Abstract
Accurately locating and quantifying carbon dioxide (CO2) leakage to the atmosphere is important for diffuse degassing studies in volcanic / geothermal areas and for safety monitoring and/or carbon credit auditing of Carbon Capture and Storage (CCS) sites. This is typically conducted by measuring CO2 flux at numerous points over a large area and applying statistics or geostatistical interpolation. Accuracy of the results will depend on many factors related to survey/data-processing choices and site characteristics, and thus uncertainties can be difficult to quantify. To address this issue, we have developed a Monte Carlo-based program (MC-Flux) that repeatedly subsamples a high-resolution synthetic or real dataset using a choice of different sampling strategies (one random and four grid types) at multiple user-defined sample densities. The program keeps track of the anomalies found and estimates total flux using two statistical and two geostatistical approaches from the literature. This paper describes the use of MC-Flux to assess the potential impact of various sampling and interpretation decisions on the accuracy of the final results. Simulations show that an offset grid sample distribution yields the best results, however relatively dense sampling is required to obtain a high probability of an accurate flux estimate. For the test dataset used, ordinary kriging interpolation produces a range of flux estimates that are centered on the true value while sequential Gaussian simulation tends to slightly overestimate values at intermediate sample spacings and is sensitive to input parameters. These results point to the need for developing new approaches that decrease uncertainty, such as integration with high-resolution co-kriging datasets that complement the more accurate point flux measurements.
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References
Annunziatellis A, Beaubien SE, Bigi S, Ciotoli G, Coltella M, Lombardi S (2008) Gas migration along fault systems and through the vadose zone in the Latera caldera (central Italy): Implications for CO2 geological storage. Int J Greenh Gas Control 2(3):353–372. https://doi.org/10.1016/j.ijggc.2008.02.003
Bain WG, Hutyra L, Patterson DC, Bright AV, Daube BC, Munger JW, Wofsy SC (2005) Wind-induced error in the measurement of soil respiration using closed dynamic chambers. Agric For Meteorol 131(3):225–232. https://doi.org/10.1016/j.agrformet.2005.06.004
Barkwith A, Beaubien SE, Barlow T, Kirk K, Lister TR, Tartarello MC, Taylor-Curran H (2020) Using near-surface atmospheric measurements as a proxy for quantifying field-scale soil gas flux. Geosci Instrum Method Data Syst 9(2):483–490. https://doi.org/10.5194/gi-9-483-2020
Beaubien SE, Ciotoli G, Coombs P, Dictor MC, Krüger M, Lombardi S, Pearce JM, West JM (2008) The impact of a naturally-occurring CO2 gas vent on the shallow ecosystem and soil chemistry of a Mediterranean pasture (Latera, Italy). Int J Greenh Gas Control 2(3):373–387. https://doi.org/10.1016/j.ijggc.2008.03.005
Beaubien SE, Ruggiero L, Annunziatellis A, Bigi S, Ciotoli G, Deiana P, Graziani S, Lombardi S, Tartarello MC (2015) The importance of baseline surveys of near-surface gas geochemistry for CCS monitoring, as shown from onshore case studies in Northern and Southern Europe. Oil Gas Sci Technol Rev IFP Energies Nouvelles 70(4):615–633. https://doi.org/10.2516/ogst/2014009
Beaubien SE, Bigi S (2021) Example data and configuration / input files for conducting probability and accuracy simulations of CO2 flux surveys using the MC-Flux program. https://doi.org/10.5281/zenodo.4573725
Beaubien SE, Bigi S (2021) MC-Flux (Version 1.0): a Monte Carlo-based program to determine how sample spacing, sample strategy, and calculation approaches impact the probability of finding CO2 leakage anomalies and the accuracy of total CO2 flux estimates. https://doi.org/10.5281/zenodo.4573575
Beaubien SE, Annunziatellis A, Ciotoli G, Lombardi S (2009) Near surface gas simulator (NSGS): a visual basic program to improve the design of near-surface gas geochemistry surveys above CO2 geological storage sites, 6th European Geosciences Union General Assembly 2009, Vienna, Austria. https://meetingorganizer.copernicus.org/EGU2009/EGU2009-12489.pdf
Beaubien SE, Jones DG, Goldberg T, Barkwith KAP, Bigi S, Graziani S, Kirk K, Mattei E, Mulder B, Pettinelli E, Ruggiero L, Tartarello M-C (2018) Innovative tools for rapidly mapping / quantifying CO2 leakage and determining its origin. In: 14th Greenhouse gas control technologies conference (GHGT-14) Melbourne, Australia. https://doi.org/10.2139/ssrn.3366264
Beaubien SE (2015) The mapping and quantification of CO2 leakage and its potential impact on groundwater quality. Ph.D. Thesis, Università Ca' Foscari, Venezia, Italia, 163 pp. http://hdl.handle.net/10579/6509
Bini G, Chiodini G, Lucchetti C, Moschini P, Caliro S, Mollo S, Selva J, Tuccimei P, Galli G, Bachmann O (2020) Deep versus shallow sources of CO2 and Rn from a multi-parametric approach: the case of the Nisyros caldera (Aegean Arc, Greece). Sci Rep 10(1):13782. https://doi.org/10.1038/s41598-020-70114-x
Bond-Lamberty B, Pennington SC, Jian J, Megonigal JP, Sengupta A, Ward N (2019) Soil respiration variability and correlation across a wide range of temporal scales. J Geophys Res Biogeosci 124(11):3672–3683. https://doi.org/10.1029/2019jg005265
Caers J (2000) Direct sequential indicator simulation. In: Kleingeld W, Krige D (eds) 6th International Geostatistics Congress, South Africa, Cape Town, South Africa, pp. 39–48. https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.217.7285&rep=rep1&type=pdf
Carapezza ML, Granieri D (2004) CO2 soil flux at Vulcano (Italy): comparison between active and passive methods. Appl Geochem 19:73–88. https://doi.org/10.1016/S0883-2927(03)00111-2
Cardellini C, Chiodini G, Frondini F (2003) Application of stochastic simulation to CO2 flux from soil: mapping and quantification of gas release. J Geophys Res Solid Earth 108(B9):2425. https://doi.org/10.1029/2002JB002165
Chiodini G, Cioni R, Guidi M, Marini L, Raco B (1998) Soil CO2 flux measurements in volcanic and geothermal areas. Appl Geochem 13:543–552. https://doi.org/10.1016/S0883-2927(97)00076-0
Chiodini G, Baldini A, Barberi F, Carapezza ML, Cardellini C, Frondini F, Granieri D, Ranaldi M (2007) Carbon dioxide degassing at Latera caldera (Italy): evidence of geothermal reservoir and evaluation of its potential energy. J Geophys Res. https://doi.org/10.1029/2006JB004896
Chiodini G, Cardellini C, Caliro S, Avino R, Donnini M, Granieri D, Morgantini N, Sorrenti D, Frondini F (2020) The hydrothermal system of Bagni San Filippo (Italy): fluids circulation and CO2 degassing. Italian J Geosci 139(3):383–397. https://doi.org/10.3301/IJG.2020.12
Davidson JR (1995) Monte Carlo tests of the Elipgrid-PC algorithm. ORNL/TM-12899. Oak Ridge National Laboratory, Oak Ridge, Tennessee. https://doi.org/10.2172/52637
Deutsch CV, Journel AG (1997) GSLIB: geostatistical software library and users guide. Oxford University Press, 2nd Edition, New York. https://doi.org/10.1080/00401706.1995.10485913
Elío J, Ortega MF, Chacón E, Mazadiego LF, Grandia F (2012) Sampling strategies using the “accumulation chamber” for monitoring geological storage of CO2. Int J Greenh Gas Control 9:303–311. https://doi.org/10.1016/j.ijggc.2012.04.006
Elío J, Ortega MF, Nisi B, Mazadiego LF, Vaselli O, Caballero J, Chacón E (2016) A multi-statistical approach for estimating the total output of CO2 from diffuse soil degassing by the accumulation chamber method. Int J Greenh Gas Control 47:351–363. https://doi.org/10.1016/j.ijggc.2016.02.012
Emery X (2004) Testing the correctness of the sequential algorithm for simulating Gaussian random fields. Stoch Environ Res Risk Assess 18(6):401–413. https://doi.org/10.1007/s00477-004-0211-7
Gilardi N, Bengio S, Kanevski M (2002) Conditional Gaussian mixture models for environmental risk mapping. In: Proceedings of the 12th IEEE workshop on neural networks for signal processing pp 777–786. Doi: https://doi.org/10.1109/NNSP.2002.1030100
Gilbert RO (1987) Statistical methods for environmental pollution monitoring. Van Nostrand Reinhold Company Inc., New York (ISBN: 978-0-471-28878-7)
Hood GM (2010) PopTools version 3.2.5. http://www.bioquest.org/esteem/esteem_details.php?product_id=248
Jones DG, Beaubien SE, Lister TR, Graziani S, Finoia MG, Barkwith AKAP, Ruggiero L, Ciotoli G, Bigi S, Lombardi S (2017) Continuous monitoring of natural CO2 emissions near Rome-lessons for low-level CO2 leakage detection. Energy Procedia 114:3824–3831. https://doi.org/10.1016/j.egypro.2017.03.1514
Kutzbach L, Schneider J, Sachs T, Giebels M, Nykanen H, Shurpali NJ, Martikainen PJ, Alm J, Wilmking M (2007) CO2 flux determination by closed-chamber methods can be seriously biased by inappropriate application of linear regression. Biogeosciences 4(6):1005–1025. https://doi.org/10.5194/bg-4-1005-2007
Leon E, Vargas R, Bullock S, Lopez E, Panosso AR, La Scala N (2014) Hot spots, hot moments, and spatio-temporal controls on soil CO2 efflux in a water-limited ecosystem. Soil Biol Biochem 77:12–21. https://doi.org/10.1016/j.soilbio.2014.05.029
Lewicki JL, Bergfeld D, Cardellini C, Chiodini G, Granieri D, Varley N, Werner C (2005) Comparative soil CO2 flux measurements and geostatistical estimation methods on Masaya volcano, Nicaragua. Bull Volcanol 68:76–90. https://doi.org/10.1007/s00445-005-0423-9
Lewicki JL, Evans WC, Montgomery-Brown EK, Mangan MT, King JC, Hunt AG (2019) Rate of magma supply beneath Mammoth Mountain, California, based on helium isotopes and CO2 emissions. Geophys Res Lett 46(9):4636–4644. https://doi.org/10.1029/2019GL082487
Matzke BD, Wilson JE, Newburn LL, Dowson ST, Hathaway JE, Sego LH, Bramer LM, Pulsipher BA (2014) Visual Sample Plan: version 7.0 user’s guide. Pacific Northwest National Laboratory for the U.S. Department of Energy, Richland. https://doi.org/10.2172/1124046
Ogretim E, Crandall D, Gray DD, Bromhal GS (2013) Effects of atmospheric dynamics on CO2 seepage at Mammoth Mountain, California USA. J Comput Multiph Flows 5(4):283–294. https://doi.org/10.1260/1757-482x.5.4.283
Oldenburg CM, Lewicki JL, Hepple RP, 2003. Near-surface monitoring strategies for carbon dioxide storage verification, Lawrence Berkeley National Laboratory. Report LBNL-54089. https://escholarship.org/uc/item/1cg241jb
Oliveira S, Viveiros F, Silva C, Pacheco JE (2018) Automatic filtering of soil CO2 flux data; different statistical approaches applied to long time series. Front in Earth Sci. https://doi.org/10.3389/feart.2018.00208
Paravarzar S, Emery X, Madani N (2015) Comparing sequential Gaussian and turning bands algorithms for cosimulating grades in multi-element deposits. Comptes Rendus Geosci 347(2):84–93. https://doi.org/10.1016/j.crte.2015.05.008
Pettinelli E, Beaubien SE, Zaja A, Menghini A, Praticelli N, Mattei E, Di Matteo A, Annunziatellis A, Ciotoli G, Lombardi S (2010) Characterization of a CO2 gas vent using various geophysical and geochemical methods. Geophysics 75(3):B137–B146. https://doi.org/10.1190/1.3420735
Riveros-Iregui DA, McGlynn BL (2009) Landscape structure control on soil CO2 efflux variability in complex terrain: scaling from point observations to watershed scale fluxes. J Geophys Res Biogeosciences. https://doi.org/10.1029/2008jg000885
Sainju UM, Jabro JD, Stevens WB (2008) Soil carbon dioxide emission and carbon content as affected by irrigation, tillage, cropping system, and nitrogen fertilization. J Environ Qual 37(1):98–106. https://doi.org/10.2134/jeq2006.0392
Schroder IF, Wilson P, Feitz AF, Ennis-King J (2017) Evaluating the performance of soil flux surveys and inversion methods for quantification of CO2 leakage. Energy Procedia 114:3679–3694. https://doi.org/10.1016/j.egypro.2017.03.1499
Singer DA (1975) Relative efficiencies of square and triangular grids in the search for elliptically shaped resource targets. J Res U.S.Geol Surv 3(2):163–167
Singer DA (1972) ELIPGRID, a FORTRAN IV program for calculating the probability of success in locating elliptical targets with square, rectangular, and hexagonal grids. Geocom Programs, vol 4: pp 1–16. https://www.researchgate.net/publication/236410051
Viveiros F, Chiodini G, Cardellini C, Caliro S, Zanon V, Silva C, Rizzo AL, Hipólito A, Moreno L (2020) Deep CO2 emitted at Furnas do Enxofre geothermal area (Terceira Island, Azores archipelago). An approach for determining CO2 sources and total emissions using carbon isotopic data. J Volcanol Geotherm Res 401:106968. https://doi.org/10.1016/j.jvolgeores.2020.106968
Wong CLY (2018) Analysis of the number of flux chamber samples and study area size on the accuracy of emission rate measurements. J Air Waste Manag Assoc 68(10):1103–1117. https://doi.org/10.1080/10962247.2018.1469555
Acknowledgements
The assistance of Pietro Sacco and Davide de Angelis for the collection of the Latera field data is gratefully acknowledged. We also thank three anonymous reviewers for their useful comments and observations that helped us improve the original manuscript.
Funding
The research leading to these results received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 653718.\
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Conceptualization [SEB], Methodology, Software, Visualization and Writing – Original Draft [SEB]; Formal Analysis [SEB, GC, MGF]; Validation [GC, MGF]; Writing – Review and Editing [GC, MGF, SB]; Supervision [SL]; Project administration and Funding acquisition [SB, SL].
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Datasets and configuration files used to conduct the reported simulations are available from the Zenodo open-source online repository at https://doi.org/10.5281/zenodo.4573725 (Beaubien and Bigi 2021b).
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The MC-Flux (V1.0) installation package and user’s manual are available from the Zenodo open-source online repository at https://doi.org/10.5281/zenodo.4573575 (Beaubien and Bigi 2021a).
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Beaubien, S.E., Ciotoli, G., Finoia, M.G. et al. Monte Carlo simulations to assess the uncertainty of locating and quantifying CO2 leakage flux from deep geological or anthropogenic sources. Stoch Environ Res Risk Assess 36, 609–627 (2022). https://doi.org/10.1007/s00477-021-02123-9
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DOI: https://doi.org/10.1007/s00477-021-02123-9