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Estimation of apparent rate coefficients for phenanthrene and pentachlorophenol interacting with sediments
Hua-Lin Chen1, Ying-Xu Chen, Yun-Tai Xu
1Department of Environmental Engineering, Huajiachi Campus, Zhejiang University, Hangzhou 310029, PR China.
Environmental Pollution (Barking, Essex : 1987)
|July 6, 2004
Summary
A compartment model tracked organic pollutants phenanthrene and pentachlorophenol (PCP) in sediments. Results show pollutant sorption involves reversible and irreversible phases, with mass transfer between them over time.
Area of Science:
- Environmental Chemistry
- Environmental Science
- Geochemistry
Background:
- Organic pollutants in water-sediment systems pose environmental risks.
- Understanding pollutant sorption dynamics is crucial for risk assessment.
- Phenanthrene and pentachlorophenol (PCP) are common organic pollutants.
Purpose of the Study:
- To investigate the sorption behavior of phenanthrene and PCP in sediments.
- To model the time-dependent interactions of these pollutants with sediment fractions.
- To elucidate the mass transfer processes between reversible and irreversible sediment phases.
Main Methods:
- Application of a compartment model to describe pollutant-sediment interactions.
- Utilizing first-order differential equations to model phase interactions.
- Employing numerical optimization software to obtain apparent rate constants.
- Experimental extraction using hot methanol to determine pollutant concentrations.
Main Results:
- The reversible sediment phase increased initially then decreased, indicating mass transfer.
- The irreversible sediment phase showed a continuous increase over the sorption period.
- Extraction efficiency of phenanthrene and PCP decreased with increasing sorption time.
- Apparent rate constants for sorption were successfully obtained via model fitting.
Conclusions:
- A compartment model effectively describes phenanthrene and PCP sorption in sediments.
- Mass transport occurs between reversible and irreversible sediment fractions.
- Sorption time influences both the partitioning of pollutants and extraction efficiency.