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Semiconductor manufacturing and process design is driven to change rapidly by technology demands and competition. Incorporating environmental considerations into this process requires decision tools which will generate environmental analyses in as short a turn-around as possible. The predictive capability of QSAR methods are investigated and U.S. government QSAR software tools are surveyed for their applicability to environmental decision analysis in semiconductor equipment design.

Heating, ventilation, and air conditioning (HVAC) systems used in the clean room environment of biotechnology and drug development and manufacturing, are extremely energy and water intensive and represent a significant operating cost for these facilities [1]. HVAC systems are also the primary source of environmental emissions for the majority of companies operating within the biotechnology and drugs sector. While the processes used in drug manufacture have negligible environmental impact, the power plants, and water treatment facilities which annually provide the billions of kilowatt hours (kWh) of required electricity and hundreds of billions of gallons of make up water [5], also produce tons of CO2, CO, VOC, PM10, SO2, NOX, and in some cases Hg [3]. These issues of water and air emissions, key concerns of the California Department of Toxic Substance Control (DTSC) and the Environmental Protection Agency (EPA), are increasingly shared by the CEOs of leading pharmaceutical and biological products companies, and are appearing in their annual Environmental Health and Safety (EHS) reporting [4] with greater frequency and detail. The HVAC system used in the clean room manufacturing environment has been modeled with a functional unit of $/CFM. Economic and environmental impacts as a function of specified performance criteria have been captured, allowing for cost of ownership assessment of both existing and future systems of varying configurations serving a variety of clean room conditions. The opportunities for increased efficiency and cost savings of HVAC systems used in clean rooms are considerable, as much as 50% [5]. The HVAC model developed may lead to these savings through estimated results, which are considerably accurate, within 25% of several industry and government organized case study results [6]. The following report details a discussion of the HVAC system model, the methodology behind its development, its capabilities, and limitations.