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Researchers Developing Software to Model Impacts of Greenhouse Gas Reduction Policies on Transportation

The University of Michigan is leading a four-university team in a $1.9-million project to develop software to help analysts craft greenhouse gas reduction policies in the transportation industry.

The premise for the research is the belief that significant greenhouse gas emissions in the United States will not decrease unless environmental costs are captured in the marketplace and new government policies are implemented. The US transportation industry produces more greenhouse gas emissions than any other country’s entire economy, so any serious reduction in emissions must include the transportation sector.

Emissions reduction policies in transportation can have significant consequences on the economy and materials use, and can fail due to unintended results that can offset environmental gains, said Steven Skerlos, associate professor of mechanical engineering at U-M.

Specifically, we want to know if proposed policies would have unintended and undesirable consequences on the function of the automotive market, on the industry’s life cycle environmental impact, or on the industry’s demand for materials.

—Steven Skerlos

The researchers will look at how the effectiveness of government policies is constrained by producer incentives, consumer preferences and technological constraints. For example, if the best economic choice for producers to respond to greenhouse gas policies is to increase their use of lighter-weight aluminum rather than steel, that could offset emissions reductions because aluminum production requires more electricity. This electricity can come from either highly intensive CO2 sources such as coal generation or less intensive sources such as hydroelectric generation.

To predict these unintended consequences, researchers must integrate models of market decisions and technological performance with life cycle assessment and materials flow analysis, a process that marries public policy, engineering, natural resources and behavioral research. The project will culminate with the development of an analytical tool called CAPA (the computational automotive policy analysis software program).

Skerlos presented the framework for the study at the annual meeting of the American Association for the Advancement of Science in San Francisco. Skerlos and James Winebrake, chair of the public policy department at Rochester Institute of Technology, are co-directors of the $1.9 million, five-year project funded by the National Science Foundation since October 2006. Other universities include the University of California at Berkeley and Northeastern University.

The project arose by chance, beginning when RIT’s Winebrake happened to be in the audience for a talk by Skerlos on government policy and sustainable design. Winebrake, an expert in public policy with experience in modeling and an interest in technology systems, approached Skerlos, an expert in environmental technology with experience in modeling and an interest in public policy.

The project is funded though the National Science Foundation MUSES program (Materials Use: Science, Engineering and Society), which supports programs that study the sustainable use of materials and the mitigation of adverse human impact on the environment.



re: 'The US transportation industry produces more greenhouse gas emissions than any other country’s entire economy,'

That seems a bit iffy. I have read repeatedly that China will pass the US in total CO2 emissions in 2009 or 2010. That means they must be getting close already.

Because transportation is only one part of US total emissions the statement as written seems to imply that everything else - mostly our power generation from coal and NG - emits relatively little CO2. That makes no sense.

The problem may be in definitions. CO2 is not the only greenhouse gas. Maybe they toss in NO2 and everything coming out of diesels. However, I suspect the writer was simply mistaken.

As for the project itself. Probably a good idea. These things are great training and serve to bring future star players into notice. The skills developed will probably be worth much more than the product itself.

Rafael Seidl

Let's hope they calibrate their model using historical data from markets other than the US. Europe has very high fuel prices and many countries' vehicle license fees are based on engine displacement, some on fuel consumption and/or rated power. Germany is considering a switch to emissions-based fees, with CO2 output the most significant factor in the formula.

All this has had the salutary effect of keeping cars smaller, lighter and less powerful than those in the US. However, the greater expense of operating a car also leads to more sophisticated fuel-saving technology which has to be paid for up front, in addition to high sales taxes (e.g. 19% in Germany). Together, these factors mitigate against frequent purchases of new cars, the average age of the general LDV fleet here is 8 years and rising. This has reduced the energy spent in vehicle production per passenger-km driven.

Unfortunately, it has also slowed the adoption of recent fuel-saving innovations and the transition to updated emissions standards. The health care costs associated with antiquated Euro 1 and 2 diesels in particular are probably significant.


The process of examining the inputs into such a model are probably worthwhile in that the building of the model will lead you to ask questions you may not have asked before and attempt to quantify variables that have never truly been quantified previously. The research into these questions may have value. The model itself will probably not be of any real value since it is far to susceptible to political interference from interested parties. My experience with models is that they will tell you exactly what you expect them to produce. Because if they don't give you the answer you want then there must be a bug in the program or a problem with the input parameters. I've been building computer models for over 25 years and what usually happens isn't garbage in garbage out, it's data in, stilted assumptions in and pre-determined thinking out.



In this particular application models probably will behave well. First of all, models for life time energy efficiency are pretty straightforward, and initial data (energy requirements to produce steel and aluminium, fuel consumption, rate of metals recycling, etc.) are well established and documented.

I believe models from respectable university will put an end for wild speculations, common as of today. I’ve read such outrageous BS as GM Hummer is being much more energy efficient per mile driven then Prius…

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