Application of stochastic simulation to CO2 flux from soil: Mapping and quantification of gas release
Identifieur interne : 000008 ( PascalFrancis/Curation ); précédent : 000007; suivant : 000009Application of stochastic simulation to CO2 flux from soil: Mapping and quantification of gas release
Auteurs : C. Cardellini [Italie] ; G. Chiodini [Italie] ; F. Frondini [Italie]Source :
- Journal of geophysical research [ 0148-0227 ] ; 2003.
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Abstract
Conditional sequential Gaussian simulations (sGs) have been applied for the first time to the study of soil diffuse degassing from different volcanic and nonvolcanic systems. The application regards five data sets of soil CO2 fluxes measured with the accumulation chamber methodology at the volcanic areas of Solfatara of Pozzuoli (Italy), Vesuvio cone (Italy), Nisyros (Greece), and Horseshoe Lake (California) and at the nonvolcanic degassing area of Poggio dell'Olivo (Italy). The sGs algorithm was used to generate 100 realizations of CO2 flux for each area. Probabilistic summaries of these simulations, together with the information given by probability plots, were used (1) to draw maps of the probability that CO2 fluxes exceed thresholds specific for a background flux, i.e., to define the probable extension of the degassing structures, (2) to calculate the total CO2 output, and (3) to quantify the uncertainty of the estimation. The results show that the sGs is a suitable tool to model soil diffuse degassing, producing realistic images of the distribution of the CO2 fluxes that honor the histogram and variogram of the original data. Moreover, the relation between the sample design and the uncertainty of estimation was investigated leading to an empirical relation between uncertainty and the sampling density that can be useful for the planning of future CO2 flux surveys.
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" level="a">Application of stochastic simulation to CO<sub>2</sub> flux from soil: Mapping and quantification of gas release</title><author><name sortKey="Cardellini, C" sort="Cardellini, C" uniqKey="Cardellini C" first="C." last="Cardellini">C. Cardellini</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Dipartimento di Scienze della Terra, University di Perugia</s1><s2>Perugia</s2><s3>ITA</s3><sZ>1 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>Italie</country></affiliation></author><author><name sortKey="Chiodini, G" sort="Chiodini, G" uniqKey="Chiodini G" first="G." last="Chiodini">G. Chiodini</name><affiliation wicri:level="1"><inist:fA14 i1="02"><s1>Osservatorio Vesuviano, Istituto Nazionale di Geofisica e Vulcanologia</s1><s2>Naples</s2><s3>ITA</s3><sZ>2 aut.</sZ></inist:fA14><country>Italie</country></affiliation></author><author><name sortKey="Frondini, F" sort="Frondini, F" uniqKey="Frondini F" first="F." last="Frondini">F. Frondini</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Dipartimento di Scienze della Terra, University di Perugia</s1><s2>Perugia</s2><s3>ITA</s3><sZ>1 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>Italie</country></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">INIST</idno><idno type="inist">04-0022324</idno><date when="2003">2003</date><idno type="stanalyst">PASCAL 04-0022324 INIST</idno><idno type="RBID">Pascal:04-0022324</idno><idno type="wicri:Area/PascalFrancis/Corpus">000032</idno><idno type="wicri:Area/PascalFrancis/Curation">000008</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Application of stochastic simulation to CO<sub>2</sub> flux from soil: Mapping and quantification of gas release</title><author><name sortKey="Cardellini, C" sort="Cardellini, C" uniqKey="Cardellini C" first="C." last="Cardellini">C. Cardellini</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Dipartimento di Scienze della Terra, University di Perugia</s1><s2>Perugia</s2><s3>ITA</s3><sZ>1 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>Italie</country></affiliation></author><author><name sortKey="Chiodini, G" sort="Chiodini, G" uniqKey="Chiodini G" first="G." last="Chiodini">G. Chiodini</name><affiliation wicri:level="1"><inist:fA14 i1="02"><s1>Osservatorio Vesuviano, Istituto Nazionale di Geofisica e Vulcanologia</s1><s2>Naples</s2><s3>ITA</s3><sZ>2 aut.</sZ></inist:fA14><country>Italie</country></affiliation></author><author><name sortKey="Frondini, F" sort="Frondini, F" uniqKey="Frondini F" first="F." last="Frondini">F. Frondini</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Dipartimento di Scienze della Terra, University di Perugia</s1><s2>Perugia</s2><s3>ITA</s3><sZ>1 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>Italie</country></affiliation></author></analytic><series><title level="j" type="main">Journal of geophysical research</title><title level="j" type="abbreviated">J. geophys. res.</title><idno type="ISSN">0148-0227</idno><imprint><date when="2003">2003</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">Journal of geophysical research</title><title level="j" type="abbreviated">J. geophys. res.</title><idno type="ISSN">0148-0227</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>California</term><term>Greece</term><term>Italy</term><term>accumulation</term><term>atmospheric emission</term><term>carbon dioxide</term><term>degassing</term><term>density</term><term>digital simulation</term><term>experimental studies</term><term>histograms</term><term>maps</term><term>models</term><term>modern</term><term>probability</term><term>sampling</term><term>soils</term><term>stochastic models</term><term>variograms</term><term>volcanism</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Italie</term><term>Grèce</term><term>Californie</term><term>Etude expérimentale</term><term>Dioxyde carbone</term><term>Simulation numérique</term><term>Sol</term><term>Dégazage</term><term>Accumulation</term><term>Volcanisme</term><term>Probabilité</term><term>Carte</term><term>Modèle</term><term>Histogramme</term><term>Variogramme</term><term>Echantillonnage</term><term>Densité</term><term>Modèle stochastique</term><term>Emission atmosphérique</term><term>Actuel</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>Italie</term><term>Grèce</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Conditional sequential Gaussian simulations (sGs) have been applied for the first time to the study of soil diffuse degassing from different volcanic and nonvolcanic systems. The application regards five data sets of soil CO<sub>2</sub> fluxes measured with the accumulation chamber methodology at the volcanic areas of Solfatara of Pozzuoli (Italy), Vesuvio cone (Italy), Nisyros (Greece), and Horseshoe Lake (California) and at the nonvolcanic degassing area of Poggio dell'Olivo (Italy). The sGs algorithm was used to generate 100 realizations of CO<sub>2</sub> flux for each area. Probabilistic summaries of these simulations, together with the information given by probability plots, were used (1) to draw maps of the probability that CO<sub>2</sub> fluxes exceed thresholds specific for a background flux, i.e., to define the probable extension of the degassing structures, (2) to calculate the total CO<sub>2</sub> output, and (3) to quantify the uncertainty of the estimation. The results show that the sGs is a suitable tool to model soil diffuse degassing, producing realistic images of the distribution of the CO<sub>2</sub> fluxes that honor the histogram and variogram of the original data. Moreover, the relation between the sample design and the uncertainty of estimation was investigated leading to an empirical relation between uncertainty and the sampling density that can be useful for the planning of future CO<sub>2</sub> flux surveys.</div></front></TEI><inist><standard h6="B"><pA><fA01 i1="01" i2="1"><s0>0148-0227</s0></fA01><fA03 i2="1"><s0>J. geophys. res.</s0></fA03><fA05><s2>108</s2></fA05><fA06><s2>B9</s2></fA06><fA08 i1="01" i2="1" l="ENG"><s1>Application of stochastic simulation to CO<sub>2</sub> flux from soil: Mapping and quantification of gas release</s1></fA08><fA11 i1="01" i2="1"><s1>CARDELLINI (C.)</s1></fA11><fA11 i1="02" i2="1"><s1>CHIODINI (G.)</s1></fA11><fA11 i1="03" i2="1"><s1>FRONDINI (F.)</s1></fA11><fA14 i1="01"><s1>Dipartimento di Scienze della Terra, University di Perugia</s1><s2>Perugia</s2><s3>ITA</s3><sZ>1 aut.</sZ><sZ>3 aut.</sZ></fA14><fA14 i1="02"><s1>Osservatorio Vesuviano, Istituto Nazionale di Geofisica e Vulcanologia</s1><s2>Naples</s2><s3>ITA</s3><sZ>2 aut.</sZ></fA14><fA20><s2>ECV3.1-ECV3.13</s2><s7>4</s7></fA20><fA21><s1>2003</s1></fA21><fA23 i1="01"><s0>ENG</s0></fA23><fA43 i1="01"><s1>INIST</s1><s2>3144</s2><s5>354000118717390140</s5></fA43><fA44><s0>0000</s0><s1>© 2004 INIST-CNRS. All rights reserved.</s1></fA44><fA45><s0>36 ref.</s0></fA45><fA47 i1="01" i2="1"><s0>04-0022324</s0></fA47><fA60><s1>P</s1></fA60><fA61><s0>A</s0></fA61><fA64 i1="01" i2="1"><s0>Journal of geophysical research</s0></fA64><fA66 i1="01"><s0>USA</s0></fA66><fC01 i1="01" l="ENG"><s0>Conditional sequential Gaussian simulations (sGs) have been applied for the first time to the study of soil diffuse degassing from different volcanic and nonvolcanic systems. The application regards five data sets of soil CO<sub>2</sub> fluxes measured with the accumulation chamber methodology at the volcanic areas of Solfatara of Pozzuoli (Italy), Vesuvio cone (Italy), Nisyros (Greece), and Horseshoe Lake (California) and at the nonvolcanic degassing area of Poggio dell'Olivo (Italy). The sGs algorithm was used to generate 100 realizations of CO<sub>2</sub> flux for each area. Probabilistic summaries of these simulations, together with the information given by probability plots, were used (1) to draw maps of the probability that CO<sub>2</sub> fluxes exceed thresholds specific for a background flux, i.e., to define the probable extension of the degassing structures, (2) to calculate the total CO<sub>2</sub> output, and (3) to quantify the uncertainty of the estimation. The results show that the sGs is a suitable tool to model soil diffuse degassing, producing realistic images of the distribution of the CO<sub>2</sub> fluxes that honor the histogram and variogram of the original data. 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