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Sci Total Environ


Title:"Explainable extreme gradient boosting tree-based prediction of toluene, ethylbenzene and xylene wet deposition"
Author(s):Stojic A; Stanic N; Vukovic G; Stanisic S; Perisic M; Sostaric A; Lazic L;
Address:"Institute of Physics Belgrade, National Institute of the Republic of Serbia, University of Belgrade, Pregrevica 118, 11000 Belgrade, Serbia. Electronic address: andreja.stojic@ipb.ac.rs. Singidunum University, Danijelova 32, 11000 Belgrade, Serbia. Institute of Physics Belgrade, National Institute of the Republic of Serbia, University of Belgrade, Pregrevica 118, 11000 Belgrade, Serbia. Institute of Public Health Belgrade, Despota Stefana 54, 11000 Belgrade, Serbia. Faculty of Physics, University of Belgrade, Studentski trg 12-16, 11000 Belgrade, Serbia"
Journal Title:Sci Total Environ
Year:2019
Volume:20181030
Issue:
Page Number:140 - 147
DOI: 10.1016/j.scitotenv.2018.10.368
ISSN/ISBN:1879-1026 (Electronic) 0048-9697 (Linking)
Abstract:"Current research suggests that, apart from photochemical reactions, toluene, ethylbenzene and xylene (TEX) removal from ambient air might be affected by atmospheric precipitation, depending on the concentrations and water solubility of the compounds, Henry's law, physico-chemical properties of the water, as well as the frequency and intensity of precipitation events. Nevertheless, existing knowledge of the role that wet deposition plays in biogeochemical cycles of volatile species remains insufficient, and this topic requires more scientific effort to be explored and understood. In this study, we employed the eXtreme Gradient Boosting tree ensemble for revealing TEX transfer from ambient air to rainwater, and applied a novel SHapley Additive exPlanations feature attribution framework to examine the relevance of the monitored parameters and identify key factors that govern wet deposition of TEX. According to the results, main impacts, including ambient air TEX concentrations, and rainwater and air temperatures, and occasional, but less important impacts, including wind speed, air pressure, turbidity, and total organic carbon, NO(3)(-), Cl(-) and K(+) rainwater concentration, shaped TEX partition between gaseous and aqueous phases during rain events"
Keywords:Btex Machine learning Multiphase system Shap Wet deposition XGBoost;
Notes:"PubMed-not-MEDLINEStojic, Andreja Stanic, Nenad Vukovic, Gordana Stanisic, Svetlana Perisic, Mirjana Sostaric, Andrej Lazic, Lazar eng Netherlands 2018/11/09 Sci Total Environ. 2019 Feb 25; 653:140-147. doi: 10.1016/j.scitotenv.2018.10.368. Epub 2018 Oct 30"

 
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