کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6962327 | 1452266 | 2016 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A parameter estimation and identifiability analysis methodology applied to a street canyon air pollution model
ترجمه فارسی عنوان
یک روش تجزیه و تحلیل پارامترها و روش شناسایی شده برای مدل آلودگی هوای خیابانی خیابان
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزار
چکیده انگلیسی
Mathematical models are increasingly used in environmental science thus increasing the importance of uncertainty and sensitivity analyses. In the present study, an iterative parameter estimation and identifiability analysis methodology is applied to an atmospheric model - the Operational Street Pollution Model (OSPM®). To assess the predictive validity of the model, the data is split into an estimation and a prediction data set using two data splitting approaches and data preparation techniques (clustering and outlier detection) are analysed. The sensitivity analysis, being part of the identifiability analysis, showed that some model parameters were significantly more sensitive than others. The application of the determined optimal parameter values was shown to successfully equilibrate the model biases among the individual streets and species. It was as well shown that the frequentist approach applied for the uncertainty calculations underestimated the parameter uncertainties. The model parameter uncertainty was qualitatively assessed to be significant, and reduction strategies were identified.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Environmental Modelling & Software - Volume 84, October 2016, Pages 165-176
Journal: Environmental Modelling & Software - Volume 84, October 2016, Pages 165-176
نویسندگان
Thor-Bjørn Ottosen, Matthias Ketzel, Henrik Skov, Ole Hertel, Jørgen Brandt, Konstantinos E. Kakosimos,