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Applications of Discrete-time Markov Chains and Poisson Processes to Air Pollution Modeling and Studies

  • Book
  • © 2013

Overview

Authors:
  1. Eliane Regina Rodrigues

    1. Area de la Investigación Científic, Instituto de Matemáticas, Universidad Nacional Autónoma de México, Mexico City, Mexico

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    You can also search for this author in PubMed   Google Scholar

  2. Jorge Alberto Achcar

    1. Universidade de São Paulo, Sao Paulo, Brazil

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    You can also search for this author in PubMed   Google Scholar

  • Focused volume on some stochastic models used to study problems related to environmental matters.
  • Includes supplementary material: sn.pub/extras

Part of the book series: SpringerBriefs in Mathematics (BRIEFSMATH)

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Table of contents (6 chapters)

  1. Front Matter

    Pages i-x
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  2. Introduction

    • Eliane Regina Rodrigues, Jorge Alberto Achcar
    Pages 1-10

  3. Markov Chain Models

    • Eliane Regina Rodrigues, Jorge Alberto Achcar
    Pages 11-23

  4. Poisson Models and Their Application to Ozone Data

    • Eliane Regina Rodrigues, Jorge Alberto Achcar
    Pages 25-64

  5. Modeling the Time Between Ozone Exceedances

    • Eliane Regina Rodrigues, Jorge Alberto Achcar
    Pages 65-78

  6. Some Counting Processes and Ozone Air Pollution

    • Eliane Regina Rodrigues, Jorge Alberto Achcar
    Pages 79-89

  7. Comments

    • Eliane Regina Rodrigues, Jorge Alberto Achcar
    Pages 91-92

  8. Back Matter

    Pages 93-107
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Keywords

About this book

​In this brief we consider some stochastic models that may be used to study problems related to environmental matters, in particular, air pollution.  The impact of exposure to air pollutants on people's health is a very clear and well documented subject. Therefore, it is very important to obtain ways to predict or explain the behaviour of pollutants in general. Depending on the type of question that one is interested in answering, there are several of ways studying that problem. Among them we may quote, analysis of the time series of the pollutants' measurements, analysis of the information obtained directly from the data, for instance, daily, weekly or monthly averages and standard deviations. Another way to study the behaviour of pollutants in general is through mathematical models. In the mathematical framework we may have for instance deterministic or stochastic models. The type of models that we are going to consider in this brief are the stochastic ones.​

Reviews

From the reviews:

“The book is dedicated to the study of air pollution in cities via stochastic modeling. … The book provides interesting approaches to the problem of air pollution in cities and it could be useful to scientists interested in this area.” (Iulian Stoleriu, Mathematical Reviews, May, 2013)

Authors and Affiliations

  • Area de la Investigación Científic, Instituto de Matemáticas, Universidad Nacional Autónoma de México, Mexico City, Mexico

    Eliane Regina Rodrigues

  • Universidade de São Paulo, Sao Paulo, Brazil

    Jorge Alberto Achcar

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