Organic contaminated sediments remediation with active caps: Nonlinear adsorption unveiled by combined isotherm and column transportation studies. (January 2019)

• Record Type: Journal Article
• Authors: Yin, Ke; Viana, Priscilla Z.; Rockne, Karl J.
• Is Part Of: Chemosphere. Volume 214(2019)
• Page Start: 710
• Page End: 718
• Publication Date: 2019-01
• Subjects: Sediments -- Organic contaminants -- Column study -- Isotherm -- Active cap; Pollution -- Periodicals; Pollution -- Physiological effect -- Periodicals; Environmental sciences -- Periodicals; Atmospheric chemistry -- Periodicals; 551.511
• DOI: 10.1016/j.chemosphere.2018.09.122
• Languages: English
• ISSNs: 0045-6535

Abstract

Abstract: Bench-scale column studies were performed with four cap materials (sand, apatite, organoclay and granular activated carbon) for five target compounds (toluene, naphthalene, phenanthrene, pyrene and dichlorobiphenyl) to represent a range of cap materials and pollutants (volatile & semi-volatile compounds) commonly found in sediments. Two moment-derived methods were used to model cap performance. Rough agreement was observed between the column experiments and modeling data with the fronting and tailing effects identified from certain breakthrough curves indicating a high potential of non-linear adsorption. Distribution coefficients ( k d ) were experimentally determined with isotherm studies together with measurements of surface area and microporosity of the cap materials via nitrogen adsorption porisimetry. These studies unveiled the occurrence of nonlinear adsorption by Freundlich simulation. The effects of nonlinear adsorption of the cap were further explored via modeling. Results suggested better prediction of cap performance assuming nonlinear adsorption instead of linear adsorption results based upon the risk of release for a 30-year period. Highlights: Peak fronting and tailing were noted in BTC suggesting nonlinear adsorption. Nonlinear adsorption was verified via Freundlich model with certain compounds. Method of temporal moments beat peak derivative one to predict BTC with step input. Nonlinear adsorption tends to reduce the risks associated with contaminants release. Increased hydrophobicity may minimize the effects due to non-linear adsorption.