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COMPARISON OF NATURAL SOURCE DEPLETION (NSZD) CHARACTERIZATION METHODS Mark Malander and Harley Hopkins (ExxonMobil) Andy Pennington, Jonathon Smith, and.

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Presentation on theme: "COMPARISON OF NATURAL SOURCE DEPLETION (NSZD) CHARACTERIZATION METHODS Mark Malander and Harley Hopkins (ExxonMobil) Andy Pennington, Jonathon Smith, and."— Presentation transcript:

1 COMPARISON OF NATURAL SOURCE DEPLETION (NSZD) CHARACTERIZATION METHODS Mark Malander and Harley Hopkins (ExxonMobil) Andy Pennington, Jonathon Smith, and Steven Gaito (Arcadis) November 2015

2 © Arcadis 2015 Agenda Study Objectives Findings from each Method Comparison of NSZD Rates Temperature Observations Summary

3 © Arcadis 2015 Biodegradation Dissolved Plume Groundwater Flow Oxygen Transport Volatilization of CH 4 and HCs Methanogenesis Mobile or Residual LNAPL NSZD Processes in the Vadose Zone Mass loss occurs from: Volatilization: Observed from soil gas concentration data Biodegradation: Inferred from oxygen, methane, and hydrocarbon soil gas depth profiles or CO 2 flux through groundsurface

4 © Arcadis 2015 NSZD Methodology Comparison: Study Objectives Temperature Datalogger LI-COR Chamber and Analyzer CO 2 Trap Side-by-side comparison of NSZD quantification methods Gradient Method Dynamic Closed Chamber (DCC) CO 2 Traps Collect duplicate CO2 trap data to evaluate repeatability Collect ancillary data: Soil moisture Rainfall from airport Barometric pressure Temperature profiles

5 © Arcadis 2015 Method Comparison Study Locations NSZD-5/MW-72 Gradient Method CO 2 Traps DCC Temperature Profile NSZD-6/MW-10 Gradient Method CO 2 Traps DCC Temperature Profile NSZD-3/MW-43 Gradient Method CO 2 Traps DCC Temperature Profile Background/MW-223 CO 2 Traps DCC Temperature Profile NSZD-2/MW-36 Gradient Method CO 2 Traps Temperature Profile 5 6 2 3

6 Gradient Method

7 © Arcadis 2015 Gradient Method NSZD-2 Soil Gas Profile Nitrogen displacement is indicative of advective flow

8 © Arcadis 2015 Vapor-Phase Porous Media Diffusion Coefficient Location ID D eff, O 2 (cm 2 /sec)Ratio March 2014Aug 20122014:2012 NSZD-20.01240.00711.75 NSZD-30.00840.02060.41 NSZD-50.00600.00850.70 NSZD-60.00420.00172.48 Diffusion coefficient is dependent on pore fluid saturation

9 CO 2 Flux Methods

10 © Arcadis 2015 Dynamic Closed Chamber (DCC) High-quality data, but demanding setup

11 © Arcadis 2015 CO 2 Flux Data (DCC): NSZD-6 Strong correlation between atmospheric temperature and flux

12 © Arcadis 2015 CO 2 Flux Data (DCC): NSZD-5 Effects of soil moisture/rainfall are significant 1-2” Rain Event

13 © Arcadis 2015 CO2 Traps

14 © Arcadis 2015 CO 2 Trap Results Duplicate Comparison

15 © Arcadis 2015 CO 2 Trap Results Modern Carbon Flux NSZD-3/MW-43 5.2 µM/m 2 /s Highest flux of modern CO 2 NSZD-2 0.30 µM/m 2 /s Lowest flux of modern CO 2 NSZD-6 1.07 µM/m 2 /s NSZD-5 2.32 µM/m 2 /s

16 © Arcadis 2015 NSZD-2 (gallons/acre/year) Gradient: 1,800 CO 2 Trap: 200 CO 2 DCC: NA NSZD-5 (gallons/acre/year) Gradient: 900 CO 2 Trap: 1,040 CO 2 DCC: 940* NSZD-6 (gallons/acre/year) Gradient: 500 CO 2 Trap: 160 CO 2 DCC: 160* NSZD-3 (gallons/acre/year) Gradient: 2,000 CO 2 Trap: 1,100 CO 2 DCC: NA Background (gallons/acre/year) Gradient: NA CO 2 Trap: 130 CO 2 DCC: 0 Site Wide Averages (gallons/acre/year) Gradient: 1,300 CO 2 Trap: 650 CO 2 DCC: 550 *DCC results are corrected using data from background location Method Comparison Site Wide Average

17 © Arcadis 2015 Gradient Method NSZD-2 Soil Gas Profile NSZD-2 (gallons/acre/year) Gradient: 1,800 CO 2 Trap: 200 CO 2 DCC: NA

18 Temperature Observations

19 © Arcadis 2015 Temperature Observations Intrinsically safe temperature dataloggers set down-well at 2.5-foot to 3-foot intervals Temperature data logged every 15 minutes Data logging resolved downward propagation of temperature variation at surface

20 © Arcadis 2015 Temperature Observations

21 © Arcadis 2015 Temperature Profile

22 © Arcadis 2015 Method Comparison Summary Notes: Gradient method includes diffusion coefficient field measurement Capital costs assume purchase of LI-COR DCC Capital Costs Field Deployment Costs Data Reliability Qualitative Evidence Data Density Ease of Use Best Application Gradient Method BCBABC Sites with existing soil gas sampling infrastructure CO 2 TrapsABACCA Well-understood sites with relatively uniform subsurface and climate conditions LI-COR DCC CABBAB Initial screening of locations; Detailed rapid measurements; Investigating complex influences

23 © Arcadis 2015 QUESTIONS AND COMMENTS Thank you!


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