Deep Learning Neural Network Approach for Predicting the Sorption of Ionizable and Polar Organic Pollutants to a Wide Range of Carbonaceous Materials

Overview

Journal Environ Sci Technol

Publisher American Chemical Society

Specialty Environmental Health

Date 2020 Mar 4

PMID 32124609

Citations 15

Authors

Gabriel Sigmund

Mehdi Gharasoo

Thorsten Huffer

Thilo Hofmann

Affiliations

Soon will be listed here.

Abstract

Most contaminants of emerging concern are polar and/or ionizable organic compounds, whose removal from engineered and environmental systems is difficult. Carbonaceous sorbents include activated carbon, biochar, fullerenes, and carbon nanotubes, with applications such as drinking water filtration, wastewater treatment, and contaminant remediation. Tools for predicting sorption of many emerging contaminants to these sorbents are lacking because existing models were developed for neutral compounds. A method to select the appropriate sorbent for a given contaminant based on the ability to predict sorption is required by researchers and practitioners alike. Here, we present a widely applicable deep learning neural network approach that excellently predicted the conventionally used Freundlich isotherm fitting parameters log and ( > 0.98 for log , and > 0.91 for ). The neural network models are based on parameters generally available for carbonaceous sorbents and/or parameters freely available from online databases. A freely accessible graphical user interface is provided.

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References

Gharasoo M, Ehrl B, Cirpka O, Elsner M . Modeling of Contaminant Biodegradation and Compound-Specific Isotope Fractionation in Chemostats at Low Dilution Rates. Environ Sci Technol. 2018; 53(3):1186-1196. PMC: 6986770. DOI: 10.1021/acs.est.8b02498. View

Wang S, Tzou Y, Lu Y, Sheng G . Removal of 3-chlorophenol from water using rice-straw-based carbon. J Hazard Mater. 2007; 147(1-2):313-8. DOI: 10.1016/j.jhazmat.2007.01.031. View

Li X, Zhao H, Quan X, Chen S, Zhang Y, Yu H . Adsorption of ionizable organic contaminants on multi-walled carbon nanotubes with different oxygen contents. J Hazard Mater. 2010; 186(1):407-15. DOI: 10.1016/j.jhazmat.2010.11.012. View

Chang Z, Tian L, Wu M, Dong X, Peng J, Pan B . Molecular markers of benzene polycarboxylic acids in describing biochar physiochemical properties and sorption characteristics. Environ Pollut. 2018; 237:541-548. DOI: 10.1016/j.envpol.2018.02.071. View

Chingombe P, Saha B, Wakeman R . Effect of surface modification of an engineered activated carbon on the sorption of 2,4-dichlorophenoxy acetic acid and benazolin from water. J Colloid Interface Sci. 2005; 297(2):434-42. DOI: 10.1016/j.jcis.2005.10.054. View

Han X, Liang C, Li T, Wang K, Huang H, Yang X . Simultaneous removal of cadmium and sulfamethoxazole from aqueous solution by rice straw biochar. J Zhejiang Univ Sci B. 2013; 14(7):640-9. PMC: 3709069. DOI: 10.1631/jzus.B1200353. View

Sun K, Ro K, Guo M, Novak J, Mashayekhi H, Xing B . Sorption of bisphenol A, 17α-ethinyl estradiol and phenanthrene on thermally and hydrothermally produced biochars. Bioresour Technol. 2011; 102(10):5757-63. DOI: 10.1016/j.biortech.2011.03.038. View

Lu Z, MacFarlane J, Gschwend P . Adsorption of Organic Compounds to Diesel Soot: Frontal Analysis and Polyparameter Linear Free-Energy Relationship. Environ Sci Technol. 2015; 50(1):285-93. DOI: 10.1021/acs.est.5b03605. View

Wang Z, Yu X, Pan B, Xing B . Norfloxacin sorption and its thermodynamics on surface-modified carbon nanotubes. Environ Sci Technol. 2009; 44(3):978-84. DOI: 10.1021/es902775u. View

10.

Uchimiya M, Wartelle L, Lima I, Klasson K . Sorption of deisopropylatrazine on broiler litter biochars. J Agric Food Chem. 2010; 58(23):12350-6. DOI: 10.1021/jf102152q. View

11.

Liao P, Yuan S, Zhang W, Tong M, Wang K . Mechanistic aspects of nitrogen-heterocyclic compound adsorption on bamboo charcoal. J Colloid Interface Sci. 2012; 382(1):74-81. DOI: 10.1016/j.jcis.2012.05.052. View

12.

Endo S, Goss K . Applications of polyparameter linear free energy relationships in environmental chemistry. Environ Sci Technol. 2014; 48(21):12477-91. DOI: 10.1021/es503369t. View

13.

Zhang C, Lai C, Zeng G, Huang D, Yang C, Wang Y . Efficacy of carbonaceous nanocomposites for sorbing ionizable antibiotic sulfamethazine from aqueous solution. Water Res. 2016; 95:103-12. DOI: 10.1016/j.watres.2016.03.014. View

14.

Huffer T, Endo S, Metzelder F, Schroth S, Schmidt T . Prediction of sorption of aromatic and aliphatic organic compounds by carbon nanotubes using poly-parameter linear free-energy relationships. Water Res. 2014; 59:295-303. DOI: 10.1016/j.watres.2014.04.029. View

15.

Ji L, Chen W, Bi J, Zheng S, Xu Z, Zhu D . Adsorption of tetracycline on single-walled and multi-walled carbon nanotubes as affected by aqueous solution chemistry. Environ Toxicol Chem. 2010; 29(12):2713-9. DOI: 10.1002/etc.350. View

16.

Liu Y, Sohi S, Jing F, Chen J . Oxidative ageing induces change in the functionality of biochar and hydrochar: Mechanistic insights from sorption of atrazine. Environ Pollut. 2019; 249:1002-1010. DOI: 10.1016/j.envpol.2019.03.035. View

17.

Kearns J, Wellborn L, Summers R, Knappe D . 2,4-D adsorption to biochars: effect of preparation conditions on equilibrium adsorption capacity and comparison with commercial activated carbon literature data. Water Res. 2014; 62:20-8. DOI: 10.1016/j.watres.2014.05.023. View

18.

Li X, Pignatello J, Wang Y, Xing B . New insight into adsorption mechanism of ionizable compounds on carbon nanotubes. Environ Sci Technol. 2013; 47(15):8334-41. DOI: 10.1021/es4011042. View

19.

Gharasoo M, Thullner M, Elsner M . Introduction of a new platform for parameter estimation of kinetically complex environmental systems. Environ Model Softw. 2017; 98:12-20. PMC: 5669308. DOI: 10.1016/j.envsoft.2017.09.005. View

20.

Jia M, Wang F, Bian Y, Stedtfeld R, Liu G, Yu J . Sorption of sulfamethazine to biochars as affected by dissolved organic matters of different origin. Bioresour Technol. 2017; 248(Pt B):36-43. DOI: 10.1016/j.biortech.2017.08.082. View