Document Type


Publication Date


Journal / Book Title

Water Environment Research


Innovative treatment materials and technologies are demanded to address urban stormwater pollutants that challenge traditional infrastructure. This study aimed to investigate adsorption behaviors of aluminum-based water treatment residual (WTR)-coated mulch for capturing representative runoff pollutants (i.e., P, Cu, Zn, and Pb) and evaluate its treatment performance in a filtration bed. Data from batch studies were fit using the nonlinear least square optimization technique. Adsorption kinetic data followed the pseudo-2 nd -order reaction patterns, while the adsorption isotherm data obeyed the Freundlich models. Model fitting passed the chi-square tests, as a statistical goodness-of-fit criterion, at a 90% confidence level. Column studies indicate that the WTR-coated mulch with a bed depth of 5.1 or 10.2 cm could effectively alleviate flow-weighted mean concentrations of these pollutants, with a minimal aluminum release, during treatment of the equivalent annual runoff in a typical U.S. Northeastern catchment. This study demonstrates that WTR-coated mulch is an effective and safe adsorbent media to tackle urban stormwater pollution. Practitioner points: Aluminum-based WTR-coated wood mulch can simultaneously and effectively capture representative metals and phosphate in urban runoff. The pollutant adsorption follows the pseudo-2 nd -order kinetic reaction patterns and the Freundlich isotherm model. WTR-coated mulch (5.1–10.2 cm bed depth) sufficiently treats the runoff generated annually in a typical U.S. Northeastern catchment. Higher and more reliable pollutant removals can be achieved with a greater bed depth of the coated mulch in a filtration bed. Aluminium release is minimal during application of the WTR-coated wood mulch.



Published Citation

Soleimanifar, H., Deng, Y., Barrett, K., Feng, H., Li, X., & Sarkar, D. (2019). Water treatment residual‐coated wood mulch for addressing urban stormwater pollution. Water Environment Research, 91(6), 523-535.