Using spatial statistics to identify the uranium hotspot in groundwater in the mid-eastern Gangetic plain, India
The occurrence of uranium in groundwater is of particular interest due to its toxicological and radiological properties. It has been considered as a relevant contaminant for drinking water even at a low concentration. Uranium is a ubiquitously occurring radionuclide in the environment. Four hundred...
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| Veröffentlicht in: | Environmental earth sciences 2018-10, Vol.77 (19), p.1-12, Article 702 |
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| creator | Kumar, Deepak Singh, Anshuman Jha, Rishi Kumar Sahoo, Sunil Kumar Jha, Vivekanand |
| description | The occurrence of uranium in groundwater is of particular interest due to its toxicological and radiological properties. It has been considered as a relevant contaminant for drinking water even at a low concentration. Uranium is a ubiquitously occurring radionuclide in the environment. Four hundred and fifty-six (456) groundwater samples from different locations of five districts of South Bihar (SB) were collected and concentrations of uranium (U) were analyzed using a light-emitting diode (LED) fluorimetric technique. Uranium concentrations in groundwater samples varied from 0.1 µg l
−1
to 238.2 µg l
−1
with an average value of 12.3 µg l
−1
in five districts of Bihar in the mid-eastern Gangetic plain. This study used hot spot spatial statistics to identify the distribution of elevated uranium concentration in groundwater. The hypothesis whether spatial distribution of high value and low value of U is more likely spatially clustered due to random process near a uranium hotspot in groundwater was tested based on
z
score and Getis-Ord Gi* statistics. The method implemented in this study, can be utilized in the field of risk assessment and decision making to locate potential areas of contamination. |
| doi_str_mv | 10.1007/s12665-018-7889-1 |
| format | Article |
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−1
to 238.2 µg l
−1
with an average value of 12.3 µg l
−1
in five districts of Bihar in the mid-eastern Gangetic plain. This study used hot spot spatial statistics to identify the distribution of elevated uranium concentration in groundwater. The hypothesis whether spatial distribution of high value and low value of U is more likely spatially clustered due to random process near a uranium hotspot in groundwater was tested based on
z
score and Getis-Ord Gi* statistics. The method implemented in this study, can be utilized in the field of risk assessment and decision making to locate potential areas of contamination.</description><identifier>ISSN: 1866-6280</identifier><identifier>EISSN: 1866-6299</identifier><identifier>DOI: 10.1007/s12665-018-7889-1</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Biogeosciences ; Contaminants ; Contamination ; Decision making ; Distribution ; Drinking water ; Earth and Environmental Science ; Earth Sciences ; Environmental Science and Engineering ; Geochemistry ; Geology ; Groundwater ; Hot spots ; Hydrology/Water Resources ; Light emitting diodes ; Original Article ; Radioisotopes ; Risk assessment ; Spatial distribution ; Statistical analysis ; Statistical methods ; Statistics ; Terrestrial Pollution ; Uranium ; Water analysis ; Water sampling</subject><ispartof>Environmental earth sciences, 2018-10, Vol.77 (19), p.1-12, Article 702</ispartof><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2018</rights><rights>Environmental Earth Sciences is a copyright of Springer, (2018). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a339t-988eea39440458ee838cf47cf976da9c3cc656dfe0de708fcbe88d198c3010eb3</citedby><cites>FETCH-LOGICAL-a339t-988eea39440458ee838cf47cf976da9c3cc656dfe0de708fcbe88d198c3010eb3</cites><orcidid>0000-0001-9077-7224</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s12665-018-7889-1$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s12665-018-7889-1$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Kumar, Deepak</creatorcontrib><creatorcontrib>Singh, Anshuman</creatorcontrib><creatorcontrib>Jha, Rishi Kumar</creatorcontrib><creatorcontrib>Sahoo, Sunil Kumar</creatorcontrib><creatorcontrib>Jha, Vivekanand</creatorcontrib><title>Using spatial statistics to identify the uranium hotspot in groundwater in the mid-eastern Gangetic plain, India</title><title>Environmental earth sciences</title><addtitle>Environ Earth Sci</addtitle><description>The occurrence of uranium in groundwater is of particular interest due to its toxicological and radiological properties. It has been considered as a relevant contaminant for drinking water even at a low concentration. Uranium is a ubiquitously occurring radionuclide in the environment. Four hundred and fifty-six (456) groundwater samples from different locations of five districts of South Bihar (SB) were collected and concentrations of uranium (U) were analyzed using a light-emitting diode (LED) fluorimetric technique. Uranium concentrations in groundwater samples varied from 0.1 µg l
−1
to 238.2 µg l
−1
with an average value of 12.3 µg l
−1
in five districts of Bihar in the mid-eastern Gangetic plain. This study used hot spot spatial statistics to identify the distribution of elevated uranium concentration in groundwater. The hypothesis whether spatial distribution of high value and low value of U is more likely spatially clustered due to random process near a uranium hotspot in groundwater was tested based on
z
score and Getis-Ord Gi* statistics. The method implemented in this study, can be utilized in the field of risk assessment and decision making to locate potential areas of contamination.</description><subject>Biogeosciences</subject><subject>Contaminants</subject><subject>Contamination</subject><subject>Decision making</subject><subject>Distribution</subject><subject>Drinking water</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Environmental Science and Engineering</subject><subject>Geochemistry</subject><subject>Geology</subject><subject>Groundwater</subject><subject>Hot spots</subject><subject>Hydrology/Water Resources</subject><subject>Light emitting diodes</subject><subject>Original Article</subject><subject>Radioisotopes</subject><subject>Risk assessment</subject><subject>Spatial distribution</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><subject>Statistics</subject><subject>Terrestrial Pollution</subject><subject>Uranium</subject><subject>Water analysis</subject><subject>Water sampling</subject><issn>1866-6280</issn><issn>1866-6299</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</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>eNp1UMFOAyEQJUYTm9oP8EbiVRSWXRaOptHaxMSLPRMKbEvTwgpsTP9eNmv05FzezOS9N5kHwC3BDwTj9jGRirEGYcJRy7lA5ALMCGcMsUqIy9-e42uwSOmAS1FCBWYz0G-S8zuYepWdOsKUC6bsdII5QGesz647w7y3cIjKu-EE9yGnPmToPNzFMHjzpbKN4ziyTs4gq1LZeLhSfmeLF-yPyvl7uPbGqRtw1aljsosfnIPNy_PH8hW9va_Wy6c3pCgVGQnOrVVU1DWum9JyynVXt7oTLTNKaKo1a5jpLDa2xbzTW8u5IYJrigm2WzoHd5NvH8PnYFOWhzBEX07KihDGmBBNVVhkYukYUoq2k310JxXPkmA5ZiunbGXJVo7ZSlI01aRJhVs-jH_O_4u-AX3nfgs</recordid><startdate>20181001</startdate><enddate>20181001</enddate><creator>Kumar, Deepak</creator><creator>Singh, Anshuman</creator><creator>Jha, Rishi Kumar</creator><creator>Sahoo, Sunil Kumar</creator><creator>Jha, Vivekanand</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7ST</scope><scope>7TG</scope><scope>7UA</scope><scope>7XB</scope><scope>88I</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>M2P</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0001-9077-7224</orcidid></search><sort><creationdate>20181001</creationdate><title>Using spatial statistics to identify the uranium hotspot in groundwater in the mid-eastern Gangetic plain, India</title><author>Kumar, Deepak ; Singh, Anshuman ; Jha, Rishi Kumar ; Sahoo, Sunil Kumar ; Jha, Vivekanand</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a339t-988eea39440458ee838cf47cf976da9c3cc656dfe0de708fcbe88d198c3010eb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Biogeosciences</topic><topic>Contaminants</topic><topic>Contamination</topic><topic>Decision making</topic><topic>Distribution</topic><topic>Drinking water</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Environmental Science and Engineering</topic><topic>Geochemistry</topic><topic>Geology</topic><topic>Groundwater</topic><topic>Hot spots</topic><topic>Hydrology/Water Resources</topic><topic>Light emitting diodes</topic><topic>Original Article</topic><topic>Radioisotopes</topic><topic>Risk assessment</topic><topic>Spatial distribution</topic><topic>Statistical analysis</topic><topic>Statistical methods</topic><topic>Statistics</topic><topic>Terrestrial Pollution</topic><topic>Uranium</topic><topic>Water analysis</topic><topic>Water sampling</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kumar, Deepak</creatorcontrib><creatorcontrib>Singh, Anshuman</creatorcontrib><creatorcontrib>Jha, Rishi Kumar</creatorcontrib><creatorcontrib>Sahoo, Sunil Kumar</creatorcontrib><creatorcontrib>Jha, Vivekanand</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & 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>ProQuest Central Student</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Science Database</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & 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>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>Environment Abstracts</collection><jtitle>Environmental earth sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kumar, Deepak</au><au>Singh, Anshuman</au><au>Jha, Rishi Kumar</au><au>Sahoo, Sunil Kumar</au><au>Jha, Vivekanand</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Using spatial statistics to identify the uranium hotspot in groundwater in the mid-eastern Gangetic plain, India</atitle><jtitle>Environmental earth sciences</jtitle><stitle>Environ Earth Sci</stitle><date>2018-10-01</date><risdate>2018</risdate><volume>77</volume><issue>19</issue><spage>1</spage><epage>12</epage><pages>1-12</pages><artnum>702</artnum><issn>1866-6280</issn><eissn>1866-6299</eissn><abstract>The occurrence of uranium in groundwater is of particular interest due to its toxicological and radiological properties. It has been considered as a relevant contaminant for drinking water even at a low concentration. Uranium is a ubiquitously occurring radionuclide in the environment. Four hundred and fifty-six (456) groundwater samples from different locations of five districts of South Bihar (SB) were collected and concentrations of uranium (U) were analyzed using a light-emitting diode (LED) fluorimetric technique. Uranium concentrations in groundwater samples varied from 0.1 µg l
−1
to 238.2 µg l
−1
with an average value of 12.3 µg l
−1
in five districts of Bihar in the mid-eastern Gangetic plain. This study used hot spot spatial statistics to identify the distribution of elevated uranium concentration in groundwater. The hypothesis whether spatial distribution of high value and low value of U is more likely spatially clustered due to random process near a uranium hotspot in groundwater was tested based on
z
score and Getis-Ord Gi* statistics. The method implemented in this study, can be utilized in the field of risk assessment and decision making to locate potential areas of contamination.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s12665-018-7889-1</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0001-9077-7224</orcidid></addata></record> |
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| subjects | Biogeosciences Contaminants Contamination Decision making Distribution Drinking water Earth and Environmental Science Earth Sciences Environmental Science and Engineering Geochemistry Geology Groundwater Hot spots Hydrology/Water Resources Light emitting diodes Original Article Radioisotopes Risk assessment Spatial distribution Statistical analysis Statistical methods Statistics Terrestrial Pollution Uranium Water analysis Water sampling |
| title | Using spatial statistics to identify the uranium hotspot in groundwater in the mid-eastern Gangetic plain, India |
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