In the environmental risk assessment of organic chemicals, persistence is of particular importance as it may lead to adverse effects. The reaction of chemicals with OH and NO3 radicals and ozone are the main abiotic degradation processes in the troposphere, so an upper limit of the atmospheric persistence of chemicals is assessed by determining their reaction rate constants with OḢ and NO3̇ and O3. Statistical models predicting the oxidation rate constants with OḢ and NO3̇ for many heterogeneous compounds have been developed by the QSAR/QSPR (Quantitative Structure-Activity/Property Relationships) approach; the structural representation of the compounds was realised using different kinds of molecular descriptors (structural, topological, empirical and WHIM descriptors). In addition, Kohonen neural networks (K-ANN) and the GA-VSS (Genetic Algorithm Variable Subset Selection) strategy were respectively used to select the most representative training set and the best descriptor subset. The predictive capability of the models on k(OH) and k(NO3) has been checked and appears to be satisfactory. Finally, the oxidation rate constants for some chemicals of concern were analysed in the Principal Component space in order to rank these chemicals according to their tropospheric degradability.

Gramatica, P., Consonni, V., Todeschini, R. (1999). QSAR Study of the Tropospheric Degradation of Organic Compounds. CHEMOSPHERE, 38(6), 1371-1378 [10.1016/S0045-6535(98)00539-6].

QSAR Study of the Tropospheric Degradation of Organic Compounds

CONSONNI, VIVIANA;TODESCHINI, ROBERTO
1999

Abstract

In the environmental risk assessment of organic chemicals, persistence is of particular importance as it may lead to adverse effects. The reaction of chemicals with OH and NO3 radicals and ozone are the main abiotic degradation processes in the troposphere, so an upper limit of the atmospheric persistence of chemicals is assessed by determining their reaction rate constants with OḢ and NO3̇ and O3. Statistical models predicting the oxidation rate constants with OḢ and NO3̇ for many heterogeneous compounds have been developed by the QSAR/QSPR (Quantitative Structure-Activity/Property Relationships) approach; the structural representation of the compounds was realised using different kinds of molecular descriptors (structural, topological, empirical and WHIM descriptors). In addition, Kohonen neural networks (K-ANN) and the GA-VSS (Genetic Algorithm Variable Subset Selection) strategy were respectively used to select the most representative training set and the best descriptor subset. The predictive capability of the models on k(OH) and k(NO3) has been checked and appears to be satisfactory. Finally, the oxidation rate constants for some chemicals of concern were analysed in the Principal Component space in order to rank these chemicals according to their tropospheric degradability.
Articolo in rivista - Articolo scientifico
QSAR, atmospheric degradation, chemometrics
English
1371
1378
8
Gramatica, P., Consonni, V., Todeschini, R. (1999). QSAR Study of the Tropospheric Degradation of Organic Compounds. CHEMOSPHERE, 38(6), 1371-1378 [10.1016/S0045-6535(98)00539-6].
Gramatica, P; Consonni, V; Todeschini, R
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/5338
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