Polymer-water partition coefficients in polymeric passive samplers

Passive samplers are of the most applied methods and tools for measuring concentration of hydrophobic organic compounds in water (c (1) (W)) in which the polymer-water partition coefficients (D) are of fundamental importance for reliability of measurements. Due to the cost and time associated with the experimental researches, development of a predictive method for estimation and evaluation of performance of polymeric passive samplers for various hydrophobic organic compounds is highly needed and valuable. For this purpose, in this work, following the fundamental chemical thermodynamic equations governing the concerned local equilibrium, successful attempts were made to establish a theoretical model of polymer-water partition coefficients. Flory-Huggins model based on the Hansen solubility parameters was used for calculation of activity coefficients. The method was examined for reliability of calculations using collected data of three polymeric passive samplers and ten compounds. A regression model of form ln(D) = 0.707ln(c (1) (p) ) - 2.7391 with an R (2) = 0.9744 was obtained to relate the polymer-water partition coefficients (D) and concentration of hydrophobic organic compounds in passive sampler (c (1) (p)). It was also found that polymer-water partition coefficients are related to the concentration of hydrophobic organic compounds in water (c (1) (W)) as ln(D) = 2.412ln(c (1) (p)) - 9.348. Based on the results, the tie lines of concentration for hydrophobic organic compounds in passive sampler (c (1) (p) ) and concentration of hydrophobic organic compounds in water (c (1) (W)) are in the form of ln(c (1) (W)) = 0.293ln(c (1) (p)) + 2.734. The composition of water sample and the interaction parameters of dissolved compound-water and dissolved compound-polymer, temperature, etc. actively influence the values of partition coefficient. The discrepancy observed over experimental data can be simply justified based on the local condition of sampling sites which alter these effective factors.