Journal
ENVIRONMENTAL ENGINEERING SCIENCE
Volume 37, Issue 7, Pages 459-471Publisher
MARY ANN LIEBERT, INC
DOI: 10.1089/ees.2019.0471
Keywords
activated carbon; adsorption modeling; biochar; contaminants of emerging concern; rapid small-scale column testing; wastewater
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Funding
- Water Environment and Reuse Foundation [WERF 13-10]
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Organic micropollutants (MPs), such as pesticides, pharmaceuticals, industrial compounds, and waste breakdown products occurring in waters at ng/L-mu g/L levels are a threat to ecosystems and human health. Adsorption of MPs using granular activated carbon (GAC) is an increasingly common treatment process. Biochar is a promising low-cost, environmentally sustainable surrogate for GAC in diverse water quality applications. Challenges remain, however, for accurately simulating real-world biochar and GAC adsorbers in laboratory experiments. The goal of this research was to develop a scale-up procedure for predicting the adsorption of organic MPs from water containing background dissolved organic matter (DOM) by GAC and biochar using bench-scale column tests. The removal of 11 native MPs in wastewater effluent by GAC and biochar was quantified using pilot-scale adsorbers and rapid small-scale column tests (RSSCTs). Batch isotherm studies were conducted and RSSCT data were fit with two different surface and pore diffusion models to obtain equilibrium and kinetic parameters for each MP-adsorbent combination. The diffusion models were used to predict MP breakthrough at full scale, and predictions compared with pilot column data. A third scale-up approach was applied using a fouling index to account for the effects of DOM competition and pore blockage on MP uptake. A fourth approach was applied using direct empirical correlation between early MP breakthrough in RSSCT and pilot columns. The criterion for comparison of the ability of model-based and empirical scale-up approaches to accurately simulate pilot-scale adsorption was the number of bed volumes treated until MP breakthrough at 10% of the influent concentration (BV10%). Data obtained in this study as well as from the literature were used to develop an empirical regression based on RSSCT BV10% values to provide a user-oriented, conservative approach to predicting full-scale MP breakthrough that can be used for the design and operation of biochar and GAC treatment systems.
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