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Predicting the rate constants of semivolatile organic compounds with hydroxyl radicals and ozone in indoor air

机译:预测室内空气中羟基自由基和臭氧的半溶血物有机化合物的速率常数

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摘要

Semivolatile organic compounds (SVOCs) in air can react with hydroxyl radicals (OH), nitrate radicals (NO3) and ozone (O-3). Two questions regarding SVOC reactivity with OH, NO3 and O-3 in the gas and particle phases remain to be addressed: according to the existing measurements in the literature, which are the most reactive SVOCs in air, and how can the SVOC reactivity in the gas and particle phases be predicted? In the present study, a literature review of the second-order rate constant (k) was carried out to determine the SVOC reactivity with OH, NO3 and O-3 in the gas and particle phases in ambient and indoor air at room temperature. Measured k values were available in the literature for 90 polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), organophosphates, dioxins, di(2ethylhexyl)phthalate (DEHP) and pesticides including pyrifenox, carbamates and terbuthylazine. PAHs and organophosphates were found to be more reactive than dioxins and PCBs. Based on the obtained data, quantitative structure-activity relationship (QSAR) models were developed to predict the k value using quantum chemical, molecular, physical property and environmental descriptors. Eight linear and nonlinear statistical models were employed, including regression models, bagging, random forest and gradient boosting. QSAR models were developed for SVOC/OH reactions in the gas and particle phases and SVOC/O-3 reactions in the particle phase. Models for SVOC/NO3 and SVOC/O-3 reactions in the gas phase could not be developed due to the lack of measured k values for model training. The least absolute shrinkage and selection operator (LASSO) regression and random forest models were identified as the most effective models for SVOC reactivity prediction according to a comparison of model performance metrics. (C) 2020 Elsevier Ltd. All rights reserved.
机译:空气中的半萎缩有机化合物(SVOC)可以与羟基自由基(OH),硝酸根(NO 3)和臭氧(O-3)反应。关于气体和颗粒阶段的oOH,NO3和O-3的SVOC反应性的两个问题仍然有待解决:根据文献中的现有测量,这是空气中最具反应性的SVOC,以及SVOC反应性如何预测气体和颗粒阶段?在本研究中,进行二阶速率常数(k)的文献综述,以在室温下在环境和室内空气中的气体和颗粒相中与OH,NO3和O-3中的SVOC反应性。测量的k值可用于90个多环芳烃(PAH),聚氯联合苯基(PCBS),有机磷,二恶英,二(2甲基己基)邻苯二甲酸酯(DEHP)和杀虫剂,包括Pyrifenox,氨基甲酸酯和Terbutbazine。发现PAHS和有机磷酸盐比二恶英和PCB更反应。基于所获得的数据,开发了定量结构 - 活性关系(QSAR)模型以使用量子化学,分子,物理性质和环境描述符来预测k值。采用了八个线性和非线性统计模型,包括回归模型,袋装,随机森林和梯度提升。 QSAR模型是用于颗粒相的气体和颗粒相的SVOC / OH反应和SVOC / O-3反应。由于模型训练的测量值缺乏测量值,因此无法开发SVOC / NO3和SVOC / O-3反应的模型。根据模型性能度量的比较,确定了绝对的收缩和选择运算符(套索)回归和随机林模型被识别为SVOC反应性预测的最有效模型。 (c)2020 elestvier有限公司保留所有权利。

著录项

  • 来源
    《Environmental Pollution》 |2020年第2期|115050.1-115050.10|共10页
  • 作者单位

    Univ Paris Est Sci & Tech Ctr Bldg CSTB Hlth & Comfort Dept French Indoor Air Qual Observ OQAI 84 Ave Jean Jaures F-77447 Marne La Vallee 2 France;

    Univ Paris Est Sci & Tech Ctr Bldg CSTB Hlth & Comfort Dept French Indoor Air Qual Observ OQAI 84 Ave Jean Jaures F-77447 Marne La Vallee 2 France;

    Univ Paris Est Sci & Tech Ctr Bldg CSTB Hlth & Comfort Dept French Indoor Air Qual Observ OQAI 84 Ave Jean Jaures F-77447 Marne La Vallee 2 France;

    Univ Paris Est Sci & Tech Ctr Bldg CSTB Hlth & Comfort Dept French Indoor Air Qual Observ OQAI 84 Ave Jean Jaures F-77447 Marne La Vallee 2 France;

    Univ Paris Est Sci & Tech Ctr Bldg CSTB Hlth & Comfort Dept French Indoor Air Qual Observ OQAI 84 Ave Jean Jaures F-77447 Marne La Vallee 2 France;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    SVOC; Reactivity; QSAR model; Machine learning; Regression; Random forest;

    机译:SVOC;反应性;QSAR模型;机器学习;回归;随机森林;

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