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Evaluating Biochar in Sustainable Stormwater Treatment of Heavy Metals

Sarah Burch
Oregon State University
Presentation file: 
PDF icon 4.3.1 Burch, Sarah.pdf3.29 MB

Heavy metals, such as copper, zinc, and cadmium, are ubiquitous in stormwater and potentially toxic to aquatic organisms at low concentrations. Removal of heavy metals contamination by conventional treatment is expensive and does not always reduce metals concentrations low enough to ensure safety of all aquatic species. This research seeks to evaluate the effectiveness of biochar as a low-cost, sustainable solution for the remediation of heavy metals in stormwater. Different biomass feedstocks of naturally available materials (Douglas fir chips and hazelnut shells) were pyrolyzed at varying temperatures to determine the effects of feedstock and production conditions on biochar characterization and metals removal. Adsorption experiments were conducted in batch reactors and constant flow fixed-bed column filtration experiments. This presentation will introduce motivations and methods of batch and fixed-bed column experiments examining copper removal in synthetic stormwater. Preliminary results of effects of feedstock and pyrolytic temperature on copper removal in batch isotherm experiments were used to select an optimal thermally-altered media. Batch and continuous flow column filtration results will be presented, which indicate that hazelnut shells pyrolyzed at 700°C exhibit superior performance in copper removal compared to other types of biochar examined and granular activated carbon (GAC), the current prevailing adsorbent. Adsorption results will be used in conjunction with biochar characterization and modeling techniques to elucidate the mechanisms for metals removal by biochar, which will be used to inform engineering design and optimize biochar production conditions to advance sustainability. Modeling of batch of continuous flow experiments will move beyond common empirical isotherm models and employ thermodynamically-based surface complexation modeling to predict metals adsorption under varying solution conditions and incorporate electrostatic effects. These electrostatic models are better equipped to evaluate metals removal in solutions of varying pH, ionic strength, and metals loading, making them more suitable for application in complex stormwater systems.

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