Midlands State University Library

Predicting natural arsenic contamination of bedrock groundwater for a local region in Korea and its application (Record no. 161589)

MARC details
000 -LEADER
fixed length control field 02362nam a22002537a 4500
003 - CONTROL NUMBER IDENTIFIER
control field ZW-GwMSU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20230403204518.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 230403b |||||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency MSU
Transcribing agency MSU
Description conventions rda
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name AHN, Joo Sung
245 ## - TITLE STATEMENT
Title Predicting natural arsenic contamination of bedrock groundwater for a local region in Korea and its application
264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Verlag
Name of producer, publisher, distributor, manufacturer Springer
Date of production, publication, distribution, manufacture, or copyright notice 2013
336 ## - CONTENT TYPE
Source rdacontent
Content type term text
Content type code txt
337 ## - MEDIA TYPE
Source rdamedia
Media type term unmediated
Media type code n
338 ## - CARRIER TYPE
Source rdacarrier
Carrier type term volume
Carrier type code nc
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Environmental earth sciences
Volume/sequential designation Volume , number ,
520 ## - SUMMARY, ETC.
Summary, etc. A logistic regression model for the probability of arsenic exceeding the drinking water guidelines (10 μg/L) in bedrock groundwater was developed for a selected county in Korea, where arsenic occurrence and release reactions have been investigated. Arsenic was enriched naturally by the oxidation of sulfide minerals in metasedimentary rocks and mineralized zones, and due to high mobility in alkaline pH conditions, concentrations were high in groundwater of the county. When considering these reactions of arsenic release and water quality characteristics, several geological and geochemical factors were selected as influencing variables in the model. In the final logistic regression model, geological units of limestone and metasedimentary rocks, the concentrations of nitrate and sulfate, and distances to closed mines and adjacent granite were retained as statistically significant variables. Predicted areas of high probability agreed well with known spatial contamination patterns in the county. The model was also applied to an adjacent county, where the groundwater has not previously been tested for the presence of arsenic, and a probability map for arsenic contamination was then produced. Through the analysis of arsenic concentrations at the wells of high probability, it was determined that the applied model accurately indicated the arsenic contamination of groundwater. The logistic regression approach of this study can be applied to predict arsenic contamination in areas of similar geological and geochemical conditions to the county used in this model.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element arsenic
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element groundwater
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element logistic regression
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name CHO, Yong-Chan
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/s12665-012-2179-9
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Journal Article
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Serial Enumeration / chronology Total Checkouts Full call number Date last seen Price effective from Koha item type Public note
    Library of Congress Classification     Main Library Main Library - Special Collections 03/04/2023 Vol.68 , No.7 (Apr 2013)   GE105 ENV 03/04/2023 03/04/2023 Journal Article For In House Use Only