Literature DB >> 19859819

Prediction of daily ground-level ozone concentration maxima over New Delhi.

Amita Mahapatra1.   

Abstract

The pollution levels in New Delhi from industrial, residential, and transportation sources are continuously growing. As one of the major pollutants, ground-level ozone is responsible for various adverse effects on both humans and foliage. The present study aims to predict daily ground-level ozone concentration maxima over a site situated in New Delhi through neural networks (NN) and multiple-regression (MR) analysis. Although these methodologies are case and site specific, they are being developed and used widely. Therefore, to test these methodologies for New Delhi where no such study is available for ground-level ozone, six models have been developed based on NNs and MR using the same input data set. The changes in the performance capability of the two methods are sensitive to the selection of input parameters. The results are encouraging, and remarkable improvements in the performance of the models have been observed.

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Year:  2009        PMID: 19859819     DOI: 10.1007/s10661-009-1223-z

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  1 in total

1.  A neural network model forecasting for prediction of daily maximum ozone concentration in an industrialized urban area.

Authors:  J Yi; V R Prybutok
Journal:  Environ Pollut       Date:  1996       Impact factor: 8.071

  1 in total
  2 in total

1.  The ground-level ozone concentration in beech (Fagus sylvatica L.) forests in the West Carpathian Mountains.

Authors:  Rastislav Janík; Martin Kubov; Branislav Schieber
Journal:  Environ Monit Assess       Date:  2020-03-12       Impact factor: 2.513

2.  Multiple regression analysis in modeling of columnar ozone in Peninsular Malaysia.

Authors:  K C Tan; H S Lim; M Z Mat Jafri
Journal:  Environ Sci Pollut Res Int       Date:  2014-03-06       Impact factor: 4.223

  2 in total

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