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Title: Bayesian hierarchical models for soil CO{sub 2} flux and leak detection at geologic sequestration sites

Abstract

Proper characterizations of background soil CO{sub 2} respiration rates are critical for interpreting CO{sub 2} leakage monitoring results at geologic sequestration sites. In this paper, a method is developed for determining temperature-dependent critical values of soil CO{sub 2} flux for preliminary leak detection inference. The method is illustrated using surface CO{sub 2} flux measurements obtained from the AmeriFlux network fit with alternative models for the soil CO{sub 2} flux versus soil temperature relationship. The models are fit first to determine pooled parameter estimates across the sites, then using a Bayesian hierarchical method to obtain both global and site-specific parameter estimates. Model comparisons are made using the deviance information criterion (DIC), which considers both goodness of fit and model complexity. The hierarchical models consistently outperform the corresponding pooled models, demonstrating the need for site-specific data and estimates when determining relationships for background soil respiration. A hierarchical model that relates the square root of the CO{sub 2} flux to a quadratic function of soil temperature is found to provide the best fit for the AmeriFlux sites among the models tested. This model also yields effective prediction intervals, consistent with the upper envelope of the flux data across the modeled sites and temperaturemore » ranges. Calculation of upper prediction intervals using the proposed method can provide a basis for setting critical values in CO{sub 2} leak detection monitoring at sequestration sites.« less

Authors:
; ; ; ; ;
Publication Date:
Research Org.:
National Energy Technology Lab. (NETL), Pittsburgh, PA, and Morgantown, WV (United States). In-house Research
Sponsoring Org.:
USDOE Office of Fossil Energy (FE)
Contributing Org.:
National Energy Technology Laboratory Carnegie Mellon University
OSTI Identifier:
1081556
Report Number(s):
TPR-3250
Journal ID: ISSN 1866--6280
DOE Contract Number:  
DE-FE0004000
Resource Type:
Journal Article
Journal Name:
Environmental Earth Sciences
Additional Journal Information:
Journal Volume: 64; Journal Issue: 3; Journal ID: ISSN 1866--6280
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 58 GEOSCIENCES; Bayesian hierarchical model; Geologic carbon sequestration; Soil respiration; CO{sub 2} flux; CO{sub 2} leakage; Statistical leak detection

Citation Formats

Yang, Ya-Mei, Small, Mitchell J., Junker, Brian, Bromhal, Grant S., Strazisar, Brian, and Wells, Arthur. Bayesian hierarchical models for soil CO{sub 2} flux and leak detection at geologic sequestration sites. United States: N. p., 2011. Web. doi:10.1007/s12665-011-0903-5.
Yang, Ya-Mei, Small, Mitchell J., Junker, Brian, Bromhal, Grant S., Strazisar, Brian, & Wells, Arthur. Bayesian hierarchical models for soil CO{sub 2} flux and leak detection at geologic sequestration sites. United States. doi:10.1007/s12665-011-0903-5.
Yang, Ya-Mei, Small, Mitchell J., Junker, Brian, Bromhal, Grant S., Strazisar, Brian, and Wells, Arthur. Sat . "Bayesian hierarchical models for soil CO{sub 2} flux and leak detection at geologic sequestration sites". United States. doi:10.1007/s12665-011-0903-5.
@article{osti_1081556,
title = {Bayesian hierarchical models for soil CO{sub 2} flux and leak detection at geologic sequestration sites},
author = {Yang, Ya-Mei and Small, Mitchell J. and Junker, Brian and Bromhal, Grant S. and Strazisar, Brian and Wells, Arthur},
abstractNote = {Proper characterizations of background soil CO{sub 2} respiration rates are critical for interpreting CO{sub 2} leakage monitoring results at geologic sequestration sites. In this paper, a method is developed for determining temperature-dependent critical values of soil CO{sub 2} flux for preliminary leak detection inference. The method is illustrated using surface CO{sub 2} flux measurements obtained from the AmeriFlux network fit with alternative models for the soil CO{sub 2} flux versus soil temperature relationship. The models are fit first to determine pooled parameter estimates across the sites, then using a Bayesian hierarchical method to obtain both global and site-specific parameter estimates. Model comparisons are made using the deviance information criterion (DIC), which considers both goodness of fit and model complexity. The hierarchical models consistently outperform the corresponding pooled models, demonstrating the need for site-specific data and estimates when determining relationships for background soil respiration. A hierarchical model that relates the square root of the CO{sub 2} flux to a quadratic function of soil temperature is found to provide the best fit for the AmeriFlux sites among the models tested. This model also yields effective prediction intervals, consistent with the upper envelope of the flux data across the modeled sites and temperature ranges. Calculation of upper prediction intervals using the proposed method can provide a basis for setting critical values in CO{sub 2} leak detection monitoring at sequestration sites.},
doi = {10.1007/s12665-011-0903-5},
journal = {Environmental Earth Sciences},
issn = {1866--6280},
number = 3,
volume = 64,
place = {United States},
year = {2011},
month = {10}
}