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Grantee Research Project Results

Web-Based Tool to Reduce GHG Emissions from Coal

EPA Grant Number: SU836794
Title: Web-Based Tool to Reduce GHG Emissions from Coal
Investigators: Castillo-Villar, Krystel K
Institution: The University of Texas at San Antonio
EPA Project Officer: Aja, Hayley
Phase: I
Project Period: November 1, 2016 through October 31, 2017
Project Amount: $15,000
RFA: P3 Awards: A National Student Design Competition for Sustainability Focusing on People, Prosperity and the Planet (2016) RFA Text |  Recipients Lists
Research Category: Sustainable and Healthy Communities , P3 Awards , P3 Challenge Area - Air Quality

Description:

The main goal of this proposal is to increase public awareness of greenhouse gas emissions for energy production and how emission can be lowered by co-firing biomass in power plants.

Objective:

The main objective of this proposal is to increase public awareness of greenhouse gas emissions for energy production and how emission can be lowered by co-firing biomass in power plants. Coal provides 34% of electricity in the United States and is one of the main sources of greenhouse gases to the atmosphere. There is an urgent need to reduce carbon emissions from fossil fuels. Co-firing a coal power plant with biomass is indicated as a low-cost and sustainable alternative for reduce carbon emissions. Studies indicate that by replacing 5% of the coal used by an average coal power plant with an equal amount of biomass (i.e., switchgrass) can reduce yearly CO2 emissions by nearly half a million tons, which is equivalent to taking approximately 40,000 cars off the roads. 

Three sub-objectives were defined: (1) apply systems modeling approach to quantify biomass crop yields and irrigation needs; (2) develop an integrated logistics optimization model for production of biomass for green energy generation; and (3) design and implement web-based tools to increase awareness about greenhouse gas emissions and provide a web-based educational expert system that assists decision makers.

Approach:

The city of San Antonio and the neighbor counties are used as the case study. The Agricultural Land Management Alternative with Numerical Assessment Criteria (ALMANAC) model and the watershed models Soil and Water Assessment Tool (SWAT) will be used to simulate the growth of different crops and will be connected to a novel logistic and agriculture production model to identify sustainable solutions for co-firing a coal power plant with biomass and reduce emissions. Some the objectives in the optimization model include: minimizing greenhouse gas emissions, production and transportation costs, and water use. The results obtained by the simulation and optimization scheme will generate inputs for the web-based educational expert system that will be disseminated to college students, farmers, and energy sector stakeholders.

Expected Results:

A novel web-based educational expert system that includes integrated models that captures the trade-offs between operational costs and greenhouse gas emissions. This project relates to pollution prevention control since biomass co-firing instantly reduces the amount of coal the power plant uses and replaces it with a sustainably harvested renewable energy source. This project has the potential to significantly reduce air pollution from coal-fired power plants. Thus, this project lies under the Clean Air Act.

Publications and Presentations:

Publications have been submitted on this project: View all 1 publications for this project

Supplemental Keywords:

Clean Air Act; GHG emissions, green energy; power plants; web-based expert system;

Progress and Final Reports:

  • Final Report
  • Top of Page

    The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.

    Project Research Results

    • Final Report
    1 publications for this project

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    Last updated April 28, 2023
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