Detecting time-changes in PM<sub>10</sub> during Covid pandemic by means of an Ornstein Uhlenbeck type process

Particulate matter with 10 micrometers or less in diameter ($PM_{10}$) from several italian cities is modeled by means of a non homogeneous Ornstein Uhlenbeck process. Such model includes two deterministic time dependent functions in the infinitesimal moments to describe the presence of exogeneous...

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Main Author: Giuseppina Albano
Format: Article
Language:English
Published: AIMS Press 2021-04-01
Series:Mathematical Biosciences and Engineering
Subjects:
Online Access:http://www.aimspress.com/article/doi/10.3934/mbe.2021047?viewType=HTML
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spelling doaj-01c12f91a2ed49a398d2c89838323a862021-04-07T01:35:51ZengAIMS PressMathematical Biosciences and Engineering1551-00182021-04-0118188890310.3934/mbe.2021047Detecting time-changes in PM<sub>10</sub> during Covid pandemic by means of an Ornstein Uhlenbeck type processGiuseppina Albano0Dipartimento di Studi Politici e Sociali, Università degli Studi di Salerno, Via Giovanni Paolo II, 84084 Fisciano (SA), ItalyParticulate matter with 10 micrometers or less in diameter ($PM_{10}$) from several italian cities is modeled by means of a non homogeneous Ornstein Uhlenbeck process. Such model includes two deterministic time dependent functions in the infinitesimal moments to describe the presence of exogeneous terms in the typical dynamics of the phenomenon. An iterative estimating procedure combining the maximum likelihood estimation and a generalized method of moments is provided. A Quandt Likelihood Ratio test for detecting structural breaks in $PM_{10}$ data, in the period from 1st January 2020 to 8th July 2020 which includes the first lockdown due to Covid pandemic, confirms the presence of time-changes. These results show that the lockdown made the air once again cleaner. It is then shown that our model and the associated estimation procedure, while not explicitly contemplating the presence of structural breaks in the time series, implicitly incorporates them in the time dependence of the functions in the infinitesimal moments of the underlying process.http://www.aimspress.com/article/doi/10.3934/mbe.2021047?viewType=HTMLnon homogeneous ornstein uhlenbeck processesestimating procedurepm10structural breaks
collection DOAJ
language English
format Article
sources DOAJ
author Giuseppina Albano
spellingShingle Giuseppina Albano
Detecting time-changes in PM<sub>10</sub> during Covid pandemic by means of an Ornstein Uhlenbeck type process
Mathematical Biosciences and Engineering
non homogeneous ornstein uhlenbeck processes
estimating procedure
pm10
structural breaks
author_facet Giuseppina Albano
author_sort Giuseppina Albano
title Detecting time-changes in PM<sub>10</sub> during Covid pandemic by means of an Ornstein Uhlenbeck type process
title_short Detecting time-changes in PM<sub>10</sub> during Covid pandemic by means of an Ornstein Uhlenbeck type process
title_full Detecting time-changes in PM<sub>10</sub> during Covid pandemic by means of an Ornstein Uhlenbeck type process
title_fullStr Detecting time-changes in PM<sub>10</sub> during Covid pandemic by means of an Ornstein Uhlenbeck type process
title_full_unstemmed Detecting time-changes in PM<sub>10</sub> during Covid pandemic by means of an Ornstein Uhlenbeck type process
title_sort detecting time-changes in pm<sub>10</sub> during covid pandemic by means of an ornstein uhlenbeck type process
publisher AIMS Press
series Mathematical Biosciences and Engineering
issn 1551-0018
publishDate 2021-04-01
description Particulate matter with 10 micrometers or less in diameter ($PM_{10}$) from several italian cities is modeled by means of a non homogeneous Ornstein Uhlenbeck process. Such model includes two deterministic time dependent functions in the infinitesimal moments to describe the presence of exogeneous terms in the typical dynamics of the phenomenon. An iterative estimating procedure combining the maximum likelihood estimation and a generalized method of moments is provided. A Quandt Likelihood Ratio test for detecting structural breaks in $PM_{10}$ data, in the period from 1st January 2020 to 8th July 2020 which includes the first lockdown due to Covid pandemic, confirms the presence of time-changes. These results show that the lockdown made the air once again cleaner. It is then shown that our model and the associated estimation procedure, while not explicitly contemplating the presence of structural breaks in the time series, implicitly incorporates them in the time dependence of the functions in the infinitesimal moments of the underlying process.
topic non homogeneous ornstein uhlenbeck processes
estimating procedure
pm10
structural breaks
url http://www.aimspress.com/article/doi/10.3934/mbe.2021047?viewType=HTML
work_keys_str_mv AT giuseppinaalbano detectingtimechangesinpmsub10subduringcovidpandemicbymeansofanornsteinuhlenbecktypeprocess
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