Life Cycle Assessment of Switchgrass Cellulosic Ethanol Production in the Wisconsin and Michigan Agricultural Contexts

Abstract

Spatial variability in yields and greenhouse gas emissions from soils has been identified as a key source of variability in life cycle assessments (LCAs) of agricultural products such as cellulosic ethanol. This study aims to conduct an LCA of cellulosic ethanol production from switchgrass in a way that captures this spatial variability and tests results for sensitivity to using spatially averaged results. The Environment Policy Integrated Climate (EPIC) model was used to calculate switchgrass yields, greenhouse gas (GHG) emissions, and nitrogen and phosphorus emissions from crop production in southern Wisconsin and Michigan at the watershed scale. These data were combined with cellulosic ethanol production data via ammonia fiber expansion and dilute acid pretreatment methods and region-specific electricity production data into an LCA model of eight ethanol production scenarios. Standard deviations from the spatial mean yields and soil emissions were used to test the sensitivity of net energy ratio, global warming potential intensity, and eutrophication and acidification potential metrics to spatial variability. Substantial variation in the eutrophication potential was also observed when nitrogen and phosphorus emissions from soils were varied. This work illustrates the need for spatially explicit agricultural production data in the LCA of biofuels and other agricultural products.

Life cycle assessment of common reed (Phragmites australis (Cav) Trin. ex Steud) cellulosic bioethanol in Jiangsu Province, China

“…Excluded biogenic GHG, the total emitted GHG estimated through the LCA system was 380 gCO 2,eq L À1 , which was compatible with the research of Sinistore et al [39]. Based on LCA calculation (Fig.…”

Introduction to High Pressure CO2 and H2O Technologies in Sustainable Biomass Processing

“…Lignocellulosic material tends to be more difficult to convert to fuels but usually provides more material per plant growth area and requires less fertilizer to grow. 10,11 Both of these attributes lead most experts to agree that second generation biofuels and bioproducts are more sustainable than their first generation equivalents. The composition of lignocellulosic material is usually about 40-50% cellulose, 25-35% hemicellulose and most of the remainders is lignin.…”

The DOE Bioenergy Research Centers: History, Operations, and Scientific Output

“…The modeling group draws on data generated by the other groups. A good example of how modeling builds on the work of other BRC scientists is included later in this issue [18]. This life cycle assessment builds on data generated from field experiments, pretreatment, deconstruction, and fuel synthesis from the BRCs and many other sources to comprehensively assess the environmental impact of eight ethanol production scenarios in Michigan and Wisconsin.…”

“…Lupoi et al [101] and Sykes et al [102] developed new spectrographic methods to characterize lignin and carbohydrate content of biomass, respectively, thereby permitting rapid screening of samples for potential yield of fuel. Konda et al [103] model the economics of fuel using microalgae feedstock, while Sinistore et al [18] model ethanol synthesis from switchgrass. The integrative nature of the BRCs focuses and supports this interdisciplinary work, which generates fundamental knowledge while always keeping an eye toward practical implications.…”