A new software tool for the analysis of noble gas data sets from (ground)water. (May 2018)

• Record Type: Journal Article
• Authors: Jung, Michael; Aeschbach, Werner
• Is Part Of: Environmental modelling & software. Volume 103(2018)
• Page Start: 120
• Page End: 130
• Publication Date: 2018-05
• Subjects: Groundwater -- Recharge conditions -- Noble gas temperature -- Excess air -- Parameter estimation; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2018.02.004
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: In this article we present the software PANGA which is a new open-source tool for the evaluation of noble gas data from (ground)water samples. In addition to most of the features of traditionally used software like NOBLE, it includes among others easy-to-use methods for Monte Carlo simulations and analyses, as well as support for newer excess air models and ensemble fits. We verify PANGA's results for two data sets by comparing them with the results of NOBLE, using different excess air models. We conclude this study with a set of recommendations for the evaluation of noble gas data sets, giving detailed step-by-step instructions, including descriptions of the Monte Carlo patterns most commonly observed. Graphical abstract: Image 1 Highlights: We present a new software tool for the determination of noble gas temperatures. PANGA includes current excess air models and powerful Monte Carlo analysis tools. PANGA's results are verified and discussed using two large published data sets. Detailed recommendations for a stepwise evaluation of noble gas data are provided.