Global warming has given a new dimension to urban design efforts that seek to integrate the infrastructure systems of a city into a sustainable and more natural built environment. For several decades, architects, planners, and designers have been calling for a more compact urban form that integrates nature with the city, as well as greater use of energy efficient building and transportation alternatives. However, the need to mitigate and adapt to climate change has created a new and more urgent driver for change. The result has been a transformation in approaches taken by leading edge designers and the elites responsible for urban infrastructure systems. Nowhere has this been more evident than in the water and energy sectors (Daigger, 2009; Dreiseitl et al, 2009; Hermanowicz, 2008 Lindsay, 2010; Poetz and Bleuze, 2008; Woltjer and Al, 2007). Mitigating carbon emissions has been taken up by local governments around the world, while water is the most visible vector for the effects of global warming. Many describe these responses under the rubric of the “eco-city.”

The eco-city rejects the idea of waste, instead seeking to transform it into beneficial uses within the city. In so doing, it seeks to reduce inputs of water and energy from afar. This concept is behind efforts to decentralize the production of energy and food and to create more local “green” employment. It also powers the three “R’s” of solid waste management as well as transportation efforts such as transit oriented development, walkable neighbourhoods, and “complete streets.” Architects, planners and landscape architects have used many of these innovations at the building site level over the past twenty years. The next breakthrough is to integrate these systems at the neighbourhood, block or development cluster to begin to approach zero emissions.

This paper begins by describing energy and water innovations at the site and building level before examining the experiences of six cities that have tried to integrate water, energy and solid waste utilities in new neighbourhoods. In so doing, these pioneers have begun to move towards the development of micro-utilities that use the landscape as the fifth infrastructure for true sustainability.

This report describes a fiscal impact study done for the City of San Jose, California, in 2003-2004, a time when the city was reeling from fiscal and economic pressures caused by the dot-com bust. With residential land prices rising due to low interest rates and industrial land declining in value, the city experienced a flood of applications for residential conversions. City staff were concerned that wholesale changes in land use to housing, particularly in the city’s high-tech campus area that forms a major part of the Silicon Valley Golden Triangle, would have negative impacts on local employment and city finances. The case study describes the institutional, political and economic context in California and San Jose before going on to outline the study methods and results. The case evaluates how the fiscal impact analysis was used by the city to set Council policy for conversion applications and how it impacted the thinking of staff, the council and the local real estate community. The case study illustrates how fiscal impact analysis can be used as a planning tool by a city or county to enable the jurisdiction to take a proactive role in preserving high value employment lands while providing for affordable housing and the fiscal health of the city. This case study can be used in a land use planning class, an economic development class, a housing or a municipal finance class.

This paper uses employment and output in high-tech industries, venture capital funding, and the number of dot-com firms per 1000 private workers, at the metropolitan level, to identify their contribution to differences in housing market outcomes. Housing prices in New Economy markets are found to be higher, peakier and more volatile than in old economy markets. Homeownership rates are found to be lower in new economy metro areas while crowding is found to be higher. Although the distribution of housing values, cost, and rents was more equal in New Economy markets, the cause would seem to be differences in metro area income levels, with poorer MSA's having greater inequalities. Regression analysis is used to identify the contribution of traditional supply and demand factors such as job growth, income, residential construction, as well as New Economy indicators, to housing market outcomes. Rather than being fundamentally different, New Economy housing markets are found to be faster and more extreme versions of traditional housing markets.