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Books > Earth & environment > The environment > Pollution & threats to the environment
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Applications of Discrete-time Markov Chains and Poisson Processes to Air Pollution Modeling and Studies (Paperback, 2013 ed.)
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Applications of Discrete-time Markov Chains and Poisson Processes to Air Pollution Modeling and Studies (Paperback, 2013 ed.)
Series: SpringerBriefs in Mathematics
Expected to ship within 10 - 15 working days
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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.
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