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Hall B
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Discussion Summary
Hall B
CIRCULAR MAKER CITY: A SPATIAL ANALYSIS ON FACTORS AFFECTING THE PRESENCE OF WASTE-TO-RESOURCE ORGANIZATIONS IN CITIES
Hall B
Abstract
Abstract Body
In recent years, implementing a circular economy in cities has been proposed by policy makers as a potential solution for achieving sustainability. One strategy for circular cities is to convert waste to resources locally, which would require cities to integrate 'circular makers' - waste-to-resource organizations such as recycling companies or manufacturers utilizing waste streams for their production processes.
Existing literature has identified a number of drivers and barriers that affect the presence of circular makers in a city, such as the affordability of land, availability of industrial sites, and proximity to various stakeholders. However, existing research is mostly based on qualitative research methods such as surveys and interviews, and lacks a spatial perspective - papers either examine individual circular makers or cities policies as a whole, rarely researching district or neighbourhood scale attributes that could explain why circular makers are clustered in certain areas in a city and not others.
The aim of this research is therefore to use GIS (Geographic Information System) spatial analysis methods to verify drivers and barriers from existing literature, in order to empirically identify the spatial factors that affect the presence of circular makers in cities.
This research will utilize data from the Dutch National Waste Registry, which records all industrial waste producers and waste flows in the Netherlands. Using this dataset, we will identify the location, scale, and industry of circular makers in the Randstad - a megalopolis consisting of the Dutch cities Amsterdam, Rotterdam, The Hague, and Utrecht. We will then use the drivers and barriers identified in existing literature to derive variables that could be used for spatial analysis. The correlation between the variables derived from literature and the presence of circular makers will be calculated using linear regression.
Using this method, we expect to identify a list of factors that are correlated with the presence of circular makers, types of circular makers that are suited for locating in urban areas, as well as types of neighbourhoods that could be well suited for circular making.