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amount of redundancy of variables, that is, the variables at least slightly overlap in
their meaning. Thanks to this redundancy, it is possible to discover a pattern in the
behavior of variables, that is, the basic idea (factor) by which they are imbued
(Žibret and Šajn 2010).
Cluster analysis is a statistical technique used to identify how different entities –
variables – can be grouped together for the sake of their characteristics. Also known
as clustering, it is a preliminary data analysis tool that aims to sort different objects
in a group in such a way that those who belong to the same group have the highest
degree of association. The most commonly processed dendrograms or clusters are
expressed by distance, Dlink/Dmax (%).
Characteristic vector analysis (PCA) is methodologically very similar to factor
analysis, in that it uses the correlation coefficient (r) to isolate new components that
do not show dependence on each other. Often the representation of the dependency
is given graphically in a two-dimensional system by the two most significant components (vectors). Component analysis provides beside graphical and tabular calculations for easy explanation of graphical representations. This module is classified
by a diagonal, symmetric, correlation, or covariance matrix.
1.6 Conclusions and Perspectives
High utilization of resources to feed economic growth exacerbates the problems of
securing supply and sustainable yields and managing environmental impacts in
terms of ecosystem absorption capacity. A challenge for politics, as well as for science, is how best to measure the environmental impacts that result from the use of
resources; several ongoing initiatives aim to better quantify environmental impacts
from resource use. Environmental degradation through air pollution, noise, chemicals, poor-quality water, and loss of natural habitat, combined with lifestyle changes,
is likely to contribute to significant increases in obesity, diabetes, and cardiovascular and neurological diseases and cancer – all of which pose major health problems
for the population. Reproductive and mental health problems are also on the rise.
Asthma, allergies, and some cancers associated with environmental stress are of
particular concern to children. All this indicates the great need for continuous qualitative and quantitative assessment of the state of the environment. Quantitative
analyses and methodologies are multidisciplinary chemometric models that are
applicable in almost all areas and enhancements to environmental research. The last
decades have seen an intense technological development, which has enabled the
launch of very sensitive, fast, accurate, and effective analytical instruments. This
development of instrumental analytical models has enabled the chemical characterization of a huge number of pollutants and toxins, which degrade the environment
even in very low concentrations.
1 General Aspects of Environmental Degradation vs. Technological Development…
amount of redundancy of variables, that is, the variables at least slightly overlap in
their meaning. Thanks to this redundancy, it is possible to discover a pattern in the
behavior of variables, that is, the basic idea (factor) by which they are imbued
(Žibret and Šajn 2010).
Cluster analysis is a statistical technique used to identify how different entities –
variables – can be grouped together for the sake of their characteristics. Also known
as clustering, it is a preliminary data analysis tool that aims to sort different objects
in a group in such a way that those who belong to the same group have the highest
degree of association. The most commonly processed dendrograms or clusters are
expressed by distance, Dlink/Dmax (%).
Characteristic vector analysis (PCA) is methodologically very similar to factor
analysis, in that it uses the correlation coefficient (r) to isolate new components that
do not show dependence on each other. Often the representation of the dependency
is given graphically in a two-dimensional system by the two most significant components (vectors). Component analysis provides beside graphical and tabular calculations for easy explanation of graphical representations. This module is classified
by a diagonal, symmetric, correlation, or covariance matrix.
1.6 Conclusions and Perspectives
High utilization of resources to feed economic growth exacerbates the problems of
securing supply and sustainable yields and managing environmental impacts in
terms of ecosystem absorption capacity. A challenge for politics, as well as for science, is how best to measure the environmental impacts that result from the use of
resources; several ongoing initiatives aim to better quantify environmental impacts
from resource use. Environmental degradation through air pollution, noise, chemicals, poor-quality water, and loss of natural habitat, combined with lifestyle changes,
is likely to contribute to significant increases in obesity, diabetes, and cardiovascular and neurological diseases and cancer – all of which pose major health problems
for the population. Reproductive and mental health problems are also on the rise.
Asthma, allergies, and some cancers associated with environmental stress are of
particular concern to children. All this indicates the great need for continuous qualitative and quantitative assessment of the state of the environment. Quantitative
analyses and methodologies are multidisciplinary chemometric models that are
applicable in almost all areas and enhancements to environmental research. The last
decades have seen an intense technological development, which has enabled the
launch of very sensitive, fast, accurate, and effective analytical instruments. This
development of instrumental analytical models has enabled the chemical characterization of a huge number of pollutants and toxins, which degrade the environment
even in very low concentrations.
1 General Aspects of Environmental Degradation vs. Technological Development…