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Estimates of Biomass Yield for Perennial Bioenergy Grasses in the USA

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Abstract

Perennial grasses, such as switchgrass (Panicum viragatum) and Miscanthus (Miscanthus × giganteus), are potential choices for biomass feedstocks with low-input and high dry matter yield per hectare in the USA and Europe. However, the biophysical potential to grow bioenergy grasses varies with time and space due to changes in environmental conditions. Here, we integrate the dynamic crop growth processes for Miscanthus and two different cultivars of switchgrass, Cave-in-Rock and Alamo, into a land surface model, the Integrated Science Assessment Model (ISAM), to estimate the spatial and temporal variations of biomass yields over the period 2001–2012 in the eastern USA. The validation with observed data from sites across diverse environmental conditions suggests that the model is able to simulate the dynamic response of bioenergy grass growth to changes in environmental conditions in the central and south of the USA. The model is applied to identify four spatial zones characterized by their average yield amplitude and temporal yield variance (or stability) over 2001–2012 in the USA: a high and stable yield zone (HS), a high and unstable yield zone (HU), a low and stable yield zone (LS), and a low and unstable yield zone (LU). The HS zones are mainly distributed in the regions with precipitation larger than 600 mm, and mean temperature range 292–294 K during the growing season, including southern Missouri, northwestern Arkansas, southern Illinois, southern Indiana, southern Ohio, western Kentucky, and parts of northern Virginia. The LU yield zones are distributed in southern parts of Great Plains with water stress conditions and higher temporal variances in precipitation, such as Oklahoma and Kansas. Three bioenergy grasses may not grow in the LS yield zones, including western parts of Great Plains due to extreme low precipitation and poor soil texture, and upper part of north central, northeastern, and northern New England due to extreme cold conditions.

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Acknowledgments

This work was partly supported by the US National Science Foundation (No. NSF-AGS-12-43071 and NSF-EFRI-083598), the USDA National Institute of Food and Agriculture (NIFA) (2011-68002-30220), and US Department of Energy (DOE) Office of Science (DOE-DE-SC0006706).

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Authors and Affiliations

  1. Department of Atmospheric Sciences, University of Illinois, Urbana, IL, 61801, USA

    Yang Song & Atul K. Jain

  2. ExxonMobil Research and Engineering Company, Annandale, NJ, 08801, USA

    William Landuyt & Haroon S. Kheshgi

  3. Department of Agriculture and Consumer Economics, University of Illinois, Urbana, IL, 61801, USA

    Madhu Khanna

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Correspondence to Atul K. Jain.

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Appendix

Appendix

Table 8 The values for various parameters used in this study. The three values separated by comma (,) the ‘Values’ column are for Miscanthus, Cave-in-Rock, and Alamo
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Table 9 Additional ISAM model equations used in this study
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Table 10 The location (latitude and longitude) and climate (annual mean temperature and accumulated precipitation) and soil characteristics of data sites used for model evaluation
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Song, Y., Jain, A.K., Landuyt, W. et al. Estimates of Biomass Yield for Perennial Bioenergy Grasses in the USA. Bioenerg. Res. 8, 688–715 (2015). https://doi.org/10.1007/s12155-014-9546-1

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