GGrantIndex
← Search

U.S. Egypt Cooperative Research: Effective Reduction of Industrial Green House Gas Emissions via Energy Integration and Biomass Utilization

$30,000FY2007O/DNSF

Texas A&M Engineering Experiment Station, College Station TX

Investigators

Abstract

0710936 ElHalwagi Description: This project supports collaborative research by Dr. Mahmoud El-Halwagi, Chemical Engineering Department, Texas A&M University, College Station, Texas in collaboration with Dr. Kamal Eiwda, Zagazig University, Zagazig, Egypt. They plan to study the Effective Reduction of Industrial GHG Emissions via Energy Integration and Biomass Utilization. Green house gases (GHGs) pose some of the most profound impact on the environment and climate change. The largest anthropogenic sources of GHG emissions are power plants and industrial processes. Two of the most viable alternatives for reducing GHGs from industrial facilities are the cogeneration and the utilization of biomass in conjunction with combined heat and power (CHP) in the process industries. The project is aimed at addressing the problem of GHG emissions from industrial facilities in Egypt and the United States. In particular, the following important strategies will be employed . Process Cogeneration: resulting in significant reduction in energy and emissions of GHGs . Biomass Utilization for Energy: leading to carbon sequestration during crop growth . Techno-Economic-Environmental Analysis and Policy Recommendations. The project will develop systematic and generally-applicable procedures to enable the foregoing three strategies and to answer various questions including the following: . How to incorporate biomass utilization in co-firing and energy production within an existing process? . How to reconcile thermal demands with cogeneration opportunities through integration? . What are the economic and policy factors to insure technical feasibility? . What is the impact on GHG emissions and what are the necessary GHG offsets/subsidies? Several industries in the US and Egypt will actively participate in the project and will serve on an Industrial Advisory Committee for the project. In addition to refereed publications and conference presentations, the research findings will be documented through software which will be developed and disseminated to industry to enable applications. Finally, a workshop will be organized at the end of the project to formalize the recommendations for policymaking to reduce GHG emissions. Intellectual Merit: This program is based on a novel framework that involves a holistic approach to optimizing process performance while minimizing environmental wastes. A combination of simulation, process synthesis, integration, and optimization models will be developed, integrated, and solved. The models will provide a new platform that can systematically provide a complete strategy for reduction in energy consumption and emission of atmospheric pollutants. These new techniques will lay the foundations for fundamental research in the emerging area of environmental biocomplexity and will result in institutionalizing an unprecedented environmental and systems research program. Broader Impact: The project will result in the creation of an active, broad-based program to address these complex environmental and processing issues in unique, fundamental, and integrated ways. The potential environmental benefits include reduction of environmental discharges, conservation of natural resources, and abatement of pollution. The work can also impact growth policies by providing cost-effective process design and operation policies. The solutions will describe the role of the various entities in solving the problem and provide a cost-benefit analysis for the proposed strategies. The developed approach is generic enough to be adapted and evolved to study pollution prevention for a wide variety of industries. This project is being supported under the US-Egypt Joint Fund Program, which provides grants to scientists and engineers in both countries to carry out these cooperative activities.

View original record on NSF Award Search →