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Technical Paper

Alternative Fuel Vehicles: Environmental and Economic Effects of Infrastructural Requirements

2000-04-26
2000-01-1482
This paper summarizes some of the environmental and economic requirements of providing the infrastructure for alternative fuel vehicles (AFV) at a large scale in the U.S. Major components of the necessary infrastructure are fuel extraction and processing plants, and fuel storage, transportation, distribution and retail systems. The type of fuel, market penetration rates, economies of scale, timely availability, longevity, and refueling mode are key to the assessment of the necessary infrastructure. Some of the infrastructure is already in place, while substantial investments will still be needed. Alcohol fuels could utilize components of the current infrastructure, with modifications, but natural gas and electric vehicles would require substantial new investments into the infrastructure.
Technical Paper

Life Cycle Inventory Combining Input-Output Techniques and Conventional Process Models - A Case Study of A Fuel-Injection System

1999-03-01
1999-01-0012
In this paper we present a hybrid approach to Life Cycle Assessment (LCA) using the case study of an electronically controlled unit injector (EUI), which is a time-controlled fuel injection system. Using the hybrid approach, we are able to quantify environmental information on upstream production processes preceding manufacture at Bosch without the need to gather all supplier data empirically. Life Cycle Inventory (LCI) data based on “conventional” process models are combined with LCI data from economic input-output relations between different industry sectors and associated pollution discharges and nonrenewable resource consumption. The economic input-output-based LCA (EIO-LCA) allows us to quantify indirect environmental impacts of production processes generally neglected in conventional LCA models. As EIO-LCA quantifies environmental impacts on a rather aggregate level, additional process models for LCA are used to account for specific characteristics of the processes investigated.
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