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MPhil in Engineering for Sustainable Development

global challenges, engineering solutions
 

Adaptivity of Urban Infrastructure to Rapid Population Growth in Cambridge

Population growth combined with outdated urban infrastructure will be a major challenge for
cities in the next decades. Urban infrastructure refers to the physical networks that create,
move, and store resources and people for a city. Two of the essential characteristics of
infrastructure under pressure from rapid changes are its resilience and adaptivity. Resilience
is the ability of a system to withstand and recover from shocks. Adaptivity is the ability of a
system to change and learn under stress; it is a subset of resilience.

The aim of this research is to identify principles and opportunities for hidden infrastructure
which will assist developed, growing cities towards adaptivity. The research focuses on
Cambridge because it has a small population but fast growth and high social inequality. Much
effort has been expended by cities to predict and prepare for urban growth. However, high
level planners usually focus first on visible infrastructure. Only secondarily do they consider
hidden infrastructure such as water, wastewater, and electricity, which is the focus of this
research.

Qualitative data is collected, coded, and then mapped using GIS. The qualitative data
comes from interviews, field notes, and grey literature. The data is processed in an SQLite
database for categorisation and data coding. The outcomes are shown on a GIS map of
Cambridge. Conflicts and coincidences of key concepts are thus represented spatially and
across infrastructure networks. The benefits of this process are that it allows intuitive, spatial
visualisation of concerns and conflicts.

Several key principles for adaptivity emerge from the findings, with the most interesting
characterised by balance or conflict. Timing and anticipation is necessary to ensure that a
city continues to function, yet planning too carefully can reduce adaptivity. The inhabitants
of a city may prevent change, but they have the potential to defend or drive adaptivity, for
example by resisting damaging developments and promoting useful ones. The size and shape
of infrastructure networks, unsurprisingly, affect adaptivity of the city, but not always in in the
way one might expect. Distributed or local infrastructure has benefits, but faces challenges in
implementation. Finally, existing infrastructure, if used intelligently, can actually support the
adaptivity of a city.

There are practical implications for this research. The Devolution Deal is an opportunity,
as is the opening of the Cambridge North Station and the existence of co-operative housing
developments. Planners need to adopt and champion new models of infrastructure, especially
distributed and smart infrastructure. There is much scope for further investigation. The
most important and obvious limitation is that currently most of the sources of qualitative
data are from Cambridge’s elite; it would be worthwhile to interview or survey non-elite
Cambridge residents to represent their views. This research may establish an engineer- and
planner-friendly means of representing qualitative data in a visual and interactive way, which
could potentially be integrated with existing data hub platforms for smart cities.

 

Course Overview

Context

The need to engage in better problem definition through careful dialogue with all stakeholder groups and a proper recognition of context.

Perspectives

An ability to work with specialists from other disciplines and professional groups acknowledging that technical innovation and business skills also must be understood, nurtured and combined as precursors to the successful implementation of sustainable solutions.

Change

An understanding of mechanisms for managing change in organisations so future engineers are equipped to play a leadership role.

Tools

An awareness of a range of assessment frameworks, sustainability metrics and methodologies such as Life Cycle Analysis, Systems Dynamics, Multi-Criteria Decision making and Impact Assessment.