Globally, bioethanol is the largest volume biofuel used in the transportation sector, with corn-based ethanol production occurring mostly in the US and sugarcane-based ethanol production occurring mostly in Brazil. Advances in technology and the resulting improved productivity in corn and sugarcane farming and ethanol conversion, together with biofuel policies, have contributed to the significant expansion of ethanol production in the past 20 years. These improvements have increased the energy and greenhouse gas (GHG) benefits of using bioethanol as opposed to using petroleum gasoline. This article presents results from our most recently updated simulations of energy use and GHG emissions that result from using bioethanol made from several feedstocks. The results were generated with the GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation) model. In particular, based on a consistent and systematic model platform, we estimate life-cycle energy consumption and GHG emissions from using ethanol produced from five feedstocks: corn, sugarcane, corn stover, switchgrass and miscanthus.We quantitatively address the impacts of a few critical factors that affect life-cycle GHG emissions from bioethanol. Even when the highly debated land use change GHG emissions are included, changing from corn to sugarcane and then to cellulosic biomass helps to significantly increase the reductions in energy use and GHG emissions from using bioethanol. Relative to petroleum gasoline, ethanol from corn, sugarcane, corn stover, switchgrass and miscanthus can reduce life-cycle GHG emissions by 19-48%, 40-62%, 90-103%, 77-97% and 101-115%, respectively. Similar trends have been found with regard to fossil energy benefits for the five bioethanol pathways.

Although the purchase price of cellulosic feedstocks is competitive with petroleum on an energy basis, the cost of lignocellulose conversion to ethanol using today's technology is high. Cost reductions can be pursued via either in-paradigm or new-paradigm innovation. As an example of new-paradigm innovation, consolidated bioprocessing using thermophilic bacteria combined with milling during fermentation (cotreatment) is analyzed. Acknowledging the nascent state of this approach, our analysis indicates potential for radically improved cost competitiveness and feasibility at smaller scale compared to current technology, arising from (a) R&D-driven advances (consolidated bioprocessing with cotreatment in lieu of thermochemical pretreatment and added fungal cellulase), and (b) configurational changes (fuel pellet coproduction instead of electricity, gas boiler(s) in lieu of a solid fuel boiler).

Bifunctional fixed-bed catalysts improve CFP performance.

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Abstract. Multiyear emission inventories of anthropogenic, biomass open burning, and industrial and commercial consumption were primary emission sources. Besides, source contributions of NMVOCs emissions showed remarkable annual variation. However, emissions of these sources had been continuously increasing, which coincided well with China's economic growth. Spatial distribution of NMVOCs emissions illustrates that high emissions mainly concentrates in developed regions of northern, eastern and southern coastal areas, which produced more emissions than the relatively underdeveloped western and inland regions. Particularly, southeastern, northern, and central China covering 35.2% of China's territory, generated 59.4% of the total emissions, while the populous capital cities covering merely 4.5% of China's territory, accounted for 24.9% of the national emissions. Annual variation of regional emission intensity shows that emissions concentrating in urban areas tended to transfer to rural areas year by year. MoreCorrespondence to: S. D. Xie (sdxie@pku.edu.cn) over, eastern, southern, central, and northeastern China were typical areas of high emission intensity and had a tendency of expanding to the northwestern China, which revealed the transfer of emission-intensive plants to these areas, together with the increase of biomass open burning.

This paper describes the development of (1) a formula correlating the variation in overall refinery energy efficiency with crude quality, refinery complexity, and product slate; and (2) a methodology for calculating energy and greenhouse gas (GHG) emission intensities and processing fuel shares of major U.S. refinery products. Overall refinery energy efficiency is the ratio of the energy present in all product streams divided by the energy in all input streams. Using linear programming (LP) modeling of the various refinery processing units, we analyzed 43 refineries that process 70% of total crude input to U.S. refineries and cover the largest four Petroleum Administration for Defense District (PADD) regions (I, II, III, V). Based on the allocation of process energy among products at the process unit level, the weighted-average product-specific energy efficiencies (and ranges) are estimated to be 88.6% (86.2%-91.2%) for gasoline, 90.9% (84.8%-94.5%) for diesel, 95.3% (93.0%-97.5%) for jet fuel, 94.5% (91.6%-96.2%) for residual fuel oil (RFO), and 90.8% (88.0%-94.3%) for liquefied petroleum gas (LPG). The corresponding weighted-average, production GHG emission intensities (and ranges) (in grams of carbon dioxide-equivalent (CO2e) per megajoule (MJ)) are estimated to be 7.8 (6.2-9.8) for gasoline, 4.9 (2.7-9.9) for diesel, 2.3 (0.9-4.4) for jet fuel, 3.4 (1.5-6.9) for RFO, and 6.6 (4.3-9.2) for LPG. The findings of this study are key components of the life-cycle assessment of GHG emissions associated with various petroleum fuels; such assessment is the centerpiece of legislation developed and promulgated by government agencies in the United States and abroad to reduce GHG emissions and abate global warming.

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