| Title: | Adsorption of low-concentration VOCs on various adsorbents: Correlating partition coefficient with surface energy of adsorbent |
| Author(s): | Liu H; Xu B; Wei K; Yu Y; Long C; |
| Address: | "State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China. State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China. Electronic address: clong@nju.edu.cn" |
| DOI: | 10.1016/j.scitotenv.2020.139376 |
| ISSN/ISBN: | 1879-1026 (Electronic) 0048-9697 (Linking) |
| Abstract: | "Accurately evaluating the adsorption properties of various adsorbents by some parameter is of great significance to select an appropriate adsorbent and remove volatile organic compounds (VOCs) efficiently. In this study, we successfully found a new parameter as a common standard in selecting adsorbents. Six classical adsorbents containing three carbon materials and three porous polymeric resins were used, and their surface energy (gamma(s)(t)) and corresponding gas-solid partition coefficients (K) of eleven VOCs were measured by inverse gas chromatography (IGC) at three different column temperatures of 343 K(or 353 K), 373 K and 403 K. Then, these values at 303 K were calculated according to the linear relationship between lnK and 1/T. It was found that surface energy was significantly correlated with K values for a specific VOC, and could be used as a common standard to well evaluate the adsorption properties of various adsorbents. Furthermore, we employed it to develop a model for predicting the adsorption properties of low-concentration VOCs on various adsorbents at 303 K. The developed model exhibited an excellent predictive ability by external validation. Moreover, the model showed wide applicability and predicted the lnK values of VOCs at 373 K and 403 K in R(2) of 0.910 and 0.889" |
| Keywords: | Adsorption Correlation Inverse gas chromatography Surface energy VOCs; |
| Notes: | "PubMed-not-MEDLINELiu, Huijuan Xu, Bowen Wei, Keyan Yu, Yansong Long, Chao eng Netherlands 2020/05/24 Sci Total Environ. 2020 Sep 1; 733:139376. doi: 10.1016/j.scitotenv.2020.139376. Epub 2020 May 15" |
