Research Reports on Transport Energy Transition

The AEMSLab has developed a multi-disciplinary approach to understanding the complex, interconnected system dynamics at play in shaping urban form, primarily transport, accessibility, energy, essentiality, adaptability and market pressures. The costs and benefits of public investments in infrastructure are no longer obvious as they were in the last century. Historically, more infrastructure facilitated more development and thus more property and retail tax revenues. However, the costs of sprawling urban growth started to outstrip the benefits in the 1980's. The benefits for residents and developers have also declined in relation to lack of access to cultural, social, service and work activities declined in suburbia. Today, the market is growing for "walkable" lifestyle as the values of reduced driving lifestyles are becoming evident.  Transit oriented, multi-activity new urban projects and cycle pathway access are providing some of the few vectors for profitable new developments.  As these factors become clear to urban planners and developers, the project of re-developing existing urban areas for 21st Century city living provides a huge opportunity for Transition Engineering. 

If you have a river to cross, you can look at examples of great bridges from around the world, and you can admire how these bridges have provided for new activities. However, if you actually want a bridge, you will have to get some engineering work done. The engineers will apply all of the science, knowledge and art to design the foundations and structure that will safely span the river, provide the access services needed, at a price the community can afford , and work through the project with all of the stakeholders and contractors to get the bridge built. 

The AEMSLab has been working on developing quantitative tools for engineering the solid foundations and functions of the urban re-development projects. In the approach we recognize that land use can undergo redevelopment, new development, or can remain the way it has already been developed. As active researchers in the area of long-term transition of energy systems, the AEMSLab has produced two of the most innovative research reports in the NZTA research database. We have also carried out research as part of the New Zealand Centre for Sustainable Cities, and sponsored by NIWA team under the Resilient Urban Futures research programme which is directly on the critical path for development of the Re-New-All Forecasting methodology. We propose case studies in Auckland’s North Shore and South Auckland.  



Data for travel behavior and the locations of activities must be gathered, but new quantitative modeling methods must be developed to assess the adaptive capacity, affordability, accessibility and future behavior for a given urban transport system. 


The methods described below have been used for the city of Dunedin as presented in the Peak Oil Vulnerability Report (2010), and they are the basis for the From the Ground Up process for Regenerating Christchurch


Risk to Essential Transport Activities (RECATS)

In 2005 Hurricane Katrina struck the city of New Orleans in the USA. The authorities warned people to leave the city. Emergency managers were shocked to discover that more than 20% of the population did not have access to transport and could not escape. This disaster led the AEMSLab to consider a modelling approach that could provide local risk assessment for transport access in the event of a disaster or fuel shortage. We contemplated, what would happen if the price of fuel doubled in a short period of time? if the amount of fuel purchased could be halved, and people could carry out their activities in another way, then the net impact on the economy of the city could be mitigated. If the amount of fuel could not be reduced, then the fuel price rise would create recessionary pressures on the economy, some long-commute properties would lose value in the market, and lower income people could lose their access to transport. In 2005 we actually got funding from the Land Transport New Zealand to develop a model to assess the transport fuel resilience of a given urban area. Many people thought it was a crazy idea that the price of fuel could double in a short period of time, or at all... but then, the 2008 oil crisis happened. Demand for fuel did dip and stop growing, the congestion eased, ridership on buses skyrocketed, housing prices in many commuter suburbs crashed, and the global recession set in. One thing we discovered in this research was that no-one had any way to assess how travel behavior choices could adapt to using less fuel. This became the subject of our next project. 

NZTA Research Report 311 (2007) is Available for Free Download 


Travel Adaptive Capacity Assessment (TACA)

The transport engineering field uses an assumption that fuel demand in inelastic. In other words, people are locked into their habits of where they live and work, how they use vehicles, and they don't want to change. But how do we even know how they could change? The 2007-2008 fuel price shock surprised government and the markets. But, given the hard facts of the future oil supply decline and climate mitigation requirements, the AEMSLab developed a computer program that both lets people explore changes in fuel use in their weekly activities and collects data about the adaptive capacity of people in a city. The TACA Sim was developed and deployed in trials in Dunedin, Christchurch and Oamaru, New Zealand. The results are really fascinating, and a first of a kind in the transportation engineering field. 

NZTA Research Report 486 (2012) is Available for Free Download


Local Area Transport Energy Evaluation (LATEE)

You can't engineer what you can't measure. How much do people drive, and is the amount of driving related to demographic factors or access to transit? This is a really good question. The traditional way of looking at Travel Behavior is to do paper surveys on one particular day, and extrapolate that data out to the year. The return rate and number of data points from National Travel Surveys are rather low. Our idea was to use the survey that everybody must participate in - the vehicle registration and warrant of fitness. For more than a decade, New Zealand has required that every vehicle undergo an inspection every 6 months, and the registration address and odometer reading are taken. It was a monumental undertaking to develop the computer program to take more than 50 million data points, and turn it into the annual vehicle kilometers traveled (VKT) and map it onto the city. But, now we can do that for any city in New Zealand for every year from 2003 onwards. The result below for Auckland is illuminating. See how the number of km driven per household declined from 2003 to after the fuel price shock in 2011? Notice which areas of the city declined more?

Results of LATEE model showing severe decline in vehicle kilometers traveled in lower income and outlying parts of Auckland after the fuel price shock of 2008.


Minimum Energy Transport Activity and Accessibility (METAA)

The architecture and decoration of a building make it attractive and influence the market value. But think about the foundation, structure, roof, plumbing, electricity, heating and ventilation systems in the building. What a building looks like is important, but the engineered systems, and the connection of the building to the surroundings are essential. The engineered systems are designed by using models that predict how the system will work largely without the interaction of human behavior. The METAA model is a computer program that uses geographical information system (GIS) data and models of transportation activities and the ability of different ages of people to travel by foot or cycle. Just like the building energy modelling uses data about the structure and science about human comfort, the METAA model gives us a way to understand how accessible the activities of a city are.  The model matches up the demographics of a census area unit with the travel demand model for the activities these people engage in, and maps out for each house, how many destinations residents could access with different mode. The example below is for the city of Christchurch. Red pixels are placed on houses that have no way to get to any activities other than driving a car - all shops, schools, work places and medical centers are a farther distance that a person could ride a cycle and have no bus service. Green pixels are placed on houses that can access all 19 categories of activities and more than 20,000 possible jobs only by walking. The grey area in the centre of the city is the industrial and commercial area where almost no housing is available. Note that the historical growth of the city was first within the grey area, then residences moving out of the city to the walkable area around the city. In the 1950's much of the yellow area was accessed by electric trams, and 60% of all work trips were made by cycle.  

62343_META Risk 

The METAA model results for ability of households to access activities without a vehicle. 


Vulnerability to Oil: Income, Land-Use, Accessibility (VOILA!)

VOILA! combines spatial data of household transport energy consumption and fuel cost with a novel transport energy-accessibility metric calculated by the METAA method. VOILA! Includes an affordability model which assigns “average household” income, mortgage and property values to each meshblock from NZ Statistics. The method will be used in the Re-New-All Forecasting method to indicate the opportunity for growth of land use that involves transition to new urban forms which are less car dominated. The analysis also indicates areas of the city that may experience saturation or negative growth as the pressures of energy supply and cost increase. The analysis can also indicate where the potential exists for development of new destinations or new public transport or more interconnections in order to increase the accessibility to destinations that are not present within the area.


VOILA! Methodology schematic which uses the core of the METAA method plus incorporation of statistical geographical data. 

An open access journal paper  on the VOILA! Method in the journal Energies is available (2014).


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