Considering Future Resource Constraints Related to Biomass Production

By Russell Martin

In my previous article, I projected biomass production estimates per state using data from the Natural Resource Inventory and the Billion Ton Report. The projection provided valuable insight for policy-makers about the spatial distribution of future bioenergy feedstocks. This article will discuss future resource constraints that pertain to feedstock production and expand on my previous analysis by projecting estimated agricultural land requirements and daily water use of potential feedstocks. I conclude that bioenergy feedstocks should: 1) require minimal resources, 2) be produced in areas that minimize competition with other land-uses vital to supporting world populations 3) be inherently resilient to disease, and 4) be derived from a diverse array of sources.

Factors and Future Resource Constraints Related to Bioenergy Production

Food (Fedoroff and Cohen 1999) and energy (DOE/EIA 2006) demand is escalating due to exponential growth in human populations across the globe. Bioenergy production has the potential to directly compete with food production if certain feedstocks, such as corn grain, are utilized to meet growing energy demands. Policy-makers must consider 3 broad factors when analyzing feedstocks, future resource constraints, and bioenergy policies.

The 3 broad factors that policy-makers must consider when analyzing potential feedstocks include productivity, composition, and displacement.

Feedstock productivity is primarily determined by the growth density and growth rate of a given feedstock; however, those attributes vary both spatially and temporally. For example, corn grain grows less dense and slower in the Great Plains than it does in the eastern US where soils are richer and annual precipitation is higher. Obviously, higher growth density and growth rate are desirable traits in bioenergy feedstocks, however, the use of artificial fertilizers, herbicides, and pesticides can make the process of intensive agricultural production unsustainable and can cause significant environmental damage (Tilman et al. 2002).

There are 2 types of composition that should be considered when evaluating a feedstock: plant composition and stand composition/rotation.

The composition of an individual plant (% lignin, % cellulose, ect) determines how much energy is required to process the biomass, which largely influences the efficiency of the entire production process, and how much energy is produced by the biomass (Ragauskas et al. 2006). Currently, biomass containing oils, starches, and sugars can be converted into biofuels. However, researchers are expecting to discover a method for converting lignocellulosic feedstocks into biofuels in the near future (Lynd 2008).

The composition of a crop stand is often forgotten about since modern agricultural practices almost always use the monocrop system. However, biorefineries, the facilities that will convert raw biomass into biofuels and bioenergy, are being designed to process a wide range of feedstocks, thus allowing policy-makers to consider poly-cropping systems. Poly-cropping, or high stand diversity, systems can suppress pest outbreaks and increase stand productivity by limiting pest movement, increasing the predator abundance of crop pests, and allowing legumes to fix nitrogen rather than applying artificial fertilizers. Rotating crops works in much the same way as poly-cropping to reduce pest outbreaks by preventing the build-up of pest populations.

The general resource constraints of bioenergy production are related to one of the attributes described by Dismukes et al (2008) to describe potential feedstocks: productivity. There is a finite land-base that can be used to produce bioenergy feedstocks before those feedstocks start competing with food production, thus only highly productive feedstocks should be considered since they will require the least amount of land for production. The inputs required to grow a given feedstock are also of significant importance since some inputs, primarily water, are becoming and will continue to be increasingly scarce (Vorosmarty et al. 2000). In a 2008 interview about climate change, recently appointed Energy Secretary, Steven Chu, discussed the displacement of agriculture from California’s Central Valley, which produces 20% of the US agricultural goods, due to water shortages (NOVA Online 2009). Both land and water are becoming increasingly scarce and warrant consideration from policy-makers when analyzing bioenergy feedstocks and policy options.

Estimating Acreage and Water Requirements for Potential Bioenergy Feedstocks

Dismukes et al. (2008) compiled statistics about 6 potential bioenergy feedstocks in their argument for the use of aquatic phototrophs as efficient alternatives to land-based feedstocks. Table 1 highlights productivity and water use for 3 of these 6 feedstocks.

table-1

Projecting Acreage Requirements of Feedstocks

Table 2 builds on my previous projection of estimated biomass production per state (Link to previous report) using data from the Natural Resource Inventory (NRCS 2007) and the Billion Ton Report (USDOE/USDA 2005). The table shows the estimated acreage required to produce each state’s projected agricultural biomass based on the productivity statistics from Table 1 (Dismukes et al. 2008) for 3 potential bioenergy feedstocks. These estimates should be considered a reference for policy-makers and land managers since they are based on a previous projection with additional simplified assumptions such as each state will produce agricultural biomass in proportion to its amount of current “agricultural” land. The acreage-required projection should be considered under the assumption that the least productive or abandoned agricultural land will be the first acreage taken out of food production in order to minimize reductions in food stocks.

table-211

table-221

Based on the productivity estimate for corn grain a state would have to use 62% of all available agricultural land for corn production in order to produce its projected agricultural biomass using corn grain the state. However, readers must realize that productivity varies spatially and temporally depending on various factors including climate, soil, annual precipitation, and inputs such as fertilizers, pesticides, and herbicides.

Both native grasses and Tetraselmis spp. have ranges of productivity estimates according to Table 1. I used the lowest and highest estimates to project the estimated acreage required for both feedstocks.

Native grasses/switchgrass would require between 29% and 120% of a state’s agricultural land to produce the projected agricultural biomass for each state. This broad range is due to the large differences in productivity of native grasses, which varies according to factors such as species composition, annual precipitation, soil type, previous land-use and numerous others.

Tetraselmis spp., a type of freshwater algae grown in open-air ponds, would require between 6% and 11% of a state’s agricultural land to produce the projected agricultural biomass for each state. The lower estimate is based on productivity averages of summer months whereas the higher estimate is based on productivity averages for an entire year.

The freshwater algae require significantly less land to produce the projected 998 million tons of biomass expected from agricultural land. The acreage required could potentially be less than what is projected here if current closed-air algae production facilities prove to be as efficient at commercial scales as they are in experimental trials.

Projecting Daily Water Requirements of Feedstocks

Table 3 also builds on my previous projection by estimating the potential daily water use required for 3 potential bioenergy feedstocks based on each state’s projected agricultural biomass production and the amount of daily water required for each feedstock. Readers should be aware that water use for each feedstock was calculated at a specific location, but is applied outside of the area that it was originally calculated. Ideally, county-specific water use for each feedstock would be measured and used for this projection since factors such as annual precipitation, soil moisture, evapotranspiration, and humidity vary according to latitude, longitude, and elevation. Readers should also note that water requirements should be met first by precipitation and supplemented by irrigation when precipitation alone is insufficient to meet the feedstocks daily needs. Annual precipitation averaged from 1971 – 2000 is also included as a reference for readers showing which states will rely more heavily on precipitation vs. irrigation (NOAA 2000).

table-31

table-32

Total US daily water use in 2000 was around 4.8E+12 gallons and daily irrigation water use was 1.4E+12 gallons (USGS 2000). In order to produce 998 million tons of agricultural biomass annually, the US would use 3.7E+12 gallons/day growing corn grain, 3.3E+11 gallons/day growing native grasses, 2.0E+12 gallons/day growing Tetraselmis spp. (low estimate), and 3.7E+12 gallons/day growing Tetraselmis spp. (high estimate) (Table 3). Native grasses would require significantly less water compared to the other 2 feedstocks and precipitation would likely meet this requirement since native grasses are adapted for optimal growth using annual precipitation of their historic range.

In reality, Dismukes et al. (2008) only discussed half of the productivity attribute component of a feedstock by describing above ground biomass productivity. The potential to sequester carbon through below ground growth is another important aspect of feedstock evaluation that deserves consideration. Of the 6 feedstocks evaluated by Dismukes et al., the only one with the potential to sequester carbon through below ground biomass is native grass grown on land previously used for agriculture production. Low-input, high-diversity mixtures of native grasses have been found to sequester up to 4.4 Mg C Ha-1 yr-1 (Tilman et al. 2006). This is potentially a major incentive for farmers to produce biomass using native grasses since carbon storage credits will bring additional income per unit area if policies are enacted that reward this beneficial behavior.

Conclusion

The demand for food and energy is projected to increase as world populations continue to grow and countries become more developed. Land and water are the most basic elements required for growing any type of agricultural product and availability of both resources is projected to decrease over the next 100 years. Policies that promote minimal resource-demanding feedstocks and feedstocks capable of growing on marginal agricultural land are needed in order to minimize conflict between supplying the world with food and energy.

Living organisms are inherently susceptible to pests and diseases. Polices are needed that minimize the probability of feedstocks failing if we are going to rely on biomass as a significant contributor to our energy stocks. There are three mechanisms that can drastically reduce the probability of bioenergy crops failing: encouraging high stand diversity, requiring a diverse feedstock “portfolio,” and encouraging proper crop rotations. High stand diversity helps regulate pest and disease outbreaks by allowing predators to reduce pest populations and to decrease disease transmission by increasing the distance between infectible individuals. A diverse feedstock “portfolio” is based on the same principle as a traditional stock portfolio: distributing risk across numerous stocks reduces overall risk. Proper crop rotations can keep pest populations at relatively harmless levels.  Incorporating fundamental ecological and economic concepts into energy policy is essential if bioenergy is going to play a significant role in future energy production.

Future resource constraints and the inherent risk associated with renewable energy sources, specifically those associated with living organisms, should be thoroughly analyzed if a significant portion of our future energy production will be derived from biomass. We, as a global community, must enact highly effective policies that considered all relevant factors and minimize the risks associated with continuous energy production.

Literature Cited

Department of Energy/Energy Information Administation. 2006. International Energy Outlook.

Dismukes, G. C., D. Carrieri, N. Bennette, G. M. Ananyev, and M. C. Posewitz. 2008. Aquatic phototrophs: efficient alternatives to land-based crops for biofuels. Current Opinion in Biotechnology 19:235-240.

Fedoroff, N.V. and J.E. Cohen. 1999. Plants and population: Is there time? Proceedings of the National Academy of Sciences 96 (11) 5903-5907.

Lynd, L. R. 2008. Energy biotechnology. Current Opinion in Biotechnology 19:199-201.

Natural Resource Conservation Service. 2007. Natural Resource Inventory.

National Oceanic and Atmospheric Administration. 2000. Total precipitation in inches by month: Climatology by state based on climate division data: 1971-2000. http://www.cdc.noaa.gov/data/usclimate/pcp.state.19712000.climo. Accessed 4/1/09.

NOVA Online. 2009. The Big Energy Gamble: 2008 Interview of Steven Chu. Public Broadcasting Service. http://www.pbs.org/wgbh/nova/energy/chu.html?gclid=CL_T6vS54ZkCFRAhDQodvFkrVg. Accessed 4/8/09.

Ragauskas, A. J., C. K. Williams, B. H. Davison, et. al. 2006. The path forward for biofuels and biomaterials. Science 311:484-489.

Tilman, D., K.G. Cassman, P.A. Matson, R. Naylor, and S. Polasky. 2002. Agricultural sustainability and intensive production practices. Nature 408: 671–677.

Tilman, D., J. Hill, and C. Lehman. 2006. Carbon-negative biofuels from low-input high-diversity grassland biomass. Science 314: 1598-1600.

United States Department of Agriculture and United States Department of Energy. 2005. Biomass as Feedstock for a Bioenergy and Bioproducts Industry: The Technical Feasibility of a Billion-Ton Annual Supply.

United States Geological Service. 2000. Estimated use of water in the United States in 2000. http://pubs.usgs.gov/circ/2004/circ1268/htdocs/table02.html. Accessed 4/1/09.

Vorosmarty, C.J., P. Green, J. Salisbury, and R.B. Lammers. 2000. Global water resources: Vulnerability from climate change and population growth. Science 289: 284–288.

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