Predicting enthalpy of vaporization for Persistent Organic Pollutants with Quantitative Structure-Property Relationship (QSPR) incorporating the influence of temperature on volatility

被引:25
|
作者
Sosnowska, Anita [1 ]
Barycki, Maciej [1 ]
Jagiello, Karolina [1 ]
Haranczyk, Maciej [2 ]
Gajewicz, Agnieszka [1 ]
Kawai, Toru [3 ]
Suzuki, Noriyuki [3 ]
Puzyn, Tomasz [1 ]
机构
[1] Univ Gdansk, Fac Chem, Inst Environm & Human Hlth Protect, Lab Environm Chemometr, PL-80308 Gdansk, Poland
[2] Univ Calif Berkeley, Lawrence Berkeley Natl Lab, Computat Res Div, Berkeley, CA 94720 USA
[3] Natl Inst Environm Studies, Res Ctr Environm Risk, Exposure Assessment Res Sect, Tsukuba, Ibaraki 3058506, Japan
基金
日本学术振兴会;
关键词
Persistent Organic Pollutants; Enthalpy of vaporization; QSPR; Temperature dependence; Quantum-mechanical descriptors; POLYCHLORINATED-BIPHENYLS PCBS; RELATIONSHIP 3D-QSPR MODELS; THERMODYNAMIC PROPERTIES; PARTITION-COEFFICIENT; DIPHENYL ETHERS; VAPOR-PRESSURE; QSAR MODELS; DESCRIPTORS; VALIDATION; CONGENERS;
D O I
10.1016/j.atmosenv.2013.12.036
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Enthalpy of vaporization (Delta H-vap) is a thermodynamic property associated with the dispersal of Persistent Organic Pollutants (POPS) in the environment. Common problem in the environmental risk assessment studies is the lack of experimentally measured Delta H-vap data. This problem can be solved by employing computational techniques, including QSPR (Quantitative Structure-Property Relationship) modelling to predict properties of interest. Majority of the published QSPR models can be applied to predict the enthalpy of vaporization of compounds from only one, particular group of POPs (i.e., polychlorinated biphenyls, PCBs). We have developed a more general QSPR model to estimate the Delta H-vap values for 1436 polychlorinated and polybrominated benzenes, biphenyls, dibenzo-p-dioxins, dibenzofurans, diphenyl ethers, and naphthalenes. The QSPR model developed with Multiple Linear Regression analysis was characterized by satisfactory goodness-of-fit, robustness and the external predictive performance (R-2 = 0.888, Q(CV)(2) = 0.878, Q(Ext)(2) = 0.842, RMSEC= w5.11, RMSECV = 5.34, RMSEP = 5.74). Moreover, we quantified the temperature dependencies of vapour pressure for twelve groups of POPs based on the predictions at six different temperatures (logP(L(T))). In addition, we found a simple arithmetic relationship between the logarithmic values of vapour pressure in pairs of chloro- and bromo-analogues. By employing this relationship it is possible to estimate logP(L(T)) for any brominated POP at any temperature utilizing only the logP(L(T)) value for its chlorinated analogues. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:10 / 18
页数:9
相关论文
共 50 条
  • [21] Validation of Quantitative Structure-Activity Relationship (QSAR) and Quantitative Structure-Property Relationship (QSPR) approaches as alternatives to skin sensitization risk assessment
    Lee, Byung-Mu
    Kim, Ji Yun
    Kim, Kyu-Bong
    JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH-PART A-CURRENT ISSUES, 2021, 84 (23): : 945 - 959
  • [22] MALDI Efficiency of Metabolites Quantitatively Associated with their Structural Properties: A Quantitative Structure-Property Relationship (QSPR) Approach
    Yukihira, Daichi
    Miura, Daisuke
    Fujimura, Yoshinori
    Umemura, Yoshikatsu
    Yamaguchi, Shinichi
    Funatsu, Shinji
    Yamazaki, Makoto
    Ohta, Tetsuya
    Inoue, Hiroaki
    Shindo, Mitsuru
    Wariishi, Hiroyuki
    JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY, 2014, 25 (01) : 1 - 5
  • [23] Quantitative structure-property relationship (QSPR) analysis of calcium aluminosilicate glasses based on molecular dynamics simulations
    Lu, Xiaonan
    Du, Jincheng
    JOURNAL OF NON-CRYSTALLINE SOLIDS, 2020, 530
  • [24] A Quantitative Structure-Property Relationship Model for Predicting the Critical Pressures of Organic Compounds Containing Oxygen, Sulfur, and Nitrogen
    Oh, Ji Ye
    Park, Kiho
    Kim, Yangsoo
    Park, Tae-Yun
    Yang, Dae Ryook
    JOURNAL OF CHEMICAL ENGINEERING OF JAPAN, 2017, 50 (06) : 397 - 407
  • [25] Thermal Conductivity Estimation of Diverse Liquid Aliphatic Oxygen-Containing Organic Compounds Using the Quantitative Structure-Property Relationship Method
    Lu, Haixia
    Liu, Wanqiang
    Yang, Fan
    Zhou, Hu
    Liu, Fengping
    Yuan, Hua
    Chen, Guanfan
    Jiao, Yinchun
    ACS OMEGA, 2020, 5 (15): : 8534 - 8542
  • [26] Predicting the Decomposition Temperature of Ionic Liquids by the Quantitative Structure-Property Relationship Method Using a New Topological Index
    Yan, Fangyou
    Xia, Shuqian
    Wang, Qiang
    Ma, Peisheng
    JOURNAL OF CHEMICAL AND ENGINEERING DATA, 2012, 57 (03) : 805 - 810
  • [27] Estimation of surface tension of organic compounds using quantitative structure-property relationship
    Dai Yi-min
    Liu You-nian
    Li Xun
    Cao Zhong
    Zhu Zhi-ping
    Yang Dao-wu
    JOURNAL OF CENTRAL SOUTH UNIVERSITY, 2012, 19 (01) : 93 - 100
  • [28] Prediction of aqueous solubility of organic compounds using a quantitative structure-property relationship
    Chen, XQ
    Cho, SJ
    Li, Y
    Venkatesh, S
    JOURNAL OF PHARMACEUTICAL SCIENCES, 2002, 91 (08) : 1838 - 1852
  • [29] Molecular Modeling of Polymers 16. Gaseous Diffusion in Polymers: A Quantitative Structure-Property Relationship (QSPR) Analysis
    Hitesh C. Patel
    John S. Tokarski
    A. J. Hopfinger
    Pharmaceutical Research, 1997, 14 : 1349 - 1354
  • [30] Molecular modeling of polymers .16. Gaseous diffusion in polymers: A quantitative structure-property relationship (QSPR) analysis
    Patel, HC
    Tokarski, JS
    Hopfinger, AJ
    PHARMACEUTICAL RESEARCH, 1997, 14 (10) : 1349 - 1354