Mark Bünger, author of the recent Lux Research report on biochemicals and biomaterials (see the article on this site), holds the opinion that the viability of a green chemical industry is dependent upon many factors, which renders general judgements rather precarious. Local factors often prove to be decisive.
‘Everyone, from government ministers to protesters in the streets, wants simple answers to questions on the viability of biochemicals and biomaterials,’ he writes in an e-mail. ‘Unfortunately, our models show that in biomass-to-chemicals processes, all the factors are highly dependent on each other. The only accurate assessments are on the level of a specific plant in a specific place, and our report walks from a ‘back of the napkin’ level to a very detailed, plant-specific model. Scientists and engineers use these because they are necessary to provide useful answers. But most simple answers are wrong.’
Details are the crux
We asked Bünger whether sugar beet production in North-western Europe, with an average yield of 14 ton sugar/ha, would provide a good basis for chemicals and materials production. His answer: ‘That’s a good yield. But how much does it cost to buy it from the farmer? How far do you have to transport it to a refinery? What fuel or chemical are you going to make from it, how much will you sell it for, to whom, and for what application? These are not minor details, they are the very crux of the matter.’
‘A recent study getting a lot of publicity this week (GlobEcon researchers claiming 8 of 10 scenarios for rapeseed biodiesel failed to meet 35% greenhouse gas savings) illustrates the same point: 2 of 10 are passing the 35%, and the others fall along a spectrum from there on down. In other words, there is no one number, and the average is meaningless since we do not know whether or not the 10 scenarios are a representative sample of all growers in the EU. We do not even know how to pick a representative sample, because there are so many variables that go into farming (Size of the farm? Condition of the soil? Rainfall? Soil composition? Age of the implements?) and every other factor in the production chain.’
A policy of continuous improvement
And Bünger ends this line of reasoning with policy advice. ‘So, what would be more useful? Rather than just setting a goal of 35%, the EU should look at what the 2 successful scenarios have in common, and promote policies along those lines. Similarly, our report and its models show some specific points of leverage that governments, investors, businesspeople, and other outsiders should look for when assessing the viability (commercial or environmental) of a biomass-to-chemicals process.’
These specific points include the following:
• ‘Collection, transportation, and storage are key factors often overlooked. Most crops (e.g. sugar beet) are not inherently a good or bad match for conversion to green chemicals; it is the way they are grown, harvested, and taken to refining that makes them so. Geographic and annual variation also completely changes any calculation or economic or environmental success.
• Since ethanol is the cheapest chemical to make, you would make almost anything else you can (e.g. succinic acid) instead, if you have a microbe that can make it at the same cost. This is true regardless of how you got the sugars (enzymatic hydrolysis). So in a sense, you can say that other chemicals give enzymatic hydrolysis an opportunity, as well as vice-versa .
• Syngas is a better fit than other conversion technologies when the volume and variability of the composition is high; in other words, when you have a lot of junk to get rid of like municipal waste or a mixed agricultural harvest. If you have a predictable stream of homogenous feedstock (corn stover, bagasse, wood) then an acid or enzymatic process will probably yield more high-value chemicals at a lower total (process and capital) cost.’
We conclude that each business case should be judged on its own specific merits, and that policy making should try to stress continuous improvement rather than set specific limits, however difficult this might be in policy making practice.