The Economic Potential of Second-Generation Biofuels: Implications for Social Welfare, Land Use and Greenhouse Gas Emissions in Illinois

This paper develops a dynamic micro-economic land use model that maximizes social welfare and internalizes externality from greenhouse gas emissions to obtain the optimal land use allocation for traditional row crops and bioenergy crops (corn stover, miscanthus and switchgrass), the mix of cellulosic feedstocks and fuel and food prices. We use this carbon tax policy as a benchmark to compare the implications of existing biofuel policies on land use, social welfare and the environment for the 2007-2022 period. The model is operationalized using yields of perennial grasses obtained from a biophysical model, county level data on yields of traditional row crops and production costs for row crops and bioenergy crops in Illinois. We show that a carbon tax policy that is directly related to carbon intensity of fuels can generate the highest social welfare among alternative policy scenarios. The existing ethanol tax credits result in substantial deadweight losses and higher GHG emissions as compared to the baseline. Ethanol blending mandates with subsidies lead to further welfare losses and higher GHG emissions. To meet advanced biofuel blending mandates, corn stover and miscanthus are used but the mix of viable cellulosic feedstocks varies spatially and temporally. Corn stover is viable mainly in central and northern Illinois while miscanthus acres are primarily concentrated on southern Illinois. The blending mandates lead to a significant shift in acreage from soybeans and pasture to corn and a change in crop rotation and tillage practices.cellulosic ethanol, land use, social welfare, greenhouse gas emissions, Land Economics/Use, Resource /Energy Economics and Policy, Q42, Q24,

A dynamic analysis of U.S. biofuels policy impact on land use, greenhouse gas emissions and social welfare

Biofuels have been promoted to achieve energy security and as a solution to reducing greenhouse gas (GHG) emissions from the transportation sector. This dissertation presents a framework to examine the extent to which biofuel policies reduce gasoline consumption and GHG emissions and their implications for land allocation among food and fuel crops, food and fuel prices and social welfare. It first develops a stylized model of the food and fuel sectors linked by a limited land availability to produce food and fuel crops. It then analyzes the mechanisms through which biofuel mandates and subsidies affect consumer choices and differ from a carbon tax policy. A dynamic, multi-market equilibrium model, Biofuel and Environmental Policy Analysis Model (BEPAM), is developed to estimate the welfare costs of these policies and to explore the mix of biofuels from corn and various cellulosic feedstocks that are economically viable over the 2007-2022 period under alternative policies. It distinguishes biofuels produced from corn and several cellulosic feedstocks including crop residues (corn stover and wheat straw) and bioenergy crops (miscanthus and switchgrass). A crop productivity model MISCANMOD is used to simulate the yields of miscanthus and switchgrass. The biofuel policies considered here include the biofuel mandate under the Renewable Fuel Standard (RFS), various biofuel subsidies and import tariffs. The effects of these policies are compared to those of a carbon tax policy that is directly targeted to reduce GHG emissions. The stylized model shows that a carbon tax can reduce gasoline consumption and lower GHG emissions, and is likely to increase biofuel consumption with a higher elasticity of substitution between gasoline and biofuels and an elastic supply of gasoline. A biofuel mandate would reduce gasoline consumption, but the effects on GHG emissions depend on parameters in the fuel sector, such as the demand elasticity of miles, the elasticity of substitution between gasoline and biofuels and the supply elasticity of gasoline. A biofuel mandate accompanied with subsidies would create incentives to increase the consumption of the blended fuel by lowering its price. Gasoline consumption and GHG emissions would increase under the mandate and subsidy relative to a mandate alone. The numerical simulation is used to analyze the impacts of biofuel mandate and subsidies relative to a carbon tax. We find a biofuel mandate alone leads to a welfare gain of 0.1% while reducing GHG emissions by 1% relative to a carbon tax of $30 per ton of CO2e (Carbon dioxide equivalent). However, it would increase corn and soybean prices in 2022 by 19$106 B relative to the tax. To meet the cellulosic biofuel mandates, a mix of feedstocks (corn stover, wheat straw, switchgrass and miscanthus) is used, where the mix differs over time, with biofuels from miscanthus meeting about 90% of the cellulosic ethanol produced between 2007- 2022. Corn stover comes primarily from the plain states while wheat straw is collected mainly in the central and northern plains and western mountain states. Production of miscanthus is more concentrated in the Great Plains and in the Midwest and along lower reaches of the Mississippi river. Switchgrass, though not as competitive as miscanthus in terms of yields and costs of production in most parts of the country, is still produced in a significant amount in northern and central Texas and Wisconsin where miscanthus yields are relatively low. We then analyze the implications of imposing import tariffs on biofuels for social welfare and GHG emissions in an open economy considering trade in biofuels. When biofuel mandates and subsidies are in place, the imposition of import tariffs would significantly reduce the imports of sugarcane ethanol by 28% relative to biofuel mandates and subsidies. It also results in a higher GHG intensity of the blended fuel and marginally increases GHG emissions but raises social welfare by 0.01% relative to biofuel mandates and subsidies

Characterization of phosphofructokinase B-type kinases from Arabidopsis thaliana leading to the identification of a plastid inosine kinase

Nucleotide metabolism is vital for plant development and dependent on the support of various enzymes including the phosphofructokinase B-type (PfkB) sugar kinases. Although some PfkB kinases such as adenosine kinase (ADK), ribokinase (RBSK), and pseudouridine kinase (PUKI) have been successfully identified and characterized in recent years, much is still unknown about these kinases. In this study, PfkB kinases from Arabidopsis thaliana were functionally screened leading to the identification of a plastid inosine kinase (PINK) that is involved in the feedback regulation of de novo purine synthesis and of kinase 6-2 (K6-2), which may be involved in negative regulation of purine synthesis. According to bioinformatic analyses, PINK is highly conserved in the plant kingdom, Subcellular localization and in vitro kinase activity analyses revealed that PINK is a plastid kinase that phosphorylates inosine, uridine, and 5-aminoimidazole-4-carboxamide ribonucleoside (AICAr). Furthermore, metabolite analysis was performed of Arabidopsis seedlings in which PINK expression was varied, which showed that PINK is not only involved in the inosine salvage but also likely contributes to feedback inhibition of de novo purine biosynthesis by regulating the plastid IMP pool. Moreover, PINK is possibly involved in pyrimidine nucleotide synthesis, at least in the context of defective uridine degradation. Additionally, another member of the PfkB family, kinase 6-2 (K6-2) was partially characterized in this work. K6-2 is localized in the chloroplast and in vitro biochemical analysis showed that K6-2 can phosphorylate AICAr, inosine, and guanosine. Furthermore, an in vivo functional study suggested that K6-2 is a negative regulator of purine de novo biosynthesis, as the biosynthesis of purine nucleotides was enhanced in the knock-down mutant of K6-2. Moreover, the reduced expression of K6-2 in Arabidopsis led to a phenotype that involved yellowing and suppressed leaf growth

Meeting the Mandate for Biofuels: Implications for Land Use and Food and Fuel Prices

Biofuels have been promoted to achieve energy security and as a solution to mitigating climate change. This research presents a framework to examine the extent to which biofuel mandates and subsidies reduce gasoline consumption and their implications for the food and fuel prices. A dynamic, multi-market equilibrium model, Biofuel and Environmental Policy Analysis Model (BEPAM), is used to estimate the effects of these policies on cropland usage between food crops and fuel crops and food and fuel prices, and to analyze the incentives provided by alternative policies for the mix of biofuels from corn and various cellulosic feedstocks that are economically viable over the 2007-2022 period. The provision of biofuel subsidies that accompany the mandate under the Renewable Fuel Standard (RFS) is found to significantly change this mix in favor of cellulosic biofuels produced from high yielding grasses and reduce the adverse impact of the RFS alone on food prices.Land Economics/Use, Resource /Energy Economics and Policy,

Mathematical Programming Modeling of Agricultural Supply Response

Agricultural and Food Policy, Land Economics/Use,

A self-adaptive alarm method for tool condition monitoring based on Parzen window estimation

Tool condition monitoring (TCM) takes an important position in CNC manufacturing processes, especially in damages avoiding of working parts and CNC itself. This paper presents a self-adaptive alarm method using probability density functions estimated with the Parzen window based on current signals, which gives an adaptively and rapidly corresponding alarm when the cutting tool fracture occurs. A CNC with cutting tools was obtained by Guangzhou CNC Company for test purpose, and the relative experiments were done in the state key laboratory. Current signals of the spindle motor and the main feed motor were acquired during the tool life. A probability model estimated with the Parzen window is established for current data fusion to alarm adaptively. At the meantime, the acoustic emission (AE) signals were acquired for comparison purpose. Experimental results show that this technique is flexible and fast enough to be implemented in real time for online tool condition monitoring