Modeling Disruptions to Urban Metabolism using Interconnected Networks

TL;DR

This paper models urban metabolism as interconnected networks, analyzing how disruptions in energy and transportation systems affect overall city functionality using real distribution data.

Contribution

It introduces a connected network modeling approach to quantify the robustness of interdependent urban infrastructure networks under disruptions.

Findings

Quantifies network robustness using real city data.

Evaluates impact of disruptions on energy and transportation networks.

Uses both unweighted and weighted metrics for analysis.

Abstract

Representation of cities as organisms with metabolic processes is a useful analogy for urban design, development and sustainability. Urban metabolism can be modeled by representing urban systems as networks. The various networks included in a city's metabolism are interdependent in complex ways. Thus, understanding the interaction among these networks is essential to understanding how a healthy urban metabolism is sustained and how injuries to the metabolic system can "heal". It is particularly important to understand how disruptions to one system in an urban area affect the functioning of other systems. Using distribution-level data from a real U.S. city on the electricity distribution system and road geometry, we apply connected network modeling to two critical inter-connected urban infrastructure sectors: energy and transportation. We quantify the robustness of these interdependent networks by evaluating the connectivity disruptions that may occur due to natural or synthetic disruptive events, using both unweighted and weighted metrics.