Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A prediction method for radon in groundwater using GIS and multivariate statistics
KTH, School of Architecture and the Built Environment (ABE), Land and Water Resources Engineering.
KTH, School of Architecture and the Built Environment (ABE), Land and Water Resources Engineering.
2006 (English)In: Science of the Total Environment, ISSN 0048-9697, E-ISSN 1879-1026, Vol. 367, no 2-3, 666-680 p.Article in journal (Refereed) Published
Abstract [en]

Radon (Rn-222) in groundwater constitutes a source of natural radioactivity to indoor air. It is difficult to make predictions of radon levels in groundwater due to the heterogeneous distribution of uranium and radium, flow patterns and varying geochemical conditions. High radon concentrations in groundwater are not always associated with high uranium content in the bedrock, since groundwater with a high radon content has been found in regions with low to moderate uranium concentrations in the bedrock. This paper describes a methodology for predicting areas with high concentrations of Rn-222 in groundwater on a general scale, within an area of approximately 185 x 145 km(2). The methodology is based on multivariate statistical analyses, including principal component analysis and regression analysis, and investigates the factors of geology, land use, topography and uranium (U) content in the bedrock. A statistical variable based method (the RV method) was used to estimate risk values related to different radon concentrations. The method was calibrated and tested on more than 4400 drilled wells in Stockholm County.

The results showed that radon concentration was clearly correlated to bedrock type, well altitude and distance from fracture zones. The weighted index (risk value) estimated by the RV method provided a fair prediction of radon potential in groundwater on a general scale. Risk values obtained using the RV method were compared to radon measurements in 12 test areas (on a local scale, each of area 25 x 25 km(2)) in Stockholm County and a high correlation (r=-0.87) was observed. The study showed that the occurrence and spread of radon in groundwater are guided by multiple factors, which can be used in a radon prediction method on a general scale. However, it does not provide any direct information on the geochemical and flow processes involved.

Place, publisher, year, edition, pages
2006. Vol. 367, no 2-3, 666-680 p.
Keyword [en]
radon, groundwater, hard rock, GIS, multivariate statistics, risk variable method
National Category
Water Engineering
Identifiers
URN: urn:nbn:se:kth:diva-8776DOI: 10.1016/j.scitotenv.2006.02.044ISI: 000240042700013Scopus ID: 2-s2.0-33746265353OAI: oai:DiVA.org:kth-8776DiVA: diva2:14200
Note
QC 20101221Available from: 2005-11-11 Created: 2005-11-11 Last updated: 2017-12-14Bibliographically approved
In thesis
1. Radon in Groundwater- Influencing Factors and Prediction Methodology for a Swedish Environment
Open this publication in new window or tab >>Radon in Groundwater- Influencing Factors and Prediction Methodology for a Swedish Environment
2005 (English)Licentiate thesis, comprehensive summary (Other scientific)
Abstract [en]

This thesis presents a method for predicting radon (222Rn) levels in groundwater on a general scale, within an area of approximately 185 x 145 km2. The method applies to Swedish conditions, where 222Rn is the main contributor to natural radioactivity. Prediction of radon potential in groundwater is complex because there are many different factors affecting radon content, including geochemical and flow processes. The proposed method is based on univariate and multivariate statistical analyses and investigated the influence of different factors such as bedrock, soils, uranium distribution, altitude, distance to fractures and land use. A statistical variable based method (the RV method) was used to estimate risk values related to different radon concentrations. The method was calibrated and tested on more than 4400 drilled wells in Stockholm County. The weighted index (risk value) estimated by the RV method provided a fair prediction of radon potential in groundwater on a general scale. The RV method was successful in estimating the median radon concentration within 12 subregions (at a local scale, each of area 25 x 25 km2), based on weighted index values obtained from half of all wells tested. A high correlation between risk values and median radon concentrations was demonstrated. The factors bedrock, altitude, distance to fracture zone and distribution of uranium in bedrock were found to be significant in the prediction approach on a general scale. Visual data mining, which comprised analysis of 3D images, was a useful tool for data exploration but could not be used as an independent method for drawing conclusions regarding radon in groundwater. Results of a field study based on 38 drilled wells on the island of Ljusterö in the Stockholm archipelago showed that 222Rn concentrations in groundwater were weakly correlated to the parent elements (226Ra and 238U) in solution.

Place, publisher, year, edition, pages
Stockholm: KTH, 2005. vii, 23 p.
Series
Trita-LWR. LIC, ISSN 1650-8629 ; 2032
Keyword
Radon, Grondwater, GIS, RV method, Multivariate statistics
National Category
Water Engineering
Identifiers
urn:nbn:se:kth:diva-491 (URN)91-7178-208-7 (ISBN)
Presentation
2005-11-21, V21, mark-och vattenteknik, Teknikringen 72, 1tr, KTH campus, 10:00
Opponent
Supervisors
Note
QC 20101221Available from: 2005-11-11 Created: 2005-11-11 Last updated: 2010-12-21Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Skeppström, KirlnaOlofsson, Bo
By organisation
Land and Water Resources Engineering
In the same journal
Science of the Total Environment
Water Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 90 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf