Gramatica, P.; Pilutti, P.; Papa, E. Predicting the NO3 radical tropospheric degradability of organic pollutants by theoretical molecular descriptors. Atmos. Environ. 2003, 37, 3115–3124.

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Gramatica, P.; Pilutti, P.; Papa, E. Predicting the NO3 radical tropospheric degradability of organic pollutants by theoretical molecular descriptors. Atmos. Environ. 2003, 37, 3115–3124.

QDB archive DOI: 10.15152/QDB.201   DOWNLOAD

QsarDB content

Property pkNO3: Degradation by NO3 radicals as -logkNO3 [-log(cm3/(s.{molecule}))]

Model: Model for organic pollutants

Regression model (regression)

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NameTypen

R2

σ

Training settraining770.9120.637
Validation setexternal validation370.9560.478

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When using this QDB archive, please cite (see details) it together with the original article:

  • Piir, G.; Sild, S. Data for: Predicting the NO3 radical tropospheric degradability of organic pollutants by theoretical molecular descriptors. QsarDB repository, QDB.201. 2017. http://dx.doi.org/10.15152/QDB.201

  • Gramatica, P.; Pilutti, P.; Papa, E. Predicting the NO3 radical tropospheric degradability of organic pollutants by theoretical molecular descriptors. Atmos. Environ. 2003, 37, 3115–3124. http://dx.doi.org/10.1016/s1352-2310(03)00293-0

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Title: Gramatica, P.; Pilutti, P.; Papa, E. Predicting the NO3 radical tropospheric degradability of organic pollutants by theoretical molecular descriptors. Atmos. Environ. 2003, 37, 3115–3124.
Abstract:The rate constant for the nighttime degradation of 114 heterogeneous organic compounds, through reaction with nitrate radicals in the troposphere, is predicted here by quantitative structure–activity relationships modelling. The multiple linear regression approach is based on a variety of theoretical molecular descriptors, selected by the genetic algorithms-variable subset selection procedure. The proposed model, calculated on a limited subset of compounds selected by a D-optimal experimental design and checked for reliability and robustness, has good predictivity, verified by internal (Q_LMO^2=89.6%) and “external” validation (Q_EXT^2=95.7%). The model applicability domain was always verified by the leverage approach in order to propose reliable predicted data. The average root-mean square error for the prediction of logKNO3 was 0.57, similar to (and even smaller than) the typical experimental error range.
URI:http://hdl.handle.net/10967/201
http://dx.doi.org/10.15152/QDB.201
Date:2017-05-24


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    Uni. Insubria (Italy), QSAR Research Unit in Environmental Chemistry and Ecotoxicology

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