A Comparison of BioVapor and Johnson and Ettinger Model Predictions to Field Data for Multiple Sites

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1 Compare to J&E? O 2 for Mitigation? A Comparison of BioVapor and Johnson and Ettinger Model Predictions to Field Data for Multiple Sites AEHS 25th Annual International Conference on Soil, Water, Energy and Air March 23-26, 2015, San Diego, California Dr. Ian Hers and Dr. Parisa Jourabchi

2 Outline Rationale and overview of models BioVapor model description Key inputs for BioVapor and sensitivity analysis Natural and engineered oxygen flux to below building and use of BioVapor model for mitigation design Comparison of BioVapor model predictions to site data Example where numerical model is useful Some slides on BioVapor were developed for ITRC Petroleum Vapor Intrusion internet-based training For additional info see A Comprehensive Evaluation of the BioVapor Model for Prediction of Petroleum Vapor Intrusion, AWMA Vapor Intrusion, Remediation and Site Closure Conference, Sept , 2014, Cherry Hill, NJ Ian Hers and Parisa Jourabchi 2

3 Rationale for Biodegradation Modeling Starting point science indicates typically rapid vadose zone attenuation of petroleum hydrocarbon vapors over short distances through aerobic biodegradation 1 Why use a model to evaluate petroleum vapor intrusion? Evaluate health risk when fail a screening process or backcalculate clean-up goals Better understand vapor fate and transport processes and identify key parameters Prioritize and focus investigations (e.g., buildings to test) Support remedial design how much oxygen do I need? KEY more Use efficient of biodegradation site investigations models can lead to less POINT: conservative and more efficient assessments 1 USEPA 2011 Comparison of Chlorinated Vapor Intrusion and Petroleum Vapor Intrusion

4 Analytical Biodegradation Models Steady state models (modified Johnson and Ettinger model) Dominant-layer and oxygen-limited biodegradation models (Johnson et al. 1999) incorporated in RISC5 Oxygen-limited first-order biodegradation rate BIOVAPOR (DeVaull, 2007) Transient models (modified Jury model) Diffusion, first-order biodegradation, sorption, no building foundation EMSOFT (Jury) Modifications include soil gas advection, building foundation and source depletion (e.g., Mills 2007; Turczynowisz & Robinson, 2007) not commercially available

5 Numerical Biodegradation Models Allow for simulation of multi-dimensional transport and provide for more realistic representation of site conditions More complex than analytical models; require additional data Examples of numerical biodegradation models include: R-UNSAT; simulates subsurface aerobic biodegradation of vapors without foundation (Lahvis and Baehr, 1998) Abreu Model; model for PVI (Abreu and Johnson, 2005) MIN3P-DUSTY; multi-component model for gas transport (Mayer et., 2002) adapted for PVI (Jourabchi, 2012) good capabilities for incorporating methane generation and soil gas advection

6 Why Use BioVapor Download at: Reviewed and accepted by EPA, basis for EPA PVIScreen Structure (Microsoft Excel spreadsheet) Unlocked, databases included, easy to use Model characteristics: Similar CSM & caveats on model applicability and use to J&E model. Order of magnitude predictions Why use: Enables the contribution of aerobic biodegradation to be quantified Parameters: Key added parameters: oxygen b.c. s, firstorder decay constant Source concentration & soil type important

7 BioVapor Input and Output Examples When available, compared measured to predicted data

8 Source Concentrations in the BioVapor Model Vapors at fuel-impacted sites are primarily aliphatic hydrocarbons; BTEX represent small percentage (typically <10%) Input screens for 1) Risk drivers, 2) Other Hydrocarbons and 3) Surrogates; flexible approach, database provided Chemical analysis and inputs should reflect oxygen demand, e.g., through TPH vapor analysis (e.g., USEPA TO-3), extended TO-15 list, or sum of aliphatic and aromatic hydrocarbon fractions (e.g., MADEP) Key Point: Source hydrocarbon concentrations input should address total oxygen demand including methane

9 USEPA PVI Database 2013

10 BioVapor User s Manual (2009) Default Source Composition Key Point: While defaults can be used, better to measure soil gas concentrations including TPH & methane

11 Oxygen in the BioVapor Model Three Options: 1. Specify oxygen concentration below foundation Measure or oxygen equal to 20.9% 2. Specify oxygen flux to below building Airflow to below foundation ( Qf ) typical set equal to J&E Qsoil value 3. Specify aerobic depth Measure vapor profile

12 Sensitivity Analysis Conducted for gasoline vapor source of varying source strength for following parameters: Hydrocarbon components: benzene, xylenes, iso-octane (for sand & mid-point of values below) First-order decay constants: geometric mean (baseline) +/- geometric standard deviation values (DeVaull, 2011) Foundation air flow rate (Qf): 1, 5, 10 L/min (Qs = Qf) Organic carbon: 0.001, 0.005, 0.03 Soil type: Sand, Loam Building size: 100, 400, 900 m 2 Baseline bold values, distance = 3 m unless noted Details in Hers and Jourabchi (2014) 12

13 Sensitivity Analysis Results For combination/range of parameters chosen, relatively high sensitivity to: Hydrocarbon components, first-order decay constant, foundation air flow rate, organic carbon, soil type Moderate sensitivity to building size Highlights the importance of site-specific data and sensitivity analysis See Hers and Jourabchi (2014) for all parameter values and results 13

14 Sensitivity Analysis Foundation Air Flow Rate and O2 Boundary Conditions (B.C.) Crack Ratio = 1 Key Point: Highly sensitive to air flow & 14 distance. For crawlspace and shallow depth, attenuation by bio not dependent on source conc.

15 Sensitivity Analysis Soil Type Benzene Indoor air to source vapor conc. ratio 1.E 02 Soil Type Depth = 3 m 1.E 03 1.E 04 1.E 05 Sand 1.E 06 Sand 1.E 07 1.E 08 Loam 1.E 09 1.E Source Vapor Concentration (mg/l)(g/m3) Key Results are highly sensitive to Point: soil type. Ds = 5', Sand Ds = 15', Sand Ds = 5', Loam Ds = 15', Loam 15

16 Building P Oxygen Flux to Below Building Natural Processes & Conventional Foundation Wind V = 10 mph Diffusion 10 m k a = m 2 K = 0.25 O 2 =20.9% Sand w =0.055, =0.375 D eff =2E-8 m 2 /s Q s = 1-10 L/min Q f = Q s = 5 L/min Bernoulli Eq P = K * (0.5 a v 2 ) Darcy s Law Q = T * W * ( k a / * 2 P/ X ) F O 2 = 23 mg-o 2 /s F O 2 = 0.4 mg-o 2 /s Key Point: Diffusion length = 7 m than Qs to incorporate other 16 O 2 ingress processes V = 10 mph average wind speed of Chicago ( windy city ) O 2 =2% 0.5 m F = Flux F O 2 = 4.5 mg-o 2 /s Soil gas advection most important, then diffusion, wind least effective in supplying oxygen to subsurface; Qf = or >

17 Oxygen Flux to Below Building Engineered Processes Subslab material options Aerated subfloor (e.g., Cupolex) Conventional sand and gravel layer Energy options Wind Wind turbine Fan positive or negative pressure both have advantages and disadvantages Small radon fans capable of providing hundreds of L/min air to subslab sand and gravel layer - ample air for biodegradation So what about wind or wind turbine?, 17

18 UK Research Passive Venting Passive Venting of Soil Gases Beneath Buildings Research Report Ove Arup & Partners Sept 1997 Computational Fluid Dynamics Modeling Volume Flow Rate Air (m3/m-hr) Gravel Soil-air Permeability Darcy s (1 Darcy = m 2 ) Ventform ~10 8 +/- Gravel ~5x10 4 +/- 1 Sand ~10 1 +/- 1 1 Mid-point Freeze & Cheery, 1979 Wind Speed (m/s) GOLDER ASSOCIATES

19 Oxygen Flux to Below Building Wind with Aerated Floor Wind V = 10 mph (moderate) Opening to air ( windcatcher ) k a = 10-4 m 2 Aerated floor or void formers common construction in UK, but much less so in US F O 2 = 4E6 mg-o 2 /s Ample air for biodegradation! 19

20 Oxygen Flux to Below Building Wind Turbines Case Study 1 Wind Turbine Hers & Hood (2012) 1746 m 2 commercial building Cupolex subfloor Simulated 55 kmh wind with leaf blower to obtain specific capacitance P=-0.15 in wc (37 Pa), exhaust air flow rate = 72 cfm Scaled to Wind = 10 mph & 100 m 2 building obtain air flow = 30 L/min (for single wind turbine!) October 4,

21 Sensitivity Analysis 10 L/min Reminder: Does not take much air Crack flow for significant Ratio = 1 biodegradation 21

22 Oxygen Flux to Below Building Wind Turbines Case Study 2 Wind Turbine Lanzon et al. (2010) 7060 m 2 commercial building Sand and gravel subslab layer Similar leaf blower test conducted Total extraction air flow rate at 10 mph estimated = 2 L/min with 6 wind turbines Scaled to 100 m 2 building obtain air flow = 0.09 L/min Key Point: Wind turbine capable of delivering air needed for biodegradation for aerated floor but not for sand & gravel October 4,

23 BioVapor Comparison to Site Data for Four Sites with Below Building Data Tesoro (Dissolved): Model overpredicts subslab concentrations Stafford (LNAPL): Model overpredicts subslab/indoor air concentrations Alameda (LNAPL): Model overpredicts subslab/indoor air concentrations by several orders of magnitude (fine-grained layer likely not accounted for) Paulsboro (LNAPL): Model underpredicts shallow soil vapor concentrations (but no data within 0.75 m of slab) Hal s (LNAPL): Model underpredicts shallow soil vapor but predicted shallow soil vapour very low (pavement scenario) Key Point: Generally reasonable match between BioVapor predictions and field data (or over-prediction) 23

24 Depth below foundation (m) BioVapor Case Study Tesoro, UT Dissolved PHC Source Case Study 0 1 Tesoro Dissolved Source TPH v = 23 mg/l Oxygen (%) Benzene subslab Benzene Measured Benzene Oxygen No Bio J&E Benzene Vapor Conc (mg/m 3 ) GW Conc (mg/l) Vapor Conc (mg/m 3 ) Measured Predicted Measured Predicted Parameter Source Source Subslab Subslab TPH Benzene < DeepGW to soil vapor attenuation factor = 0.1 Shallow dissolved hydrocarbon source below townhouses (source building separation = 1.22 m) Source GW concentrations: TPH = 12 mg/l, benzene 4 mg/l Measured subslab < predicted concentrations (model conservative) Modeling added line of evidence for no concern with respect to indoor air

25 Depth below foundation (m) BioVapor Case Study Tesoro, UT Dissolved PHC Source Case Study 0 1 Tesoro Dissolved Source TPH v = 23 mg/l Oxygen (%) Benzene subslab Vadoze Zone Bio (BioF) Benzene Measured Benzene Oxygen No Bio J&E Benzene Vapor Conc (mg/m 3 ) GW Conc (mg/l) Vapor Conc (mg/m 3 ) Measured Predicted Measured Predicted Parameter Source Source Subslab Subslab TPH Benzene < DeepGW to soil vapor attenuation factor = 0.1 Shallow dissolved hydrocarbon source below townhouses (source building separation = 1.22 m) Source GW concentrations: TPH = 12 mg/l, benzene 4 mg/l Measured subslab < predicted concentrations (model conservative) Modeling added line of evidence for no concern with respect to indoor air

26 Depth below foundation (m) BioVapor Case Study Stafford, NJ LNAPL PHC Source Case Study Stafford LNAPL Source TPH v = 200 mg/l Oxygen (%) No bio J&E Benzene Iso octane Measured Benzene Measured Iso octane Oxygen J&E No bio Benzene & Iso Octane Vapor Conc (mg/m 3 ) Source Vapor Indoor Air Conc. ( g/m 3 ) Conc. (mg/m 3 ) Predicted Measured Benzene <2.5 Hexane <2.5 Iso octane MTBE Shallow LNAPL source below houses (source building separation = 1.52 m) Source SV concentrations: benzene = 0.66 mg/l; TPH = 200 mg/l (estimated) Measured indoor air & subslab < predicted concentrations (model conservative) Modeling added line of evidence for evaluating background, predicts aromatics & aliphatics behavior well

27 Depth below foundation(m) BioVapor Case Study Paulsboro and Alameda LNAPL PHC Sources Case Study Paulsboro LNAPL source TPH v = 200 mg/l Oxygen (%) Benzene Measured Benzene Oxygen Measured Oxygen J&E Benzene Vapor Conc. (mg/m 3 ) Source Vapor Indoor Air Conc. ( g/m 3 ) Conc. (mg/m 3 ) Predicted Measured Benzene Depth below foundation (m) Alameda LNAPL Source TPH v = 200 mg/l Oxygen (%) Oxygen Benzene Iso pentane Measured Benzene Measured Iso pentane Oxygen J&E Benzene & Iso pentane Conc. (mg/m 3 ) Source Vapor Indoor Air Conc. ( g/m 3 ) Conc. (mg/m 3 ) Predicted Measured Benzene Iso pentane

28 Depth below pavement (m) Case Study BioVapor Case Study Hal s Site Hal's VW 10 Loam TPH v = 32 mg/l Oxygen (%) E 05 1.E 01 1.E+03 1.E+07 Hydrocarbon Vapor Conc. (ug/m3) Benzene Measured Benzene Oxygen TPH Measured TPH Measured Oxygen Diffusion Only Soil gas measurments below pavement (VW-10) Can set parameters such that J&E simulates paved site Crack ratio = 1 Assumed same properties for pavement and soil Assumed very high air change rate (atmospheric dilution) Assumed fixed O 2 b.c.= 20.9%

29 Benzene BioF (shallow J&E predicted soil vapor / measured soil vapor) Site BioF Tesoro 8100 Stafford 680 Alameda 190 Paulsboro ~ 1 but no subslab vapor data Hal s > 4 orders of magnitude Key Point: BioF > 2 orders of magnitude (except Paulsboro site). BioF is semi-quantitative indicator that may be useful together with BioVapor results for communication of biodegradation potential April 6,

30 Comparison of BioVapor Model and MIN3P- DUSTY Numerical Model Simulations Models used to predict hydrocarbon fluxes at ground surface for input to risk assessment of ambient exposures for given: soil vapour concentrations soil type and moisture conditions in the vadose zone Predicted fluxes compared to flux chamber measurements Hydrocarbon components: benzene, chlorobenzene, and naphthalene April 6,

31 Model Processes Comparison of BioVapor Model and MIN3P- DUSTY Numerical Model Simulations Scenario Diffusion Firstorder Decay Sorption Multilayers BIOVAPOR Yes Yes No No MIN3P-DUSTY Yes Yes Yes Yes April 6,

32 Comparison of BioVapor Model and MIN3P- DUSTY Numerical Model Simulations Predicted Hydrocarbon Fluxes at Ground Surface Scenario Benzene (mg/m 2 /day) Chlorobenzene (mg/m 2 /day) Naphthalene (mg/m 2 /day) BIOVAPOR Homogeneous sandy soil 2.8E-4-0 MIN3P-DUSTY Homogeneous sandy soil 9E MIN3P-DUSTY Heterogeneous soil 9E Heterogeneous Soil: Five alternating layers of sand and silty clay with water saturation ranging from 36% to 45% 2. Homogeneous Soil: Sand with water saturation of 36% April 6,

33 Conclusions Important to use model that incorporates aerobic biodegradation for petroleum hydrocarbon compounds BioVapor order of magnitude predictive tool should be used with care - several parameters have high sensitivity (soil type, decay rate, foundation air flow) indicating importance of sensitivity analysis and site-specific measurements BioVapor model can be used to provide insight on vapor mitigation requirements using engineered processes for oxygen addition not much oxygen needed Data from 3 of 4 sites indicated BioVapor predictions of subslab/indoor air concentrations were conservative Some sites may warrant the use of a numerical model where heterogeneity and sorption can be important 33

34 Thank you! Questions? 34

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