ARSENIC IN THE SHALLOW GROUND WATERS OF CONTERMINOUS UNITED STATES: ASSESSMENT, HEALTH RISKS, AND COSTS FOR MCL COMPLIANCE1

A methodology consisting of ordinal logistic regression (OLR) is used to predict the probability of occurrence of arsenic concentrations in different threshold limits in shallow ground waters of the conterminous United States (CONUS) subject to a set of influencing variables. The analysis considered...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of the American Water Resources Association 2006-04, Vol.42 (2), p.275-294
Hauptverfasser: Twarakavi, Navin Kumar C., Kaluarachchi, Jagath J.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 294
container_issue 2
container_start_page 275
container_title Journal of the American Water Resources Association
container_volume 42
creator Twarakavi, Navin Kumar C.
Kaluarachchi, Jagath J.
description A methodology consisting of ordinal logistic regression (OLR) is used to predict the probability of occurrence of arsenic concentrations in different threshold limits in shallow ground waters of the conterminous United States (CONUS) subject to a set of influencing variables. The analysis considered a number of maximum contaminant level (MCL) options as threshold values to estimate the probabilities of occurrence of arsenic in ranges defined by a given MCL of 3, 5, 10, 20, and 50 μg/l and a detection limit of 1 μg/l. The fit between the observed and predicted probability of occurrence was around 83 percent for all MCL options. The estimated probabilities were used to estimate the median background concentration of arsenic in the CONUS. The shallow ground water of the western United States is more vulnerable than the eastern United States. Arizona, Utah, Nevada, and California in particular are hotspots for arsenic contamination. The risk assessment showed that counties in southern California, Arizona, Florida, and Washington and a few others scattered throughout the CONUS face a high risk from arsenic exposure through untreated ground water consumption. A simple cost effectiveness analysis was performed to understand the household costs for MCL compliance in using arsenic contaminated ground water. The results showed that the current MCL of 10 μg/l is a good compromise based on existing treatment technologies.
doi_str_mv 10.1111/j.1752-1688.2006.tb03838.x
format Article
fullrecord <record><control><sourceid>proquest_wiley</sourceid><recordid>TN_cdi_proquest_miscellaneous_36201644</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>36201644</sourcerecordid><originalsourceid>FETCH-LOGICAL-p1455-53f5e1f13c774b5723dc86f821d3c9a46819a5663af4b362591c7ba143605e283</originalsourceid><addsrcrecordid>eNqFkU1Lw0AQhoMoqNX_sHjwZOLOfmXrRZZ0a6JpItmUelvSmEBLtbWxWPHPu1Xx4MW57CzzzgPD43lngANwdTkPIOTEByFlQDAWwesUU0llsN3zjn5H-67HfeqzkD0cesddN8cYOEh65H2owugsiVCSoTLWyMQqTfMJuinycTZAE1XqwqB8iKI8c-0oyfKxQeMsKfUAmdKNzRVSxmhjRjorL1CsVVrGqEjMnblAyjGi3JQGDfMCjaLU_Ub3aaKySMOJd9BWi645_Xl73nioyyj20_wmiVTqr4Bx7nPa8gZaoHUYsikPCX2spWglgUda9ysmJPQrLgStWjalgvA-1OG0AkYF5g2RtOedf3NX6-XLpule7dOsq5vFonpulpvOuh0MgrF_gwQIoQ7vgmd_gvPlZv3sjrAORSnjX7Tr79DbbNG829V69lSt3y1gu1Nn53bnx-782J06-6PObu2tmhQk5PQTxo6Dxw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>201334544</pqid></control><display><type>article</type><title>ARSENIC IN THE SHALLOW GROUND WATERS OF CONTERMINOUS UNITED STATES: ASSESSMENT, HEALTH RISKS, AND COSTS FOR MCL COMPLIANCE1</title><source>Access via Wiley Online Library</source><creator>Twarakavi, Navin Kumar C. ; Kaluarachchi, Jagath J.</creator><creatorcontrib>Twarakavi, Navin Kumar C. ; Kaluarachchi, Jagath J.</creatorcontrib><description>A methodology consisting of ordinal logistic regression (OLR) is used to predict the probability of occurrence of arsenic concentrations in different threshold limits in shallow ground waters of the conterminous United States (CONUS) subject to a set of influencing variables. The analysis considered a number of maximum contaminant level (MCL) options as threshold values to estimate the probabilities of occurrence of arsenic in ranges defined by a given MCL of 3, 5, 10, 20, and 50 μg/l and a detection limit of 1 μg/l. The fit between the observed and predicted probability of occurrence was around 83 percent for all MCL options. The estimated probabilities were used to estimate the median background concentration of arsenic in the CONUS. The shallow ground water of the western United States is more vulnerable than the eastern United States. Arizona, Utah, Nevada, and California in particular are hotspots for arsenic contamination. The risk assessment showed that counties in southern California, Arizona, Florida, and Washington and a few others scattered throughout the CONUS face a high risk from arsenic exposure through untreated ground water consumption. A simple cost effectiveness analysis was performed to understand the household costs for MCL compliance in using arsenic contaminated ground water. The results showed that the current MCL of 10 μg/l is a good compromise based on existing treatment technologies.</description><identifier>ISSN: 1093-474X</identifier><identifier>EISSN: 1752-1688</identifier><identifier>DOI: 10.1111/j.1752-1688.2006.tb03838.x</identifier><language>eng</language><publisher>Oxford, UK: Blackwell Publishing Ltd</publisher><subject>Arsenic ; Cost analysis ; Drinking water ; ground water ; Groundwater ; Health risk assessment ; logistic regression ; Public health ; Regression analysis ; vulnerability</subject><ispartof>Journal of the American Water Resources Association, 2006-04, Vol.42 (2), p.275-294</ispartof><rights>Copyright American Water Resources Association Apr 2006</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fj.1752-1688.2006.tb03838.x$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fj.1752-1688.2006.tb03838.x$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids></links><search><creatorcontrib>Twarakavi, Navin Kumar C.</creatorcontrib><creatorcontrib>Kaluarachchi, Jagath J.</creatorcontrib><title>ARSENIC IN THE SHALLOW GROUND WATERS OF CONTERMINOUS UNITED STATES: ASSESSMENT, HEALTH RISKS, AND COSTS FOR MCL COMPLIANCE1</title><title>Journal of the American Water Resources Association</title><description>A methodology consisting of ordinal logistic regression (OLR) is used to predict the probability of occurrence of arsenic concentrations in different threshold limits in shallow ground waters of the conterminous United States (CONUS) subject to a set of influencing variables. The analysis considered a number of maximum contaminant level (MCL) options as threshold values to estimate the probabilities of occurrence of arsenic in ranges defined by a given MCL of 3, 5, 10, 20, and 50 μg/l and a detection limit of 1 μg/l. The fit between the observed and predicted probability of occurrence was around 83 percent for all MCL options. The estimated probabilities were used to estimate the median background concentration of arsenic in the CONUS. The shallow ground water of the western United States is more vulnerable than the eastern United States. Arizona, Utah, Nevada, and California in particular are hotspots for arsenic contamination. The risk assessment showed that counties in southern California, Arizona, Florida, and Washington and a few others scattered throughout the CONUS face a high risk from arsenic exposure through untreated ground water consumption. A simple cost effectiveness analysis was performed to understand the household costs for MCL compliance in using arsenic contaminated ground water. The results showed that the current MCL of 10 μg/l is a good compromise based on existing treatment technologies.</description><subject>Arsenic</subject><subject>Cost analysis</subject><subject>Drinking water</subject><subject>ground water</subject><subject>Groundwater</subject><subject>Health risk assessment</subject><subject>logistic regression</subject><subject>Public health</subject><subject>Regression analysis</subject><subject>vulnerability</subject><issn>1093-474X</issn><issn>1752-1688</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqFkU1Lw0AQhoMoqNX_sHjwZOLOfmXrRZZ0a6JpItmUelvSmEBLtbWxWPHPu1Xx4MW57CzzzgPD43lngANwdTkPIOTEByFlQDAWwesUU0llsN3zjn5H-67HfeqzkD0cesddN8cYOEh65H2owugsiVCSoTLWyMQqTfMJuinycTZAE1XqwqB8iKI8c-0oyfKxQeMsKfUAmdKNzRVSxmhjRjorL1CsVVrGqEjMnblAyjGi3JQGDfMCjaLU_Ub3aaKySMOJd9BWi645_Xl73nioyyj20_wmiVTqr4Bx7nPa8gZaoHUYsikPCX2spWglgUda9ysmJPQrLgStWjalgvA-1OG0AkYF5g2RtOedf3NX6-XLpule7dOsq5vFonpulpvOuh0MgrF_gwQIoQ7vgmd_gvPlZv3sjrAORSnjX7Tr79DbbNG829V69lSt3y1gu1Nn53bnx-782J06-6PObu2tmhQk5PQTxo6Dxw</recordid><startdate>200604</startdate><enddate>200604</enddate><creator>Twarakavi, Navin Kumar C.</creator><creator>Kaluarachchi, Jagath J.</creator><general>Blackwell Publishing Ltd</general><scope>3V.</scope><scope>7QH</scope><scope>7ST</scope><scope>7UA</scope><scope>7X2</scope><scope>7XB</scope><scope>88I</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H97</scope><scope>HCIFZ</scope><scope>KR7</scope><scope>L.G</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M2P</scope><scope>M7P</scope><scope>M7S</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>S0X</scope><scope>SOI</scope><scope>H96</scope></search><sort><creationdate>200604</creationdate><title>ARSENIC IN THE SHALLOW GROUND WATERS OF CONTERMINOUS UNITED STATES: ASSESSMENT, HEALTH RISKS, AND COSTS FOR MCL COMPLIANCE1</title><author>Twarakavi, Navin Kumar C. ; Kaluarachchi, Jagath J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p1455-53f5e1f13c774b5723dc86f821d3c9a46819a5663af4b362591c7ba143605e283</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Arsenic</topic><topic>Cost analysis</topic><topic>Drinking water</topic><topic>ground water</topic><topic>Groundwater</topic><topic>Health risk assessment</topic><topic>logistic regression</topic><topic>Public health</topic><topic>Regression analysis</topic><topic>vulnerability</topic><toplevel>online_resources</toplevel><creatorcontrib>Twarakavi, Navin Kumar C.</creatorcontrib><creatorcontrib>Kaluarachchi, Jagath J.</creatorcontrib><collection>ProQuest Central (Corporate)</collection><collection>Aqualine</collection><collection>Environment Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural &amp; Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric &amp; Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) 3: Aquatic Pollution &amp; Environmental Quality</collection><collection>SciTech Premium Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) Professional</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Science Database</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric &amp; Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>SIRS Editorial</collection><collection>Environment Abstracts</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy &amp; Non-Living Resources</collection><jtitle>Journal of the American Water Resources Association</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Twarakavi, Navin Kumar C.</au><au>Kaluarachchi, Jagath J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>ARSENIC IN THE SHALLOW GROUND WATERS OF CONTERMINOUS UNITED STATES: ASSESSMENT, HEALTH RISKS, AND COSTS FOR MCL COMPLIANCE1</atitle><jtitle>Journal of the American Water Resources Association</jtitle><date>2006-04</date><risdate>2006</risdate><volume>42</volume><issue>2</issue><spage>275</spage><epage>294</epage><pages>275-294</pages><issn>1093-474X</issn><eissn>1752-1688</eissn><abstract>A methodology consisting of ordinal logistic regression (OLR) is used to predict the probability of occurrence of arsenic concentrations in different threshold limits in shallow ground waters of the conterminous United States (CONUS) subject to a set of influencing variables. The analysis considered a number of maximum contaminant level (MCL) options as threshold values to estimate the probabilities of occurrence of arsenic in ranges defined by a given MCL of 3, 5, 10, 20, and 50 μg/l and a detection limit of 1 μg/l. The fit between the observed and predicted probability of occurrence was around 83 percent for all MCL options. The estimated probabilities were used to estimate the median background concentration of arsenic in the CONUS. The shallow ground water of the western United States is more vulnerable than the eastern United States. Arizona, Utah, Nevada, and California in particular are hotspots for arsenic contamination. The risk assessment showed that counties in southern California, Arizona, Florida, and Washington and a few others scattered throughout the CONUS face a high risk from arsenic exposure through untreated ground water consumption. A simple cost effectiveness analysis was performed to understand the household costs for MCL compliance in using arsenic contaminated ground water. The results showed that the current MCL of 10 μg/l is a good compromise based on existing treatment technologies.</abstract><cop>Oxford, UK</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1111/j.1752-1688.2006.tb03838.x</doi><tpages>20</tpages></addata></record>
fulltext fulltext
identifier ISSN: 1093-474X
ispartof Journal of the American Water Resources Association, 2006-04, Vol.42 (2), p.275-294
issn 1093-474X
1752-1688
language eng
recordid cdi_proquest_miscellaneous_36201644
source Access via Wiley Online Library
subjects Arsenic
Cost analysis
Drinking water
ground water
Groundwater
Health risk assessment
logistic regression
Public health
Regression analysis
vulnerability
title ARSENIC IN THE SHALLOW GROUND WATERS OF CONTERMINOUS UNITED STATES: ASSESSMENT, HEALTH RISKS, AND COSTS FOR MCL COMPLIANCE1
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-27T11%3A52%3A45IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_wiley&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=ARSENIC%20IN%20THE%20SHALLOW%20GROUND%20WATERS%20OF%20CONTERMINOUS%20UNITED%20STATES:%20ASSESSMENT,%20HEALTH%20RISKS,%20AND%20COSTS%20FOR%20MCL%20COMPLIANCE1&rft.jtitle=Journal%20of%20the%20American%20Water%20Resources%20Association&rft.au=Twarakavi,%20Navin%20Kumar%20C.&rft.date=2006-04&rft.volume=42&rft.issue=2&rft.spage=275&rft.epage=294&rft.pages=275-294&rft.issn=1093-474X&rft.eissn=1752-1688&rft_id=info:doi/10.1111/j.1752-1688.2006.tb03838.x&rft_dat=%3Cproquest_wiley%3E36201644%3C/proquest_wiley%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=201334544&rft_id=info:pmid/&rfr_iscdi=true