guadagnini
Journal:  Environ Sci Pollut Res Int       Date:  2013-08-16       Impact factor: 4.223

5.  Mapped Predictions of Manganese and Arsenic in an Alluvial Aquifer Using Boosted Regression Trees.

Authors:  Katherine J Knierim; James A Kingsbury; Kenneth Belitz; Paul E Stackelberg; Burke J Minsley; J R Rigby
Journal:  Ground Water       Date:  2022-01-07       Impact factor: 2.887

  5 in total

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