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Location model for CCA-treated - wood waste remediation units
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Resumo(s)
There is growing concern about the environmental impacts and increasing
difficulty to dispose preservative treated wood products at the end of their service
life. In the next decades, in Portugal, a significant increase is expected in the
amounts of treated wood that annually needs to be properly disposed. The
recycling of these wastes, containing chromium, copper and arsenic (in the case
of CCA-treated wood), should only be made after its remediation, so planning
and optimisation of the remediation units locations is of major importance.
The objective of this study is the development of a location model to optimise the
location of remediation plants for the treatment of CCA-treated wood waste for
further recycling, minimizing costs and respecting environmental criteria.
The location model was implemented with geographic information using
Geographic Information Systems (ArcGIS 8.2 © ESRI). All the uses of treated
wood products were considered, using soil occupation data and the results of a
questionnaire sent to wood preservation industries.
Two different clustering methods (Self-Organizing Maps and K-means) were
tested in different conditions to solve the multisource Weber problem using
SOMToolbox for MATLAB.
The solutions obtained with our data and with both clustering methods make
sense and could be used to decide on the location of these plants. SOM has
provided more robust and reproducible results than k-means, with the
disadvantage of longer computing times. The main advantage of k-means,
compared to SOM, is the reduced computing time allied to the fact that it allows
us to obtain the best solutions in the majority of the cases, in spite of bigger
variances and more geographical dispersion.
Descrição
Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica
Palavras-chave
CCA-treated wood waste Integrated waste management Location models Self-organizing maps (SOM) K-means Optimisation Resíduos de madeira preservada com CCA Gestão integrada de resíduos Modelos de localização Self-organizing maps (SOM) K-means Optimização