A spatio-temporal method for impact assessment

Case study of the impact of organic waste collection system scenarios in Amsterdam

Master thesis (2018)

Authors

R.F.L. Teeuwen Architecture and the Built Environment

Contributors

R. Sileryte (mentor)
J.A. Lopes Gil (mentor)
Faculty
Architecture and the Built Environment, Architecture and the Built Environment
Copyright: © 2018 Roos Teeuwen
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Published Date

26-06-2018

Language

English

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Faculty

Architecture and the Built Environment

Abstract

Amsterdam circular economy ambitions raise the question of what would be the impact of an organic waste collection system on inhabitants. Impact is an effect of a source on a receptor. Existing impact modelling studies describe impact either from source or from receptor perspective. In spatial planning, both source and receptor are variant over space. However, incorporation of the spatial dimension in existing impact modelling studies is limited, especially in presentation of outcomes.

The objective of this research is to answer: what spatio-temporal method is suitable to assess the impacts of organic waste collection system scenarios in Amsterdam? Tools used are QGIS and GRASS GIS, combined with PyQGIS scripting.

Five impact indicators were defined: three nuisance indicators (noise, odour and congestion), all quantified in three factors (intensity, temporality and affected population), and two sustainable planning indicators (CO2 emission and waste collection), quantified in intensity factor only. Calculations are performed using simple theoretical principles, implemented from both source and receptor point of view.

It was found that basic spatial tools and calculation principles suffice to quantify impact spatio-temporally. For congestion and waste collection modelling network calculations are needed. All indicator outcomes except for CO2 emission are relevant to present spatially. Both source and receptor point of view have their advantages and challenges, and therefore are complementing each other. Aggregation of factor values into one results in loss of information and transparency, which is contradicting to information and transparency gained by the high granularity spatio-temporal model. However, overview and simplicity in presentation of outcomes could be maintained by describing all impact factors per indicator in one clock-like marker. Impact assessment outcomes should be presented for individual sources and receptors. When presenting them on small scale, spatial aggregation into total values per neighbourhood is needed as well. Compared to presentation in a non-spatial graph, the spatial presentation of outcomes is of added value.