APPENDIX 3-VII REGIONAL DATA ANALYSIS

APPENDIX 3-VII REGIONAL DATA ANALYSIS

Cenovus FCCL Ltd. - i - Appendix 3-VII TABLE OF CONTENTS SECTION PAGE 1 OBJECTIVES OF ANALYSIS... 1 2 METHODS... 4 2.1 SOIL REGIONAL ANALYSIS... 4 2.1.1 Soil Regional Principal Components Analysis... 4 2.2 BIOACCUMULATION FACTOR REGIONAL ANALYSIS... 5 3 RESULTS... 7 3.1 SOIL REGIONAL ANALYSIS... 7 3.1.1 Conclusions of Regional Soil Analysis... 11 3.2 REGIONAL SOIL CONCENTRATIONS... 11 3.3 VEGETATION REGIONAL BIOACCUMULATION FACTOR ANALYSIS... 12 3.3.1 Labrador Tea Regional Bioaccumulation Factor Analysis... 12 3.3.2 Alder Regional Bioaccumulation Factor Analysis... 16 3.3.3 Berry Regional Bioaccumulation Factor Analysis... 17 3.3.4 Cattail Regional Bioaccumulation Factor Analysis... 23 3.3.5 Conclusions of Vegetation Principal Component Analysis... 30 3.4 REGIONAL BIOACCUMULATION FACTORS... 30 3.5 REGIONAL VEGETATION CONCENTRATIONS... 33 4 REFERENCES... 38 5 ABBREVIATIONS... 40 6 GLOSSARY... 41 LIST OF TABLES Table 1 Available Regional Soil and Vegetation Chemistry Data... 3 Table 2 Summary of Regional Vegetation Chemistry Data Used in the Principal Components Analysis... 6 Table 3 Summary of Principal Components Analysis on Soil Metals Data... 7 Table 4 Summary of 95% Upper Confidence Limit of the Mean Soil Concentrations... 12 Table 5 Summary of Principal Components Analysis on Labrador Tea Regional Bioaccumulation Factor Data... 13 Table 6 Summary of Principal Components Analysis on Alder Regional Bioaccumulation Factor Data... 16 Table 7 Summary of Principal Components Analysis on Berry Regional Bioaccumulation Factor Data... 20 Table 8 Summary of Principal Components Analysis on Cattail Root Bioaccumulation Factors Collected From Organic Soil... 24 Table 9 Summary of Principal Components Analysis on Cattail Root Bioaccumulation Factors Collected From Mineral Soil... 27 Table 10 Regional 95% Upper Confidence Limit of the Mean Bioaccumulation Factor for Labrador Tea Samples... 31

Cenovus FCCL Ltd. - ii - Appendix 3-VII Table 11 Regional 95% Upper Confidence Limit of the Mean Bioaccumulation Factor for Alder Samples... 31 Table 12 Regional 95% Upper Confidence Limit of the Mean Bioaccumulation Factor for Berry Samples... 32 Table 13 Regional 95% Upper Confidence Limit of the Mean Bioaccumulation Factor for Cattail Root Samples in Organic Soil... 32 Table 14 Regional 95% Upper Confidence Limit of the Mean Bioaccumulation Factor for Cattail Root Samples in Mineral Soil... 33 Table 15 Regional 95% Upper Confidence Limit of the Mean for Labrador Tea Samples... 34 Table 16 Regional 95% Upper Confidence Limit of the Mean for Alder Samples... 35 Table 17 Regional 95% Upper Confidence Limit of the Mean for Berries... 36 Table 18 Results of Chemical Analysis for Peeled Cattail Root Samples... 37 LIST OF FIGURES Figure 1 Data Used in Regional Analysis... 2 Figure 2 Ordination Plot of Regional Soil Data Based on Metal Concentrations... 9 Figure 3 Box Plot of Regional Soil PC 1 and PC 2 Scores... 10 Figure 4 Ordination Plot of Regional Labrador Tea Bioaccumulation Factors... 14 Figure 5 Box Plot of PC 1 and PC 2 for Regional Labrador Tea Bioaccumulation Factors... 15 Figure 6 Ordination Plot of Regional Alder Bioaccumulation Factors... 18 Figure 7 Box Plot of PC 1 and PC 2 for Regional Alder Bioaccumulation Factors... 19 Figure 8 Ordination Plot of Regional Berry Bioaccumulation Factors... 21 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Box Plot of PC 1 and PC 2 Scores for Regional Berry Bioaccumulation Factors... 22 Ordination Plot of Regional Cattail Root in Organic Soil Bioaccumulation Factors... 25 Box Plot of PC 1 and PC 2 Scores for Cattail Roots in Organic Soil Bioaccumulation Factors... 26 Ordination Plot of Regional Cattail Root in Mineral Soil Bioaccumulation Factors... 28 Box Plot of PC 1 and PC 2 Scores for Cattail Roots in Soil Bioaccumulation Factors... 29

Cenovus FCCL Ltd. - 1 - Appendix 3-VII 1 OBJECTIVES OF ANALYSIS Soil and vegetation chemistry data have not been collected as part of the Christina Lake Thermal Project - Phase H and Eastern Expansion (the Project). However, several soil and vegetation sampling programs have been completed in support of recent in-situ projects in the region of northeastern Alberta that lies south of Gregoire Lake, north of the Cold Lake Air Weapons Range, east of Christina River, and west of the Alberta and Saskatchewan border (herein referred to as the region ; Figure 1). These programs included two projects immediately adjacent to the Project (Christina Lake Phases E, F and G, and Narrows Lake), for which the Local Study Areas (LSAs) overlap as well as three other projects in the region. When combined, data from these projects potentially provide representative baseline soil and vegetation chemistry for the region that could be applied to the Project Regional Study Area (RSA) and LSA. This appendix provides the methods and results of the statistical evaluation of the soil and vegetation data conducted to meet the following objectives: exploring spatial patterns in baseline chemistry for soil to determine whether combining these data yields a representative regional data set; calculating the Bioaccumulation Factors (BAFs) from soil to alder, cattails, berries and Labrador tea to determine if combining these data yields a representative regional data set; and when applicable, using the regional data set to calculate the 95% upper confidence limit of the mean for BAFs and for concentrations measured in soil and vegetation for use in the human and wildlife health risk assessments.

Cenovus FCCL Ltd. - 3 - Appendix 3-VII Project-specific data from the region that was screened for inclusion in the regional data set included the baseline soil and vegetation chemistry data from the following projects (Table 1 and Figure 1): Canadian Natural Resources Limited Kirby In-Situ Oil Sands Project (Canadian Natural Kirby) (Canadian Natural 2007, 2008); Canadian Natural Primrose East In-Situ Oil Sands Project (Canadian Natural Primrose) (Canadian Natural 2006); Cenovus FCCL Ltd. (formerly EnCana FCCL Ltd.) Christina Lake Thermal Expansion Project, Phases 1E, 1F and 1G (Cenovus CLTP Phases E, F and G) (EnCana 2009); and Cenovus FCCL Ltd. Narrows Lake Project (Cenovus Narrows Lake) (Cenovus 2010). Table 1 Available Regional Soil and Vegetation Chemistry Data Project Mineral Soil Organic Soil Number of Samples for Each Medium Cattails Labrador Tea Berries Cenovus Narrows Lake 85 9 18 19 20 17 Cenovus CLTP, Phases E, F and G 15 7 5 8 8 8 Canadian Natural Primrose 44 7 13 16 12 13 Canadian Natural Kirby 33 5 8 10 10 10 ConocoPhillips Surmont 25 0 8 13 12 15 Sum of regional data set 202 28 52 66 62 63 Source: Canadian Natural 2006, 2007; Cenovus 2010; EnCana 2009. Alder Baseline soil and vegetation chemistry data have also been collected by ConocoPhillips Canada (ConocoPhillips) in the Surmont lease area. This data has not been reported to date, but, permission was obtained from ConocoPhillips to use the data in the regional analysis.

Cenovus FCCL Ltd. - 4 - Appendix 3-VII 2 METHODS 2.1 SOIL REGIONAL ANALYSIS A Principal Components Analysis (PCA) was used to evaluate the regional soil data. The regional analysis of soil data were limited to metal concentrations, because Polycyclic Aromatic Hydrocarbon (PAH) concentrations were less than analytical detection limits in the majority of soil samples. Conducting the PCA on data with similar percentages of non-detect values and similar analytical detection limits was considered important to reduce uncertainty in the conclusions drawn from the analysis. Therefore, data were screened for inclusion in the PCA using the percentage of non-detect values as the selection criterion. Metals included in the PCA included those present at detectable concentrations in at least 50% of the collected soil samples. The metal distributions in soil and vegetation were found to be logarithmically distributed during the preliminary data analysis. Therefore, metal concentrations were log-transformed because PCA requires that the data follow a normal distribution. All non-detect data were assumed to be at the maximum of the detection limit for the PCA. 2.1.1 Soil Regional Principal Components Analysis The metal concentration data were summarized using PCA (Gauch 1982). Principal Components Analysis is an ordination method that can be used to summarize a complex data set consisting of a large number of variables (e.g., 26 metals in soil samples), in the form of fewer, independent variables (often only two) referred to as Principal Components (PCs). Principal Components are new variables that represent groups of variables (e.g., metals) that vary in a similar manner among samples; each sample is assigned a score for each PC, which is representative of metal concentrations. Often as few as two PCs are sufficient to represent all or most of the original variables. This method allows illustration of the among-sample variation in concentrations of a large number of metals as a scatter-plot of scores on only two PCs (referred to as an ordination plot), with each point on the plot representing a sample. The position of each sample on the ordination plot provides an indication of metal concentrations. Samples with similar concentrations for most metals are close to one another on the plot and may form clusters, allowing identification of groups of samples with similar chemistry. A PCA can be used to evaluate whether samples grouped by geographic location are also more similar to one another based on soil chemistry.

Cenovus FCCL Ltd. - 5 - Appendix 3-VII The objective of the PCA of regional soil data were to explore spatial patterns in baseline soil chemistry to determine whether combining these data yields a representative regional data set that can be applied for all projects within the region. This objective was addressed by examining the ordination plots to determine whether the metal concentrations (as represented by PCs) measured in soil from each of the lease areas were similar. If the PCA showed that soil metal chemistry from each Lease Area was similar to each other, this result would support combining the data to form a regional data set to represent metals concentrations in soil from the region. If the PCA showed that samples collected in each Lease Area were unique, then combining the data would not be recommended as this result would suggest that there were differences in soil metal chemistry across the region. If the results of the regional soil PCA indicated that soil data from the different areas lack spatial patterns, then a 95% upper confidence limit of the mean concentration for each metal was calculated to represent soil conditions in the RSA and LSA for the Project. 2.2 BIOACCUMULATION FACTOR REGIONAL ANALYSIS Soil-to-plant BAFs were calculated using the baseline data for soil and plant tissues. For all sample locations in the region, paired samples of soil and vegetation were obtained. The paired samples were used to calculate site-specific BAFs using the formula: C BAF = C t s Where: C t = Concentration in tissue (mg/kg, dry weight); and C s = Concentration in soil (mg/kg, dry weight). Labrador tea, alder and berries were all collected from mineral soil. Cattails were collected from mineral and organic soils and therefore, BAFs were separated into two groups on based soil type. At locations where triplicates (for Quality Assurance/Quality Control [QA/QC] purposes) of soil and plant tissues were collected, only one of the triplicate samples was used in the BAF analysis to avoid sample location bias. Metal parameters in soil

Cenovus FCCL Ltd. - 6 - Appendix 3-VII and plants which had greater than 60% non-detects were removed from the analysis to avoid a type II error (concluding false similarity). In addition, all non-detects were assessed as the maximum of the detection limit. Also, this analysis was not conducted for PAHs because soil and vegetation concentrations for all PAHs were predominantly below detection limits. A PCA was then conducted on the BAF data to explore the regional uptake of metals from soils to vegetation. All BAFs were log transformed before running the PCA to normalize the distributions of the data sets. Preliminary statistical analysis found the logarithmic distribution to fit most parameters. The parameters used to conduct the PCA analysis for BAFs are listed in Table 2. Table 2 Summary of Regional Vegetation Chemistry Data Used in the Principal Components Analysis Parameters Cattails Alder Labrador Tea Berries Aluminum Antimony X x x x Arsenic x x x Barium Beryllium x x x x Bismuth x x x x Boron Cadmium x x Chromium Cobalt Copper Lead Manganese Mercury x Molybdenum Nickel Selenium x x x Silver x x x x Strontium Thallium x x x x Uranium x x x Vanadium x Zinc = indicates that the parameter had less than 60% non-detects; x = indicates more than 60% non-detects. Bioaccumulation from soil to plant tissues is identified in the Terms of Reference for the Project (ESRD 2012) and is necessary to understand the following: describe how changes to soil quality will result in human exposure; and identify the effects to human health from the potential contamination of country and natural food sources taking into consideration the Project and future projects in the region.

Cenovus FCCL Ltd. - 7 - Appendix 3-VII 3 RESULTS 3.1 SOIL REGIONAL ANALYSIS A total of 202 soil samples were used to examine variation in soil metals concentrations for the region. The first two components derived by PCA explained a large proportion of the variance in the soil data set (72.5%; Table 3). Therefore, the first two PCs were used to illustrate variation in metal concentrations in soils throughout the region. Soil PC 1 represents concentrations of all metals (except lead, mercury and selenium) as indicated by the high loadings (bolded correlation coefficients) on this component in Table 3. Soil PC 2 indicates additional variability in the concentrations of the two groups of metals with an apparent inverse relationship between the group containing boron, mercury and strontium, compared to the group containing aluminum, chromium, titanium and vanadium. Table 3 Summary of Principal Components Analysis on Soil Metals Data Metal PC 1 PC 2 Aluminum 0.747-0.598 Arsenic 0.881-0.008 Copper 0.907 0.019 Barium 0.886 0.278 Beryllium 0.817-0.299 Bismuth 0.664-0.265 Boron 0.642 0.607 Cadmium 0.709 0.452 Calcium 0.806 0.467 Chromium 0.837-0.51 Cobalt 0.901-0.29 Iron 0.862-0.274 Lead 0.445-0.001 Magnesium 0.941 0.019 Manganese 0.831 0.135 Mercury 0.417 0.518 Molybdenum 0.58 0.393 Nickel 0.941-0.187 Potassium 0.813-0.231 Selenium 0.336 0.313 Sodium 0.704 0.454 Strontium 0.783 0.567 Titanium 0.531-0.747 Uranium 0.661 0.249 Vanadium 0.796-0.538 Zinc 0.83 0.036 % Variance Explained 57.6 14.9 Note: Principal component loadings representing Pearson Correlation Coefficient more than 0.5 are bolded.

Cenovus FCCL Ltd. - 8 - Appendix 3-VII Lead and selenium did not correlate to either PC 1 or PC 2 and therefore there may be additional factors which influence the regional variability of these metals. However, for consistency, and given the representativeness of other metals across the region, it was still considered appropriate to make regional-level estimates of the concentrations of lead and selenium. The ordination plot (Figure 2) illustrates scores by each sample on PC 1 and PC 2, with each point representing individual samples. The overall pattern on the plot reflects the combination of two groups of samples, one large group with generally inter-correlated concentrations for all metals (located along the bottom of the plot) and a smaller group with lower concentrations of metals associated with PC 2 (located in the upper right part of the plot; negative loadings on PC 2 indicate that samples with lower concentrations are closer to the top of the plot rather than the bottom). Box plots of soil PC 1 PC 2 scores show a high degree of overlap in metal concentrations among the different lease areas (Figure 3), suggesting that none of the areas are unique in terms of soil chemistry. Box plots of the PC 1 and PC 2 scores for the two projects immediately adjacent to the Project (Cenovus CLTP Phases E, F and G and Cenovus Narrows Lake) overlap almost entirely with the remaining projects suggesting that the range of variability in the region is also representative of the immediate vicinity of the Project. Overall, based on the large data set (the range of concentrations represented in the data set and the degree of overlap in metal concentrations among data sets from the different areas (Figures 2 and 3), the data set appears to provide a reasonable representation of the regional range of metal concentrations in soils. Therefore, it was considered appropriate to pool the regional data to obtain a larger, more robust data set upon which summary statistics could be calculated.

CHRISTINA LAKE THERMAL PROJECT PHASE H AND EASTERN EXPANSION ORDINATION PLOT OF REGIONAL SOIL DATA BASED ON METAL CONCENTRATIONS 10.1346.0044.8800 10134600168800C003 TZ O8/01/2013 BSW 09/01/2013 CT 07/03/2013 SNS 07/03/2013 AS SHOWN 0 FIGURE: 2

PC 1 PC 2 CHRISTINA LAKE THERMAL PROJECT PHASE H AND EASTERN EXPANSION BOX PLOT OF REGIONAL SOIL PC 1 AND PC 2 SCORES 10.1346.0044.8800 10134600168800C004 TZ O8/01/2013 BSW 09/01/2013 CT 07/03/2013 SNS 07/03/2013 AS SHOWN 0 FIGURE: 3

Cenovus FCCL Ltd. - 11 - Appendix 3-VII 3.1.1 Conclusions of Regional Soil Analysis Based on the results of the regional soil analysis, the following conclusions were made: spatial patterns in soil chemistry indicate that combining individual data from the five lease areas yields a representative regional data set that can be applied for the Project RSA and LSA; the spatial variability of metal concentrations in soil indicates that use of regional BAFs from soil to vegetation may be appropriate (examined in Section 3.3); and it is appropriate to use summary statistics (e.g., Upper Confidence Limit of the Mean [UCLM]) from the regional soil data set to represent concentrations from the RSA/LSA for use in the human and wildlife health risk assessments. 3.2 REGIONAL SOIL CONCENTRATIONS The findings of the soil regional analysis supported combining the soil data into a regional data set. Therefore, the regional data were combined into one data set and entered into a statistical software package ProUCL (Version 4.0). ProUCL was designed by the United States Environmental Protection Agency (U.S. EPA 2006) for risk assessment practitioners to determine the quality and upper confidence limit of environmental data in risk assessment evaluations. ProUCL computes the appropriate Upper Confidence Limits (UCLs) for each entered parameter. Therefore, ProUCL was used to calculate the 95% UCL of the mean concentration in each of the soil types (mineral soil and organic soil) for which baseline data were available. ProUCL results and baseline metals concentrations used in the risk assessment for soil are presented in Table 4. Because the majority of the PAH data were less than analytical detection limits in all media, the PAH concentrations used in the risk assessment were equivalent to onehalf the applicable detection limit.

Cenovus FCCL Ltd. - 12 - Appendix 3-VII Table 4 Summary of 95% Upper Confidence Limit of the Mean Soil Concentrations Parameter 95% UCLM Concentration [dry weight mg/kg] Percent of Results Less than Detection Limit Aluminum 2,679 0.0 Antimony 0.12 67.4 Arsenic 1.92 0.0 Barium 52.4 0.0 Beryllium 0.15 41.7 Bismuth 0.04 34.5 Boron 7.76 25.2 Cadmium 0.1 31.7 Chromium 4.5 0.0 Cobalt 5.7 0.0 Copper 3.08 12.2 Lead 2.8 6.6 Manganese 402.2 0.0 Mercury 0.04 15.7 Molybdenum 0.39 7 Nickel 5.4 1.3 Selenium 0.27 53.2 Silver <1.0 100 Strontium 28.0 0.0 Thallium 0.08 96.5 Uranium 0.65 0.0 Vanadium 7.14 0.0 Zinc 34.6 4.8 3.3 VEGETATION REGIONAL BIOACCUMULATION FACTOR ANALYSIS 3.3.1 Labrador Tea Regional Bioaccumulation Factor Analysis Fifty-two paired mineral soil and Labrador tea samples were used to examine variation in BAFs for the region. The first two components derived by PCA explained a large proportion of the variance in the Labrador tea BAF data set (76.1%; Table 5). PC 1 in Labrador tea represents a single universal gradient of variability (Table 5). In PC 2, there is an inverse relationship between boron and strontium, versus aluminum, chromium and vanadium.

Cenovus FCCL Ltd. - 13 - Appendix 3-VII Table 5 Summary of Principal Components Analysis on Labrador Tea Regional Bioaccumulation Factor Data Metal PC 1 PC 2 Aluminum 0.732-0.572 Barium 0.788 0.457 Boron 0.63 0.691 Chromium 0.761-0.536 Cobalt 0.888-0.345 Copper 0.869 0.104 Lead 0.63-0.319 Manganese 0.882 0.173 Mercury 0.572 0.439 Molybdenum 0.701 0.039 Nickel 0.889-0.144 Strontium 0.708 0.616 Vanadium 0.655-0.648 Zinc 0.813 0.164 % Variance Explained 57.5 18.6 Note: Principal component loadings more than 0.5 are bolded. All metals in Table 5 were included in either PC 1 or PC 2 as represented by the high loadings (bolded correlation coefficients). This finding indicates that metals do not require site-specific assessment of BAFs for Labrador tea and that combining regional BAF data to obtain a larger, more-robust data set is appropriate. Most sample locations in the region fall in a common area of PC 1 and PC 2 and no single area appears to have unique mineral soil to Labrador tea BAFs for the region as indicated in Figure 4. Box plots of soil PC 1 PC 2 scores show a high degree of overlap in the BAFs among the different lease areas (Figure 5), especially for PC 2, suggesting that none of the areas are unique in terms of BAFs. The Cenovus Narrows Lake and ConocoPhillips Surmont areas have a similar mean and range of PC 1 scores. However, the Cenovus Narrows Lake PC 1 box-plots indicate a larger variability compared to the ConocoPhillips Surmont area. The box plots of PC 1 scores indicate that the Cenovus CLTP Phases E, F and G and Canadian Natural Primrose areas have a similar central tendency and distribution. The Canadian Natural Kirby area has the largest central tendency and range of PC 1 scores. Cenovus Narrows Lake, ConocoPhillips Surmont and Canadian Natural Kirby areas have similar ranges of PC 2 scores. The Cenovus CLTP Phases E, F and G area has the greatest mean and therefore largest BAFs for PC 2 metals. The Canadian Natural Primrose and Cenovus CLTP Phases E, F and G areas have the lowest variability for PC 2 metals. The Canadian Natural Primrose and ConocoPhillips Surmont areas have similar mean PC 2 scores.

CHRISTINA LAKE THERMAL PROJECT PHASE H AND EASTERN EXPANSION ORDINATION PLOT OF REGIONAL LABRADOR TEA BIOACCUMULATION FACTORS 10.1346.0044.8800 10134600168800C005 TZ O8/01/2013 BSW 09/01/2013 CT 07/03/2013 SNS 07/03/2013 AS SHOWN 0 FIGURE: 4

PC 1 PC 2 CHRISTINA LAKE THERMAL PROJECT PHASE H AND EASTERN EXPANSION BOX PLOT OF PC 1 AND PC 2 FOR REGIONAL LABRADOR TEA BIOACCUMULATION FACTORS 10.1346.0044.8800 10134600168800C006 TZ O8/01/2013 BSW 09/01/2013 CT 07/03/2013 SNS 07/03/2013 AS SHOWN 0 FIGURE: 5

Cenovus FCCL Ltd. - 16 - Appendix 3-VII Overall, the box plots of the PC 1 and PC 2 scores for the two projects immediately adjacent to the Project (Cenovus CLTP Phases E, F and G, and Cenovus Narrows Lake) overlap with the boxplots of most of the remaining projects suggesting that the range of variability in Labrador tea BAFs in the region is also representative of the immediate vicinity of the Project. This similar range of variability also suggests similar chemical uptake of mineral soil to Labrador tea for the region. 3.3.2 Alder Regional Bioaccumulation Factor Analysis A total of 62 paired mineral soil and alder leaf samples were used to examine regional BAFs for metals. The first two components derived by PCA explained a large proportion of the variance (59.1%; Table 6) in the alder BAF data set. PC 1 had positive correlations for most metal parameters. A separate factor for variability (PC 2 ) indicates an inverse relationship of boron and cadmium versus aluminum, chromium and vanadium. In Table 6, lead, molybdenum and zinc are not well-represented in either PC 1 or PC 2, suggesting that the variability of lead, molybdenum and zinc are related to different factors than the other metals examined. Table 6 Summary of Principal Components Analysis on Alder Regional Bioaccumulation Factor Data Metal PC 1 PC 2 Aluminum 0.646-0.702 Barium 0.835 0.309 Boron 0.359 0.733 Cadmium 0.337 0.693 Chromium 0.516-0.689 Cobalt 0.831-0.155 Copper 0.784 0.257 Lead 0.434-0.431 Manganese 0.76 0.065 Mercury 0.36 0.486 Molybdenum -0.098 0.035 Nickel 0.849-0.049 Strontium 0.828 0.415 Vanadium 0.488-0.719 Zinc 0.325-0.008 % Variance explained 37.2 21.9 Note: Principal component loadings more than 0.5 are bolded.

Cenovus FCCL Ltd. - 17 - Appendix 3-VII The PCA findings for alder BAFs (Figure 6) are similar but not identical to the findings for Labrador tea BAFs (Figure 4). Most sample locations from the region show a similar scatter in PC 1 and PC 2. A few sample locations from the Canadian Natural Kirby area indicate a high score in PC 1 and a low score in PC 2. A few sample locations from Cenovus Narrows Lake, ConocoPhillips Surmont and Canadian Natural Kirby areas are low in both PC 1 and PC 2 scores. No single area has a unique pattern although some areas (i.e., Canadian Natural Kirby and Cenovus CLTP Phases E, F and G) do show greater variability. As with Labrador tea, the box plots of alder PC 1 and PC 2 scores show a high degree of overlap in the BAFs among the different lease areas (Figure 7), especially for PC 2, suggesting that none of the areas are unique in terms of BAFs. The box plots of PC 1 scores by lease area indicate that Cenovus Narrows Lake and the Canadian Natural Primrose areas have similar ranges of PC 1 scores. The Cenovus CLTP Phases E, F and G and Canadian Natural Kirby areas have a similar range and mean for PC 1 scores. The ConocoPhillips Surmont area has the lowest PC 1 scores in the region. All areas have similar ranges of PC 2 scores. The Cenovus CLTP Phases E, F and G, Canadian Natural Primrose and Canadian Natural Kirby areas have similar mean PC 2 scores. The ConocoPhillips Surmont and Narrow Lake areas have similar mean PC 2 scores. The high degree of overlap for PC 1 and PC 2 scores suggests that uptake of metals from soil to alder leaves is similar in the region. 3.3.3 Berry Regional Bioaccumulation Factor Analysis A total of 56 paired mineral soil and berry samples were used to examine the regional BAF for metals. The first two components derived by PCA explained a large proportion of the variance (62.0%; Table 7) in the berry BAF data set. PC 1 had positive correlations for most metal parameters and explains most of the sample variability (Table 7). PC 2 had strong positive correlations for barium and boron. Molybdenum was the only metal in Table 7 which was not included in either PC 1 or PC 2.

CHRISTINA LAKE THERMAL PROJECT PHASE H AND EASTERN EXPANSION ORDINATION PLOT OF REGIONAL ALDER BIOACCUMULATION FACTORS 10.1346.0044.8800 10134600168800C007 TZ O8/01/2013 BSW 09/01/2013 CT 07/03/2013 SNS 07/03/2013 AS SHOWN 0 FIGURE: 6

PC 1 PC 2 CHRISTINA LAKE THERMAL PROJECT PHASE H AND EASTERN EXPANSION BOX PLOT OF PC 1 AND PC 2 FOR REGIONAL ALDER BIOACCUMULATION FACTORS 10.1346.0044.8800 10134600168800C011 TZ O8/01/2013 BSW 09/01/2013 CT 07/03/2013 SNS 07/03/2013 AS SHOWN 0 FIGURE: 7

Cenovus FCCL Ltd. - 20 - Appendix 3-VII Table 7 Summary of Principal Components Analysis on Berry Regional Bioaccumulation Factor Data Metal PC 1 PC 2 Aluminum 0.777-0.35 Barium 0.724 0.547 Boron 0.469 0.767 Chromium 0.775-0.375 Cobalt 0.819-0.289 Copper 0.809 0.183 Lead 0.582-0.431 Manganese 0.711 0.21 Molybdenum 0.199 0.053 Nickel 0.836 0.066 Strontium 0.576 0.372 Zinc 0.635-0.448 % Variance explained 46.6 15.4 Note: Principal component loadings more than 0.5 are bolded. Similarities occurred for the berry BAF PCA (Figure 8) compared to Labrador tea and alder PCAs (Figures 4 and 6, respectively). A plot of berry PC 1 and PC 2 scores (Figure 8) indicate that most of the BAFs are clustered together. A few sample locations for the Canadian Natural Primrose and ConocoPhillips Surmont areas appear different from the regional cluster (Figure 8). However, there is overlap between all lease areas without a single lease area appearing unique for uptake of metals from mineral soil to berries. The box plots of berry PC 1 and PC 2 scores show a high degree of overlap in the BAFs among the different lease areas (Figure 9), especially for PC 2, suggesting that none of the areas are unique in terms of BAFs. Cenovus Narrows Lake, Cenovus CLTP Phases E, F and G, Canadian Natural Primrose and Canadian Natural Kirby areas each have an overlapping range of PC 1 scores with the Cenovus CLTP Phases E, F and G and Canadian Natural Kirby areas having similar mean PC 1 scores. Box plots of PC 2 scores indicate overlapping ranges for all of the lease areas. Cenovus Narrows Lake, Cenovus CLTP Phases E, F and G and Canadian Natural Primrose areas have a similar mean for PC 2 scores (Figure 9). The Canadian Natural Kirby and ConocoPhillips Surmont areas have similar mean PC 2 scores.

CHRISTINA LAKE THERMAL PROJECT PHASE H AND EASTERN EXPANSION ORDINATION PLOT OF REGIONAL BERRY BIOACCUMULATION FACTORS 10.1346.0044.8800 10134600168800C008 TZ O8/01/2013 BSW 09/01/2013 CT 07/03/2013 SNS 07/03/2013 AS SHOWN 0 FIGURE: 8

PC 1 PC 2 CHRISTINA LAKE THERMAL PROJECT PHASE H AND EASTERN EXPANSION BOX PLOT OF PC 1 AND PC 2 SCORES FOR REGIONAL BERRY BIOACCUMULATION FACTORS 10.1346.0044.8800 10134600168800C012 TZ O8/01/2013 BSW 09/01/2013 CT 07/03/2013 SNS 07/03/2013 AS SHOWN 0 FIGURE: 9

Cenovus FCCL Ltd. - 23 - Appendix 3-VII Overall, the box plots of the PC 1 and PC 2 scores for the two project immediately adjacent to the Project (Cenovus CLTP Phases E, F and G, 1E, 1E and 1F; and Narrow Lake) overlap with the boxplots of most of the remaining projects suggesting that the range of variability in berry BAFs in the region is also representative of the immediate vicinity of the Project. This similar range of variability also suggests that uptake for metals from mineral soil to berries is similar for the region. 3.3.4 Cattail Regional Bioaccumulation Factor Analysis Cattail roots were collected in two media, organic soil and mineral soil. A total of 28 paired organic soil and cattail root samples were available from the regional data set to perform the analysis. However, only 14 paired cattail root and mineral soil samples were available to conduct the analysis as a lower proportion of cattails grown in mineral soil was found in the region compared to organic soil. For cattail roots collected from organic soil there is a fair amount of overlap in samples collected from the different lease areas as shown in Figure 10. PC 1 and PC 2 describe 60.8% of the variability in cattail BAFs (for organic soil) as shown in in Table 8. However, molybdenum and boron were less well-represented in either PC 1 or PC 2. A few sample locations from the ConocoPhillips Surmont area indicate greater variability. Overall, there is a high degree of overlap of sample location scores for PC 1 and PC 2 for the different areas. Sample locations from the Cenovus CLTP Phases E, F and G, Canadian Natural Primrose and ConocoPhillips Surmont areas have a similar range of PC 1 scores. Cenovus Narrows Lake has the lowest variability of PC 1 scores (Figure 11) while the Cenovus CLTP Phases E, F and G and Canadian Natural Primrose areas have similar means for PC 1 scores. The Canadian Natural Kirby and ConocoPhillips Surmont areas have similar means for PC 1 scores. The Cenovus CLTP Phases E, F and G, Canadian Natural Kirby and Canadian Natural Primrose areas have similar ranges and means for PC 2 scores as do Cenovus Narrows Lake and ConocoPhillips Surmont areas. The analysis of the limited data set (i.e., 28 samples) indicates there is similarity for ranges and means of PC 1 and PC 2 scores suggesting that uptake of metals to cattail roots from organic soil is similar for the region.

Cenovus FCCL Ltd. - 24 - Appendix 3-VII Table 8 Summary of Principal Components Analysis on Cattail Root Bioaccumulation Factors Collected From Organic Soil Metal PC 1 PC 2 Aluminum 0.847 0.059 Arsenic 0.475-0.753 Barium 0.381-0.737 Boron 0.302-0.306 Cadmium 0.77 0.343 Chromium 0.768 0.016 Cobalt 0.883 0.102 Copper 0.828 0.358 Lead 0.404-0.725 Manganese 0.434 0.548 Mercury 0.689 0.359 Molybdenum 0.361-0.098 Nickel 0.896-0.002 Selenium 0.322-0.516 Strontium 0.641 0.381 Uranium 0.786-0.115 Vanadium 0.596-0.678 Zinc 0.518 0.54 % Variance explained 40.8 20.0 Note: Principal component loadings more than 0.5 are bolded.

CHRISTINA LAKE THERMAL PROJECT PHASE H AND EASTERN EXPANSION ORDINATION PLOT OF REGIONAL CATTAIL ROOT IN ORGANIC SOIL BIOACCUMULATION FACTORS 10.1346.0044.8800 10134600168800C009 TZ O8/01/2013 BSW 09/01/2013 CT 07/03/2013 SNS 07/03/2013 AS SHOWN 0 FIGURE: 10

PC 1 PC 2 CHRISTINA LAKE THERMAL PROJECT PHASE H AND EASTERN EXPANSION BOX PLOT OF PC 1 AND PC 2 SCORES FOR CATTAIL ROOTS IN ORGANIC SOIL BIOACCUMULATION FACTORS 10.1346.0044.8800 10134600168800C013 TZ O8/01/2013 BSW 09/01/2013 CT 07/03/2013 SNS 07/03/2013 AS SHOWN 0 FIGURE: 11

Cenovus FCCL Ltd. - 27 - Appendix 3-VII Cattail roots collected from mineral soil were not as common in the region compared to root samples collected from organic soil. Selenium was the only metal not wellrepresented in either PC 1 or PC 2. The samples which have been collected indicate that there is a difference in bioaccumulation in cattail roots collected from organic soil compared to cattail roots collected from mineral soil (comparing to Table 9). A lack of distinct patterns for sample locations using PC 1 and PC 2 scores was found, as shown in Figure 12. A good degree of overlap occurs between the three areas (i.e., Cenovus Narrows Lake, Canadian Natural Kirby and Canadian Natural Primrose) where cattails were collected from mineral soil. Table 9 Summary of Principal Components Analysis on Cattail Root Bioaccumulation Factors Collected From Mineral Soil Metal PC 1 PC 2 Aluminum 0.561-0.705 Arsenic 0.765 0.12 Barium 0.978 0.021 Boron 0.716 0.544 Cadmium 0.839 0.291 Chromium 0.755 0.121 Cobalt 0.951-0.043 Copper 0.788 0.194 Lead 0.738-0.427 Manganese 0.725 0.48 Mercury 0.843 0.064 Molybdenum -0.261 0.643 Nickel 0.921 0.012 Selenium 0.489-0.008 Strontium 0.892 0.185 Uranium 0.704-0.57 Vanadium 0.768-0.469 Zinc 0.951 0.12 % Variance explained 60.5 13.2 Note: Principal component loadings more than 0.5 are bolded. Box plots of the PC 1 and PC 2 scores (Figure 13) indicate similar ranges and means for the three projects where cattails were collected from mineral soil. Although limited (i.e., 14 samples) the available data suggest that uptake of metals from mineral soil to cattail roots is similar across the region.

CHRISTINA LAKE THERMAL PROJECT PHASE H AND EASTERN EXPANSION ORDINATION PLOT OF REGIONAL CATTAIL ROOT IN MINERAL SOIL BIOACCUMULATION FACTORS 10.1346.0044.8800 10134600168800C010 TZ O8/01/2013 BSW 09/01/2013 CT 07/03/2013 SNS 07/03/2013 AS SHOWN 0 FIGURE: 12

PC 1 PC 2 CHRISTINA LAKE THERMAL PROJECT PHASE H AND EASTERN EXPANSION BOX PLOT OF PC 1 AND PC 2 SCORES FOR CATTAIL ROOTS IN MINERAL SOIL BIOACCUMULATION FACTORS 10.1346.0044.8800 10134600168800C014 TZ O8/01/2013 BSW 09/01/2013 CT 07/03/2013 SNS 07/03/2013 AS SHOWN 0 FIGURE: 13

Cenovus FCCL Ltd. - 30 - Appendix 3-VII 3.3.5 Conclusions of Vegetation Principal Component Analysis Based on the results of the regional BAF analysis, the following conclusions were made: most of the metal variance is explained by PC 1 in all the evaluated vegetation BAFs; some sample locations appear to have unique chemistry which does not follow the regional pattern; PC 1 and PC 2 box plots for BAFs indicate similar ranges and means which suggest that pooling the regional data are appropriate; although the BAF analysis for cattails is limited to a smaller sample size and two different rooting media (i.e., n=14 for mineral soil and n=28 for organic soil), the results suggest that BAFs are similar across areas and thus it was considered appropriate to use the regional data; overall, the results of the PCA for BAFs for all vegetation types, indicates that combining individual areas yield a representative regional data set; and it is considered appropriate to use summary statistics (e.g., Upper Confidence Limit of the Mean [UCLM]) from the regional BAF data set to represent metals uptake in the RSA/LSA for use in the human and wildlife health risk assessments. 3.4 REGIONAL BIOACCUMULATION FACTORS The regional BAF analysis indicated that the uptake of metals from mineral soil to vegetation was similar for the region. Therefore, paired tissue and soil samples for similar species from the region were pooled and regional statistics were computed using ProUCL to calculate BAFs for use in the human and wildlife health risk assessments. Non-detects in tissues and soil were treated as the full detection limit. If a sample was non-detect in both tissue and soil, it was not included in the regional statistics. Samples which had non-detects in either soil or plant tissue were included in the BAF data set. ProUCL was used to calculate 95% UCLM for soil to plant uptake factors for use in the human and wildlife health risk assessment (Tables 10 to 14).

Cenovus FCCL Ltd. - 31 - Appendix 3-VII Table 10 Regional 95% Upper Confidence Limit of the Mean Bioaccumulation Factor for Labrador Tea Samples Metal 95% UCLM Bioaccumulation Factor Aluminum 0.32 Arsenic 0.56 Barium 6.73 Bismuth 0.46 Boron 19.20 Cadmium 0.42 Chromium 2.80 Cobalt 0.72 Copper 4.50 Lead 0.27 Manganese 45.90 Mercury 2.93 Molybdenum 0.55 Nickel 3.20 Strontium 5.02 Uranium 0.18 Vanadium 0.66 Zinc 4.60 Table 11 Regional 95% Upper Confidence Limit of the Mean Bioaccumulation Factor for Alder Samples Metal 95% UCLM Bioaccumulation Factor Aluminum 0.10 Arsenic 0.13 Barium 1.81 Boron 20.20 Cadmium 9.52 Chromium 0.82 Cobalt 1.40 Copper 3.40 Lead 1.12 Manganese 10.74 Mercury 2.20 Molybdenum 4.01 Nickel 4.10 Strontium 8.60 Vanadium 0.08 Zinc 17.90

Cenovus FCCL Ltd. - 32 - Appendix 3-VII Table 12 Regional 95% Upper Confidence Limit of the Mean Bioaccumulation Factor for Berry Samples Metal 95% UCLM Bioaccumulation Factor Aluminum 0.13 Arsenic 0.15 Barium 2.21 Bismuth 1.00 Boron 14.10 Cadmium 1.34 Chromium 1.02 Cobalt 0.43 Copper 6.70 Lead 0.86 Manganese 24.60 Mercury 1.06 Molybdenum 6.56 Nickel 2.20 Strontium 3.80 Vanadium 0.07 Zinc 2.56 Table 13 Regional 95% Upper Confidence Limit of the Mean Bioaccumulation Factor for Cattail Root Samples in Organic Soil Metal 95% UCLM Bioaccumulation Factor Aluminum 1.32 Arsenic 2.27 Barium 2.09 Bismuth 0.70 Boron 9.35 Cadmium 0.874 Chromium 4.58 Cobalt 0.86 Copper 1.13 Lead 0.7 Manganese 1.8 Mercury 2.87 Molybdenum 9.03 Nickel 2.4 Selenium 0.82 Strontium 3.3 Uranium 0.66 Vanadium 1.34 Zinc 1.17

Cenovus FCCL Ltd. - 33 - Appendix 3-VII Table 14 Regional 95% Upper Confidence Limit of the Mean Bioaccumulation Factor for Cattail Root Samples in Mineral Soil Metal Aluminum 1.7 95% UCLM Bioaccumulation Factor Arsenic 10.5 Barium 3.5 Bismuth 2.34 Boron 7.3 Cadmium 3.6 Chromium 5.2 Cobalt 3.4 Copper 2.6 Lead 1.47 Manganese 87.9 Mercury 5.0 Molybdenum 6.2 Nickel 5.7 Selenium 3.6 Strontium 5.7 Uranium 1.25 Vanadium 1.26 Zinc 6.4 3.5 REGIONAL VEGETATION CONCENTRATIONS The PCA of mineral soil and soil to plant uptake factors indicated that the individual lease areas could be relied on to describe regional patterns. Therefore, it was inferred that vegetation would follow the same pattern. Therefore, regional vegetation data were combined by vegetation type into one data set and the 95% UCLM concentrations for each of the vegetation types was computed (Tables 15 to 17). Cattail roots were analyzed as peeled and un-peeled samples. Cattail roots form a tough outer skin and all new growth is at the centre of the root (which is the recommended edible portion; Elias and Dykeman 1990). The human health risk assessment assumed that people in the region consume peeled cattails. Therefore, five cattail root samples collected from Cenovus Narrows Lake and Cenovus CLTP Phases E, F and G in 2007 and 2008 were peeled and then analyzed. The results are presented in Table 18 and the maximum concentration of the five samples was used in the human health risk assessment.

Cenovus FCCL Ltd. - 34 - Appendix 3-VII Table 15 Regional 95% Upper Confidence Limit of the Mean for Labrador Tea Samples Parameter 95% UCLM Concentration [dry weight mg/kg] Percent of Results Less than Detection Limit Moisture 58.5 0.0 Aluminum 272.3 0.0 Antimony 0.13 97.0 Arsenic 0.25 84.5 Barium 85.73 0.0 Beryllium <0.05 100.0 Bismuth 0.03 94.0 Boron 19.8 0.0 Cadmium 0.03 86.3 Chromium 5.07 0.0 Cobalt 0.24 1.5 Copper 5.8 0.0 Lead 0.41 1.5 Manganese 376 0.0 Mercury 0.019 12.2 Molybdenum 0.325 37.9 Nickel 2.8 0.0 Selenium <0.1 98.5 Silver <1.0 100.0 Strontium 12.33 0.0 Thallium <0.06 100.0 Uranium <0.02 100.0 Vanadium 0.369 53.3 Zinc 25.1 0.0

Cenovus FCCL Ltd. - 35 - Appendix 3-VII Table 16 Regional 95% Upper Confidence Limit of the Mean for Alder Samples Parameter 95% UCLM Concentration [dry weight mg/kg] Percent of Results Less than Detection Limit Moisture 64.6 0.0 Aluminum 80.7 0.0 Antimony 0.17 96.8 Arsenic 0.08 85.7 Barium 32.5 0.0 Beryllium 0.05 93.7 Bismuth 0.27 95.2 Boron 26.5 0.0 Cadmium 0.41 46.0 Chromium 2.4 3.2 Cobalt 0.8 0.0 Copper 5.7 0.0 Lead 0.58 3.2 Manganese 330 0.0 Mercury 0.02 35.0 Molybdenum 2.3 6.4 Nickel 4.6 0.0 Selenium 0.12 95.2 Silver <1.0 100.0 Strontium 21.5 0.0 Thallium <0.06 100.0 Uranium <0.02 93.3 Vanadium 0.13 52.4 Zinc 100.4 0.0

Cenovus FCCL Ltd. - 36 - Appendix 3-VII Table 17 Regional 95% Upper Confidence Limit of the Mean for Berries Parameter 95% UCLM Concentration [dry weight mg/kg] Percent of Results Less than Detection Limit Moisture 81.78 0.0 Aluminum 240.6 0.0 Antimony <0.06 100.0 Arsenic 0.1 90.2 Barium 25.17 0.0 Beryllium <0.05 100.0 Bismuth 0.03 93.4 Boron 14.8 0.0 Cadmium 0.06 68.9 Chromium 1.5 13.11 Cobalt 0.131 1.64 Copper 8.02 8.2 Lead 0.45 23.0 Manganese 262.9 0.0 Mercury 0.06 95.0 Molybdenum 1.7 1.6 Nickel 2.07 0.0 Selenium 0.11 96.7 Silver <1.0 100 Strontium 23.5 0.0 Thallium <0.06 100.0 Uranium <0.02 98.3 Vanadium 0.2 90.0 Zinc 21.4 0.0

Cenovus FCCL Ltd. - 37 - Appendix 3-VII Table 18 Results of Chemical Analysis for Peeled Cattail Root Samples Sample Cenovus CLTP Phases E, F and G Concentration [mg/kg dry weight] Cenovus Narrows Lake SP4A-C C-7 C-7D C-7T C-8 Maximum % Moisture 90.6 78.0 89.0 85.0 93.0 93.0 Aluminum 75 11.0 23.0 14.0 27.0 75.0 Arsenic 0.5 0.07 0.08 0.17 0.05 0.5 Silver <1.0 <1.0 <1.0 <1.0 <1.0 <1.0 Barium 15.3 7.51 9.19 7.8 5.52 15.3 Beryllium <0.05 <0.05 <0.05 <0.05 <0.05 0.05 Boron 7.8 6.9 7.3 8.5 8.2 8.5 Cadmium <0.02 <0.02 <0.02 <0.02 <0.02 0.02 Chromium 1.3 <0.1 0.7 0.1 1.5 1.5 Cobalt 0.28 0.02 0.05 0.03 0.05 0.28 Copper 0.5 0.3 0.9 0.4 1.0 1.0 Lead 0.2 0.07 0.07 0.11 0.1 0.2 Mercury 0.009 <0.008 <0.008 <0.008 <0.008 0.009 Manganese 673 164 312 167 99.6 673 Molybdenum 2.04 0.15 0.24 0.22 0.18 2.04 Nickel 0.8 <0.1 0.8 0.1 0.9 0.9 Antimony <0.06 <0.06 <0.06 <0.06 <0.06 <0.06 Selenium <0.1 <0.1 <0.1 <0.1 <0.1 0.1 Strontium 9.89 13.7 19.3 13.3 14.3 19.3 Thallium <0.06 <0.06 <0.06 <0.06 <0.06 <0.06 Uranium <0.02 <0.02 <0.02 <0.02 <0.02 <0.02 Vanadium 0.13 <0.06 <0.06 <0.06 <0.06 0.13 Zinc 18.1 10.8 38 11.9 39.5 39.5

Cenovus FCCL Ltd. - 38 - Appendix 3-VII 4 REFERENCES Canadian Natural (Canadian Natural Resources Limited). 2006. Primrose In-Situ Oil Sands Project. Primrose East Expansion Application for Approval. Volumes 1 to 6. Submitted to Alberta Energy and Utilities Board and Alberta Environment. Prepared by Golder Associates Ltd. Calgary, AB. Submitted January 2006. Canadian Natural. 2007. Kirby In-Situ Oil Sands Project Application for Approval. Volumes 1 to 6. Submitted to Energy Resources Conservation Board and Alberta Environment. September 2007. Calgary, AB. Canadian Natural. 2008. Kirby In-Situ Oil Sands Project Application for Approval. Human Health Risk Impact Assessment, Wildlife Health Risk Impact Assessment, Supplemental Baseline Data. Submitted to Energy Resources Conservation Board and Alberta Environment. February 2008. Calgary, AB. Cenovus (Cenovus FCCL Ltd.). 2010. Application for Approval of the Cenovus Narrows Lake Project. Integrated Application and Environmental Impact Assessment. Submitted to the Alberta Energy Resources Conservation Board and Alberta Environment. June 2010. Calgary, AB. Cenovus. 2011. Christina Lake Thermal Project Phases F and G Application for Amendment to Energy Resources Conservation Board Approval No. 8591 and Alberta Environment and Water Approval 48522-01-00. Submitted to Alberta Energy Resources Conservation Board and Alberta Environment and Water. December 2011. Elias, T.S. and P.A. Dykeman. 1990. Edible Wild Plants: A North American Field Guide. Published 1990 by Sterling publishing Co. Inc. 387 Park Avenue South. New York. NY 10016. Distributed in Canada by Sterling publishing. ISBN 0-8069-7488-5. EnCana (EnCana FCCL Ltd.). 2009. Application for Approval of the EnCana Christina Lake Thermal Expansion Project, Phases 1E, 1F and 1G. Integrated Application and Environmental Impact Assessment. Submitted to the Alberta Energy Resources Conservation Board and Alberta Environment, October 2009. Calgary, AB.

Cenovus FCCL Ltd. - 39 - Appendix 3-VII ESRD (Alberta Environment and Sustainable Resource Development). 2012. Terms of Reference Environmental Impact Assessment Report for Cenovus FCCL Ltd.'s Proposed Christina Lake Thermal Project - Phase H and Eastern Expansion Approximately 20 km from Conklin, Alberta. Issued by Alberta Environment and Sustainable Resources Development November 15, 2012. Edmonton, AB. 19 pp. Gauch, H.G. 1982. Multivariate Analysis in Community Ecology. Cambridge University Press. New York, NY. U.S. EPA (United States Environmental Protection Agency). 2006. Data Quality Assessment: Statistical Methods for Practitioners QA/G-9S. EPA/240/B- 06/003. Washington, D.C., Office of Environmental Information. Ref Type: Report.

Cenovus FCCL Ltd. - 40 - Appendix 3-VII 5 ABBREVIATIONS % Percent < Less than BAF Canadian Natural Canadian Natural Kirby Bioaccumulation Factors Canadian Natural Resources Limited Canadian Natural Resources Limited Kirby In-Situ Oil Sands Project Canadian Natural Primrose Canadian Natural Resources Limited Primrose East In-Situ Oil Sands Project Cenovus CLTP Phases E, F and G ConocoPhillips C s C t LSA mg/kg n PAH PCA PCs QA/QC RSA the Project U.S. EPA UCL UCLM Cenovus FCCL Ltd. Christina Lake Thermal Project Phases 1E, 1F and 1G ConocoPhillips Canada Concentration in soil Concentration in tissue Local Study Area Milligrams per kilogram Number of samples Polycyclic aromatic hydrocarbons Principal Components Analysis Principal Components Quality Assurance/Quality Control Regional Study Area Christina Lake Thermal Project Phase H and Eastern Expansion United States Environmental Protection Agency Upper Confidence Limit Upper Confidence Limit of the Mean

Cenovus FCCL Ltd. - 41 - Appendix 3-VII 6 GLOSSARY Baseline Bioaccumulation Country Foods Local Study Area (LSA) Mineral Soil Organic soil Peat Polycyclic Aromatic Hydrocarbon (PAH) Regional Study Area (RSA) Wildlife A surveyed or predicted condition that serves as a reference point to which later surveys are coordinated or correlated. When an organism stores within its body a higher concentration of a substance than is found in the environment. This is not necessarily harmful. For example, freshwater fish must bioaccumulate salt to survive in intertidal waters. Many toxicants, such as arsenic, are not included among the dangerous bioaccumulative substances because they can be handled and excreted by aquatic organisms. Dietary items from the local region which are used for sustenance. Country food items include: fruit, vegetables, herbs, medicinal plants, fish and game. Defines the spatial extent directly or indirectly affected by the project. Soils containing low levels of organic matter. Soils that have evolved on fluvial, glaciofluvial, lacustrine and morainal parent material. The A, B and C horizons and underlying parent material. A material composed almost entirely of organic matter from the partial decomposition of plants growing in wet conditions. A material composed almost entirely of organic matter from the partial decomposition of plants growing in wet conditions. A chemical by-product. Aromatics are considered to be highly toxic components of petroleum products. PAHs, many of which are potential carcinogens, are composed of at least two fused benzene rings. Toxicity increases along with molecular size and degree of alkylation of the aromatic nucleus. Represents the area of study for the assessment of cumulative (combined) effects of the Project and other past, existing or planned developments. Under the Species at Risk Act, wildlife is defined as a species, subspecies, variety or geographically or genetically distinct population of animal, plant or other organism, other than a bacterium or virus that is wild by nature and is native to Canada or has extended its range into Canada without human intervention and has been present in Canada for at least 50 years.