In Bio-Fuel We Trust

In bio-fuel we trust. Or do we? In this chapter, ethnographic material from Sweden is used to discuss ways sin which trust may influence the choice of bio-fuel for heating purposes. The meaning and substance of trust or distrust, as well as the very conditions for trust, are elaborated on in relation to solar and bio-pellet systems, district heating with bio-fuel, and traditional fireplaces. An important conclusion of this chapter is that the degree to which people perceive others as being like themselves or not tends to be decisive for whether these others are to be trusted, and therefore worth listening to. The context and situation in which a certain heating system is being chosen does not only involve trust in individuals, however, but in companies and the authorities, as well as in the arterfacts themselves. An example is given on how distrust of district heating companies led house owners to reject an offer of district heating despite the comfort and environmental benefit this could have provided. it is shown how this distrust might be resolved by making the rhythm of households and sitrict heating companies more in step with one another. The strong emotional attachment to and deep-felt trust in the traditional fireplace is also analysed, and a question is put forward as to whether these feelings could be transferred to modern bio-pellet stoves. Finally, our great and assured trust in bio-fuel as a main solution to global climate change is shortly commented upon and partly questioned.

Geoprocessing journey-to-work data : delineating commuting regions in Dalarna, Sweden

Delineation of commuting regions has always been based on statistical units, often municipalities or wards. However, using these units has certain disadvantages as their land areas differ considerably. Much information is lost in the larger spatial base units and distortions in self-containment values, the main criterion in rule-based delineation procedures, occur. Alternatively, one can start from relatively small standard size units such as hexagons. In this way, much greater detail in spatial patterns is obtained. In this paper, regions are built by means of intrazonal maximization (Intramax) on the basis of hexagons. The use of geoprocessing tools, specifically developed for the processing ofcommuting data, speeds up processing time considerably. The results of the Intramax analysis are evaluated with travel-to-work area constraints, and comparisons are made with commuting fields, accessibility to employment, commuting flow density and network commuting flow size. From selected steps in the regionalization process, a hierarchy of nested commuting regions emerges, revealing the complexity of commuting patterns.