Perennial grasses are touted as sustainable feedstocks for energy production. Such benefits, however, may be offset if excessive nitrogen (N) fertilization leads to economic and environmental issues. Furthermore, as yields respond to changes in climate, nutrient requirements will change, and thus guidance on minimal N inputs is necessary to ensure sustainable bioenergy production.
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Sustainable production of algae will depend on understanding trade-offs at the energy-water nexus. Algal biofuels promise to improve the environmental sustainability profile of renewable energy along most dimensions. In this assessment of potential US freshwater production, we assumed sustainable production along the carbon dimension by simulating placement of open ponds away from high-carbon-stock lands (forest, grassland, and wetland) and near sources of waste CO 2 .
Practicing agriculture decreases downstream water quality when compared to non-agricultural lands. Agricultural watersheds that also grow perennial biofuel feedstocks can be designed to improve water quality compared to agricultural watersheds without perennials. The question then becomes which conservation practices should be employed and where in the landscape should they be situated to achieve water quality objectives when growing biofuel feedstocks.
Advanced biomass feedstocks tend to provide more non-fuel ecosystem goods and services (ES) than 1st-generation alternatives. We explore the idea that payment for non-fuel ES could facilitate market penetration of advanced biofuels by closing the profitability gap. As a specific example, we discuss the Mississippi-Atchafalaya River Basin (MARB), where 1st-generation bioenergy feedstocks (e.g., corn-grain) have been integrated into the agricultural landscape.
Ecological disturbances are occurring with greater frequency and intensity than in the past. Under projected shifts in disturbance regimes and patterns of recovery, societal and environmental impacts are expected to be more extreme and to span larger spatial extents. Moreover, preexisting conditions will require a longer time to re‐establish, if they do so at all. The word “unprecedented” is appearing more often in news reporting on droughts, fires, hurricanes, tsunamis, ice storms, and insect outbreaks.
Policy makers are interested in estimates of the potential economic impacts of oil price shocks, particularly during periods of rapid and large increases that accompany severe supply shocks. Literature estimates of the economic impacts of oil price shocks, summarized by the oil price elasticity of GDP, span a very wide range due to both fundamental economic and methodological factors. This paper presents a quantitative meta-analysis of the oil price elasticity of GDP for net oil importing countries, with a focus on the United States (US).
Bio-oil derived via fast pyrolysis is being developed as a renewable fuel option for petroleum distillates. The compatibility of neat bio-oil with 18 plastic types was evaluated using neat diesel fuel as the baseline.
Several crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long‐term production potentials in the United states.
Energy market conditions have shifted dramatically since the USA renewable fuel standards (RFS1 in 2005; RFS2 in 2007) were enacted. The USA has transitioned from an increasing dependence on oil imports to abundant domestic oil production. In addition, increases in the use of ethanol, the main biofuel currently produced in the USA, is now limited by the blend wall constraint. Given this, the current study evaluates alternative biofuel deployment scenarios in the USA, accounting for changes in market conditions.
This analysis estimates the cost of selected oil and biomass supply shocks for producers and consumers in the light-duty vehicle fuel market under various supply chain configurations using a mathematical programing model, BioTrans. The supply chain configurations differ by whether they include selected flexibility levers: multi-feedstock biorefineries; advanced biomass logistics; and the ability to adjust ethanol content of low-ethanol fuel blends, from E10 to E15 or E05.