A Hybrid Deterministic-Statistical Model Integrating Economic, Meteorological and Environmental Variables to Air Pollution
The following study is based on a hybrid statistical-deterministic model designed for the assessment of the daily concentration of sulfur dioxide, carbon monoxide and particulate matter (PM10) as major pollutants in the Greater Tehran Area (GTA): the capital of Iran. The model uses three available...
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2017-02-01
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doaj-39182f11b99041ce8f42767e88b411612020-11-25T01:11:11ZengIranian Association for Energy EconomicsEnvironmental Energy and Economic Research2538-49882676-49972017-02-0111234210.22097/eeer.2017.4645546455A Hybrid Deterministic-Statistical Model Integrating Economic, Meteorological and Environmental Variables to Air PollutionFarhang Shaparaki0Majid Abbaspour1Majid Shafei-Pour2Mahmoud Mahmoudi3Islamic Azad University Sciences and Research Branch, Tehran, IranSharif University of Technology, Tehran, IranGraduate Faculty of Environment, University of Tehran, Tehran, IranTehran University of Medical Science, Tehran, IranThe following study is based on a hybrid statistical-deterministic model designed for the assessment of the daily concentration of sulfur dioxide, carbon monoxide and particulate matter (PM10) as major pollutants in the Greater Tehran Area (GTA): the capital of Iran. The model uses three available or assessable variables including economic, meteorological and environmental in the GTA for the year 2003. Economic sectors which are examined in this study are firstly traffic, secondly residential-commercial heating and thirdly industry. The model determines to what degree each of the aforementioned sectors, in accordance to their associated fuel consumption, is responsible for air pollution. The model also relates emission data from the three sectors whilst taking into consideration meteorological parameters. Thereafter, economic and meteorological parameters as independent explanatory variables opposed to the concentration of pollutants measured at the monitoring network stations which are dependent variables. All data is given in the form of time series for the year 2003 in specified areas discussed. The method adopted for the calculation of the regression coefficients of the model, is based on nonlinear least squares multiple regression analysis. The model has been tested on the available monitoring network stations for aforementioned pollutants in the GTA. Model verification has been carried out spatially in the year 2003 and temporally for the year 2005. Results show that the concentration of pollutants in the GTA can be estimated using this model. Areas of further research are outlined which indicate possible enhancement of this approach and relevant application extensions.http://www.eeer.ir/article_46455_f230ca84911fcdc248c9f220582b2c07.pdfEmpirical hybrid modelStatistical-deterministic distributionAir pollution modelingTraffic pollution |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Farhang Shaparaki Majid Abbaspour Majid Shafei-Pour Mahmoud Mahmoudi |
spellingShingle |
Farhang Shaparaki Majid Abbaspour Majid Shafei-Pour Mahmoud Mahmoudi A Hybrid Deterministic-Statistical Model Integrating Economic, Meteorological and Environmental Variables to Air Pollution Environmental Energy and Economic Research Empirical hybrid model Statistical-deterministic distribution Air pollution modeling Traffic pollution |
author_facet |
Farhang Shaparaki Majid Abbaspour Majid Shafei-Pour Mahmoud Mahmoudi |
author_sort |
Farhang Shaparaki |
title |
A Hybrid Deterministic-Statistical Model Integrating Economic, Meteorological and Environmental Variables to Air Pollution |
title_short |
A Hybrid Deterministic-Statistical Model Integrating Economic, Meteorological and Environmental Variables to Air Pollution |
title_full |
A Hybrid Deterministic-Statistical Model Integrating Economic, Meteorological and Environmental Variables to Air Pollution |
title_fullStr |
A Hybrid Deterministic-Statistical Model Integrating Economic, Meteorological and Environmental Variables to Air Pollution |
title_full_unstemmed |
A Hybrid Deterministic-Statistical Model Integrating Economic, Meteorological and Environmental Variables to Air Pollution |
title_sort |
hybrid deterministic-statistical model integrating economic, meteorological and environmental variables to air pollution |
publisher |
Iranian Association for Energy Economics |
series |
Environmental Energy and Economic Research |
issn |
2538-4988 2676-4997 |
publishDate |
2017-02-01 |
description |
The following study is based on a hybrid statistical-deterministic model designed for the assessment of the daily concentration of sulfur dioxide, carbon monoxide and particulate matter (PM10) as major pollutants in the Greater Tehran Area (GTA): the capital of Iran. The model uses three available or assessable variables including economic, meteorological and environmental in the GTA for the year 2003. Economic sectors which are examined in this study are firstly traffic, secondly residential-commercial heating and thirdly industry. The model determines to what degree each of the aforementioned sectors, in accordance to their associated fuel consumption, is responsible for air pollution. The model also relates emission data from the three sectors whilst taking into consideration meteorological parameters. Thereafter, economic and meteorological parameters as independent explanatory variables opposed to the concentration of pollutants measured at the monitoring network stations which are dependent variables. All data is given in the form of time series for the year 2003 in specified areas discussed. The method adopted for the calculation of the regression coefficients of the model, is based on nonlinear least squares multiple regression analysis. The model has been tested on the available monitoring network stations for aforementioned pollutants in the GTA. Model verification has been carried out spatially in the year 2003 and temporally for the year 2005. Results show that the concentration of pollutants in the GTA can be estimated using this model. Areas of further research are outlined which indicate possible enhancement of this approach and relevant application extensions. |
topic |
Empirical hybrid model Statistical-deterministic distribution Air pollution modeling Traffic pollution |
url |
http://www.eeer.ir/article_46455_f230ca84911fcdc248c9f220582b2c07.pdf |
work_keys_str_mv |
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