Predicting Thermal Behavior of Secondary Organic Aerosols
| Autor: | Michael Lewandowski, Mohammed Jaoui, Jonathan Krug, John H. Offenberg, Theran P. Riedel, David A. Olson, Kenneth S. Docherty, Tadeusz E. Kleindienst |
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| Rok vydání: | 2017 |
| Předmět: |
010504 meteorology & atmospheric sciences
Activation function Thermodynamics Overfitting 01 natural sciences Article 010104 statistics & probability Environmental Chemistry Organic chemistry 0101 mathematics 0105 earth and related environmental sciences Aerosols chemistry.chemical_classification Air Pollutants Chemistry Hydrogen Peroxide General Chemistry Function (mathematics) Carbon Aerosol Oxygen Hydrocarbon Volume (thermodynamics) Measurement uncertainty Akaike information criterion Oxidation-Reduction |
| Zdroj: | Environmental Science & Technology. 51:9911-9919 |
| ISSN: | 1520-5851 0013-936X |
| DOI: | 10.1021/acs.est.7b01968 |
| Popis: | Volume concentrations of steady-state secondary organic aerosol (SOA) were measured in 139 steady- state single precursor hydrocarbon oxidation experiments after passing through a temperature controlled inlet tube. Higher temperatures resulted in greater loss of particle volume, with all experiments following linear relationships between natural log of concentration vs. temperature−1. Negatives of observed slopes are converted to effective enthalpies of vaporization (ΔHeff) which range from 6 to 67 kJ mol−1. These values depend upon the properties of the parent hydrocarbon (e.g. number of carbon atoms, number of internal or external double bonds, presence of aromatic or non-aromatic ring structures), as well as conditions of the experiment (relative humidity, oxidant system, oxidant concentrations) and the products of the complex reactions (e.g. aerosol loading). The observed response to change in temperature can be well predicted through a feedforward Artificial Neural Network. The most parsimonious model, as indicated by consensus of several Information Criteria, is comprised of 13 input variables, a single hidden layer of 3 tanh activation function nodes, and a single linear output function. This model predicts the thermal behavior of single precursor aerosols to less than +/− 5%, which is within the laboratory measurement uncertainty, while limiting the problem of overfitting. The selected model reveals that prediction of the thermal behavior of SOA can be performed by a concise number of molecular descriptors of the reactant hydrocarbon, and a general description of the conditions of laboratory oxidation, namely the oxidant in the experiment and the mass of SOA formed. The inclusion of detailed experimental conditions, such as reacted hydrocarbon concentration (Δ HC), chamber relative humidity, chamber volumetric residence time, and/or initial oxidant concentration lead to over-fitted models. Additional input variables are not necessary for an efficient, accurate predictive model of the thermal behavior of the SOA produced. This work indicates that similar predictive modelling methods may be advantageous over current descriptive techniques for assignment of input parameters into air quality models. |
| Databáze: | OpenAIRE |
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