PMID- 35944777
OWN - NLM
STAT- MEDLINE
DCOM- 20220914
LR  - 20220914
IS  - 1873-6424 (Electronic)
IS  - 0269-7491 (Linking)
VI  - 311
DP  - 2022 Oct 15
TI  - Versatile in silico modeling of XAD-air partition coefficients for POPs based on 
      abraham descriptor and temperature.
PG  - 119857
LID - S0269-7491(22)01071-5 [pii]
LID - 10.1016/j.envpol.2022.119857 [doi]
AB  - The concentration of persistent organic pollutants (POPs) makes remarkable 
      difference to environmental fate. In the field of passive sampling, the partition 
      coefficients between polystyrene-divinylbenzene resin (XAD) and air (i.e., 
      K(XAD-A)) are indispensable to obtain POPs concentration, and the K(XAD-A) is 
      generally thought to be governed by temperature and molecular structure of POPs. 
      However, experimental determination of K(XAD-A) is unrealistic for countless and 
      novel chemicals. Herein, the Abraham solute descriptors of poly parameter linear 
      free energy relationship (pp-LFER) and temperature were utilized to develop 
      models, namely pp-LFER-T, for predicting K(XAD-A) values. Two linear (MLR and 
      LASSO) and four nonlinear (ANN, SVM, kNN and RF) machine learning algorithms were 
      employed to develop models based on a data set of 307 sample points. For the 
      aforementioned six models, R(2)(adj) and Q(2)(ext) were both beyond 0.90, 
      indicating distinguished goodness-of-fit and robust generalization ability. By 
      comparing the established models, the best model was observed as the RF model 
      with R(2)(adj) = 0.991, Q(2)(ext) = 0.935, RMSE(tra) = 0.271 and 
      RMSE(ext) = 0.868. The mechanism interpretation revealed that the temperature, 
      size of molecules and dipole-type interactions were the predominant factors 
      affecting K(XAD-A) values. Concurrently, the developed models with the broad 
      applicability domain provide available tools to fill the experimental data gap 
      for untested chemicals. In addition, the developed models were helpful to 
      preliminarily evaluate the environmental ecological risk and understand the 
      adsorption behavior of POPs between XAD membrane and air.
CI  - Copyright (c) 2022 Elsevier Ltd. All rights reserved.
FAU - Tao, Cuicui
AU  - Tao C
AD  - School of Environmental Science and Engineering, Yangzhou University, Yangzhou, 
      225127, Jiangsu, China.
FAU - Chen, Ying
AU  - Chen Y
AD  - School of Environmental Science and Engineering, Yangzhou University, Yangzhou, 
      225127, Jiangsu, China.
FAU - Tao, Tianyun
AU  - Tao T
AD  - College of Agriculture, Yangzhou University, Yangzhou, 225009, Jiangsu, China.
FAU - Cao, Zaizhi
AU  - Cao Z
AD  - School of Environmental Science and Engineering, Yangzhou University, Yangzhou, 
      225127, Jiangsu, China.
FAU - Chen, Wenxuan
AU  - Chen W
AD  - School of Civil Engineering, Southeast University, Nanjing, 210096, Jiangsu, 
      China.
FAU - Zhu, Tengyi
AU  - Zhu T
AD  - School of Environmental Science and Engineering, Yangzhou University, Yangzhou, 
      225127, Jiangsu, China. Electronic address: tyzhu@yzu.edu.cn.
LA  - eng
PT  - Journal Article
DEP - 20220806
PL  - England
TA  - Environ Pollut
JT  - Environmental pollution (Barking, Essex : 1987)
JID - 8804476
RN  - 0 (Environmental Pollutants)
RN  - 059QF0KO0R (Water)
SB  - IM
MH  - Algorithms
MH  - Computer Simulation
MH  - *Environmental Pollutants/analysis
MH  - Molecular Structure
MH  - Temperature
MH  - Water/chemistry
OTO - NOTNLM
OT  - Machine learning
OT  - POPs
OT  - Temperature
OT  - XAD-Air partition coefficients
COIS- Declaration of competing interest The authors declare that they have no known 
      competing financial interests or personal relationships that could have appeared 
      to influence the work reported in this paper.
EDAT- 2022/08/10 06:00
MHDA- 2022/09/15 06:00
CRDT- 2022/08/09 19:35
PHST- 2022/05/26 00:00 [received]
PHST- 2022/07/17 00:00 [revised]
PHST- 2022/07/23 00:00 [accepted]
PHST- 2022/08/10 06:00 [pubmed]
PHST- 2022/09/15 06:00 [medline]
PHST- 2022/08/09 19:35 [entrez]
AID - S0269-7491(22)01071-5 [pii]
AID - 10.1016/j.envpol.2022.119857 [doi]
PST - ppublish
SO  - Environ Pollut. 2022 Oct 15;311:119857. doi: 10.1016/j.envpol.2022.119857. Epub 
      2022 Aug 6.