Electrocoagulation for the Treatment of Oil Sands Tailings Water
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Bibliographic record
Abstract
Title: Electrocoagulation for the treatment of oil sands tailings water The Canadian oil sands industry has been receiving widespread International criticism on environmental issues, among which is its use of water resources. A major process to recover the valuable bitumen (a heavy, viscous form of petroleum) from the oil sands resource is surface mining. A by-product of mining operations is large volumes of toxic tailings water which are stored in large dykes, the infamous ‘tailings ponds’, covering a total area greater than 175 sq. km. These have led to significant environmental damage because of land displacement, the contamination of natural waters, and impact on wildlife such as waterfowl that land into the water surface. Large volumes of fresh water are withdrawn to make up for the water being stored as tailings water. On average about 3 barrels of fresh water are withdrawn per barrel of bitumen produced, the main source of fresh water being the Athabasca River. The local communities and stakeholders have expressed concerns about fresh water withdrawal rates, potentially creating water shortage issues. The nature of contaminants in tailings wastewaters makes the treatment processes costly in order to minimize environmental impact, hence the operators are forced to store the water as ponds. Tailings water is a complex mixture of contaminants, very fine clay particles that take decades to settle, toxic organic compounds such as naphthenic acids and polycyclic aromatic hydrocarbons (PAH’s), silica, and heavy metals including nickel, vanadium, arsenic and mercury. Since the start of mining operations in 1967, the oil sands industry is yet to implement a method to treat tailings water, alleviate the use of tailings ponds, and significantly increase recycle rates. Electrocoagulation (EC) is one technology that could address these issues. Prior research on various other wastewaters has shown that EC can remove several contaminants including fine suspended solids, toxic organic matter, silica, and heavy metals [1] which are the common contaminants in oil sands tailings water. In its simplest form, EC uses an electrochemical cell to generate coagulating agents in the wastewater by electrochemical reactions, resulting in flocculation of contaminated particles which separate out by settling or flotation. Currently, coagulation and flocculation of most industrial wastewaters are performed by the use of chemicals like metal salts. However, EC has many advantages over the chemical method. The electric field used in EC enhances the flocculation process by setting the charged colloidal particles in motion resulting in the coagulation of even very fine suspended solids [2]. This will be advantageous when applied to tailings water because the most difficult to remove contaminant it contains are the very fine, slow settling clay particles. In addition, EC simultaneously removes heavy metals by precipitation as the pH increases during the process. Furthermore, hydrogen gas bubbles generated at the cathode by water reduction reaction will float the flocculated particles to the water surface, thus providing better separation of contaminants. Another major advantage is that no chemicals are required, minimizing secondary pollution. The high conductivity of tailings water is an advantage, as it will provide low electrolytic solution resistance, leading to low energy requirement. Increased contaminants removal rates, the avoidance of chemical addition, and lower energy consumption suggest that EC could reduce the environmental impact and cost of water treatment for treating tailings water. The main research objectives are to investigate the effectiveness of EC for the treatment of tailings water and by removing several contaminants simultaneously. The potential to eliminate tailings ponds by using EC have been explored. Experiments with EC have been conducted on real industrial samples of tailings water and on synthetic wastewater samples prepared in the lab. Contaminant removals have been assessed by measuring various water quality parameters such as turbidity, total suspended solids, “Chemical Oxygen Demand (COD)” and “Total Organic Carbon (TOC)” both of which quantifies the amount of oil present, and the concentrations of heavy metals. Moreover, special attention has been given to the removal of fine particles by the use of water contaminated with fine kaolin clay, the most burdensome of all the contaminants. Also, the effect of different electrochemical reactor designs have been explored. The results are very promising, several contaminants are being removed simultaneously, with removal rates as high as 90%. The results gathered demonstrate that some of the different types of reactor designs tested not just improve contaminant removal rates but also reduce energy consumption significantly. References: [1] M. Emamjomeh, M. Sivakumar, J Environ Manage. 90 (2009) 1663. [2] T. Harif, A. Adin, Water Res. 41 (2007) 2951.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it