Structuring empirical knowledge on environmental issues : urban heavy metal metabolism

Detta är en avhandling från Linköping : Linköpings universitet

Sammanfattning: During the last century, there has been a large import of heavy metals to urban areas. Only a small fraction, about 10%, has reached the biosphere, the rest is still residing in various goods such as cables, construction materials, technical equipment and batteries, which are still in use or abandoned in infrastructure, buildings, households, enterprises and vehicles.Emissions from industry and production have been attended and regulated, but emissions from consumption have mainly been ignored. Recent decades, aproactive research has evolved to earlier identify flows and stocks of materials that may cause environmental problems. The methodology used in the thesis is based on systems analysis and called material flow analysis, MFA.This thesis presents a system analysis approach to data management, organisation and presentation of empirical knowledge on the use of the heavy metals cadmium (Cd), copper (Cu), chromium (Cr), mercury (Hg), nickel (Ni), lead (Pb) and zinc (Zn) during the twentieth century. The data collection was made during a case study in Stockholm, Sweden, 1994- 1997.A simple model implemented as a spreadsheet program was used to structure the empirical data. To be useful for proactive analyses, the model included data on for instance the inflow of heavy metal containing goods, the stock in use, and estimations of emissions to the biosphere.Societal data of heavy metal use turned out to be scarce and have large uncertainties. An analysis of the data sources is made in this thesis, and some methods for construction of data to fit the model are presented. A separate part is a discussion of the uncertainties, where it is suggested that lognormaldistributions may be assumed to manage data with large uncertainties, and that subjectively estimated uncertainties, e.g. from expert judgements, may be cautiously used in the same framework.The problem with societal environmental modelling is not to make the models, rather to fill them with reliable data. Since societal data are scarce, it is not necessary with complicated databases or models to structure the data.A decision-making situation related to environmental issues generally involves many decision-makers with different goals. It is then important that the models used for organisation and presentation are flexible and easy to see through.

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