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预测室内空气中半挥发性有机化合物与羟基自由基和臭氧的反应速率常数。

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

机构信息

University of Paris-Est, Scientific and Technical Center for Building (CSTB), Health and Comfort Department, French Indoor Air Quality Observatory (OQAI), 84 Avenue Jean Jaurès, Champs sur Marne, 77447, Marne La Vallée Cedex 2, France.

University of Paris-Est, Scientific and Technical Center for Building (CSTB), Health and Comfort Department, French Indoor Air Quality Observatory (OQAI), 84 Avenue Jean Jaurès, Champs sur Marne, 77447, Marne La Vallée Cedex 2, France.

出版信息

Environ Pollut. 2020 Nov;266(Pt 2):115050. doi: 10.1016/j.envpol.2020.115050. Epub 2020 Jun 27.

Abstract

Semivolatile organic compounds (SVOCs) in air can react with hydroxyl radicals (OH), nitrate radicals (NO) and ozone (O). Two questions regarding SVOC reactivity with OH, NO and O 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, NO and O 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(2-ethylhexyl)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 reactions in the particle phase. Models for SVOC/NO and SVOC/O 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.

摘要

半挥发性有机化合物(SVOCs)在空气中会与羟基自由基(OH)、硝酸根自由基(NO)和臭氧(O)发生反应。关于 SVOC 在气相和颗粒相中的 OH、NO 和 O 反应性,有两个问题仍有待解决:根据文献中的现有测量结果,哪些是空气中最具反应性的 SVOC,以及如何预测 SVOC 在气相和颗粒相中的反应性?本研究对文献中的二级反应速率常数(k)进行了综述,以确定在环境和室内空气中 SVOC 在室温下与 OH、NO 和 O 在气相和颗粒相中的反应性。文献中提供了 90 种多环芳烃(PAHs)、多氯联苯(PCBs)、有机磷酸酯、二恶英、邻苯二甲酸二(2-乙基己基)酯(DEHP)和杀虫剂包括吡氟禾草灵、氨基甲酸酯和特丁津的测量 k 值。发现 PAHs 和有机磷酸酯比二恶英和 PCBs 更具反应性。根据获得的数据,开发了定量结构-活性关系(QSAR)模型,使用量子化学、分子、物理性质和环境描述符来预测 k 值。采用了八种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。为 SVOC/OH 在气相和颗粒相中的反应以及 SVOC/O 在颗粒相中的反应开发了 QSAR 模型。由于缺乏用于模型训练的 SVOC/NO 和 SVOC/O 在气相中的测量 k 值,因此无法开发 SVOC/NO 和 SVOC/O 在气相中的反应模型。根据模型性能指标的比较,最小绝对收缩和选择算子(LASSO)回归和随机森林模型被确定为 SVOC 反应性预测的最有效模型。

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