Literature DB >> 18234341

Procedures for estimation of modelling uncertainty in air quality assessment.

C Borrego1, A Monteiro, J Ferreira, A I Miranda, A M Costa, A C Carvalho, M Lopes.   

Abstract

The main objectives of this work focus, firstly, on a review of the current existent methodologies to estimate air quality modelling uncertainty, and, secondly, in the preparation of guidelines for modelling uncertainty estimation, which can be used by local and regional authorities responsible for air quality management. From the application exercise, it was concluded that it is possible to define a subset of statistical parameters able to reproduce the general uncertainties estimation. Concerning the quality indicators defined by EU directives, the results show that the legislated uncertainty estimation measures are ambiguous and inadequate in several aspects, mainly in what concerns the error measures for hourly and daily indicators based on the highest observed concentration. A relative error at the percentile correspondent to the allowed number of exceedances of the limit value was suggested and tested, showing that is a more robust and appropriate parameter for model performance evaluation.

Mesh:

Year:  2008        PMID: 18234341     DOI: 10.1016/j.envint.2007.12.005

Source DB:  PubMed          Journal:  Environ Int        ISSN: 0160-4120            Impact factor:   9.621


  6 in total

1.  Dispersion and deposition estimation of fugitive iron particles from an iron industry on nearby communities via AERMOD.

Authors:  Hamid Omidvarborna; Mahad Baawain; Abdullah Al-Mamun; Ala'a H Al-Muhtaseb
Journal:  Environ Monit Assess       Date:  2018-10-18       Impact factor: 2.513

2.  Impact assessment of PM10 cement plants emissions on urban air quality using the SCIPUFF dispersion model.

Authors:  Vincenzo Leone; Guido Cervone; Pasquale Iovino
Journal:  Environ Monit Assess       Date:  2016-08-02       Impact factor: 2.513

3.  A new approach combining a simplified FLEXPART model and a Bayesian-RAT method for forecasting PM10 and PM2.5.

Authors:  Lifeng Guo; Baozhang Chen; Huifang Zhang; Yanhu Zhang
Journal:  Environ Sci Pollut Res Int       Date:  2019-11-26       Impact factor: 4.223

4.  Predicting hourly air pollutant levels using artificial neural networks coupled with uncertainty analysis by Monte Carlo simulations.

Authors:  Mohammad Arhami; Nima Kamali; Mohammad Mahdi Rajabi
Journal:  Environ Sci Pollut Res Int       Date:  2013-01-06       Impact factor: 4.223

5.  Particulate matter and health risk under a changing climate: assessment for Portugal.

Authors:  Daniela Dias; Oxana Tchepel; Anabela Carvalho; Ana Isabel Miranda; Carlos Borrego
Journal:  ScientificWorldJournal       Date:  2012-05-01

6.  Emission Inventories and Particulate Matter Air Quality Modeling over the Pearl River Delta Region.

Authors:  Diogo Lopes; Joana Ferreira; Ka In Hoi; Ka-Veng Yuen; Kai Meng Mok; Ana I Miranda
Journal:  Int J Environ Res Public Health       Date:  2021-04-14       Impact factor: 3.390

  6 in total

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