WCA gas trap results and ebullition modeling: testing an ebullition model shows the importance of pore structure William Wright¹, Jorge Ramirez², Xavier Comas¹ ¹Department of Geosciences, Florida Atlantic University. Boca Raton, FL ²University of Bern, Institute of Geography. Bern, Switzerland April 17 th 2017
1. Introduction Both deep and shallow models show similar processes: CH₄ produced is either : 1) released through ebullition 2) lost through consumption 3) lost via diffusion 4) stored in-situ
1. Introduction Ebullition research looking for controls: Environmental factors as control: -change in atmp (increase and/or decrease) [Comas and Wright, 2012, 2014; Chen and Slater, 2015] -gas reaching a threshold volume [Baird et al, 2004; Yu et al, 2014] -overpressuring of gas pockets [Glaser et al, 2004] Peat structure as a control: -effective porosity (tortuosity) [Chen and Slater, 2015] -presence of gas confining layers [Comas et al, 2011] -lower porosity masks diurnal production [Ramirez et al, 2015a] -larger pore spaces= larger bubbles [Ramirez et al, 2016] From Wright GEER 2017 poster #009 From Chen and Slater, 2015
2. Methods Peat core in profile Model of Ebullition and Gas storage (MEGA) Modeled peat Ebullition Peat is represented by a set of shelves Bubbles behave like inverted sand piles Gas movement = avalanches Production gas water peat after Ramirez et al (2015)
2. Methods Peat core in profile Model of Ebullition and Gas storage (MEGA) Modeled peat Ebullition Peat is represented by a set of shelves Bubbles behave like inverted sand piles Gas movement = avalanches Production gas water peat after Ramirez et al (2015)
2. Methods Peat core in profile Model of Ebullition and Gas storage (MEGA) Modeled peat Ebullition Peat is represented by a set of shelves Bubbles behave like inverted sand piles Gas movement = avalanches Production gas water peat after Ramirez et al (2015)
2. Study Sites Set up model parameters following measurements at 2 field sites (green circles): o o Peat thickness Porosity Also, took weekly traditional measurements: o o o gas flux Gas content (GPR) CH4 production (from GPR + flux) Modified from Wright and Comas, 2016
3. Methods GPR Theory : EM pulses sent from transmitter to receiver and bouncing off interfaces, finding travel times yields EM wave velocity EM wave travels fastest through air, slowest in water By assuming fully saturated conditions changes in travel time correspond with changes in gas content. Modified from Wright and Comas, 2016
3. Methods Estimating gas content from GPR velocity o Complex Refractive Index Model (CRIM): V c r(b) * Assuming low-loss medium, EM Velocity (v) is related to bulk dielectric permittivity ( r(b )) a r( b) a 1 r n w r s r a a n a o % gas content = porosity (n) volumetric water content (Ѳ) o Variables accounted for: permittivity of water (ε rw ) as a function of Temperature a is rotational component of dielectric permittivity YIELDS GAS CONTENT, IN % BY VOLUME
3. Methods Gas traps and Time-Lapse cameras *flux rates at 30 min. intervals from Wright, Ramirez, and Comas, in prep.
3. Methods Mass Balance approach: Total Production (P) = Sum of: (E) ebullition Wright, W., and Comas, X. "Estimating methane gas production in peat soils of the Florida Everglades using hydrogeophysical methods." Journal of Geophysical Research: Biogeosciences 121.4 (2016): 1190-1202. (C) consumption (D) diffusion (G₂-G₁) Δ gas content
3. Methods Field Sites Ebullition (weekly) Δ Gas Content Physical Properties Peat thickness, porosity Production Model MEGA Model Production rate Ebullition (30 min.) Ebullition (30 min) Gas Storage Wright, Ramirez and Comas, Methane ebullition from subtropical peat: testing an ebullition model reveals the importance of pore structure (in prep.)
4. Results Ebullition Δ storage PRODUCTION Site 1 Avg = 0.31 g CH₄ m ² d ¹ (488 ml CH₄ m ² d ¹) Modified from Wright and Comas, 2016 Input to MEGA Site 2 Avg = 0.18 g CH₄ m ² d ¹ (280 ml CH₄ m ² d ¹)
4. Results a F1 F2 F3 F4 F5 gas cluster (ml) 3-250 250-1000 1000-3000 3000-8722 Fig. 7: site2 (a) gas content and (b) ebullition from structurally open (funnel 2) and closed (funnel 4) peats. b ebullition (ml m -2 d -1 ) Funnel 2 Funnel 4 1 from Wright, Ramirez, and Comas, in prep. time (days)
ebullition (ml m -2 d -1 ) b 4. Results a c 30 minute flux values ebullition (ml m -2 d -1 ) d b c d from Wright, Ramirez, and Comas, in prep.
Normalized frequency 4. Results normalized frequency c d Histograms of ebullition events: observed vs. modelled plus or minus one standard deviation of production. Normalized frequency observed Production modeled rate high +1 σ mean low -1 σ ebullition (ml m -2 d -1 ) from Wright, Ramirez, and Comas, in prep.
4. Results a Site 1 b Site 2 T1 T2 T3 T4 T5 T1 T2 T3 T4 T5 Funnels above large gas clusters (i.e. high tortuosity) match observed ebullition more closely. gas cluster (ml) 1-250 250-500 500-1000 1000-1500 1500-2264 water peat Normalized frequency Modelled gas content ranges between 5-25% Gas content Clusters of Shelves are random. Porosity is held at a constant over length of column. from Wright, Ramirez, and Comas, in prep.
4. Results Site 1 Modelled Observed Peat surface Normalized frequency Column sample extracted from field, site 1. gas content measured with GPR (1 cm resolution) Porosity measured Areas of Enhanced accumulation? Driven by porosity? from Wright, Ramirez, and Comas, in prep.
4. Results Observed Peat surface Normalized frequency Site 1 Column sample extracted from field, site 1. gas content measured with GPR (1 cm resolution) Porosity measured From: Slater, Lee, Xavier Comas, Dimitrios Ntarlagiannis, and Maitry Roy Moulik. "Resistivity based monitoring of biogenic gases in peat soils." Water resources research 43, no. 10 (2007). Similar increases of gas content at shallow depths. Driven by porosity?
5. Discussion / Conclusions Model replicated observed ebullition patterns well using only structure variables - NO environmental variables considered Ebullition patterns may be controlled by physical properties of the peat matrix Modelled gas storage clusters seem to replicate gas contents observed in column sample - Higher production rates within the peat column? - Are these driven by zones of increased porosity?
Thank you Much thanks to our fellow bubble counters: Nathan Sharp, Tommy Shahan, Greg Mount, Matt McClellan, Matt Sirianni, Mario Job And to our funding agencies: NOAA (GC11-337) U.S. Geological Survey (under the Greater Everglades Priority Ecosystems Science)