FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2111092308> ?p ?o ?g. }

• W2111092308 endingPage "142" @default.
• W2111092308 startingPage "119" @default.
• W2111092308 abstract "Numerous methods have been proposed to estimate the pre-nuclear-detonation 14C content of dissolved inorganic carbon (DIC) recharged to groundwater that has been corrected/adjusted for geochemical processes in the absence of radioactive decay (14C0) — a quantity that is essential for estimation of radiocarbon age of DIC in groundwater. The models/approaches most commonly used are grouped as follows: (1) single-sample-based models, (2) a statistical approach based on the observed (curved) relationship between 14C and δ13C data for the aquifer, and (3) the geochemical mass-balance approach that constructs adjustment models accounting for all the geochemical reactions known to occur along a groundwater flow path. This review discusses first the geochemical processes behind each of the single-sample-based models, followed by discussions of the statistical approach and the geochemical mass-balance approach. Finally, the applications, advantages and limitations of the three groups of models/approaches are discussed. The single-sample-based models constitute the prevailing use of 14C data in hydrogeology and hydrological studies. This is in part because the models are applied to an individual water sample to estimate the 14C age, therefore the measurement data are easily available. These models have been shown to provide realistic radiocarbon ages in many studies. However, they usually are limited to simple carbonate aquifers and selection of model may have significant effects on 14C0 often resulting in a wide range of estimates of 14C ages. Of the single-sample-based models, four are recommended for the estimation of 14C0 of DIC in groundwater: Pearson's model, (Ingerson and Pearson, 1964; Pearson and White, 1967), Han & Plummer's model (Han and Plummer, 2013), the IAEA model (Gonfiantini, 1972; Salem et al., 1980), and Oeschger's model (Geyh, 2000). These four models include all processes considered in single-sample-based models, and can be used in different ranges of 13C values. In contrast to the single-sample-based models, the extended Gonfiantini & Zuppi model (Gonfiantini and Zuppi, 2003; Han et al., 2014) is a statistical approach. This approach can be used to estimate 14C ages when a curved relationship between the 14C and 13C values of the DIC data is observed. In addition to estimation of groundwater ages, the relationship between 14C and δ13C data can be used to interpret hydrogeological characteristics of the aquifer, e.g. estimating apparent rates of geochemical reactions and revealing the complexity of the geochemical environment, and identify samples that are not affected by the same set of reactions/processes as the rest of the dataset. The investigated water samples may have a wide range of ages, and for waters with very low values of 14C, the model based on statistics may give more reliable age estimates than those obtained from single-sample-based models. In the extended Gonfiantini & Zuppi model, a representative system-wide value of the initial 14C content is derived from the 14C and δ13C data of DIC and can differ from that used in single-sample-based models. Therefore, the extended Gonfiantini & Zuppi model usually avoids the effect of modern water components which might retain ‘bomb’ pulse signatures. The geochemical mass-balance approach constructs an adjustment model that accounts for all the geochemical reactions known to occur along an aquifer flow path (Plummer et al., 1983; Wigley et al., 1978; Plummer et al., 1994; Plummer and Glynn, 2013), and includes, in addition to DIC, dissolved organic carbon (DOC) and methane (CH4). If sufficient chemical, mineralogical and isotopic data are available, the geochemical mass-balance method can yield the most accurate estimates of the adjusted radiocarbon age. The main limitation of this approach is that complete information is necessary on chemical, mineralogical and isotopic data and these data are often limited. Failure to recognize the limitations and underlying assumptions on which the various models and approaches are based can result in a wide range of estimates of 14C0 and limit the usefulness of radiocarbon as a dating tool for groundwater. In each of the three generalized approaches (single-sample-based models, statistical approach, and geochemical mass-balance approach), successful application depends on scrutiny of the isotopic (14C and 13C) and chemical data to conceptualize the reactions and processes that affect the 14C content of DIC in aquifers. The recently developed graphical analysis method is shown to aid in determining which approach is most appropriate for the isotopic and chemical data from a groundwater system." @default.
• W2111092308 created "2016-06-24" @default.
• W2111092308 creator A5024609980 @default.
• W2111092308 creator A5074715793 @default.
• W2111092308 date "2016-01-01" @default.
• W2111092308 modified "2023-09-25" @default.
• W2111092308 title "A review of single-sample-based models and other approaches for radiocarbon dating of dissolved inorganic carbon in groundwater" @default.
• W2111092308 cites W143446 @default.
• W2111092308 cites W1555262330 @default.
• W2111092308 cites W1600028230 @default.
• W2111092308 cites W1611907149 @default.
• W2111092308 cites W1631751404 @default.
• W2111092308 cites W1968796659 @default.
• W2111092308 cites W1968945335 @default.
• W2111092308 cites W1969715815 @default.
• W2111092308 cites W1975717988 @default.
• W2111092308 cites W1976350916 @default.
• W2111092308 cites W1980276652 @default.
• W2111092308 cites W1984118031 @default.
• W2111092308 cites W1984498606 @default.
• W2111092308 cites W1984673975 @default.
• W2111092308 cites W1989999472 @default.
• W2111092308 cites W1990922872 @default.
• W2111092308 cites W1994612352 @default.
• W2111092308 cites W1999276545 @default.
• W2111092308 cites W2000170194 @default.
• W2111092308 cites W2000589719 @default.
• W2111092308 cites W2000859078 @default.
• W2111092308 cites W2001592607 @default.
• W2111092308 cites W2002267146 @default.
• W2111092308 cites W2004317235 @default.
• W2111092308 cites W2008902772 @default.
• W2111092308 cites W2012044151 @default.
• W2111092308 cites W2015459247 @default.
• W2111092308 cites W2017365986 @default.
• W2111092308 cites W2019432820 @default.
• W2111092308 cites W2019995838 @default.
• W2111092308 cites W2023496383 @default.
• W2111092308 cites W2027396019 @default.
• W2111092308 cites W2028594355 @default.
• W2111092308 cites W2028961679 @default.
• W2111092308 cites W2032101287 @default.
• W2111092308 cites W2034575670 @default.
• W2111092308 cites W2036377891 @default.
• W2111092308 cites W2037146358 @default.
• W2111092308 cites W2038735558 @default.
• W2111092308 cites W2040168058 @default.
• W2111092308 cites W2042048833 @default.
• W2111092308 cites W2042424543 @default.
• W2111092308 cites W2043349976 @default.
• W2111092308 cites W2050663288 @default.
• W2111092308 cites W2052664974 @default.
• W2111092308 cites W2053473062 @default.
• W2111092308 cites W2054385409 @default.
• W2111092308 cites W2056036385 @default.
• W2111092308 cites W2056776742 @default.
• W2111092308 cites W2059718749 @default.
• W2111092308 cites W2060123769 @default.
• W2111092308 cites W2070022169 @default.
• W2111092308 cites W2070670437 @default.
• W2111092308 cites W2072672045 @default.
• W2111092308 cites W2073049625 @default.
• W2111092308 cites W2077849516 @default.
• W2111092308 cites W2084303988 @default.
• W2111092308 cites W2084911272 @default.
• W2111092308 cites W2089283726 @default.
• W2111092308 cites W2092868494 @default.
• W2111092308 cites W2095065076 @default.
• W2111092308 cites W2096504411 @default.
• W2111092308 cites W2102534963 @default.
• W2111092308 cites W2104581682 @default.
• W2111092308 cites W2116611810 @default.
• W2111092308 cites W2120678191 @default.
• W2111092308 cites W2141148171 @default.
• W2111092308 cites W2148871206 @default.
• W2111092308 cites W2149324757 @default.
• W2111092308 cites W2153892536 @default.
• W2111092308 cites W2154883160 @default.
• W2111092308 cites W2159991269 @default.
• W2111092308 cites W2164376815 @default.
• W2111092308 cites W2189750130 @default.
• W2111092308 cites W2217057747 @default.
• W2111092308 cites W2314696016 @default.
• W2111092308 cites W2396313114 @default.
• W2111092308 cites W2485746975 @default.
• W2111092308 cites W2493661033 @default.
• W2111092308 cites W2498268657 @default.
• W2111092308 cites W2513084811 @default.
• W2111092308 cites W3133375876 @default.
• W2111092308 cites W4249751050 @default.
• W2111092308 cites W4294555410 @default.
• W2111092308 doi "https://doi.org/10.1016/j.earscirev.2015.11.004" @default.
• W2111092308 hasPublicationYear "2016" @default.
• W2111092308 type Work @default.
• W2111092308 sameAs 2111092308 @default.
• W2111092308 citedByCount "76" @default.
• W2111092308 countsByYear W21110923082016 @default.
• W2111092308 countsByYear W21110923082017 @default.

• next