I should point out that the report specifically excludes analysis of algae-to-ethanol production, such as that being pursued by Algenol, which says it is only a few years away from commercial-scale deployment.

Overall, I found the report to be a bit of a downer. “The availability of the resources required for microalgae production — land, climate, water, and, perhaps most critically, carbon dioxide — at the same site, will likely limit the U.S. potential for algae oil production to less than a few billion gallons annually. While minor compared to total U.S. transportation fuels consumption (about 200 billion gallons per year), renewable algae oil could be a major contributor to biofuel resources, particularly in specific markets, such as aviation fuel.” I agree on the last part with regards to jet fuel, but I’m a bit more optimistic on the overall market impact. The good news is that 10 years isn’t such a long time to wait, unless you’re a VC firm waiting to cash out.

The problem with this conclusion? Clarens based the life-cycle analysis on data that was mostly 10 years old. For example, some current algae cultivation practices, particularly those based on wastewater or sea water, tackle the fertilizer issue head on. So the age of the data is an important bit of information that should have been made very clear in the study — even the abstract. Ten years in the world of technology, particular cleantech, is a long time. I mean, the big R&D push around algae-based fuels only began three or four years ago, and 10 years ago the “cleantech” sector didn’t exist in name. Ten years ago the world was still wrapping its head around Y2K, George W. Bush was just getting into office, Google was still a start-up years from going public, and the TV show CSI (the original one) had its world premiere. In other words, you can expect data about algae cultivation to be, well, rather useless as a reflection of current practices.

This isn’t to blame Clarens. As he told the New York Times’ Green Inc., the most current data out there is simply unavailable to academia. It’s proprietary. “I’d be happy to model it if somebody produces it,” he said. This, of course, is a general problem with a lot of studies looking into lifecycle analyses. Researchers can only go with the data they can get, and perhaps this explains a lot of the earlier controversy around ethanol from corn. It’s still something we want to move away from, but certainly not as bad as guys like David Pimental of Cornell University like to paint it. I’d argue these studies should do two things: make a greater effort of emphasizing data limitations; and make a clear distinction between technologies/processes already deployed and those in pre-commercial phase.

Look at it this way: Can you imagine a study coming out in 2010 comparing different Internet search engines, but basing it on data available in 2000? Now, the Internet isn’t cleantech, but in certain areas there’s no reason to believe that the pace of innovation is any different.

Life-cycle analysis is hugely important work, but if it can’t keep up with innovation then it can become dated before it’s even published.