Robert John Stuetzle. A Thesis presented to The University of Guelph

Transcription

1 Vertical Profiling Data Sets for Improved Characterization of Hydrologic Units Influencing Contaminant Migration in Strongly Heterogeneous Triassic Sediments By Robert John Stuetzle A Thesis presented to The University of Guelph In partial fulfillment of requirements for the degree of Master of Applied Science in Water Resources Engineering Guelph, Ontario, Canada Robert John Stuetzle, May, 2014

2 ABSTRACT VERTICAL PROFILING DATA SETS FOR IMPROVED CHARACTERIZATION OF HYDROLOGIC UNITS INFLUENCING CONTAMINANT MIGRATION IN STRONGLY HETEROGENEOUS TRIASSIC SEDIMENTS Robert John Stuetzle University of Guelph, 2014 Advisors: Professor Beth L. Parker Professor John A. Cherry Professor James Irving A large, former state-owned East German chemical park, has contaminated the subsurface. These contaminants migrate through a variably-lithified sequence of fractured, Triassic, interbedded clay/shale and sand/sandstone of fluvio-iacustrine origin. Conventional characterization techniques have indicated that contamination by volatile organic compounds (VOCs) exists in the source zone as DNAPL and in a dissolved phase plume stretching hundreds of metres down-gradient. In 2011, high-resolution core and borehole methods were applied at two cored holes: UoG1, 42.5 m deep, in the source zone; and UoG2, 68 m deep, 500 m down-gradient. This study demonstrates that high-resolution vertical profiles of contaminant concentrations, at a spatial scale informed by observed textural layering and fracture frequency, provide the basis for improved delineation of laterally continuous hydrologic units. These data were corroborated with conventional geophysical logs and detailed depth discrete hydraulic head profiles from MLSs, providing an improved site conceptual model for groundwater flow and contaminant transport.

3 Acknowledgements I would like to thank my supervisor Dr. Beth Parker and advisor Dr. John Cherry for the many hours of support that they have provided me. From their guidance in the planning stages of this project, through to their comments on my many revisions of text and figures for this thesis, their insight has been invaluable. I would also like to thank the third member of my advisory committee, Dr. James Irving, who through his teaching in the early portion of my graduate studies, provided me with an understanding of geophysics that proved very useful in interpreting the down-hole geophysical logs collected for this project. I would like to give special mention to the former G360 Scientific Operations Manager, Suzanne O Hara, who put forth immense effort to ensure the success of the project from a management standpoint. I would also like to acknowledge the funding for this project generously provided by The Dow Chemical Company (Dow), The University Consortium for Field-Focused Groundwater Contamination Research directed by Dr. Cherry, The Natural Sciences and Engineering Research Council of Canada (NSERC) Industrial Research Chair held by Dr. Parker and Landesanstalt für Altlastenfreistellung des Landes Sachsen-Anhalt (LAF). In addition, in-kind support was provided by FLUTe, Solinst Canada Ltd. and Golder Associates Ltd. A great number of people participated in this research project and without them it could not have succeeded. I would like to extend my sincere gratitude to Dave Wandor, Paul Van Riet and Fred Richter from Dow for providing us the opportunity to conduct our research at the Schkopau site. Robert Upmann and Jens Härtig from Tauw facilitated all on-site work, from coordinating contractors to providing office space, and overall ensured that our time in Germany enjoyable. Frank Synwoldt from MUEG provided geological expertise from decades of field experience on the site and in the surrounding Page iii

4 area. Walter Lenz and Christoph Möbus of HG, provided valuable feedback on our interpretations throughout the project, leading to insightful discussions about the science as it applies to the site. I would also like to thank all of the folks at the G360 centre for applied groundwater research (G360): Dr. Jessica Meyer, who helped in developing the project work plan; Ryan Kroeker for his long hours in the field and companionship while spending months away from home; Dr. Peeter Pehme for his technical guidance in down-hole geophysics and his help in designing the multilevel systems; Maria Gorecka and Rashmi Jadeja for managing and analyzing my rock core VOC samples; Dr. Thomas Eckert for providing continuing project management; Deborah Ruprecht and Andrea Harvie for ensuring that everything went smoothly from an administrative standpoint; and Paul Trudell, Thomas Coleman, Jonathan Munn, Kenley Bairos, Brent Ramdial, Carlos Maldaner and Andrey Fomenko, with whom I shared an office, for providing many insightful discussions and a few good laughs. Most of all, I would like to thank my parents Robert and Patricia Stuetzle, sister Karien Stuetzle, brotherin-law Dr. Boris Pavlin, as well as my girlfriend Alice Cudmore and her family for their endless patience, understanding, support and encouragement. Page iv

5 Table of Contents Abstract... ii Acknowledgements... iii Table of Contents... v List of Tables and Figures... vi Introduction... 1 Site Description... 4 Strategy and Approach... 7 Continuous Coring... 8 Geophysics/Hydrogeophysics Multilevel Systems Estimation of Phase Partitioning in VOCs Samples Results and Discussion Scale and Continuity of Depositional & Geologic Features Post-Depositional Features: Fractures & Faults Geophysical Responses to Geologic Variability Indicators of the Groundwater Flow System Contaminant Distributions Comparison of UoG1 and UoG2 in a Longsect Style Context Process Based Site Conceptual Model Limitations and Uncertainties Summary of Conclusions Recommendations References Captions for Tables and Figures Column Descrptions for Montages (Figures 4, 5, 9 and 10) Appendix A: Physical Property Samples Appendix B: Phase Partitioning Estimation Steps Appendix C: NAPLANAL Simulations Appendix D: VOC Concentration Profiles Appendix E: 1-D Diffusion Modeling Appendix F: Geophysical Tool Spec Sheets Page v

6 List of Tables and Figures Table 1: Physiochemical properties of Schkopau Analytes Table 2: Physiochemical properties of lithology types observed in UoG1 and UoG Figure 1: Site Map Figure 2: Area of Investigation Figure 3: Cross Section Figure 4: UoG1 Montage Figure 5: UoG2 Montage Figure 6: Geologic Summary Table Figure 7: Conventional Monitoring Well Clusters Vs. FLUTe MLS at UoG Figure 8: Accumulation, Lateral spreading and mixing of DNAPL Figure 9: Examples of Local Scale Variability Indicating Contaminant Migration Pathways Figure 10: Stratigraphically Aligned Montage of Logs from UoG1 and UoG Figure 11: Schematic Cross-section of the Process Based Site Conceptual Model Page vi

7 Introduction Industrial organic contaminants have entered systems decades ago and their mobility as separate phase liquids allows them to migrate deep into the subsurface across many distinct hydrologic units due to high density and low viscosity. They serve as long term subsurface (secondary) sources long after operations are improved to avoid continuing releases. Decades later these subsurface contamination problems however, are difficult, impractical or not feasible to remediate due to depth and subsurface complexity, especially if in fractured rock. They commonly create groundwater plumes extending large distances down-gradient, however the variability and connectivity of the hydrogeologic system can be difficult to discern with conventional monitoring approaches given heterogeneity scale and features dominating fluid flow and transport and reaction processes. High resolution characterization methods based on measurements in boreholes are needed to identify and quantify the features and system processes controlling contaminant behavior to make informed decisions for site management. High-resolution characterization of this style, using vertical profiles of core and groundwater data, is not a new approach. It was used in pioneering contaminant hydrogeology work in unconsolidated sandy aquifers conducted in the 1950 s and 1960 s (Parsons, 1960), (Parsons, 1961), (Parsons, 1962 A), (Parsons, 1962 B), (Perlmutter, Lieber, & Frauenthal, 1963). However, it was not continued after the profession and environmental regulations in the 1970 s sanctioned conventional monitoring wells as tools for characterization and monitoring at real sites leading to a tendency to skip the characterization stage (Weist Jr. & Pettijohn, 1975). But field researchers continued to show that high resolution spatial (and temporal) data are needed to inform a process-based site conceptual model (Roberts, Cherry, & Schwartz, 1982), (Schwartz, Cherry, & Roberts, 1982), (MacFarlane, Cherry, Gillham, & Sudicky, 1983), (Cherry, Gillham, Anderson, & Johnson, 1983), (Egboka, Cherry, Farvolden, & Frind, 1983), (Sudicky, Cherry, & Frind, 1983), (Dance & Reardon, 1983), (Nicholson, Cherry, & Reardon, 1983), Page 1

8 (Greenhouse & Harris, 1983). In the 1990s and 2000s investigations at sites contaminated with chlorinated solvents specifically used cores and sampling to show features and quantify processes with stratigraphic layers and fractures. In clay, Foley(1992), Parker (1996) and Morrison (1998) showed very small scale features in sedimentary deposits controlling DNAPL migration (as separate fluid) in sand stringers in a clay aquitard at CFB Borden. In a thick lacustrine clay unit in the Sarnia, Ontario area, O'Hara, Parker, Jørgensen, & Cherry (2000), Kirkpatrick (1998) and Lane (2001) showed that DNAPL readily penetrates through natural fractures that are not detectable with conventional hydraulic testing methods. During the same time period, in soft sedimentary rock (i.e. chalk), Lawrence, Chilton, Barron, & Thomas (1990) conducted the first study focused on the sampling of rock core for VOCs in a chalk aquifer in the UK. Later, Sterling (1999) adapted the rock core method for use in hard sandstone and shale applied it with higher resolution sampling for his M.Sc. thesis. Although Sterling s average spatial resolution of sampling was lower than in this study, and focused primarily on fractures, that work laid the groundwork for the rock core VOC sampling methodology used in this study. A methodology for this kind of high-resolution site characterization using a diverse set of state of the science methods was developed and fine-tuned since 1999 into what is now known as the Discrete Fracture Network (DFN) Approach by researchers at the University of Guelph (UoG) and is outlined by Parker, Cherry, & Chapman (2012). The DFN Approach is a suite of high resolution core and borehole methods that are used in complement to indentify and quantify the contaminant distribution and to inform about the relative role or importance of transport mechanisms, advection, diffusion and their interplay. The DFN field approach as described in Parker, Cherry, & Chapman (2012) is currently being applied at several contaminated sites across the world in geologic settings ranging from clastic sedimentary to carbonate and even granitic bedrock. This paper discusses its application and the adaptation of the Page 2

9 methods to a field site in Germany (the Schkopau site). What makes the Schkopau site unique among the existing field sites is: The extreme lithologic variability, with abrupt changes from lithified to unconsolidated and sand/sandstone to clay/shale within a matter of centimeters or decimeters; the large variety of contaminants present; and the number of contaminant release locations. Since the 1980's, extensive characterization focused largely on lithostratigraphy has been carried out using conventional characterization techniques such as continuous coring, borehole geophysics and conventional monitoring wells installed based on stratigraphic layers to investigate the nature and extent of the contaminant distribution and macro-structural geology (faulting) across the site. These studies are well documented in the consulting reports (MUEG and IHU, 1993), (MUEG and IHU, 1998), (IHU and MUEG, 2008) and (IHU and Mueg, 2010). Although these previous investigations have provided a detailed model of the lithostratigraphy and site-scale faulting, influences of the high degree of smallscale heterogeneity and fractures have not been thoroughly assessed. To assess the influence of these characteristics on the hydrogeologic system, two borehole locations were chosen, one in the CVOC source zone (UoG1) and another 500m down-gradient within the plume (UoG2). A specially selected set of high resolution investigation methods that best suited the known geological conditions at the site were chosen from the full suite of techniques in the DFN Field Approach. The specific goals and objectives of this study were: 1) Use newly developed DFN methods in combination with traditional methods at higher spatial resolution to measure geologic, hydraulic and contaminant distribution characteristics in a highly layered, fractured and faulted sedimentary sequence. 2) Adapt the existing methods for the extremely small scale, strong vertical heterogeneity of the sedimentary lithologies. Page 3

10 3) Identify the position and geometry (thickness) of lower bulk vertical hydraulic conductivity (K v ) units. 4) Evaluate contaminant composition and position from source to plume to identify lateral continuity of hydrogeologic units (HGUs) with distinct hydrologic properties, based on preferential solute movement along some layers. 5) Evaluate the likelihood of hydraulically active fractures in clay-rich, lower bulk K zones, acting as preferential pathways with respect to DNAPL migration. These five goals and objectives were used as the framework for a study to test the following hypotheses: 1) High resolution measurement techniques (spatial scale) allow for the use of contaminants as tracers that are diagnostic of system characteristics at a point in time but that exist as a result of the past processes. 2) Vertical fractures occur to some degree within all lithological layers at the site and are sufficiently interconnected to allow for DNAPL migration downward, through multiple aquitards, deep into the system. 3) Hydrogeologic units are continuous between the borehole locations and are correlateable using the vertical profiles of various data types. Site Description Dow Olefinverbund GmbH is a large modern chemical manufacturing park located approximately 30km west of Leipzig, in the town of Schkopau in the state of Saxony-Anhalt, Germany. Figure 1 provides an aerial view of the site as it sits today. There are several surface water bodies within close proximity to the site: The River Saale flows northward nearby the northern and eastern boundaries; an eastward flowing tributary known as the Laucha denotes the southern boundary; and a former aggregate mine, now a small lake known as the Rattmannsdorfer Teich lies directly adjacent to the northern boundary. The village of Korbetha and the town of Schkopau lie to the northeast and east respectively, between Page 4

11 the site and the river. The site s proximity to these potential receptors highlights the necessity for proper site management to prevent off-site migration of contaminants. The site itself sits upon what is best described as an anthropogenically graded plateau with an elevation of 100m above sea level (masl). A landfill comprised of calcium hydroxide sludge (31%), industrial sludge (27%), ash (22%) and demolition waste (17%) (Einecke, 2010) rises to 130 masl southwest of the site, while the topography drops to between 80masl (north) and 90masl (south) into the floodplains of the River Saale and the Laucha to the south, east and north of the site (IHU and MUEG, 2008). The area of investigation for the UoG research project shown in Figure 2 is located in the north-east section of the site, extending from the former CVOC manufacturing area (source zone) 500 m northward (downgradient) towards the river. The underlying geology is a Lower Triassic lithostratigraphic sequence known as the Middle Buntsandstein Subgroup, part of the Buntsandstein Group, which was deposited in the Germanic Basin that stretches beneath a large portion of Europe. Three formations of the Middle Buntsandstein (Volpriehausen fm., Detfurth fm. and Hardegsen fm.) are present at the location of the UoG2 research borehole, whereas the uppermost formation, the Hardegsen, is absent at the UoG1 borehole location. In general, the sequences show cycles of sandy fluvial deposition to floodplain and lacustrine deposits of silt and clay, with an increased floodplain/lacustrine to fluvial ratio towards the top of each sequence (Bachmann, Beutler, Szurlies, Barnasch, & Franz, 2005). The site lies in what was a marginal zone of the basin and as a result, the cyclic nature of the depositional environment is accentuated resulting in greater lithological diversity (Geluk & Röhling, 1997). Due to the extreme cyclical nature of the depositional environment, the geology at the site is very complex in that it is heavily layered with sharp changes in lithology occurring on the centimeter to decimeter scale. In addition to the complex lithology, the site is in the vicinity of a known fault zone as it appears in Figure 1A of Szurlies (2007), Page 5

12 resulting in a high degree of faulting throughout the area due to halokinetic processes (deep salt movement) in the underlying Permian Zechstein (Warren, 2008). The stratigraphy is generally considered to be relatively flat-lying but vertically shifted by the faulting, resulting in correlateable strata occurring at different elevations across the site as illustrated in the fence diagram in Figure 3. All of these factors contribute to the complexity of the subsurface at the site and must be considered when trying to understand hydrogeologic processes. The complexity of the site lies not only in the geological variability, but also in the diversity of the contaminants and their distribution across the site. The production history at the site dates back to 1936, when the IG Farben Group began construction of the synthetic rubber plant at Schkopau. The synthetic rubber manufactured at the site was formed by the polymerization of 1,3-butadiene (Bu) with sodium (Na) resulting in the name Buna. As such, the site was named Merseburg BUNA-werke GmbH Schkopau and is still today largely known simply as BUNA. The location of the site was chosen because of an abundance of nearby brown coal and salt mines (Kind, 2005). Brown coal provided fuel for electricity and steam generation and acted as the feedstock for the acetylene aldol butylene glycol butadiene reaction (Morris, 1998, pp ). Salt was used as the feedstock to create brine used in the Castner-Kellner chloralkali process, which generated sodium hydroxide and chlorine (Richter & Flachberger, 2010). The chlorine by-product of this process in turn acted as feedstock for the production of various chlorinated compounds such as polyvinyl chloride (PVC), perchlorethylene (PCE) and trichloroethylene (TCE). The production of this wide range of products along with their related intermediates and byproducts are the reason for the chemical complexity of the contamination at the site. After WW2, since it was located in the Soviet Occupation Zone, which later became East Germany, the facility became the state owned entity (Volkseigener Betrieb) VEB Chemische Werke Buna. Upon the Page 6

13 reunification of Germany, the government sought to privatize the facility and in 1995, Dow acquired the site and formed Dow Olefinverbund GmbH. (Kind, 2005). By the time of acquisition, there was abundant organic solvent contamination occurring in the layered and fractured sedimentary bedrock beneath the site. Since that time, there has been extensive environmental investigation, which has provided stratigraphic information from hundreds boreholes and hydraulic information from conventional monitoring wells across the site. The contaminant plumes, as currently defined using these methods, are being controlled by pump and treat systems at the boundaries for containment (~50 m 3 /h) and mid-site within the source zone to remove contaminant mass (~28 m 3 /h), in an effort to provide hydraulic capture/containment of the plume. Strategy and Approach Although the DFN Approach is being successfully applied at numerous sites around the world, what makes the Schkopau site unique compared to the other current UoG field sites are the extreme lithologic variability, large variety of contaminants present and numerous faults occurring throughout the site. The lithology changes drastically on a centimeter to decimeter scale, requiring centimeter scale core logging and increased resolution of geophysical and hydrogeophysical methods by appropriately low feed rates. The contaminants present are a result of an unknown number of releases of unknown composition, quantity and exact location over a period of almost 60 years. As such, an expanded list of 27 compounds was analyzed for in the rock core VOC samples, each of which was assessed for NAPL presence using well established effective solubility relationships. For those samples without suspected NAPL presence, the partitioning between dissolved and sorbed phases of each compound was calculated using the methods described in Feenstra, Mackay, & Cherry (1991). For those samples where concentrations were greater than 50% of the effective solubility of the contaminant mixture, the Page 7

14 algorithm NAPLANAL presented in Mariner, Jin, & Jackson (1997) is used to solve for the partitioning between dissolved, sorbed and NAPL phases using an iterative approach. The two drilling locations, in the source zone (UoG1) and down gradient in the plume (UoG2), were chosen to assess the small-scale variability within the vertical profile and its influence on the contaminant distribution and hydraulics of the system independently at each location and comparatively between the two locations to identify preferential contaminant migration pathways and lateral continuity of the hydraulic units. The following sections describe in detail the methods applied at the Schkopau site for this investigation: Continuous Coring Two boreholes were continuously cored for this project, one within the source zone and the other, 500 metres down-gradient within the plume. An AGBO model G300 truck-mounted full hydraulic rotary drilling rig was used by Bohrgesellschaft Roßla mbh at both holes. The holes were dry rotary drilled through the surficial fill zone using a bucket auger style tool (Boulding, 1993, pp ) with a removable side hatch for retrieval of the cuttings. The cuttings produced were core-like and appeared minimally disturbed based on intact bedding. A 178 mm OD (152 mm ID) steel casing was then advanced to 5 m at UoG1 and to 24.8 m at UoG2. The casing at UoG2 extended to this depth due to a high amount of washout occurring above that point. After the steel casing was in place, coring commenced using an Atlas Copco Geobor S S-size double-tube wireline system with a mm OD diamond coring bit, producing a 146 mm nominal diameter hole and a 102 mm diameter core. The double-tube coring system consisted of an outer tube (the drill stem) with the attached coring bit and a non-rotating, 1.5 m long inner tube (core barrel) with a core catcher to prevent the core from sliding out during retrieval. The only drilling fluid used while drilling these holes was water. No drilling mud was used in an effort to minimize effects on the formation surrounding the borehole. When the core was retrieved and brought Page 8

15 to the surface, the core catcher was removed from the end of the core barrel, allowing the core to be carefully extracted and placed in dedicated core boxes built to hold two 1 m long sections of core side by side. The core was then brought to the core logging table approximately 10m from the drill rig and transferred from the dedicated core box to a logging tray lined with clean aluminum foil on an elevated table, allowing for close inspection. Once placed in the tray, core recovery and RQD lengths were recorded according to Deere & Deere (1989). Due to the extremely high lithologic variability and incidence of fractures, a preliminary assessment of the core was performed to identify zones of interest for VOC sampling which are preferentially logged and sampled immediately, reducing the time that the core sits on the table before sampling in an effort to minimize volatilization of the contaminants. Rock core VOC sampling locations were chosen to fulfill the criteria of one of the following three sample categories: 1) Samples associated with a feature such as a fracture, rubble zone or vug. These are taken directly adjacent to the feature and at a spacing of 8 cm and 16 cm away from the feature in an effort to characterize the diffusion halo extending into the matrix. Due to the close spacing of many features in the core at Schkopau, the halo sampling was not always feasible. 2) Samples associated with lithology changes. These are taken above and below lithological contacts. Due to the extremely variable nature of the lithology at the site, this sampling was focused on major lithology changes rather than the closely spaced lithological changes in the alternating sequences. 3) Samples that fill in the gaps where no features or lithology changes are observed within sections of core greater than m. As a result of the highly variable nature of the subsurface material at Schkopau, very few of this kind of sample were collected. Page 9

16 Samples were collected using a clean chisel rock chisel and 3lb drilling hammer as described by Lima, Parker, & Meyer (2012). Once collected, each VOC sample was wrapped in clean aluminum foil, placed into an individual zip-top plastic bag and then temporarily stored in a cooler with ice packs until all samples were collected for the run. The cooler was then taken to the crushing station a few meters away, where each sample was trimmed to remove the outer portion of the core, crushed and preserved as described by Meyer (2013). All VOC samples were sent to the University of Guelph on ice for extraction by the shake-flask method described by Dincutoiu, Gorecki, & Parker (2003) and analysis by the method described in Gorecka, Gorecki, & Parker (2001). After collecting the VOC samples, the remainder of the core was logged. Geological properties of the rock (primary material, secondary material, Munsell coded colour, grainsize, sorting, sedimentary structure, ichnofabric index, cementation index and bedding) were logged by the on-site geologist while the features (fractures, vugs, etc.), their approximate dip and characteristics such as roughness, oxidation and presence of mineral precipitate as visible in the core were logged by a hydrogeologist as in Lima, Parker, & Meyer (2012) and Meyer (2013) with the exception that the logging was conducted on the 1cm as opposed to the 5cm scale to address the small scale lithologic variability. Following detailed logging of the core, samples were selected for physical properties testing. Selection was based upon grain size, apparent clay content, colour and cementation. Where possible, the sample was homogeneous, intact and ideally 30cm long to provide enough material that a full suite of physical properties tests could be conducted on the sample. At Schkopau, as the bedding occurs on such a small scale, many of the samples were approximately 10cm in length. The samples were removed from the core using a 3lb rock hammer and chisel and then wrapped in clean aluminum foil, plastic wrap, and Parafilm. The samples were then sealed in zip top plastic bags and shipped on ice to the laboratory in Guelph for storage at 4 C prior to analysis as in Meyer (2013). The samples were analyzed for: Page 10

17 Fraction of organic carbon by the University of Guelph Agriculture & Food Laboratory Soil Testing Services using the (ISO 10694:1995) standard; and for bulk density and porosity using (ASTM D (2008)) Test Method B, specific gravity using (ASTM D854-06) Test Method A and grain size distribution using (ASTM D422-63(2007)) at Golder Associates Ltd. in Mississauga, Ontario. In UoG1, 141 samples were collected for VOC analysis and 38 samples were collected for physical properties testing over a total depth of 42.5m. In UoG2, 183 samples were collected for VOC analysis and 21 samples were collected for physical properties testing over a total depth of 68m. VOC samples were approximately 5cm in length, whereas physical properties samples ranged from 3-27cm in length, usually limited by bed thickness. Geophysics/Hydrogeophysics Immediately after coring each hole, BLM Gesellschaft für Bohrlochmessungen mbh performed a suite of wireline geophysics in the open borehole. At UoG1, mechanical caliper, focused electrolog (FEL), gamma-gamma (GG), gamma-ray (GR), neutron-neutron (NN) and acoustic televiewer (ATV) logs were collected (Probe specs provided in Appendix F). The same suite of logs was collected at UoG2 with the exception of FEL, as the probe malfunctioned and it was deemed too high-risk to re-log the hole due to the high probability of borehole collapse. Soon after collecting the geophysical logs in each borehole, material collapse had caused bridging. Each borehole was cleaned out using the drill rig and a FLUTe hydraulic conductivity profile was conducted to identify transmissive zones along the length of the borehole (Keller, Cherry, & Parker, 2013). The FLUTe liner was left in place after profiling to prevent vertical cross-connection within the borehole, to prevent further borehole collapse and to allow for Active Line Source Temperature Logging (ALS) to be conducted as described by Pehme, Parker, Cherry, Molson, & Greenhouse (2013). Esentially, ALS is used to identify ambient flow in fractures and high permeability zones by heating the column of water inside Page 11

18 the FLUTe liner and monitoring the rate of cooling along the length of in the hole at a very fine scale, where higher groundwater flow in contact with the liner results in a higher rate of cooling at that depth. Multilevel Systems After conducting the down-hole geophysical and hydrogeophysical testing, a multilevel systems (MLSs) was installed in each borehole. The WaterFLUTe style of multilevel system, as described in detail by Cherry, Parker, & Keller (2007), was chosen over the other commercially available multilevel systems (CMT, Solinst Waterloo and Westbay) because of several unique attributes that suit the specific hydrogeologic conditions at the Schkopau site particularly well. Due to the high degree of lithologic variability encountered in the boreholes, maximizing the number of monitoring intervals (ports) to characterize the hydrogeologic variability was a key priority. Because of the large diameter of the boreholes and thin tubing used, a large number of ports could be achieved; and because the FLUTe seals directly to the borehole wall without packers or bentonite seals, which are prone to leakage if not sufficiently long, the short spacing between those ports could be achieved. Also, the WaterFLUTe system is installed from the surface downward, insuring that ports are accurately deployed at their intended depths, even if the system is not deployed to its total design depth. This makes it is ideally suited to the unstable geology encountered in the boreholes which, makes them prone to collapse. The WaterFLUTe is able to be installed quickly, accurately deploying as many of the ports as possible before collapse. The removability of the WaterFLUTe multilevel system was also an attractive feature for the site owner, as current regulatory standards at the site dictate the installation of large diameter conventional monitoring wells, which could be installed later if deemed necessary by the regulators. UoG1 was designed as a 20 port system, whereas UoG2 was designed as a 19 port system. These were the maximum number of ports that could be implemented in each of the holes respectively based on their diameter and depth to water. Due to borehole collapse however, only the uppermost 18 ports were successfully deployed in each hole. The primary goal of installing the MLSs was to obtain depth Page 12

19 discrete hydraulic head measurements to generate high-resolution vertical profiles. Based on head measurements from conventional monitoring well clusters nearby UoG1, we expect that there is approximately 15m of head differential between the top of the bedrock and the bottom of UoG1. The MLS head profiles in this case are expected to show a decline in head with depth, with some zones showing relatively large vertical hydraulic gradients across the most hydraulically resistive layers. The head profile is intended to show exactly where the hydraulically resistive layers (i.e. the layers with the relatively lowest bulk vertical hydraulic conductivity) are situated in the system. Each port in the MLSs has head measurement and groundwater sampling capability as well as the ability for an Air Coupled Transducer (ACT) to be attached. The standard design for a WaterFLUTe MLS has three tubes extending to the surface for each port: A ½ OD tube for manual measurement, a ¼ OD tube for sample output and a 3/16 OD tube for attachment to an ACT. The manual water level measurement in most ports is measured with a Solinst Model 102 Narrow Diameter Water Level Indicator (¼ stainless steel probe). However, the tubing for the top 3 ports on UoG1 was designed to be minimal in order to save space in the tubing bundle, maximizing the number of ports that could be installed. These ports have a single ¼ OD tube extending from port to surface for water level measurement, sampling and ACT attachment. The water level in these ports is measured by drawing a known vacuum on the tube with a peristaltic pump and measuring the visible water level in the tube once it has been drawn above ground surface. From the height of the water in the tube and the measured vacuum, a head value for the port can be calculated, treating the induced vacuum in a similar way to atmospheric pressure correction: h Head in the port [m H 2 O] h Head under induced pressure change [m H 2 O] dp A Change in atmospheric pressure (induced pressure change) [m H 2 O] Page 13

20 Estimation of Phase Partitioning in VOCs Samples For each VOC sample, the lab reports the concentration of each analyte in µg/l as measured in an aliquot of the MeOH extractant. Assuming that all of the contaminant mass has been extracted from the wet rock sample and is dissolved in the extractant, the mass of contaminant in the wet rock sample can be calculated and the partitioning between mass dissolved in the porewater and sorbed to the matrix material can be estimated as described in Feenstra, Mackay, & Cherry (1991) using physical and chemical properties of the matrix and physiochemical properties of the contaminants. The physical properties of the matrix for each sample are based upon measured values from lithologically similar category of physical properties samples collected in the boreholes (Table 2). The physiochemical properties of the contaminants (Table 1) are based on literature values. When NAPL is present in the sample however, the partitioning equations described above break down because the equivalent porewater concentration estimated from the total mass in wet rock would exceed effective solubility of the compound by including NAPL mass and as a result, also overestimate the sorbed mass as it is a ratio (k d ) of the porewater concentration. Because of this, each sample must be assessed to determine if NAPL is likely present. In Feenstra, Mackay, & Cherry (1991), a method is discussed for assessing the presence of NAPL in soil samples. This method involves estimating the partitioning of a given contaminant between dissolved, sorbed and vapour phases, then comparing the dissolved partition as a porewater concentration with the effective solubility of that compound. In the case where the calculated porewater concentration approaches or exceeds the effective solubility, it is likely that NAPL is present in the sample. However, to determine the effective solubility of a compound, the contaminant mixture must be known in terms of a mole fraction of each contaminant present in the NAPL. The paper suggests determining this composition directly from a sample of the NAPL or if a sample of the NAPL cannot be obtained, by using the contaminant mixture in samples that exhibit visual evidence of NAPL or are highly contaminated (thousands of Page 14

21 mg/kg or more) and using that composition to assess the presence of NAPL in samples with lower concentrations. Unfortunately, due to the numerous releases of unknown composition over the 60 year history of the site, it cannot be assumed that the NAPL composition from any single sample is suitable this purpose. Instead, we can formulate a method to test for the likelihood of any given NAPL composition using the following relationship for effective solubility that has previously been confirmed by Banerjee (1984); Mackay, Shiu, Maijanen, & Feenstra (1991); Cline, Delfino, & Rao (1991); Lee, Hagwall, Delfino, & Rao (1992); Lee, Rao, & Okuda (1992); and Broholm & Feenstra (1995): S i Solubility of the compound i in water [g L -1 ] S e i Effective solubility of the compound i in water [g L -1 ] X i Mole fraction of compound i in the contaminant in the NAPL mixture [ ] Using the definition of the mole fraction: X i Mole fraction of compound i in the contaminant in the NAPL mixture [ ] The equation for effective solubility can thus be rearranged as: S i Solubility of the compound i in water [g L -1 ] S e i Effective solubility of the compound i in water [g L -1 ] Page 15

22 As an assessment of NAPL presence, equivalent porewater concentration (C i,epw ) is substituted in for effective solubility (S e i) which yields the following relationships: NAPL not present in sample NAPL not present in sample but likely nearby NAPL present in sample S i Solubility of the compound i in water [g L -1 ] S e i Effective solubility of the compound i in water [g L -1 ] C i,epw Equivalent pore water concentration of the compound i [µg L -1 ] In the case where this relationship yields a value greater than 1, NAPL is likely present and an iterative method is used to solve for the phase distribution. An algorithm employing the Newton Raphson method as presented in Mariner, Jin, & Jackson (1997) is used to solve for the NAPL composition and phase partitioning in these samples. Results and Discussion Scale and Continuity of Depositional & Geologic Features Contrasts in the physical and chemical properties of the subsurface material are what define the hydrogeologic system, and these contrasts are best identified using high-resolution vertical profiles. Figures 4 and 5 are montages of various types of data collected at UoG1 and UoG2 respectively, presented as depth discrete vertical profiles. There are four categories of measured data presented sideby-side and aligned to elevation (Figs.4 and 5, Col. A): Core logs (Figs.4 and 5, Col. B), wireline Page 16

23 geophysical logs (Figs.4 and 5, Col. C), hydraulic head measurements (Figs.4 and 5, Col. D) and rock core VOC concentrations (Figs.4 and 5, Col. E). The comparison of these various data types presented in this fashion allows for the identification of interfaces with a precision that would not normally be possible through interpretation of any single data type at once. Each data type has its own strengths and limitations which must be taken into account and compared with complementary data types in order to generate robust interpretations of the hydrogeologic processes at work. In terms of the traditional lithostratigraphic core logging approach conducted by the on-site geologist, the lithostratigraphic units (Figs.4 and 5, Col. B1) were encountered at different depths in the two holes but exhibited roughly the same thickness (+/- 0.6m) at both holes, with the exception of a much thinner Detfurth Clay (smdt) and absent Hardegsen sequence (smh) at UoG1. This missing material is due to a horst and graben type structure with subsequent erosion and anthropogenic grading, leading to the conditions shown in Figure 3. In general, these metre-scale units tend to be defined by the style of lithostratigraphic sequence rather than the discrete lithological changes within them. The lithostratigraphic units appear to be useful for vertical orientation within the lithological succession and provide understanding of the macro-structural geology across the site but due to their internal variability, do not suffice in defining hydrogeological units or flow paths. In contrast to the traditional logging of metre-scale units, centimeter scale logging conducted on the core reveals the highly variable nature of the lithology within these larger groupings by identifying the colour (Figs.4 and 5, Col. B2) and primary matrix material (Figs.4 and 5, Col. B3) of each centimeter to decimeter scale layer. The Dominant Lithology column of Figure 6 summarizes the typical make-up of each traditional lithostratigraphic unit in terms of this fine-scale lithologic logging. The supporting Core Photos column of Figure 6 shows the nature of the lithology characteristic to each unit, particularly whether the lithologic variability is sharp or gradational. These small scale lithological layers as observed Page 17

24 in the core were broken down into 15 lithology categories, which are summarized in Table 2. The categories take into account the apparent clay content as well as the induration of these layers, as the lithologies ranged from loose sand to well indurated sandstone and from malleable clay to platy shale. An important property of the clayey layers, specifically the greenish grey clayey layers are their high total organic carbon (TOC) content, namely lithologies 11 and 14, which contain 0.439% and 0.478% TOC respectively. These high values are consistent with the statement in (Voigt, Gaupp, & Röhling, 2011) that the grey claystone beds tend to have TOC in the range of %. This high TOC value indicates the potential for these grayish green clay layers to have significant attenuative properties, while the high percentage of fines indicated by the grainsize analysis (28.75% Clay, 26.72% Silt) points the likelihood of a very low matrix permeability, making this a very good aquitard material both in a contaminant sense and a hydraulic sense. Though an important tool for resolving where changes in hydrogeologic connectivity might be occurring, lithology alone cannot predict hydrogeologic properties within the system. aspects such as post-depositional features within those lithologies must be taken into account. Post-Depositional Features: Fractures & Faults Further to logging the small-scale lithological layering, special attention must be paid to the competency of the core in terms of RQD (Figs.4 and 5, Col. B4) and more specifically the frequency of fractures, vugs and other potential flow-influencing post-depositional features (Figs.4 and 5, Col. B5), previously ignored in the traditional characterization approach but known to have a significant influence in terms of contaminant transport processes. An average of 7.43 and 8.63 horizontal and low-angle (<30 from horizontal) fractures per metre were observed in the core at UoG1 and UoG2 respectively, many of which occur along bedding planes. An average of 2.27 and 2.67 vertical and high-angle (>30 from horizontal) fractures per metre were observed in the core at UoG1 and UoG2 respectively, the majority of which are likely a result of the salt-tectonic-induced faulting observed across the site. Page 18

25 Fractures of this style seem to occur more frequently in the sandstone layers (Figure 6: Features A, B and D) and are less common in the clayey layers, presumably due to the increased plasticity which changes the way these layers react to stress. A second style of vertical fracture was observed in the clay/shale layers resembling desiccation cracks. These vertical cracks, as observed were filled with brown oxidized sand (Figure 6 Feature C). This sand could be of aeolian origin, deposited later during the arid episode or of fluvial origin, from the onset of the subsequent flooding episode. Desiccation cracks are also noted in other marginal zones of the Germanic basin by Bruun-Petersen & Krumbein (1975). This is considered to be a result of an ephemeral lake or floodplain type depositional environment, where during times of particularly arid conditions, sediment would be exposed, allowing for the formation of the desiccation cracks in the sediment as well as aeolian deposition (Bourquin, Guillocheau, & Peron, 2009). Due to the contrast in geomechanical properties from one lithology to another and as the two types of vertical/high-angle fractures observed in the core are caused by different stress regimes, the fractures were observed to be discontinuous or offset from layer to layer (Figure 6: Feature B), consistent with the behavior observed in the field and simulated in numerical models by Larsen & Gudmundsson (2010). While most fracture sets resulting from one type of stress (tectonic) tend to be discontinuous from layer to layer due to contrasting geomechanical properties, they may be interconnected at some points with fracture sets in adjacent layers produced by a different stress regime (desiccation cracks), these interconnected fractures are known as mixed-mode fractures (Larsen & Gudmundsson, 2010). Although mixed-mode fracture connectivity was not identified in the core at either hole, it is not practical to assess connectivity of the fracture sets based solely on observation of the core. Many layers showed a complete absence of vertical or high-angle fracturing in the core, though this does not confirm the absence of fractures within the layer. This lack of fractures can be attributed to the small cross-sectional area of the 102mm core and the sampling bias resulting from the use of a vertical hole to intersect Page 19

26 vertical and high-angle fractures as discussed in (Munn, 2012). Furthermore in the clayey intervals, smearing resulting from the drilling process as discussed by D'Astous, Ruland, Bruce, Cherry, & Gillham (1989) could potentially mask fractures on the surface of the core. For this reason it is important to consider that no detection of fractures in zone of the core represents a low fracture frequency relative to the rest of the core. Geophysical Responses to Geologic Variability Wireline geophysical methods (Figs.4 and 5, Col. C) were employed in both holes to assess properties of the formation that could not be quantifiably determined by core examination in the field. The GR logs, displayed with tan-blue shading in Figs.4 and 5, Col. C2 of the profiles, are heavily influenced by clay content in the formation. At both borehole locations, elevated GR readings occurred in zones where the lithology was logged as clayey, notably so in the smdt and smdz lithostratigraphic units. However, in contrast to the high-resolution lithostratigraphic core logs based on visual inspection, the GR logs were able to differentiate a zone of notably higher clay content near the base of the Detfurth Clay (smdt). At UoG1, the peak reading of the anomalous zone was roughly 280 API compared with an average reading of roughly 190 API in the rest of the smdt and at UoG2 a similar response was seen with the values of ~250 API and ~150 API respectively. Unfortunately, GR logging was conducted using higher than ideal run speeds (4 m/min), meaning that the number of measurements per metre were insufficient to resolve the small scale lithological layering observed in the core. The result is a dampened response that effectively shows a moving average over a longer interval, masking smaller beds and making it difficult to identify the exact location of lithological contacts. The NN log, overlain on the GR log as a red line (Figs.4 and 5, Col. C2), is heavily influenced by both porosity and clay content. Porosity is inversely proportional to the NN reading in counts per second (CPS), though clay content is also inversely proportional to the NN reading. With the help of the lithology logs and the GR log, the responses can be assessed to determine which property they pertain to and in turn, how the flow system might be Page 20

27 influenced. In the specific case of UoG1 and UoG2, special attention must be paid to the lithological logs, as the GR logs are at too low a resolution to allow for direct comparison with the NN logs alone. The NN logs appear to respond to thinner clayey layers observed in the core, which tend to be masked by the low resolution of the GR. An example of this occurs at an elevation of masl in UoG1, where the GR log shows no significant response to the clayey layer observed in the core, however the NN log indicates a strong negative response. This is likely a result of the NN probe being higher-resolution than the GR probe in terms of more measurements per second, allowing for greater precision at the same run speed. In order to facilitate the comparison of the two logs, the GR run-speed should be reduced to 0.8 m/min. Indicators of the Groundwater Flow System ALS temperature logging performed in the water column of the FLUTe lined boreholes is used to indicate active flow features intersecting and within close proximity to the borehole walls. Points of more rapid cooling along the temperature profiles were interpreted as high (pink), medium (blue) and low (green) response features and plotted as a profile of colour-coded horizontal lines in Column C2 of Figures 4 and 5. These profiles show numerous high response features in the smdt lithostratigraphic unit at UoG1 but fewer and less intense responses in the same unit at UoG2. The increased number of features at UoG1 is likely due to increased weathering resulting from the unit s close proximity to ground surface and possible daylighting pre anthropogenic grading. The presence of these active features within the clay is not unexpected and is evidenced by oxidation at features observed in the core throughout this zone (Fig. 6 Feature A). Although these features show a high response, that does not necessarily indicate that they are high-flow zones in an absolute sense. The interpreted responses indicate zones of increased cooling relative to the cooling rate in the surrounding depth interval. In effect, these responses likely show the contrast in fracture flow relative to matrix flow. Thus in a fractured clay like the smdt, fracture flow would be much higher relative to matrix flow, generating a higher intensity cooling response; Page 21

28 whereas in fractured sandstones such as in the smdub, the matrix flow would be higher, diminishing the contrast with fracture flow and a producing less intense cooling response in the logs. The result is that the response intensity can only be correlated with flow intensity relatively in a local sense (within the same lithology) and that the method is much more effective at locating active fractures in zones with lower matrix permeability such as the smdt lithostratigraphic unit. Depth-discrete hydraulic head measurements from multilevel systems allow for the quantification of vertical hydraulic gradients a scale necessary to identify the locations of aquitards. When water levels are plotted against screen depths in terms of elevation (Figs.4 and 5, Col. D1), sharp head drops between monitoring intervals indicate where zones of low vertical hydraulic conductivity limit connectivity between hydraulic units. A downward gradient is observed at both holes, with a head differential of 10.97m and 8.67m between the topmost and bottom most ports in UoG1 and UoG2 respectively. A downward gradient was expected, based on data from the conventional monitoring well clusters as shown in Figure 7. In contrast to the head profiles from the long screen conventional monitoring wells however, the MLS profiles show much more detail, namely that the head differential occurs over a few short intervals, as opposed to relatively uniformly over the entire depth. The sharp inflections identified in the head profiles are further emphasized by plots of the vertical gradients calculated between monitoring intervals (Figs.4 and 5, Col. D2). Furthermore, contrasts between two sets of measurements collected in April and October help show temporal (seasonal) variability, to which the response in some zones is greater than others. This variability indicates contrasts in hydraulic properties, further helping to delineate hydraulic units, that would otherwise go unnoticed using a single snapshot in time. Based on these head inflections and further refined using information from the rock core logs, the geophysical logs and the rock core VOC data, five aquitards were identified in UoG1 and six in UoG2, the locations of which are overlain on the head profiles (Figs.4 and 5, Col. D) as grey shading. Page 22

29 Contaminant Distributions Analysis of groundwater samples can provide information about the dissolved phase concentration of contaminants as a blended value over the sampling interval and in rare cases, can confirm the presence of NAPL phase within an interval where a sufficient mobile quantity exists to occur in the sample. In comparison, analysis of the saturated porous media for contaminant mass and physical properties provides the means to estimate the dissolved, sorbed and NAPL phases present at the discrete sampling point by means of tested partitioning calculations. Together, the distribution of these phases with depth and at different locations within the plume can serve as a time weighted fingerprint of important contaminant flow and migration pathways in the system (O'Hara, Parker, Jørgensen, & Cherry, 2000) and can provide insight into the transport mechanisms (NAPL flow, advection, diffusion, sorption and degradation) at work in the system. With high-resolution rock-core VOC data, vertical profiles of contaminant mass can be plotted to provide an overview of contaminant distribution with depth (Appendix D). However, in order to more effectively identify the locations of the elements affecting these transport processes, we look specifically for contrasts in the profile. A contrast in the contaminant mixture or magnitude is a result of one or more of the following: a change in bulk K of the material, a change in f oc of the matrix material, a change in fracture geometry/distribution or a change in the mineralogy of the material. To better identify the contrasts, and to compare major and minor constituents on an equivalent scale so as not to miss any of the more subtle cues, each compound is plotted in vertical profile as cumulative mass with depth on a percentage scale (Figs. 4 and 5, Cols. E1-5b). Much like a vertical profile of hydraulic head, the contrasts are shown as inflections in the slope of the line. To better highlight inflections, gradients between measurement points are calculated and displayed adjacent to the profiles as horizontal bars on a log-scale indicating the delta value of cumulative mass increase over the sample spacing (Figs. 4 and 5, Cols. E1-5b). The result is a series of plots that when compared side by side, indicate changes in the composition of the contaminant mixture Page 23

30 as well as changes in the magnitude of contaminant concentration. Factors such as accumulation of contaminant mass as NAPL (Figure8 and Figure 9a), lateral influx of contaminants from up-gradient in transmissive zones (Figure 9b) and the presence of diffusion profiles in low permeability zones bounding contaminant migration pathways (Figure 9c), shape the distribution. These changes indicate a contrast in the contaminant transport properties of that zone and help to identify features important to contaminant migration. These contaminant migration zones, as delineated by contrasts in the rock core VOC data, are plotted as dashed lines atop the vertical profiles of cumulative mass (Figs. 4 and 5, Col. E). 41 of these contrasting contaminant migration zones are observed in the contaminant profiles at UoG1 and 50 at UoG2. The profile of contaminant mass at UoG1 exhibits concentrations of chlorinated hydrocarbons from the upper sampling intervals all the way to total depth. These compounds, in the mixtures that they occur in the rock core samples, have a density higher than water ( g/ml) and as a result would migrate downward through preferential pathways in the system as a free phase liquid (DNAPL). Evidence for this is the likely presence of DNAPL as calculated from rock core samples, where equivalent porewater concentrations of components in the contaminant mixture exceeded their estimated effective solubility limits (Samples: DS-001, DS-003, DS-005, DS-008, DS-019 and DS-110) and in some cases exceeded the absolute solubility limits for PCE and TCE (PCE: DS-003, DS-019, DS-110; TCE: DS-019, DS-110). This NAPL occurrence in the uppermost layers ( mbgs) and extending deep into the system (30.58 mbgs) indicates the presence of vertical migration pathways through at least 4 aquitards, with a strong likelihood of even deeper penetration in the vicinity, based on the presence of these compounds in the deepest sample collected at mbgs (12.02 µg/ml calculated porewater concentration) just above the 42.5 mbgs total depth. The presence of DNAPL at shallow depth indicates that a release of those contaminants, either as a mixture or separately over time, occurred at or very close to the location of UoG1. At a depth of mbgs the NAPL shows a different contaminant composition, which is likely a Page 24

31 result of lateral spreading and mixing in a zone of higher permeability atop a low permeability capillary boundary (Figure 8). In addition to these local source zone contaminants, we also see isolated zones of BTEX contamination, that due to their absence above and below in the profile and the occurrence of a known source zone up-gradient, provide evidence of lateral arrival. These areas of lateral arrival most likely indicate zones of higher permeability and flow than those where the upgradient contaminants are not present. UoG2 exhibits a very different contaminant profile compared to that of UoG1. The concentrations detected in the rock core VOC samples tend to be roughly 2 orders of magnitude lower (max µg/g total VOCs in wet rock) than those at UoG1 (max µg/g total VOCs in wet rock). The contamination also occurs in isolated zones with samples below the detection limit above and below, pointing to lateral arrival in the higher flow zones or preferential contaminant migration pathways, as would be characteristic of a down-plume location. Some of these preferential contaminant migration pathways in UoG2 only show the arrival of chlorinated compounds, presumably from the source zone at UoG1, while some show BTEX arrival from a known source up-gradient of UoG1. Based on this, zones with BTEX arrival would indicate higher flow zones or zones with lesser attenuating properties. Comparison of UoG1 and UoG2 in a Longsect Style Context When compared side by side, referenced to elevation, the logs of the two boreholes show little similarity. However, when the UoG2 logs are shifted 25.2m upward, aligning the distinct smdob - smdz contact at the two locations, the correlation between the logs becomes very clear. With the lithostratigraphic units aligned, the variability in the degree of lithological layering (Fig. 10, Cols. B2 and B3) and the geophysical responses (Fig. 10, Cols. C1) correlate well between the two locations. The hydraulic head profiles match up closely, with increased hydraulic gradients occurring over the same intervals once stratigraphically aligned, providing evidence for the lateral continuity of the confining layers that they represent. The contaminant migration zones, delineated independently at each location Page 25

32 by contrasts in the contaminant profiles, also tend to correlate well. The contaminant distribution itself however does not match well at first glance, but rather provides insight into the properties of the migration zones. The arrival of contamination and its composition along the vertical profile at the downgradient location (UoG2) is controlled by factors governing reactive transport: characteristics of the fracture network, physical and chemical properties of the matrix, physiochemical properties of the contaminants and their interactions. For example, the contaminant distribution differs in that the relative lack of contamination in smdt at UoG2 vs. at UoG1 is likely due to the low matrix permeability and high fraction of organic carbon (FOC) of the clay, which provides a high degree of attenuation in terms of lateral transport. In contrast, the underlying smd st zone shows a high degree of contamination in UoG2 relative to the rest of the profile, likely due to its higher permeability and lower attenuative properties. Based on the lateral arrival of contaminants at UoG2, preferential contaminant migration pathways were identified, shaded in green and projected onto the corresponding migration zones at UoG1 (Figure 10, UoG1 and UoG2, Col. E). Most of the preferential contaminant migration pathways identified using the contaminant profiles at UoG2, already show arrival of BTEX in UoG1 from the up-gradient source zone where they have not yet arrived at UoG2. This helps us further discern which pathways may be higher permeability than others in a relative sense. Using a similar approach, intermediate contaminant migration pathways, where significant contamination has not yet arrived at UoG2, were shaded in yellow and projected onto the corresponding migration zones at UoG1 (Figure 10, UoG1 and UoG2, Col. E). The intermediate contaminant migration pathways presumably have a lower lateral hydraulic conductivity or other significant attenuating properties. Aquitards, over which a notable hydraulic gradient occurs and which tend to exhibit little or no lateral arrival of contaminants at UoG2 are shaded in red and projected onto the corresponding contaminant migration units at UoG1. These aquitard units limit vertical advective connectivity between contaminant migration pathways, dividing the system into Page 26

33 hydrogeologic units (HGUs). The occurrence of preferential and intermediate contaminant migration pathways provides the basis for further division of the HGUs into sub-units. The continuity of the HGUs between UoG1 and UoG2, in terms of head and contaminant distribution, despite the large shift in elevation of the lithostratigraphic units, indicates that faulting may not be as abrupt as depicted in Figure 3; but rather a more stepped deformation, with clayey layers being smeared as modeled in Schmatz, Vrolijk, & Urai (2010). This smearing effect allows the aquitard units to remain intact across fault zones, limiting cross-connection of the HGUs. Process Based Site Conceptual Model The interpretations formed of these multiple high-resolution data sets are meant to inform a process based site conceptual model. The hydrogeologic units and sub-units which control the contaminant migration and distribution at the site are used to describe the system and to make predictions about contaminant transport for site management and remediation. A graphical representation of the process based site conceptual model defined by this investigation is shown in Figure 11. The figure depicts a longsect through UoG1 and UoG2. To the far left (South) the BTEXS source zone sits at a location where the bedrock geology is uplifted and the upper 5 aquitards observed at UoG1 are absent. UoG1 is located directly in the CVOC source zone where the DNAPL has entered the ground from multiple sources. It pools at capillary barriers and spreads out laterally atop those interfaces. While the majority of the contaminant mass is stuck in the low permeability, high f oc smdt clay, which now acts as a long term secondary source, DNAPL has also travelled deep into the system, penetrating through at least the four topmost aquitards. Lateral migration occurs through preferential and to a lesser degree intermediate contamination migration pathways, with CVOC contamination and in the fastest migration pathways, BTEXS contamination from up gradient, reaching UoG2. The bulk hydraulic properties of the hydrogeologic units govern groundwater flow between the two borehole locations, while variability in the reactive properties of the matrix and geometry of the fracture network within the hydrogeological Page 27

34 units further govern the contaminant distribution. Interactions between the reactive properties of the matrix and the physiochemical properties of each contaminant control diffusion into lower permeability zones, sorption to the matrix material and degradation by biotic and abiotic processes. These complex interactions within the contaminant migration units result in the variability of contaminant arrival that is evident along the vertical profiles. The lateral migration occurs across fault zones with minimal crossconnection between HGUs. Gradual stair-stepping deformation occurs at these faults as opposed to a single abrupt break and clayey aquitards are smeared/deformed at fault zones as opposed to broken, as modeled in Schmatz, Vrolijk, & Urai (2010), preventing connectivity HGUs. Limitations and Uncertainties This investigation has involved the use of a diverse suite of measurement techniques in an effort to generate a more robust interpretation of hydrogeologic processes at work in the subsurface. Though each dataset has its own inherent limitations, using several data types helps to reinforce interpretations. Although using multiple high-resolution data sets can increase confidence at a given measurement location, the spatial variability that exists in all natural hydrogeologic systems means that there will always be some degree of uncertainty in the interpretations. Evidence of spatial variability on the sample scale exists in that variability can be encountered within a sample-split of core for physical properties analysis. Sample UoG2-PP001 and its split UoG2-PP100 collected from UoG2 at mbgs show a TOC of 0.349% and 0.218% respectively. On the borehole scale, there is further variability in physical properties of seemingly similar lithologies. 38 samples from the two locations were used as analogs for 15 different lithology types observed in the core. Though many samples within those 15 lithology types correlate well, variability can be seen within the samples representing each category. Site-scale variability is also a factor when trying to form a site conceptual model. In the case of this investigation, the high resolution measurement techniques were only applied at two locations 500m apart. This can only at best provide insight into the system between the two points in a 2D sense. Even Page 28

35 then, based data from the existing conventional wells, we assume that UoG2 is on the same flow-path, downgradient of UoG1, though it is likely offset to some degree. To decrease the uncertainty from spatial variability to a manageable level, it would be ideal to increase sampling density by further investigation at additional borehole locations. Further to uncertainty resulting from spatial variability in the natural system, there is also a degree of uncertainty introduced by the parameters used in the calculation of the contaminant data. Literature values for the physiochemical properties of the analytes vary greatly from source to source, particularly for solubility and partitioning coefficients, especially for the less common compounds. The best way to reduce the uncertainty in this sense would be to conduct bench scale tests using the same mixtures of contaminants observed in the rock core VOC samples and for sorption tests, using samples of the lithologies found at the site. However, although there are these uncertainties indicated here, the high-resolution data from the two holes is sufficient to indicate clearly the style of the contamination relevant to the entire site because the geology of these two holes is representative of the site. Summary of Conclusions Through the use of vertical profiles generated from multiple high spatial resolution measurement techniques, a process-based hydrogeological site conceptual model has been developed for a section of the Schkopau site between two borehole locations. These two boreholes are located the middle of a DNAPL impacted source zone and 500m down-gradient in the plume centreline as informed by water quality data from numerous conventional wells, to provide insight into the contaminant distribution and to serve as a guide for further site characterization work. Page 29

36 Detailed contaminant profiles from densely collected rock core samples allow for the use of those samples as tracers in the system, both in a vertical sense at each borehole and in terms of lateral migration in a cross-hole sense. Top- to-bottom contamination at the UoG1 source zone borehole is evidence of deep DNAPL penetration into the system. Vertical connectivity through fractures, with preferential accumulation zones above lower K layers, and in some instances, at the base of lower K layers, as the DNAPL enters low entry pressure (P e ) porous sandstone, highlight those boundaries in the system. The combination of vertical migration and lateral migration from more distant source zones explains the variability in DNAPL composition along the profile. At the UoG2 down-gradient borehole, arrival of contaminants at concentrations roughly 2 orders of magnitude lower, in isolated zones, are likely due to lateral migration and indicate preferential contaminant migration pathways within the system. These VOC data show contrasts along the vertical profile of each borehole at a much higher resolution than even densely instrumented MLSs which are considered high-resolution in practice compared to conventional methods. Once boundaries of distinct hydrologic units were identified using the high spatial resolution rock core contaminant profiles, interpretations of the HGUs were strengthened using information from the detailed inspection of continuous core, geophysics and MLS head profiles. Inflections in the MLS head profiles helped to show intervals within which, one or more of the contaminant-delimited hydrologic units behaves as an aquitard. Though these aquitards exhibit integrity through high bulk vertical hydraulic resistance in the head data, partitioning calculations performed on the rock core VOC results indicated the presence of DNAPL deep within the system at UoG1. This DNAPL occurs below the 4 uppermost aquitards, providing evidence for downward migration pathways/fractures through those aquitards and throughout the system. These head inflections result from low matrix permeability in the vertical direction due lower conductivity clay/shale layers and the discontinuity of fracture sets between the lithological layers presenting a tortuous path for vertical fracture flow in those few mixed-mode Page 30

37 interconnected fractures, thus increasing vertical hydraulic resistance. However, those few interconnected fractures sets between lithology types appear to have provided downward migration pathways for DNAPL with sufficient driving head to overcome the required entry pressures. Through the use of head profiles to identify vertical hydraulic boundaries within the system and contaminant profiles to characterize contaminant migration through the system, hydrogeologic units (HGUs) and sub-units were identified at each borehole location, which appear to be continuous between the two locations. Similar hydraulic head profiles, lithologic characteristics and contaminant mixtures are detected in same intervals (HGUs) at both holes once the profiles are lithostratigraphically aligned by a 25.2m shift. Based on this lateral continuity, it is likely that the fault zones behave as modelled in Schmatz, Vrolijk, & Urai (2010), in that deformation occurs in a gradual manner with smearing of the clay aquitards, meaning that the HGUs remain continuous and limited cross-connection occurs between those HGUs. The insights gained using these two borehole locations contribute to the development of a process based hydrogeologic conceptual model for the area of investigation, as shown graphically in Figure 11. With further application of these investigation techniques site-wide, this could be expanded to a sitescale process based hydrogeologic conceptual model, which could be used to make predictions about contaminant behaviour for the design and management of remediation efforts. This study demonstrates that high resolution vertical profiles of contaminant concentrations at a spatial scale informed by textural layering and fracture frequency observed in continuous core, provide the basis for improved delineation of multiple laterally continuous hydrologic units. The contaminant profiles were sufficiently resolved to determine boundaries using concepts for DNAPL flow and solute migration to interpret the data set. These data were corroborated with detailed depth discrete hydraulic Page 31

38 head profiles from MLSs and conventional geophysical logs, providing an improved site conceptual model for groundwater flow and contaminant transport. Recommendations This investigation can only provide insight into a limited, two dimensional section of the subsurface at the Schkopau site. Though through use of multiple high resolution datasets, the amount of insight gained with those two holes is remarkable. This investigation is the first stage in applying the DFN approach site-wide, refining the methods to suit the specific characteristics of the site and serving as a guide for future characterization of this style. To further assess the performance of this investigation and to further minimize the uncertainty associated with the interpretations before applying the DFN approach site-wide, a comparison of estimated porewater concentrations with groundwater samples from the high-resolution depth discrete multilevel systems should be made to assess the accuracy of the partitioning estimates discussed. Also, as only between 1-5 samples were used from each of the 15 lithology types as analogs for those lithology types along the entire profile, further samples should be collected and analyzed for physical properties to minimize uncertainty in the properties of each lithology type and the partitioning calculations that they are used for. Further to that, bench scale tests could be run using controlled quantities of the contaminants in samples of the lithology to experimentally determine their interactions. Once the performance of this small-scale investigation has been assessed and the understanding of the contaminant-lithology interactions have been fine-tuned, additional high-resolution investigation locations in transect of the plume will be required to more precisely characterize migration direction. Additional high-resolution investigation locations along the long-axis of the plume would also be necessary: upgradient of UoG1 to characterize upgradient sources; between UoG1 and UoG2 to better Page 32

39 assess migration rates; and downgradient from UoG2 at the plume front to characterize the lateral extent of contamination. Angled coreholes should also be used, particularly at fault zones to better characterize vertical and high-angle fractures and to understand the style of faulting. The goal of this expanded scope would be to improve the level of interpretation from simply identifying preferential migration pathways, to quantifying migration rates within those pathways, which could be used to make predictions for site management and remediation needs. Page 33

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46 Captions for Tables and Figures TABLE 1 Table listing literature values for the the physiochemical properties of the contaminants analyzed for at the Schkopau site. These values were used in the partitioning calculations for the rock core VOC samples. TABLE 2 Table listing the experimental results of physical properties testing on rock core samples from UoG1 and UoG2. The samples were grouped into 15 lithology types that represent all of the lithological layers observed in the core. Grainsize analysis was only conducted on samples that could be easily crumbled by hand, as mechanically crushing strongly indurated lithologies might result in altered grainsize distributions resulting from the crushing procedure. FIGURE 1 Present day aerial view showing the Schkopau site shaded in yellow with an opaque yellow line delineating the property boundaries. The locations of the UoG1 and UoG2 research boreholes are indicated by the red stars and accompanying labels superimposed onto the map. The top right inlay indicates the location of Schkopau within Germany, approximately 30km west of Leipzig. The top left inlay is an aerial photo taken northward over the site in 1991, showing the dense network of production facilities, storage tanks and infrastructure present before redevelopment in the late 1990s. FIGURE 2 Detailed plan view map of the site between and nearby UoG1 and UoG2 indicating their locations as well as the locations of nearby conventional monitoring wells and well clusters. FIGURE 3 South-North fence diagram with the locations of UoG1 and UoG2 projected on, as a longsect of the lithostratigraphic layering and faulting between the two locations and across the site. The fence diagram extends to the current maximum depth of investigation on the site, which is the base of the middle Triassic. Page 40

47 The overview map indicates the presumed fault locations as red lines, the fence-line as a black line, the fence wells as green points and UoG1 and UoG2 as blue points. FIGURE 4 Montage of the high spatial resolution geological (B), geophysical (C), hydraulic (D) and chemical (E) data collected at UoG1, presented as vertical profiles. HGUs are delineated by spatial and temporal changes in hydraulic head, using geological, geophysical and chemical data to further refine their locations. These HGUs overlay the hydraulic data (D) with aquitards indicated by grey shading. The rock core contaminant data (E) is displayed in vertical profiles of cumulative mass for each compound, allowing for the identification of contrasts in contaminant mass and mixture, including minor constituents, on a comparable scale. Contaminant migration units were identified from these contrasts and delineated with dashed lines overlain on the contaminant data. FIGURE 5 Montage of the high spatial resolution geological (B), geophysical (C), hydraulic (D) and chemical (E) data collected at UoG2, presented as vertical profiles. HGUs are delineated by spatial and temporal changes in hydraulic head, using geological, geophysical and chemical data to further refine their locations. These HGUs overlay the hydraulic data (D) with aquitards indicated by grey shading. The rock core contaminant data (E) is displayed in vertical profiles of cumulative mass for each compound, allowing for the identification of contrasts in contaminant mass and mixture, including minor constituents, on a comparable scale. Contaminant migration units were identified from these contrasts and delineated with dashed lines overlain on the contaminant data. FIGURE 6 Page 41

48 Table providing descriptions and accompanying core photos of the lithostratigraphic units as observed at UoG1 and UoG2. The far right column provides photographic examples of some of the key types of fractures and flow-influencing features observed in the core. FIGURE 7 Comparison of water level measurements from the UoG1 FLUTe multilevel system (red) to two nearby conventional monitoring well clusters (blue). The water level measurements are displayed in terms of water level elevation (X-axis) vs. port elevation (Y-axis) to generate vertical profiles of hydraulic head. The screened interval of each conventional monitoring well is shown as an I-bar, whereas the FLUTe MLS ports are shown only as a point because of their short screened intervals. FIGURE 8 Schematic of downward DNAPL migration through fractures in the Detfurth Clay with pooling within a heavily fractured sandstone interbed resulting in lateral spreading and mixing of DNAPL from two different sources. FIGURE 9A Excerpt of the UoG1 montage (Figure 4) from masl highlighting NAPL accumulation in the Detfurth Clay (smdt) as illustrated in Figure 8. FIGURE 9B Excerpt of the UoG2 montage (Figure 5) from masl highlighting lateral influx of contaminants from up-gradient in a transmissive zone. The presence of BTEX compounds indicates a higher rate of contaminant migration, as the known BTEX source zone is upgradient of the CVOC source zone. FIGURE 9C Excerpt of the UoG1 montage (Figure 4) from masl highlighting diffusion of contaminants into a lower permeability zone. A diffusion halo of Ethylbenzene can be observed originating from the Page 42

49 preferential contaminant migration pathway below, while diffusion haloes of CVOCs have formed from the NAPL accumulation zone (illustrated in Figure 8) above. FIGURE 10 Montages as described in Figures 4 and 5 compared side-by-side, with UoG1 shifted 25.2m downward for lithological alignment. When lithologically aligned, the hydraulically defined hydrogeologic units identified at each location correspond closely with one another. Based on the lateral arrival of contaminants at UoG2, preferential contaminant migration pathways were identified, shaded in green and projected onto the corresponding migration units at UoG1. Many of the preferential contaminant migration pathways at UoG1 tend to show presence of contaminants from other sources (BTEX) located up-gradient. Intermediate contaminant migration pathways, where significant contamination has not yet arrived at UoG2 were shaded in yellow and projected onto the corresponding migration units at UoG1. The intermediate contaminant migration pathways presumably have a lower lateral hydraulic conductivity or other significant attenuating properties. Aquitards, over which a notable hydraulic gradient occurs and which tend to exhibit little or no lateral arrival of contaminants in UoG2 are indicated in red and projected onto the corresponding contaminant migration units at UoG1. FIGURE 11 Schematic of the hydrogeological conceptual model for the study area showing fragmented faulting with smearing of the clayey aquitards as opposed to a single abrupt break and shift in the lithology. The figure depicts a longsect through UoG1 and UoG2. To the far left (South) the BTEXS source zone sits at a location where the bedrock geology was is uplifted and the upper 5 aquitards observed at UoG1 are absent. UoG1 is located directly in the CVOC source zone where the DNAPL has entered the ground from multiple sources. It pools at capillary barriers and spreads out laterally atop those interfaces. While the majority of the contaminant mass is stuck in the low permeability, high foc smdt clay, which now acts as Page 43

50 a long term secondary source, DNAPL has also travelled deep into the system, penetrating through at least the four topmost aquitards. Lateral migration occurs through preferential and to a lesser degree intermediate contamination migration pathways, with CVOC contamination and in the fastest migration pathways, BTEXS contamination from up gradient, reaching UoG2. Page 44

51 Column Descrptions for Montages (Figures 4, 5, 9 and 10) A B C Elevation in metres above sea level Rock Core Data Wireline geophysical logs 1 Existing litholostratigraphically derived framework 2 Primary munsell colour 3 Primary lithological material Rock Quality Designation (RQD). Calculted as the sum of the 4 lengths of intact core longer than 10cm, divided by the total length of core recovered in a given core run. Fracture/feature frequency log. Number of fractures, vugs, 5 rubble zones per 25cm, calculated every 1cm. Natural gamma (tan-blue gradient shading) with neutronneutron (Red line) overlain. 1 Active line source (ALS) flow interpretation log. Pink = high, 2 blue = medium, green = low flow zones. a Horizontal and low angle fractures <30 from horizontal b Vertical and high angle fractures >30 from horizontal D Hydraulic head data from manual measurements taken in a FLUTe multilevel system (MLS) installed in the borehole. Major hydrolgeologic units overlain and shaded. Dark grey indicates aquitards. 1 2 Hydraulic head profiles generated by plotting the head in masl on the X-axis vs. the midpoint of the port screen on the Y-axis. Screened intervals are indicated by I-bars. Maximum hydraulic head gradient between MLS ports. Calculated as the difference in head (m) divided by the length (m) of the unscreened interval between the two ports. a Measurements collected in April 2013 b Measurements collected in October BTEX+S Chlorinated methanes a % of total cumulative mass with depth Gradient of % of total cumulative mass with depth. Benzene; Toluene; Ethylbenzene; Xylene; b Styrene a % of total cumulative mass with depth Gradient of % of total cumulative mass with depth. Carbon tetrachloride; Chloroform; b Dichloromethane; Chrloromethane. a % of total cumulative mass with depth E Rock core VOC data overlain by contaminant migration zones indicated by dashed lines. 3 4 Chlorinated ethanes Chlorinated ethenes b Gradient of % of total cumulative mass with depth. Hexachloroethane; Pentachloroethane; 1,1,1,2- Tetrachloroethane; 1,1,2,2-Tetrachloroethane; 1,1,1-Trichloroethane; 1,1,2-Trichloroethane; 1,1- Dichloroethane; 1,2-Dichloroethane; Chloroethane. a % of total cumulative mass with depth b Gradient of % of total cumulative mass with depth. Tetrachloroethene; Trichloroethene; 1,1- Dichrloroethene; Cis-dichloroethene; Trans-dichloroethene; Vinyl chloride. 5 6 chlorinated compounds Mass of contaminants (ug) per mass of wet rock (g) a % of total cumulative mass with depth Gradient of % of total cumulative mass with depth. 1,2-Dichloropropane; Bis(2-chloroisopropyl) b ether. a Sum of chlorinated hydrocarbons (CHCs) b Sum of BTEX+S 7 NAPL likely present based on phase partitioning estimates from NAPLANAL Page 45

52 Table 1: Physiochemical Properties of Schkopau Analytes 1 Molecular Mass 1 Density 1 Solubility 1 Solubility 2 log Kow ( 3 Koc Compound 1 CAS No. (g/mol) (g/cm 3 ) (mg/l) (mol/l) ) (L/Kg) 1,1,1,2 TCA E E ,1,1 TCA E E ,1,2,2 TCA E E ,1,2 TCA E E ,1 DCA E E ,1 DCE E E ,2 DCA E E ,2 Dichloropropane E E Benzene E E Bis(2 chloroisopropyl) ether E E c DCE E E CF E E Chloroethane E E Chloromethane E E CT E E DCM E E Ethylbenzene E E Hexachloroethane E E m+p Xylene E E o Xylene E E PCE E E Pentachloroethane E E Styrene E E TCE E E t DCE E E Toluene E E VC E E Sources 1 United States Environmental Protection Agency Regions 3, 6, and 9. Accessed January 18, Regional Screening Levels for Chemical Contaminants at Superfund Sites. Retrieved from website: 2 Mackay, D., Shiu, W. Y., Ma, K., & Lee, S. C. (2007).Handbook Of Physical Chemical Properties And Environmental Fate For Organic Chemicals(2nd ed.). Boca Raton, FL, USA: CRC Press Taylor & Francis Group. 3 Calculated from log K ow using the equation logk oc =0.7919K ow except Styrene where logk oc =0.983K ow was used because it is considered semi volatile. (US EPA. United States Environmental Protection Agency, Office of Solid Waste and Emergency Response: Superfund. (1996). Soil screening guidance: Technical background document table of contents. part 5 (EPA/540/R 95/128). Retrieved from website: Page 46

53 Table 2: Physical Properties Sample Category Average Values Category Number of Samples Specific Gravity Porosity ρ dry (g/cm 3 ) ρ sat (g/cm 3 ) % Inorganic Carbon % Organic Carbon % Total Carbon No. Samples % Clay (<0.002mm) 1 Average Grain Size Distribution % Silt (<0.063mm) % Fine Sand (<0.2mm) % Medium Sand (<0.63mm) 0 0 % Coarse Sand (<2.0mm) Category Description Crumbly pinkish grey coarse grained porous sandstone Hard grey/tan med grained sandstone visible porosity Very hard pinkish grey/tan med fine grained 0 sandstone (low visible porosity) Loosely cemented white sandstone with orange staining Light grey fine grained silty sandstone Loosely cemented grey fine to medium sand, trace clay Light grey clayey silt and sand, orange 0 staining Very light coloured sandy silt and clay Hard bluish grey sandy clay Hard red sandy clay Massive unconsolidated greenish sandy plastic clay Red sandy clayey shale Bluish grey plastic clay Greenish/bluish grey shaley clay Dark grey well bedded clayey shale 1 Grain size categories based on Geotechnical investigation and testing Identification and classification of soil Part 1: Identification and description. ISO :2002. Accessed March 15, Page 47

54 Figure 1: Site Map SCHKOPAU UoG2 UoG1 1 km N Page 48

55 Figure 2: Area of Investigation ~ ", Dow Olefinverbund GmbH Schkopou, Germany Mop of UoG Borehole Loco tlons DATE: March 10, 2012 GENERATED BY: R.J. STUETZLE Page 49

56 Figure 3: Cross Section Page 50

57 Figure 4: UoG1 Montage Page 51

58 Figure 5: UoG2 Montage Page 52

59 Figure 6: Geologic Summary Table Aquifer No. Abbreviation Name Dominant Lithology Core Photo Features/Fractures 10cm A Fill 2 smh Hardegsen Reddish brown and greyish brown sand and gravel. Light grey uncemented clayey fine sand, sections of increased clay content showing a greenish tint. A smdt Detfurth Clay Green to dark grey shaley clay with some sandy interbeds. B 3.1 smd'st Detfurth Alternating Sequence (Wechselfolge) Bluish grey clay and shale alternating with pinkish grey and tan medium grained sand and sandstone. 3.2o smdob smdz Detfurth Sandstone Overbank (Oberbank) Detfurth Intermediate Unit (Zwischenmittel) Sequences of light grey coarse to medium sandstone fining upwards to bluish grey clay. Occasional red and bluish grey clay beds. Red clayey fine sandstone with tan fine sandstone mottling and interbeds. C 3.2u smdub smva'ts Detfurth Sandstone Sub-bank (Unterbank) Volpriehausen Avicula Layers Sequences of light grey coarse to medium sandstone fining upwards to bluish grey clay. Occasional red and bluish grey clay beds. Pinkish grey to light yellow sandstone of varying grainsize thinly interbedded with bluish grey and red shales. D Page 53

60 Figure 7: Conventional Monitoring Well Clusters vs. FLUTe MLS at UoG1 100m 90m Cluster m 95.10m Cluster m 94.52m Hydraulic Head Profile: Conventional Well Clusters vs UoG1 FLUTe MLS Water FLUTe MLS UoG1 Elevation (masl) 80m 70m 60m 50m 40m 30m 82.92m 85.25m A (Fill) smdt smd st smdob smdz smdub Filter Pack Midpoint Elevation (masl) 20m smva ts smva s Hydraulic Head (masl) Sand pack locations for 3981 and 3982 are unknown but estimated at 4m above top of screen, based on other wells in the same series. Cluster 1 stratigraphy is based on depths at 3981 from Figure (Fugro, 2010), smdob, smdz and smdub were identified as a single lithostratigraphic unit when the cluster was installed. Locations of these units were estimated based on their thicknesses at Cluster 2. Cluster 2 stratigraphy is based on the borehole log for Distance between wells in each cluster ~1m Page 54

61 Figure 8: Accumulation, Lateral Spreading and Mixing of DNAPL A SOURCE (DNAPL 1) UoG1 SOURCE (DNAPL 2) NAPL Composition in Rock Core Samples DS % PCE 34% TCE 4% Hexachloroethane 3% 1,1,2,2,-TeCA <1% DS % TCE 46% PCE 2% 1,1,2,2,-TeCA <1% smdt DS % PCE 36% TCE <1% GW Aquitard DS % TCE 44% PCE <1% smd st GW DS % TCE 31% 1,1,2,2,-TeCA 14% Vinyl Chloride 8% PCE 11% Page 55

62 Fi gur e9a Fi gur e9b Fi gur e9c Page 56

63 Figure 10: Stratigraphically Aligned Montage of Logs from UoG1 and UoG2 Page 57

64 Figure 11: Schematic Cross-section of the Process Based Site Conceptual Model UoG1 UoG2 BTEX CVOC CVOC CVOC BTEXS Page 58

65 Appendix A: Physical Property Samples Of the 59 samples collected from the core for the analysis of physical properties, 38 were chosen for analysis to represent all of the lithology types observed in the continuous core at the two borehole locations. Provided herein are: A table of the results for each sample; the lab reports from Golder and UoG for the physical properties and carbon analyses respectively; and profiles of specific gravity, porosity and % organic carbon with depth for UoG1 and UoG2, with measured values displayed as a solid square and inferred values assigned by lithology type shown as hollow circles. Page 59

66 Physical Properties Samples Selected for Analysis (Appendix A) Moisture Top Bottom Length Water Specific Porosity % Carbon %Clay %Silt % Fine Sand % Med. Sand % Coarse Sand Sample ID Preserved? Depth (m) Depth (m) (m) Geo. Unit Content (%) Gravity Trial 1 Trial 2 Average Inorganic Organic Total Category <0.002mm <0.063mm <0.2mm <0.63mm <2.0mm UoG1 PP001 Y smd'st 13.20% <0.01% <0.01% <0.01% 2 UoG1 PP002 Y smd'st 14.10% <0.01% UoG1 PP003 Y smdob 15.90% <0.01% UoG1 PP004 Y smdz 12.30% <0.01% UoG1 PP005 Y smdub 10.20% <0.01% UoG1 PP007 N smva'ts 12.30% N/A 0.27 <0.01% UoG1 PP008 N smva'ts 3.80% <0.01% <0.01% <0.01% 5 UoG1 PP009 N smva'ts 0.02% <0.01% UoG1 PP010 N smva'ts 12.10% N/A UoG1 PP012 N smdub 16.80% <0.01% UoG1 PP014 N smdub 0.10% <0.01% <0.01% <0.01% 6 UoG1 PP016 N smdub 3.40% <0.01% <0.01% <0.01% 6 UoG1 PP017 N smdz 8.90% UoG1 PP021 N smdob 8.20% <0.01% UoG1 PP022 N smdob 0.10% N/A 0.27 <0.01% <0.01% <0.01% 6 UoG1 PP023 N smdob 8.70% UoG1 PP024 N smdob 0.30% N/A 0.3 <0.01% UoG1 PP025 N smdob 0.50% <0.01% UoG1 PP026 N smdob 4.00% <0.01% UoG1 PP028 N smd'st 5.00% <0.01% UoG1 PP031 N smd'st 14.70% <0.01% UoG1 PP032 N smdt 14.20% <0.01% UoG1 PP034 N smdt 10.20% <0.01% UoG1 PP035 N smdt 8.10% <0.01% UoG1 PP036 N smdt 10.10% <0.01% UoG1 PP037 N smdt 8.00% UoG1 PP100 N smdt 8.50% <0.01% DUPLICATE OF UoG1 PP034 UoG2 PP001 Y smdt 12.60% UoG2 PP002 Y smdt 10.40% UoG2 PP003 Y smdob 11.70% <0.01% <0.01% <0.01% UoG2 PP005 N smh 16.70% <0.01% UoG2 PP007 N smh 16.30% <0.01% UoG2 PP009 N smh 10.30% <0.01% <0.01% <0.01% UoG2 PP012 N smh 16.90% UoG2 PP013 N smdt 5.40% UoG2 PP015 N smd'st 3.30% <0.01% <0.01% <0.01% 3 UoG2 PP017 N smdz 11.30% <0.01% UoG2 PP100 Y smdt 11.30% <0.01% DUPLICATE OF UoG2 PP001 Page 60

67 cj'golder ~ Associates February 19, 2013 Project No Mr. Robert Stuetzle University of Guelph - School of Engineering 50 Stone Road East Guelph, Ontario N1G 2W1 GEOTECHNICAL LABORATORY TESTING Dear Sir This letter reports the results of laboratory testing carried out on the samples received at our office in Mississauga. The resu lts of the tests are summarized in the attached tables and figures. The testing services reported herein have been performed in accordance with the indicated recognized standard, unless noted otherwise. This report is for the sole use of the designated client. This report constitutes a testing service only and does not represent any results interpretation or opinion regarding specification compliance or material suitability. We trust that the results are sufficient for your current requirements. If you have any questions, please do not hesitate to call us. Yours truly GOLDER ASSOCIATES LTD. J'~~JJ9~ Marijana Manojlovic Laboratory Manager MM/ig Golder Associates Ltd Argentia Road, Mississauga, On tario, Canada L5N 5Z7 Tel: + 1 (905) Fax: +1 (905) Golder Associates: Operations in Africa, Asia, Australasia, Europe, North America and South America Golder, Golder Associates and the GA globe design are trademarks of Golder Associates Corporation. Page 61

68 DENSITY AND POROSITY DETERMINATIONS OF IRREGULAR SHAPE SAMPLES ASTM D TEST METHOD B Sample Number UoG1-PP1 (Trial 1) UoG1-PP1 (Trial 2) UoG1-PP2 (Trial 1) Wet Mass of Rock in Air, Wet Mass of Rock + Wax in Air, Wet Mass of Rock + Wax in Water, Weight of Wax, Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, % Unit Weight, kn/m Dry Unit Weight, kn/m Sample Number UoG1-PP3 (Trial 1) UoG1-PP3 (Trial 2) UoG1-PP4 (Trial 1) Wet Mass of Rock in Air, Wet Mass of Rock + Wax in Air, Wet Mass of Rock + Wax in Water, Weight of Wax, Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, % Unit Weight, kn/m Dry Unit Weight, kn/m UoG1-PP2 (Trial 2) UoG1-PP4 (Trial 2) Project Number Tested By Date Tested January, 2013 Checked By Ian I Bobby J{JJ Golder Associates Page 62

69 DENSITY AND POROSITY DETERMINATIONS OF IRREGULAR SHAPE SAMPLES ASTM D TEST METHOD B Sample Number UoG1-PP5 (Trial 1) UoG1-PP5 (Trial 2) UoG1-PP7 (Trial 1) Wet Mass of Rock in Air, Wet Mass of Rock + Wax in Air, Wet Mass of Rock + Wax in Water, Weight of Wax, Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, % Unit Weight, kn/m Dry Unit Weight, kn/m Sample Number UoG1-PP8 (Trial 1) UoG1-PP8 (Trial 2) UoG1-PP9 (Trial 1) Wet Mass of Rock in Air, Wet Mass of Rock + Wax in Air, Wet Mass of Rqck + Wax in Water, Weight of Wax, Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, % Unit Weight, kn/m Dry Unit Weight, kn/m UoG1-PP7 (Trial 2) insufficient material UoG1-PP9 (Trial 2) Project Number Tested By Date Tested January, 2013 Checked By Ian I Bobby J;~ Golder Associates Page 63

70 DENSITY AND POROSITY DETERMINATIONS OF IRREGULAR SHAPE SAMPLES ASTM D TEST METHOD B Sample Number UoG1-PP10 (Trial 1) UoG1-PP10 (Trial 2) UoG1-PP12 (Trial 1) Wet Mass of Rock in Air, insufficient material Wet Mass of Rock + Wax in Air, Wet Mass of Rock + Wax in Water, Weight of Wax, Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, % Unit Weight, kn/m Dry Unit Weight, kn/m Sample Number UoG1-PP14 (Trial 1) UoG1-PP14 (Trial 2) UoG1-PP16 (Trial 1) Wet Mass of Rock in Air, Wet Mass of Rock + Wax in Air, Wet Mass of Rock + Wax in Water, Weight of Wax, Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, % Unit Weight, kn/m Dry Unit Weight, kn/m UoG1-PP12 (Trial 2) UoG1-PP16 (Trial 2) Project Number Tested By Date Tested January, 2013 Checked By Ian I Bobby --4J.t Golder Associates Page 64

71 DENSITY AND POROSITY DETERMINATIONS OF IRREGULAR SHAPE SAMPLES ASTM D TEST METHOD B Sample Number UoG1-PP17 (Trial 1) UoG1-PP17 (Trial 2) UoG1-PP21 (Trial 1) Wet Mass of Rock in Air, Wet Mass of Rock + Wax in Air, g Wet Mass of Rock + Wax in Water, Weight of Wax, Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, " Unit Weight, kn/m Dry Unit Weight, kn/m Sample Number UoG1-PP22 (Trial 1) UoG1-PP22 (Trial 2) UoG1-PP23 (Trial 1) Wet Mass of Rock in Air, insufficient material Wet Mass of Rock + Wax in Air, Wet Mass of Rock + Wax in Water, Weight of Wax, Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, " Unit Weight, kn/m Dry Unit Weight, kn/m UoG1-PP21 (Trial 2) UoG1-PP23 (Trial 2) Project Number Tested By Date Tested January, 2013 Checked By Ian I Bobby JJJj Golder Associates Page 65

72 DENSITY AND POROSITY DETERMINATIONS OF IRREGULAR SHAPE SAMPLES ASTM D TEST METHOD B Sample Number UoG1-PP24 (Trial 1) UoG1-PP24 (Trial 2) UoG1-PP25 (Trial 1) Wet Mass of Rock in Air, insufficient material Wet Mass of Rock + Wax in Air, Wet Mass of Rock + Wax in Water, Weight of Wax, Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, " Unit Weight, kn/m Dry Unit Weight, kn/m Sample Number UoG1-PP26 (Trial 1) UoG1-PP26 (Trial 2) UoG1-PP28 (Trial 1) Wet Mass of Rock in Air, Wet Mass of Rock + Wax in Air, Wet Mass of Rock + Wax in Water, Weight of Wax, Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, " Unit Weight, kn/m Dry Unit Weight, kn/m UoG1-PP25 (Trial 2) UoG1-PP28 (Trial 2) Project Number Tested By Date Tested January, 2013 Checked By Ian I Bobby ~~ Golder Associates Page 66

73 DENSITY AND POROSITY DETERMINATIONS OF IRREGULAR SHAPE SAMPLES ASTM D TEST METHOD B Sample Number UoG1-PP31 (Trial 1) UoG1-PP31 (Trial 2) UoG1-PP32 (Trial 1) Wet Mass of Rock in Air, g Wet Mass of Rock + Wax in Air, g Wet Mass of Rock + Wax in Water, g Weight of Wax, g Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, % Unit Weight, kn/m Dry Unit Weight, kn/m Sample Number UoG1-PP34 (Trial 1) UoG1-PP34 (Trial 2) UoG1-PP35 (Trial 1) Wet Mass of Rock in Air, Wet Mass of Rock + Wax in Air, g Wet Mass of Rock + Wax in Water, g Weight of Wax, g Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, % Unit Weight, kn/m Dry Unit Weight, kn/m UoG1-PP32 (Trial 2) UoG1-PP35 (Trial 2) Project Number Tested By Date Tested January, 2013 Checked By Ian I Bobby Jw Golder Associates Page 67

74 DENSITY AND POROSITY DETERMINATIONS OF IRREGULAR SHAPE SAMPLES ASTM D TEST METHOD B Sample Number UoG1-PP36 (Trial 1) UoG1-PP36 (Trial 2) UoG1-PP37 (Trial 1) Wet Mass of Rock in Air, Wet Mass of Rock + Wax in Air, Wet Mass of Rock + Wax in Water, Weight of Wax, Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, % Unit Weight, kn/m Dry Unit Weight, kn/m UoG1-PP37 (Trial 2) Sample Number UoG1-PP100 (Trial 1) UoG1-PP100 (Trial 2) Wet Mass of Rock in Air, Wet Mass of Rock + Wax in Air, Wet Mass of Rock + Wax in Water, Weight of Wax, Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, % Unit Weight, kn/m Dry Unit Weight, kn/m Project Number Tested By Date Tested January, 2013 Checked By l~obby Golder Associates Page 68

75 DENSITY AND POROSITY DETERMINATIONS OF IRREGULAR SHAPE SAMPLES ASTM D TEST METHOD B Sample Number UoG2-PP1 (Trial 1) UoG2-PP1 (Trial 2) UoG2-PP2 (Trial 1) Wet Mass of Rock in Air, Wet Mass of Rock + Wax in Air, Wet Mass of Rock + Wax in Water, Weight of Wax, Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, % Unit Weight, kn/m Dry Unit Weight, kn/m Sample Number UoG2-PP3 (Trial 1) UoG2-PP3 (Trial 2) UoG2-PP5 (Trial 1) Wet Mass of Rock in Air, Wet Mass of Rock + Wax in Air, Wet Mass of Rock + Wax in Water, Weight of Wax, Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, % Unit Weight, kn/m Dry Unit Weight, kn/m UoG2-PP2 (Trial 2) UoG2-PP5 (Trial 2) Project Number Tested By Date Tested 1/15/2013 Checked By Ian 1 Bobby Jt~ Golder Associates Page 69

76 DENSITY AND POROSITY DETERMINATIONS OF IRREGULAR SHAPE SAMPLES ASTM D TEST METHOD B Sample Number UoG2-PP7 (Trial 1) UoG2-PP7 (Trial 2) UoG2-PP9 (Trial 1) Wet Mass of Rock in Air, Wet Mass of Rock + Wax in Air, Wet Mass of Rock + Wax in Water, Weight of Wax, Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, % Unit Weight, kn/m Dry Unit Weight, kn/m Sample Number UoG2-PP12 (Trial 1) UoG2-PP12 (Trial 2) UoG2-PP13 (Trial 1) Wet Mass of Rock in Air, Wet Mass of Rock + Wax in Air, Wet Mass of Rock + Wax in Water, Weight of Wax, Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, % Unit Weight, kn/m Dry Unit Weight, kn/m UoG2-PP9 (Trial 2) UoG2-PP13 (Trial 2) Project Number Tested By Date Tested 1/15/2013 Checked By Ian I Bobby J{~ Golder Associates Page 70

77 DENSITY AND POROSITY DETERMINATIONS OF IRREGULAR SHAPE SAMPLES ASTM D TEST METHOD B Sample Number UoG2-PP15 (Trial 1) UoG2-PP15 (Trial 2) UoG2-PP17 (Trial 1) Wet Mass of Rock in Air, Wet Mass of Rock + Wax in Air, Wet Mass of Rock + Wax in Water, Weight of Wax, Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, % Unit Weight, kn/m Dry Unit Weight, kn/m UoG2-PP17 (Trial 2) Sample Number UoG2-PP100 (Trial 1) UoG2-PP100 (Trial 2) Wet Mass of Rock in Air, Wet Mass of Rock + Wax in Air, Wet Mass of Rock + Wax in Water, Weight of Wax, Displaced Volume, cm Displaced Wax, cm Volume of Rock, cm Specific Gravity, measured Volume of Solids, cm Volume of Voids, cm Porosity Water Content, % Unit Weight, kn/m Dry Unit Weight, kn/m Project Number Tested By Date Tested 1/15/2013 Checked By Ian I Bobby ~ Golder Associates Page 71

78 SPECIFIC GRAVITY TEST RESUL TS ASTM D TEST METHOD A PROJECT NUMBER PROJECT NAME U of Guelph School of Engineering DATE TESTED February, 2013 Sample No. Specific Gravity UoG1-PP UoG1-PP UoG1-PP UoG1-PP UoG1-PP UoG1-PP UoG1-PP UoG1-PP UoG1-PP UoG1-PP UoG1-PP UoG1-PP UoG1-PP UoG1-PP UoG1-PP UoG1-PP UoG1-PP UoG1-PP UoG1-PP UoG1-PP UoG1-PP Checked By: ~..u Golder Associates Page 72

79 SPECIFIC GRAVITY TEST RESULTS ASTM D TEST METHOD A PROJECT NUMBER PROJECT NAME DATE TESTED U of Guelph School of Engineering February, 2013 Sample No. UoG1-PP32 UoG1-PP34 UoG1-PP35 UoG1-PP36 UoG1-PP37 UoG1-PP100 UoG2-PP1 UoG2-PP2 UoG2-PP3 UoG2-PP5 UoG2-PP7 UoG2-PP9 UoG2-PP12 UoG2-PP13 UoG2-PP15 UoG2-PP17 UoG2-PP100 Specific Gravity Checked By: ~ J.J Golder Associates Page 73

80 GRAIN SIZE DISTRIBUTION FIGURE Size of openings, inches U.S.S Sieve size, meshes/inch 6"4)1," 3" 1%" 1"%" %"3/8" z <C :z:: I a: W z ii: 50 I- Z W 0 40 a: w D GRAIN SIZE, mm LEGEND SYMBOL SAMPLE UoG1-PP3 Project Number: Checked BY: ~~- Golder Associates Date: 13-Feb-13 Page 74

81 GRAIN SIZE DISTRIBUTION FIGURE Size of openings. inches S"4W 3" 1W' 1"0/." Y,"318" 3 4 U.S.S Sieve size. meshes/inch z c( :I: I- a::: W Z u:: I Z W ~ W GRAIN SIZE, mm e 'j------t I ' ~.-~ COBBLE, COARSE! FINE I COARSE' MEDIUM I FINE I SILT AND CLAY SIZES :r=-:::.l J r SIZE l GRAVEL SIZE SAND SIZE i FINE GRAINED L. ~..._.... LEGEND SYMBOL SAMPLE UoG1-PP5 Project Number: vb~ Checked By:.._..... Golder Associates Date: 13-Feb-13 Page 75

82 GRAIN SIZE DISTRIBUTION FIGURE Size of openings, inches U.S.S Sieve size, meshes/inch 6"4W' 3" 1Y,!' 1"%" )4"3/8" z c( :I: I- It:: w Z u:: I Z W o It:: w a GRAIN SIZE, mm LEGEND SYMBOL SAMPLE UoG1-PP21 Project Number: ~~ Checked By: Golder Associates Date: 28-Jan-13 Page 76

83 1 :11! i GRAIN SIZE DISTRIBUTION FIGURE Size of openings, inches U.S.S Sieve size, meshes/inch z ct ::I: I- It: w Z u::: I- Z W 0 It: w D SO "414" 3" 1W' 1"%" W'31S" I!i Ii ,1 r I r II III II! i 1III i II Iii III I i 111 ['III II' ' It 1+- III I III II,! 'I,! 'I I :11:,Ii i j II i,\i I III Illr' Ilill!!, Iii! 11"" r- I : I III I Ii Ii i III III I 1-\ _ II, I II i III I i ~L Ii I11I i I Ii!!TTltrf I!I j,1 i~i'i! I]!1!il,111 II jill 1,1 i I!I ~I 1 I,:",,1 1 I 1,----'++H-I!+--f-+-+~1 +-H+H-+- I I I t.f!ll!ll! illl II II!' III I _-+-- I " I I t II Ii 1 iillll! i 1 '~,irlll I 1,1 II i I I i I Ii, III-H-_ 'III I' II' "'I II1II i I! :1111 1, '. 'lil'l I I II:m, i I III, I-+--i- I1I11 ',11,'11'! II 'ii I I1II I r! II! I ~ I illii.: I III i I I! t----++!+-h t'ttll++-1' -+1 -Httt+tt~l I i I Il III i! +-U.' I! II I I I I i Ii III I ,1 I I' Iii III, l i Ii II! 1,11,1 II! I,,,', 1,1!,' i 'III' Iii.llii,! I, I,! ~_~lllijl," I 't+,i, --H III 1 I I ti+ i i,i i + ' "-- III, i ++--~ I,jl!1111 1II1I Ii ] [ Illll! !,ill!!i!i~11 i, II!IIIIIIIW-'! 1'1,1 1 jl I ft' I -1i::' i ';1' It-H 'II'I;;!: I!:I i i I I IIIII!! i ' : - I,,',II, i,iii! I I 1, 'I,,' I I ' I i I! II'I I! Ii i, I", I I I' III' -Ii! I I I I1II Ii [I I I, i I Iii!,,! II I ill I -! I Ii' Ii Ii 'I II!, Ii' j 'll II i GRAIN SIZE, mm COB;LE:I-- i COAR~~COA~~L MEDIUM I FINE t--t SILTANDCLAYSIZES-----~- --,-- --~~ ~~ SIZE I, GRAVEL SIZE SAND SIZE L-. FINE GRAINED _ LEGEND SYMBOL SAMPLE UoG1-PP25 Project Number: ~~ Checked By: Golder Associates Date: 2S-Jan-13 Page 77

84 I I' GRAIN SIZE DISTRIBUTION FIGURE Size of openings, inches U.S.S Sieve size, meshes/inch 6"414" 3" 1)1," 1"%" )1,"3/8" '~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ;1 II II It II I I I Illrni\ i 1I111 I I,I! I I 90 1 ; r-~i -fill :1 II t-i1~11 j\ ; I i i L~--++I il~! ' IIIII I I II II Z 70 1 II I. +'] Ii! VI i II : II1II I I I I I ' I I!II I III ~ j i', Illftl III, It II I I fit I 'I \ d I I! I I SO' 'I L I,II i I I _ IIIII! 1-N----t+H H-+-t---I-t+I i' r t---t ;1 1 Iii 1'.,Jjlll I il!ii'1 I'~ I, II I '!,t i# ~.. 'I r- f i I ~ II i I ~ I i I _-++++' +H, l-+-t--+--I! ::1] I : i i!! I n -\ ~ t l, 11- i ,rr-IIII ;++... I*.' it I~ +-+, HI-il--+-mill++I-+-+-+I ! I I, II I,-+- jill, I, " I I f, I' I, +l ! ljw j II i --If Ij i+1-t-!,i H I--ii--+j -f-h-h;, " '-"'11-,', ih r++i H 1! 1 II 20 1IIIIIIi.. lillllll 1111!14,I tlll J... III1II1I!I' --H-+ I! ---I +t++-t--+ I I iii ' --l I! I I, i ~...J..i --I.I.iiJ..I.lll.J-III...J.I-JI---I,I...uII... i I..I-I..J...J- 11-=-:,+++ il IJ.J., i +-1:1 ~...u+++ill.j..i..+-+-ii.i..i..i+-+ 1 II :11..- ~J.J.-I c----._-h~~ii..ui:t--+i' ~~..I..I~--I 1 :L-!---U.JII..I..i i! I ;u.i..i GRAIN SIZE, mm t l L----+-t ~~~----- COBBLE~~.:'ARSE..l.. FINE icoarse! MEDIUM I FINE SILT AND CLAY SIZES SIZE I GRAVEL SIZE.L.. SAND SIZE r,i +-+-J...J.: ' ~_~ GRAINED ~ LEGEND -----_.._ ~------~ ~--.- SYMBOL SAMPLE UoG2-PP3 Golder Associates Date: 2S-J an-13 Page 78

85 I!illm+i--t rrt I. GRAIN SIZE DISTRIBUTION FIGURE Size of openings, inches U.S.S Sieve size, meshes/inch 6"4W' 3" 1%" 1"0/." %"3/8" ~~~~~~~~~~~~~~~~~~~~~~--~~~~ II i II i I I , I,! I r I r Itt~,,~ I I I : I i I : 1+ I J 1 I [~ 'I 1 I, III!'lli!! I i III 1,1 11,1 I II I II *H" 80r-'-1 --]- Ililllllll' I I II!! I,: I I '1I1 I!!' I I 701-_~-"i I! 1++ :;!III'I! ' I! ~I ~l+~ ii! l\! ' IIIII!! I Iii, I' i Iii! \',,illh++- II II I I g 60 1ITIT1+l1 ih.j i ' I ffi I i!ii II I I II!, I I I III II I III ~ 50 I iii :,1 ~ 40--ttf4-W--! III I I i II I rr,j j :11 '1 i Iii II 1-'1 I, iii I I: i II t---+i++-i I 1:+ 1 l, 11 Hi -+-' I,-L----U+' I II I I t-t--+-t+t+;:~+++-i--++t++-h-+---r---i :++tt-t- --*1 d+-ii ' I! I, I! I I, I I I ' I II 1 1I,Ittmi i I I il!1 II I! i I III! 1 ill i,'ii 1 i I I' 1"11 \ I I',I I '1Iill+++' I II 1 til" I III I.. illl' 20[----<rIT l ':' " I '1 mttt I II, ~ _/lllli_!!u II III ill Llilli! I 'I Iii! IIIIIII!, I 1 II1I I! II - -ml : 10 --nt1+-+!:. I: ill! : i 1 t~i+ i W t-t--it1 III II 1 II!! I" I I II, /1 : i,l: ; I I,,1, , II " i Illi I r! I I Ii IIIII I I III, I! 1I1II1 I i 1IIII11 i i o~~~~~~~~~--~~~~~~~~~~~~--~~~~ GRAIN SIZE, mm LEGEND SYMBOL SAMPLE UoG2-PP5 Golder Associates Date: 28-Jan-13 Page 79

86 GRAIN SIZE DISTRIBUTION FIGURE Size of openings, inches U.S.S Sieve size, meshes/inch 6"4%,'3" 114" 1"%,' %"3/8" z «J: ~ a: w z u:: ~ z w ~ W D GRAIN SIZE, mm I ',. I --l ~OBB~~~~sEt--~~---lcOA~tMEo,uM.l. FI~~~+-_==--= SILT A;~~YSIZ~~-=.. - S~-- GRAVEL SIZE! SAND SIZE! FINE GRAINED ~ ~ I LEGEND SYMBOL SAMPLE UoG2-PP7 Project Number: )) Checked By: _ ~_ Golder Associates Date: 13-Feb-13 Page 80

87 GRAIN SIZE DISTRIBUTION FIGURE Size of openings, inches U.S.S Sieve size, meshes/inch 6"4Y,"3" 114"1"0/."%"3/8" GRAIN SIZE, mm LEGEND _._----._ _._-----_._-_._ _._ SYMBOL SAMPLE UoG2-PP9 Project Number: ~ Checked By:.._..._... Golder Associates Date: 28-Jan-13 Page 81

88 REVISED FINAL Submission# Reported: Report Feb-25 Agriculture and Food Laboratory Submitted By: UNIVERSITY OF GUELPH CPES - ENGINEERING ROBERT STUETZLE 50 STONE ROAD WEST DAY HALL ROOM 209B GUELPH, ON Owner: BETH PARKER Phone: Sampling Date: Not given Received Date: 2012-Dec-18 Quotation #: QI0215 Carbon Package Date Authorized: 2013-Feb-25 12:14 Rev* = REVISED Sample ID Client Sample ID Specimen Sampling date / time Test Result Note 0001 UOG1-PP1 Total Carbon 0.00 Rev* 0001 UOG1-PP1 Inorganic Carbon 0.00 Rev* 0001 UOG1-PP1 Organic Carbon <0.01 Rev* 0002 UOG1-PP2 Total Carbon Rev* 0002 UOG1-PP2 Inorganic Carbon 0.00 Rev* 0002 UOG1-PP2 Organic Carbon Rev* 0003 UOG1-PP3 Total Carbon Rev* 0003 UOG1-PP3 Inorganic Carbon 0.00 Rev* 0003 UOG1-PP3 Organic Carbon Rev* 0004 UOG1-PP4 Total Carbon Rev* 0004 UOG1-PP4 Inorganic Carbon 0.00 Rev* 0004 UOG1-PP4 Organic Carbon Rev* 0005 UOG1-PP5 Total Carbon Rev* 0005 UOG1-PP5 Inorganic Carbon 0.00 Rev* 0005 UOG1-PP5 Organic Carbon Rev* 0006 UOG1-PP7 Total Carbon Rev* 0006 UOG1-PP7 Inorganic Carbon 0.00 Rev* 0006 UOG1-PP7 Organic Carbon Rev* 0007 UOG1-PP8 Total Carbon 0.00 Rev* 0007 UOG1-PP8 Inorganic Carbon 0.00 Rev* 0007 UOG1-PP8 Organic Carbon <0.01 Rev* 0008 UOG1-PP9 Total Carbon Rev* See Below 0008 UOG1-PP9 Inorganic Carbon 0.00 Rev* Agriculture and Food Laboratory - Guelph, ON N1H 8J7 - Page 1 of 5 Printed: 2013-Feb-25 Page 82

89 REVISED FINAL Report Submission# Reported: 2013-Feb-25 Carbon Package...Continued Date Authorized: 2013-Feb-25 12:14 Rev* = REVISED 0008 UOG1-PP9 Organic Carbon Rev* 0009 UOG1-PP10 Total Carbon Rev* 0009 UOG1-PP10 Inorganic Carbon Rev* 0009 UOG1-PP10 Organic Carbon Rev* 0010 UOG1-PP12 Total Carbon Rev* 0010 UOG1-PP12 Inorganic Carbon 0.00 Rev* 0010 UOG1-PP12 Organic Carbon Rev* 0011 UOG1-PP14 Total Carbon 0.00 Rev* 0011 UOG1-PP14 Inorganic Carbon 0.00 Rev* 0011 UOG1-PP14 Organic Carbon <0.01 Rev* 0012 UOG1-PP16 Total Carbon 0.00 Rev* 0012 UOG1-PP16 Inorganic Carbon 0.00 Rev* 0012 UOG1-PP16 Organic Carbon <0.01 Rev* 0013 UOG1-PP17 Total Carbon Rev* 0013 UOG1-PP17 Inorganic Carbon Rev* 0013 UOG1-PP17 Organic Carbon Rev* 0014 UOG1-PP21 Total Carbon Rev* See Below 0014 UOG1-PP21 Inorganic Carbon 0.00 Rev* 0014 UOG1-PP21 Organic Carbon Rev* 0015 UOG1-PP22 Total Carbon 0.00 Rev* 0015 UOG1-PP22 Inorganic Carbon 0.00 Rev* 0015 UOG1-PP22 Organic Carbon <0.01 Rev* 0016 UOG1-PP23 Total Carbon Rev* 0016 UOG1-PP23 Inorganic Carbon Rev* 0016 UOG1-PP23 Organic Carbon Rev* 0017 UOG1-PP24 Total Carbon Rev* 0017 UOG1-PP24 Inorganic Carbon 0.00 Rev* 0017 UOG1-PP24 Organic Carbon Rev* 0018 UOG1-PP25 Total Carbon Rev* 0018 UOG1-PP25 Inorganic Carbon 0.00 Rev* 0018 UOG1-PP25 Organic Carbon Rev* 0019 UOG1-PP26 Total Carbon Rev* 0019 UOG1-PP26 Inorganic Carbon 0.00 Rev* Agriculture and Food Laboratory - Guelph, ON N1H 8J7 - Page 2 of 5 Printed: 2013-Feb-25 Page 83

90 REVISED FINAL Report Submission# Reported: 2013-Feb-25 Carbon Package...Continued Date Authorized: 2013-Feb-25 12:14 Rev* = REVISED 0019 UOG1-PP26 Organic Carbon Rev* 0020 UOG1-PP28 Total Carbon Rev* 0020 UOG1-PP28 Inorganic Carbon 0.00 Rev* 0020 UOG1-PP28 Organic Carbon Rev* 0021 UOG1-PP31 Total Carbon Rev* 0021 UOG1-PP31 Inorganic Carbon 0.00 Rev* 0021 UOG1-PP31 Organic Carbon Rev* 0022 UOG1-PP32 Total Carbon Rev* 0022 UOG1-PP32 Inorganic Carbon 0.00 Rev* 0022 UOG1-PP32 Organic Carbon Rev* 0023 UOG1-PP34 Total Carbon Rev* 0023 UOG1-PP34 Inorganic Carbon 0.00 Rev* 0023 UOG1-PP34 Organic Carbon Rev* 0024 UOG1-PP35 Total Carbon Rev* 0024 UOG1-PP35 Inorganic Carbon 0.00 Rev* 0024 UOG1-PP35 Organic Carbon Rev* 0025 UOG1-PP36 Total Carbon Rev* See Below 0025 UOG1-PP36 Inorganic Carbon 0.00 Rev* 0025 UOG1-PP36 Organic Carbon Rev* 0026 UOG1-PP37 Total Carbon Rev* 0026 UOG1-PP37 Inorganic Carbon Rev* 0026 UOG1-PP37 Organic Carbon Rev* 0027 UOG1-PP100 Total Carbon Rev* 0027 UOG1-PP100 Inorganic Carbon 0.00 Rev* 0027 UOG1-PP100 Organic Carbon Rev* 0028 UOG2-PP1 Total Carbon Rev* 0028 UOG2-PP1 Inorganic Carbon Rev* 0028 UOG2-PP1 Organic Carbon Rev* 0029 UOG2-PP2 Total Carbon Rev* 0029 UOG2-PP2 Inorganic Carbon Rev* 0029 UOG2-PP2 Organic Carbon Rev* 0030 UOG2-PP3 Total Carbon 0.00 Rev* 0030 UOG2-PP3 Inorganic Carbon 0.00 Rev* Agriculture and Food Laboratory - Guelph, ON N1H 8J7 - Page 3 of 5 Printed: 2013-Feb-25 Page 84

91 REVISED FINAL Report Submission# Reported: 2013-Feb-25 Carbon Package...Continued Date Authorized: 2013-Feb-25 12:14 Rev* = REVISED 0030 UOG2-PP3 Organic Carbon <0.01 Rev* 0031 UOG2-PP5 Total Carbon Rev* 0031 UOG2-PP5 Inorganic Carbon 0.00 Rev* 0031 UOG2-PP5 Organic Carbon Rev* 0032 UOG2-PP7 Total Carbon Rev* 0032 UOG2-PP7 Inorganic Carbon 0.00 Rev* 0032 UOG2-PP7 Organic Carbon Rev* 0033 UOG2-PP9 Total Carbon 0.00 Rev* 0033 UOG2-PP9 Inorganic Carbon 0.00 Rev* 0033 UOG2-PP9 Organic Carbon <0.01 Rev* 0034 UOG2-PP12 Total Carbon Rev* 0034 UOG2-PP12 Inorganic Carbon Rev* 0034 UOG2-PP12 Organic Carbon Rev* 0035 UOG2-PP13 Total Carbon 1.10 Rev* 0035 UOG2-PP13 Inorganic Carbon Rev* 0035 UOG2-PP13 Organic Carbon 1.03 Rev* 0036 UOG2-PP15 Total Carbon 0.00 Rev* 0036 UOG2-PP15 Inorganic Carbon 0.00 Rev* 0036 UOG2-PP15 Organic Carbon <0.01 Rev* 0037 UOG2-PP17 Total Carbon Rev* See Below 0037 UOG2-PP17 Inorganic Carbon 0.00 Rev* 0037 UOG2-PP17 Organic Carbon Rev* 0038 UOG2-PP100 Total Carbon Rev* 0038 UOG2-PP100 Inorganic Carbon 0.00 Rev* 0038 UOG2-PP100 Organic Carbon Rev* Comments: UOG1-PP9 Total Carbon Total Carbon Duplicate <.01 UOG1-PP21 Total Carbon Total Carbon Duplicate UOG1-PP36 Total Carbon Total Carbon Duplicate UOG2-PP17 Total Carbon Total Carbon Duplicate indicates a value of Carbon <0.01% This revised report replaces the previous report. Results marked Rev* have been revised. Agriculture and Food Laboratory - Guelph, ON N1H 8J7 - Page 4 of 5 Printed: 2013-Feb-25 Page 85

92 REVISED FINAL Report Submission# Reported: 2013-Feb-25 Test method(s): CHEM-046 Supervisor: Nicolaas Schrier MSc ext This report may not be reproduced except in full without written approval by Laboratory Services. These test results pertain only to the specimens tested. Agriculture and Food Laboratory - Guelph, ON N1H 8J7 - Page 5 of 5 Printed: 2013-Feb-25 Page 86

93 Page 87

94 Page 88

95 Appendix B: Phase Partitioning Estimation Steps For each VOC sample, the lab reports the concentration of each analyte in µg/l as measured in an aliquot of the MeOH extractant. Assuming that all of the contaminant mass has been extracted from the wet rock sample and is dissolved in the extractant, the mass of contaminant in the wet rock sample can be calculated using the following formula: C i, TWR Total concentration of the compound i in wet rock [µg g -1 ], [mol g -1 ] C i, E Concentration of the compound i in methanol aliquot [µg L -1 ], [mol L -1 ] V E Volume of methanol extractant [ml], [L] M WR Mass of wet rock [g] To determine the volume of extractant (V E ) and mass of wet rock (M WR ) in a given sample, we use three masses measured in the field (M V, M V+E, M V+E+WR,Field ) and a mass measured once the sample arrives at the lab for analysis (M V+E+WR,Lab ). M WR Mass of wet rock [g] M V+E+WR,Field Mass of 40ml VOA vial containing methanol extractant and sample of wet rock, measured at the field site [g] M V+E Mass of 40ml VOA vial containing methanol extractant [g] V E Volume of methanol extractant [ml], [L] M V+E+WR, Lab Mass of 40ml VOA vial containing methanol extractant and sample of wet rock, measured at the lab [g] M V Mass of empty 40ml VOA vial [g] M E Mass of methanol extractant [g] Page 89

96 Once the total concentration in wet rock (C i, TWR ) is known, an equivalent pore water concentration can be calculated by the method adapted from (Pankow & Cherry, 1996, p. 438) using measured physical properties of the rock matrix and physiochemical properties of the analyte from literature. C i,epw Equivalent pore water concentration of the compound i [µg L -1 ], [mol L -1 ] C i, TWR Total concentration of the compound i in wet rock [µg g -1 ], [mol g -1 ] ρ b,wet Wet bulk density [g cm 3-1 ] R Retardation Factor [cm 3 g -1 ] m Matrix porosity [ ] R Retardation Factor [cm 3 g -1 ] ρ b, dry Dry bulk density [g cm 3-1 ] m Matrix porosity [ ] K d Sediment-Water partitioning coefficient [cm 3 g -1 ] K d Sediment-Water partitioning coefficient [cm 3 g -1 ] K OC Organic carbon normalized sorption coefficient [L kg -1 ] f oc Fraction of organic carbon For semi-volatile compounds (Styrene) (Di Toro, 1985): For volatile compounds the (US EPA, 1996) modified the equation from (Di Toro, 1985) to fit experimental data providing the following empirical relationship: K OC Organic carbon normalized sorption coefficient [L kg -1 ] K ow Octanol-Water partitioning coefficient [ ] Page 90

97 In the case where NAPL phase is present in the sample, the calculated equivalent porewater concentration does not yield a figure representative of the true concentration of dissolved mass in the porewater, as the result would exceed the effective solubility limit of the analyte. Because of this, to ensure that the calculation method is valid, a check must be performed to determine whether or not NAPL is likely present in the sample. The check is based on the following relationship for effective solubility that has previously been confirmed by (Banerjee, 1984), (Mackay, Shiu, Maijanen, & Feenstra, 1991), (Cline, Delfino, & Rao, 1991), (Lee, Hagwall, Delfino, & Rao, 1992), (Lee, Rao, & Okuda, 1992), and (Broholm & Feenstra, 1995)): S i Solubility of the compound i in water [g L -1 ] S e i Effective solubility of the compound i in water [g L -1 ] X i Mole fraction of compound i in the contaminant in the NAPL mixture [ ] Since the definition of the mole fraction is: X i Mole fraction of compound i in the contaminant in the NAPL mixture [ ] By rearranging and substitution we have: Page 91

98 S i Solubility of the compound i in water [g L -1 ] S e i Effective solubility of the compound i in water [g L -1 ] As an assessment of NAPL presence, equivalent porewater concentration (C i,epw ) is substituted in for effective solubility (S e i) which yields the following relationships: NAPL not present in sample NAPL not present in sample but likely nearby NAPL present in sample S i Solubility of the compound i in water [g L -1 ] S e i Effective solubility of the compound i in water [g L -1 ] C i,epw Equivalent pore water concentration of the compound i [µg L -1 ] For samples in which NAPL is likely present, the algorithm presented in (Mariner, Jin, & Jackson, 1997) can be used for estimating partitioning between NAPL, dissolved and sorbed phases. For those samples in which NAPL is not likely present, once the porewater concentration has been calculated, a value for mass sorbed to the matrix material can be estimated using: C i, S Sorbed phase concentration of the compound i with respect to dry rock [µg g -1 ] C i,dpw Dissolved phase pore water concentration of the compound i [µg L -1 ] K d Sediment-Water partitioning coefficient [cm 3 g -1 ] Page 92

99 Appendix C: NAPLANAL Simulations Page 93

100 APPENDIX C: NAPLANAL Simulations Schkopau Samples >50% Effective Solubility NAPLANAL Version Date and Time: 12/27/2013 6:40:10 PM Schkopau NAPL Samples Sample Name Identification DS 001 Model used: Liquid saturated & porosity known Porosity (Volume Frac.) Fraction organic carbon (foc) NAPLANAL ANALYSIS RESULTS: ~~~~~~~~~~~~~~~~~~~~~~~~~~ ID# Name Total Mass Mass in Mass Conc. Sorbed Conc. Mole fraction mass in water in soil in NAPL in water in soil in NAPL in NAPL (mg/kg)* (mg/kg)* (mg/kg)* (mg/kg)* (mg/l) (mg/kg)^ (kg/l) === ====== ====== ====== ====== ====== ====== ====== ====== ====== 56 1,1,1,2 tetrachloroethane 2.08E E E E E E E E ,1,2,2 tetrachloroethane 2.88E E E E E E E E ,1,2 trichloroethane 1.69E E E E E E E E ,2 dichloroethane 2.74E E E E E E E E ,2 dichloropropane 6.97E E E E E E E E cis 1,2 dichloroethylene 2.10E E E E E E E E 03 2 chloroform 1.67E E E E E E E E hexachloroethane 1.10E E E E E E E E tetrachloroethylene (pce) 8.56E E E E E E E E trichloroethylene (tce) 1.54E E E E E E E E 01 (mg/kg)* mg per kg of soil sample (wet soil) (mg/kg)^ mg per kg of solid (dry soil) Water Volume Frac.(l/l) NAPL Volume Frac.(l/l) Soil Volume Frac.(l/l) Porosity (Volume Frac.) Bulk Density (kg/l) NAPL Density (kg/l) NAPL Saturation (%) Numerical Accuracy Information ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The solution converged in 5 iterations with residual less than 1.0E 6. Page 1 of 7 Page 94

101 APPENDIX C: NAPLANAL Simulations Schkopau Samples >50% Effective Solubility Sample Name Identification DS 003 Model used: Liquid saturated & porosity known Porosity (Volume Frac.) Fraction organic carbon (foc) NAPLANAL ANALYSIS RESULTS: ~~~~~~~~~~~~~~~~~~~~~~~~~~ ID# Name Total Mass Mass in Mass Conc. Sorbed Conc. Mole fraction mass in water in soil in NAPL in water in soil in NAPL in NAPL (mg/kg)* (mg/kg)* (mg/kg)* (mg/kg)* (mg/l) (mg/kg)^ (kg/l) === ====== ====== ====== ====== ====== ====== ====== ====== ====== 12 1,1,2,2 tetrachloroethane 2.65E E E E E E E E ,2 dichloropropane 2.04E E E E E E E E hexachloroethane 1.37E E E E E E E E trichloroethylene (tce) 4.45E E E E E E E E ,1,2 trichloroethane 3.45E E E E E E E E tetrachloroethylene (pce) 3.03E E E E E E E E 01 (mg/kg)* mg per kg of soil sample (wet soil) (mg/kg)^ mg per kg of solid (dry soil) Water Volume Frac.(l/l) NAPL Volume Frac.(l/l) Soil Volume Frac.(l/l) Porosity (Volume Frac.) Bulk Density (kg/l) NAPL Density (kg/l) NAPL Saturation (%) Numerical Accuracy Information ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The solution converged in 359 iterations with residual less than 1.0E 6. Page 2 of 7 Page 95

102 APPENDIX C: NAPLANAL Simulations Schkopau Samples >50% Effective Solubility Sample Name Identification DS 005 Model used: Liquid saturated & porosity known Porosity (Volume Frac.) Fraction organic carbon (foc) NAPLANAL ANALYSIS RESULTS: ~~~~~~~~~~~~~~~~~~~~~~~~~~ ID# Name Total Mass Mass in Mass Conc. Sorbed Conc. Mole fraction mass in water in soil in NAPL in water in soil in NAPL in NAPL (mg/kg)* (mg/kg)* (mg/kg)* (mg/kg)* (mg/l) (mg/kg)^ (kg/l) === ====== ====== ====== ====== ====== ====== ====== ====== ====== 19 1,2 dichloropropane 1.11E E E E E E E E hexachloroethane 1.76E E E E E E E E trichloroethylene (tce) 2.97E E E E E E E E tetrachloroethylene (pce) 1.63E E E E E E E E 01 (mg/kg)* mg per kg of soil sample (wet soil) (mg/kg)^ mg per kg of solid (dry soil) Water Volume Frac.(l/l) NAPL Volume Frac.(l/l) Soil Volume Frac.(l/l) Porosity (Volume Frac.) Bulk Density (kg/l) NAPL Density (kg/l) NAPL Saturation (%) Numerical Accuracy Information ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The solution converged in 6 iterations with residual less than 1.0E 6. Page 3 of 7 Page 96

103 APPENDIX C: NAPLANAL Simulations Schkopau Samples >50% Effective Solubility Sample Name Identification DS 008 Model used: Liquid saturated & porosity known Porosity (Volume Frac.) Fraction organic carbon (foc) NAPLANAL ANALYSIS RESULTS: ~~~~~~~~~~~~~~~~~~~~~~~~~~ ID# Name Total Mass Mass in Mass Conc. Sorbed Conc. Mole fraction mass in water in soil in NAPL in water in soil in NAPL in NAPL (mg/kg)* (mg/kg)* (mg/kg)* (mg/kg)* (mg/l) (mg/kg)^ (kg/l) === ====== ====== ====== ====== ====== ====== ====== ====== ====== 12 1,1,2,2 tetrachloroethane 2.52E E E E E E E E ,1,2 trichloroethane 1.95E E E E E E E E ,1 dichloroethylene 5.81E E E E E E E E ,2 dichloroethane 4.06E E E E E E E E ,2 dichloropropane 1.53E E E E E E E E cis 1,2 dichloroethylene 1.54E E E E E E E E hexachloroethane 7.30E E E E E E E E tetrachloroethylene (pce) 1.36E E E E E E E E trichloroethylene (tce) 4.89E E E E E E E E trans 1,2 dichloroethylene 9.81E E E E E E E E 04 (mg/kg)* mg per kg of soil sample (wet soil) (mg/kg)^ mg per kg of solid (dry soil) Water Volume Frac.(l/l) NAPL Volume Frac.(l/l) Soil Volume Frac.(l/l) Porosity (Volume Frac.) Bulk Density (kg/l) NAPL Density (kg/l) NAPL Saturation (%) Numerical Accuracy Information ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The solution converged in 5 iterations with residual less than 1.0E 6. Page 4 of 7 Page 97

104 APPENDIX C: NAPLANAL Simulations Schkopau Samples >50% Effective Solubility Sample Name Identification DS 019 Model used: Liquid saturated & porosity known Porosity (Volume Frac.) Fraction organic carbon (foc) NAPLANAL ANALYSIS RESULTS: ~~~~~~~~~~~~~~~~~~~~~~~~~~ ID# Name Total Mass Mass in Mass Conc. Sorbed Conc. Mole fraction mass in water in soil in NAPL in water in soil in NAPL in NAPL (mg/kg)* (mg/kg)* (mg/kg)* (mg/kg)* (mg/l) (mg/kg)^ (kg/l) === ====== ====== ====== ====== ====== ====== ====== ====== ====== 12 1,1,2,2 tetrachloroethane 1.98E E E E E E E E ,1,2 trichloroethane 6.74E E E E E E E E ,1 dichloroethane 6.70E E E E E E E E ,1 dichloroethylene 6.12E E E E E E E E ,2 dichloroethane 3.09E E E E E E E E bis(2 chloroisopropyl)ether 2.01E E E E E E E E cis 1,2 dichloroethylene 9.03E E E E E E E E 02 1 dichloromethane 5.95E E E E E E E E hexachloroethane 3.35E E E E E E E E tetrachloroethylene (pce) 4.69E E E E E E E E pentachloroethane 2.32E E E E E E E E trichloroethylene (tce) 1.74E E E E E E E E trans 1,2 dichloroethylene 5.40E E E E E E E E vinyl chloride 5.12E E E E E E E E 01 (mg/kg)* mg per kg of soil sample (wet soil) (mg/kg)^ mg per kg of solid (dry soil) Water Volume Frac.(l/l) NAPL Volume Frac.(l/l) Soil Volume Frac.(l/l) Porosity (Volume Frac.) Bulk Density (kg/l) NAPL Density (kg/l) NAPL Saturation (%) Numerical Accuracy Information ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The solution converged in 113 iterations with residual less than 1.0E 6. Page 5 of 7 Page 98

105 APPENDIX C: NAPLANAL Simulations Schkopau Samples >50% Effective Solubility Sample Name Identification DS 110 Model used: Liquid saturated & porosity known Porosity (Volume Frac.) Fraction organic carbon (foc) NAPLANAL ANALYSIS RESULTS: ~~~~~~~~~~~~~~~~~~~~~~~~~~ ID# Name Total Mass Mass in Mass Conc. Sorbed Conc. Mole fraction mass in water in soil in NAPL in water in soil in NAPL in NAPL (mg/kg)* (mg/kg)* (mg/kg)* (mg/kg)* (mg/l) (mg/kg)^ (kg/l) === ====== ====== ====== ====== ====== ====== ====== ====== ====== 56 1,1,1,2 tetrachloroethane 4.26E E E E E E E E ,1,2,2 tetrachloroethane 5.96E E E E E E E E ,1 dichloroethylene 2.12E E E E E E E E ,2 dichloroethane 5.44E E E E E E E E ,2 dichloropropane 2.47E E E E E E E E benzene 1.23E E E E E E E E bis(2 chloroisopropyl)ether 6.95E E E E E E E E 04 2 chloroform 6.66E E E E E E E E ethylbenzene 6.04E E E E E E E E hexachloroethane 1.59E E E E E E E E tetrachloroethylene (pce) 1.72E E E E E E E E trichloroethylene (tce) 4.98E E E E E E E E trans 1,2 dichloroethylene 1.44E E E E E E E E vinyl chloride 1.08E E E E E E E E 03 (mg/kg)* mg per kg of soil sample (wet soil) (mg/kg)^ mg per kg of solid (dry soil) Water Volume Frac.(l/l) NAPL Volume Frac.(l/l) Soil Volume Frac.(l/l) Porosity (Volume Frac.) Bulk Density (kg/l) NAPL Density (kg/l) NAPL Saturation (%) Numerical Accuracy Information ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The solution converged in 40 iterations with residual less than 1.0E 6. Page 6 of 7 Page 99

106 APPENDIX C: NAPLANAL Simulations Schkopau Samples >50% Effective Solubility The Thermodynamic Physical Properties of the Chemical Components Used in This Set of Soil Data Analysis Database Source of Reference: Schkopau REVISED ============================================================================================================================= ID# CAS# Name Molecular Weight Density Henry's Constant Water Solubility Koc (g/mol) (kg/l) (atm L/mol) (mg/l) (ml/g) ============================================================================ ,1,2,2 tetrachloroethane 1.68E E E E E ,2 dichloropropane 1.13E E E E E hexachloroethane 2.37E E E E E trichloroethylene (tce) 1.31E E E E E ,1,2 trichloroethane 1.33E E E E E tetrachloroethylene (pce) 1.66E E E E E ,1 dichloroethylene 9.69E E E E E ,2 dichloroethane 9.90E E E E E cis 1,2 dichloroethylene 9.69E E E E E trans 1,2 dichloroethylene 9.69E E E E E ,1 dichloroethane 9.90E E E E E bis(2 chloroisopropyl)ether 1.71E E E E E dichloromethane 8.49E E E E E pentachloroethane 2.02E E E E E vinyl chloride 6.25E E E E E ,1,1,2 tetrachloroethane 1.68E E E E E benzene 7.81E E E E E chloroform 1.19E E E E E ethylbenzene 1.06E E E E E+02 ***************************************************************************************************************************** END OF RECORDS Page 7 of 7 Page 100

107 Appendix D: VOC Concentration Profiles Page 101

108 Page 102

109 Page 103

110 Appendix E: 1-D Diffusion Modeling To demonstrate that the rock core VOC data shows evidence of diffusion into low permeability material, calculated porewater concentrations were compared against modelled diffusion curves. A 1-D analytical solution for diffusion derived by Crank (1956), with a retardation factor included, was used to model the curves. The tortuosity value for the clay was estimated to be 0.09 based on a value for Lake Agassiz clay from Oscarson (1994), the retardation factors (R) were calculated from measured values of organic carbon content and the aqueous diffusion coefficients were sourced from Kresic (2007). The following slides show the 1-D analytical solution, its application to TCE diffusing from accumulated DNAPL in a sandy rubble zone into a low permeabily clay and ethylbenzene diffusing upwards into the same clay unit from a preferential contaminant migration zone. The times used were: 40 years for the TCE, as it is thought to have been released at that location and has been in production there since 1937; and 15 years for the ethylbenzene, as it is thought to have arrived at the location by lateral migration from an upgradient source, possibly meaning more recent arrival. Page 104

111 1-D Analytical Solution for Diffusion C x, t) R t e C i (x,t) = Concentration at distance x and time t (µg/ml) C 0 = Concentration at source (µg/ml) x = Distance from source (cm) t = Time (s) D e = Effective diffusion coefficient (cm 2 /s) R = Retardation = C i ( 0 erfc 2 D x D e = D d τ D e = Effective diffusion coefficient (cm 2 /s) D d = Diffusion coefficient in water (cm 2 /s) Ƭ = Tortuosity coefficient Page 105

112 11.0 mbgs Sandy Rubble Zone mbgs Diffusion Downward Into Clay 1.00E E E TCE Diffusion Profile C o = 421 µg/ml D d = 1 x 10-5 cm 2 /s Ƭ= 0.09 D e = 9 x 10-7 cm 2 /s t= 50 Years smdt smd st 12.5 mbgs TCE Effective Solubility TCE (ug/ml dissolved porewater) R= 1.9 Page 106

113 11.0 mbgs Diffusion Ethylbenzene Profiles Diffusion Profile C o = 10.4 µg/ml D d = 8.3x10-6 cm 2 /s smdt smd st Diffusion Upward Into Clay 12.5 mbgs Ethylbenzene (ug/ml dissolved porewater) Ƭ= 0.09 D e = 7.47x10-7 cm 2 /s t= 15 Years R= 1.6 Page 107

114 11.0 mbgs Sandy Rubble Zone mbgs Diffusion Downward Into Clay 1.00E E E TCE Effective 11.4 Solubility TCE and Ethylbenzene Diffusion Profiles TCE (ug/ml dissolved porewater) Ethylbenzene (ug/ml dissolved porewater) smdt smd st Diffusion Upward Into Clay 12.5 mbgs Page 108

115 Appendix F: Geophysical Tool Spec Sheets Page 109

116 Sondenkatalog BLM Gesellschaft für Bohrlochmessungen mbh GOMMERN GOTHA MÜNCHEN ABF - Acoustic Televiewer 9804 Länge: 1930 mm Messbereich (BL-Ø): 74 mm mm Gewicht: 14 kg Abtastraten: 1 cm/ 2 cm/ 10 cm max. Einsatztemperatur: 85 C empf. Messgeschw.: 2 m/min max. Einsatzdruck: 103 bar kombinierbar: NEIN Sondendurchmesser: 50,8 mm Endtool: JA Bezug GR: 304,8 mm Bezug Neigung: 1750 mm Messbereich: API-un. Messbereich: 0-90 Messunsicherheit: +/- 5 % Messunsicherheit: +/- 0,5 Bezug Azimut: 1750 mm Bezug AA & ATT 1750 mm Messbereich: Messunsicherheit: +/- 2,55 mm Messunsicherheit: +/- 2 Toolskizze: Sondenkopf Messpunkt GR Messpunkt Azimut Messpunkt Neigung Messpunkt Acoustic Amplitude Messpunkt Acoustic Travel Time BLM Sondenkatalog C011.doc Page 110

117 Sondenkatalog BLM Gesellschaft für Bohrlochmessungen mbh GOMMERN GOTHA MÜNCHEN CARI-4 - Vierarmkaliber Länge ohne Zentr.: 1975 mm Bezug: 1940 mm Länge mit Zentr.verl.: 2975 mm Abtastraten: 1 cm/ 2,5 cm/ 5 cm Gewicht: 30 kg Messbereich o. Verl.: 87 mm mm max. Einsatztemperatur: 100 C Messbereich m. Verl.: 87 mm mm Azimutorientierung Arm 1 Messunsicherheit: +/- 2 % kombinierbar: NEIN empf. Messgeschw.: 8 m/min Seriennr. 101: Durchmesser: 84 mm max. Einsatzdruck: 400 bar Seriennr. 113: Durchmesser: 72 mm max. Einsatzdruck: 300 bar Toolskizze: Foto: Sondenkopf Zentrierung Messpunkt Verlängerung für Zentrierung BLM Sondenkatalog G001.doc Page 111