Stochastic Modeling of Problematic Air Pollution with Particulate Matter in the City of Pernik, Bulgaria

Air quality in urban areas is an important prerequisite for a healthy environment. This paper focuses on the study of the problematic pollutant PM10 in the air over the city of Pernik in order to prevent the worsening of air pollution and to meet the requ...

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Main Author: Maya P. Stoimenova
Format: Article
Language:English
Published: Union of Scientists in Bulgaria 2016-12-01
Series:Ecologia Balkanica
Subjects:
Online Access:http://web.uni-plovdiv.bg/mollov/EB/2016_vol8_iss2/033-041__eb.16128.pdf
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spelling doaj-67f33e8301cf47de83705a6383b4af982021-02-02T01:07:01ZengUnion of Scientists in BulgariaEcologia Balkanica1314-02131313-99402016-12-01823341Stochastic Modeling of Problematic Air Pollution with Particulate Matter in the City of Pernik, BulgariaMaya P. Stoimenova0University of Plovdiv „Paisii Hilendarski“, Faculty of Mathe matics and Informatics, Department of Applied Mathematics and Modeling 24 Tzar Assen Str., 4000 Plovdiv, BULGARIAAir quality in urban areas is an important prerequisite for a healthy environment. This paper focuses on the study of the problematic pollutant PM10 in the air over the city of Pernik in order to prevent the worsening of air pollution and to meet the requirements of the applicable regulations and directives, as well as to improve public awareness with regard to health and environmental issues. In this paper, stochastic mathematical models are developed using average 24-hour concentrations of PM10 in atmospheric air over the city for the period from 1 January 2010 until 31 December 2014. The measured values systematically exceed European Union regulations with require that mean daily concentrations should be below 50 μg/m3. Univariate time-dependent models are derived in the form of time series. The constructed models describe the examined data adequately and also make it possible to forecast future pollution within a timeframe of several days. The selected type of modelling facilitates the decision making needed in the efforts to decrease the pollution levels in future.http://web.uni-plovdiv.bg/mollov/EB/2016_vol8_iss2/033-041__eb.16128.pdfPart iculate matter PM10air pollutionstochastic model
collection DOAJ
language English
format Article
sources DOAJ
author Maya P. Stoimenova
spellingShingle Maya P. Stoimenova
Stochastic Modeling of Problematic Air Pollution with Particulate Matter in the City of Pernik, Bulgaria
Ecologia Balkanica
Part iculate matter PM10
air pollution
stochastic model
author_facet Maya P. Stoimenova
author_sort Maya P. Stoimenova
title Stochastic Modeling of Problematic Air Pollution with Particulate Matter in the City of Pernik, Bulgaria
title_short Stochastic Modeling of Problematic Air Pollution with Particulate Matter in the City of Pernik, Bulgaria
title_full Stochastic Modeling of Problematic Air Pollution with Particulate Matter in the City of Pernik, Bulgaria
title_fullStr Stochastic Modeling of Problematic Air Pollution with Particulate Matter in the City of Pernik, Bulgaria
title_full_unstemmed Stochastic Modeling of Problematic Air Pollution with Particulate Matter in the City of Pernik, Bulgaria
title_sort stochastic modeling of problematic air pollution with particulate matter in the city of pernik, bulgaria
publisher Union of Scientists in Bulgaria
series Ecologia Balkanica
issn 1314-0213
1313-9940
publishDate 2016-12-01
description Air quality in urban areas is an important prerequisite for a healthy environment. This paper focuses on the study of the problematic pollutant PM10 in the air over the city of Pernik in order to prevent the worsening of air pollution and to meet the requirements of the applicable regulations and directives, as well as to improve public awareness with regard to health and environmental issues. In this paper, stochastic mathematical models are developed using average 24-hour concentrations of PM10 in atmospheric air over the city for the period from 1 January 2010 until 31 December 2014. The measured values systematically exceed European Union regulations with require that mean daily concentrations should be below 50 μg/m3. Univariate time-dependent models are derived in the form of time series. The constructed models describe the examined data adequately and also make it possible to forecast future pollution within a timeframe of several days. The selected type of modelling facilitates the decision making needed in the efforts to decrease the pollution levels in future.
topic Part iculate matter PM10
air pollution
stochastic model
url http://web.uni-plovdiv.bg/mollov/EB/2016_vol8_iss2/033-041__eb.16128.pdf
work_keys_str_mv AT mayapstoimenova stochasticmodelingofproblematicairpollutionwithparticulatematterinthecityofpernikbulgaria
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