Uncertainties in Life Cycle Greenhouse Gas Emissions from Advanced Biomass Feedstock Logistics Supply Chains in Kansas

Abstract

To meet Energy Independence and Security Act (EISA) cellulosic biofuel mandates, the United States will require an annual domestic supply of about 242 million Mg of biomass by 2022. To improve the feedstock logistics of lignocellulosic biofuels in order to access available biomass resources from areas with varying yields, commodity systems have been proposed and designed to deliver quality-controlled biomass feedstocks at preprocessing "depots". Preprocessing depots densify and stabilize the biomass prior to long-distance transport and delivery to centralized biorefineries. The logistics of biomass commodity supply chains could introduce spatially variable environmental impacts into the biofuel life cycle due to needing to harvest, move, and preprocess biomass from multiple distances that have variable spatial density. This study examines the uncertainty in greenhouse gas (GHG) emissions of corn stover logistics within a bio-ethanol supply chain in the state of Kansas, where sustainable biomass supply varies spatially. Two scenarios were evaluated each having a different number of depots of varying capacity and location within Kansas relative to a central commodity-receiving biorefinery to test GHG emissions uncertainty. The first scenario sited four preprocessing depots evenly across the state of Kansas but within the vicinity of counties having high biomass supply density. OPEN ACCESSEnergies 2014, 7 7126The second scenario located five depots based on the shortest depot-to-biorefinery rail distance and biomass availability. The logistics supply chain consists of corn stover harvest, collection and storage, feedstock transport from field to biomass preprocessing depot, preprocessing depot operations, and commodity transport from the biomass preprocessing depot to the biorefinery. Monte Carlo simulation was used to estimate the spatial uncertainty in the feedstock logistics gate-to-gate sequence. Within the logistics supply chain GHG emissions are most sensitive to the transport of the densified biomass, which introduces the highest variability (0.2-13 g CO2e/MJ) to life cycle GHG emissions. Moreover, depending upon the biomass availability and its spatial density and surrounding transportation infrastructure (road and rail), logistics can increase the variability in life cycle environmental impacts for lignocellulosic biofuels. Within Kansas, life cycle GHG emissions could range from 24 g CO2e/MJ to 41 g CO2e/MJ depending upon the location, size and number of preprocessing depots constructed. However, this range can be minimized through optimizing the siting of preprocessing depots where ample rail infrastructure exists to supply biomass commodity to a regional biorefinery supply system.

Enhancing Eco-Efficiency of Agro-Products’ Closed-Loop Supply Chain under the Belt and Road Initiatives: A System Dynamics Approach

“…For instance, subsidizing the logistic processes can effectively lower emission intensity. This is also an indirect proof that the carbon emissions of the agro-product supply chain largely originate from the logistic processes [38]. In comparison, subsidizing bioenergy enterprise is ineffective in terms of emission reduction.…”

GIS method to design and assess the transportation performance of a decentralized biorefinery supply system and comparison with a centralized system: case study in southern Quebec, Canada

“…The sizing of the depots is based on a resource approach that determines the available supply of corn stover in the territory. The assumptions of depots’ size in this study are smaller than those in the literature because of the pedoclimatic conditions, the dispersion of the feedstock in the territory, and the low participation rate of farmers. To select the sizing of the biomass depots, Eqn (3) is used (adapted from Ministry of Natural Resources of Quebec) to estimate the potential tonnage of corn stover technically and ecologically available in southern Quebec: where CS a is the potential corn stover technically and ecologically available annually in the research area (DMg); A is the potential harvested corn lands area, set to ~200 k ha (120 km radius); LR is the ratio of corn lands in Quebec that can tolerate material removal, set to 50% authors’ assumption based on literature; Y is the grain yield, average 2015–2017, set to 10.2 Mg ha −1 (163 bu ac −1 ) (15% moisture content); WR is the residue‐to‐grain weight ratio, set to 66% authors’ assumption based on the land yield and the culture condition; RR is the stover removal ratio, set to 25% based on the soil quality and yield; and AR is the annual biomass availability rates (farmers’ participation rate), set to 10–40% authors’ assumption based on literature…”

“…A conventional centralized supply configuration implies that all the biomass processing steps take place at the same geographic location. A centralized configuration has been documented to operate in a local supply context in high biomass‐yield areas . The implementation of a large‐scale stand‐alone biorefinery faces many logistical challenges .…”

Sustainable Supply Chain Management: The Influence of Disposal Scenarios on the Environmental Impact of a 2400 L Waste Container

“…Sustainable transport has a relevant issue: environmental impact [2]. The environmental impact of the supply chain is highly influenced by vehicle technology and operational decisions [3,4]. The relationships between supply chain decisions and environmental impact have been studied due the relevance of transport systems in sustainable development strategies, such as traffic policies [5], green innovation [6], or life cycle assessment (LCA) [7][8][9].…”