Cambridge - 
The Next 50 Years

In this section:

Introduction

How will Cambridge develop over the next 50 years?

Cambridge Futures has attempted to examine this question by projecting current trends into the future, and looking at how different planning options would affect the Cambridge area.

Computer modelling was used to simulate the effects of development in seven different planning scenarios. The planning impacts of each of these scenarios has been evaluated in terms of economic efficiency, social equity, and environmental quality.

Basic assumptions

To make a consistent analysis of the alternatives for the future, two sets of assumptions have been made concerning the number of people who might live in the area and the number of jobs which might be available.

  • Population growth will continue at a declining rate; current numbers will increase by 44%, but because of declining household size, there will be 80% more households.

  • Employment will continue to grow, boosting current levels by 47%. This represents half the rate of growth experienced during the last 50 years.

To facilitate analysis, employment has been divided into basic or service employment. Basic employment is concerned with exporting goods and services outside the region, and bringing money back into it which supports households and services in the region. The rest is essentially service employment, the role of which is to support the basic sector and the residential population.

  • Basic sector

    • primary employment (agricultural and extractive) would probably continue to decline through time

    • secondary employment (manufacturing and large scale warehousing) would probably stay the same or slightly increase through time

    • tertiary employment (high-tech and further education) would probably continue to grow through time.

  • Service sector (retail, private and public services) would grow considerably during the period as income grows.

  • Extra buildings and land would be required to meet the expected growth of households and employment for the period up to 2016.

    • dwellings: 40,000

    • industrial and warehousing: 130,000 m2

    • office floorspace: 1,200,000 m2

    • commercial floorspace: 200,000 m2

Estimating the impacts

Computer simulation models have been used to estimate the likely outcome of the policies implemented for each option. One of the models, MENTOR, simulates the workings of the market for location (land use) and the other, SATURN, simulates the market for transport. The models estimate:

  • Location of firms and households. MENTOR calculates the probability of firms and households locating in each area of the region, taking account of the availability of commercial floorspace and dwellings, costs, accessibility to transport, and the attractiveness of the area.

  • Price of commercial property and of dwellings. MENTOR calculates the equilibrium price of the buildings. If the area is highly attractive, the prices would increase, reducing the demand to locate there.

  • Transport flows. The model calculates the number of people travelling between areas of the region for work, shopping, education and other purposes. It also calculates the probability of using different means of transport, such as walking, cycling, bus, train or car.

  • Congestion in the network. SATURN calculates the number of vehicles using the road network during the peak hours, estimating traffic delays, and thus the accessibility of different areas of the region.

Evaluation - 3 'E's

From the results of the simulation models, it is possible to compare the options under three headings:

  • Efficiency. Economic efficiency is measured by calculating the cost of living and production costs for each area and for the region as a whole. The cost of living includes housing, goods, services and transport. Cost of production, measured by employee, includes floorspace rental, wage levels, services and transport. Options which increase the region’s costs would probably also threaten its prosperity, making it less competitive.

  • Equity. Social equity is measured by the composition of socio-economic groups within areas of the region. Highly segregated location of, say, high income professional and managerial groups or of unskilled groups would not contribute to equity. A more balanced socio-economic mix means affordable housing and equitable opportunities for work and services.

  • Environment. Environmental quality can only be established by more subjective criteria. Nevertheless some quantitative estimates are possible, particularly traffic congestion, vehicle emissions and pollution levels. The amount of open space in the form of private gardens and agricultural land, is another indicator of quality. Impacts on man-made amenities such as buildings and public spaces are more difficult to assess.

A consideration of all three aspects – efficiency, equity and environment – should lead to a proper assessment of the sustainability of each option. All three aspects are relevant and if one of them falls short, the long term sustainability of the region will be impaired.

To summary of the options