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    Toward More Accurate Greenhouse Gas Predictions
    By News Staff | March 5th 2013 12:40 PM | Print | E-mail | Track Comments

    The timber industry, including pulp and paper producers, are among Canada's most important industries  - but they are also one of the largest producers of wastewater and greenhouse gas emissions in wastewater is a concern. 

    Until now, greenhouse gas emission estimates have been limited by the mathematical models used to predict them. Researchers have recently developed a new dynamic method to better predict the emission content of these gases.   

    "Currently used steady-state models are able to give an overall prediction but dynamic models can estimate the variation in greenhouse gas emissions in response to changes in the wastewater management system. Dynamic models are therefore more accurate and provide more information," says Laleh Yerushalmi, an adjunct professor at
    Concordia University
    's Department of Building, Civil and Environmental Engineering and co-author of a paper in
    Environmental Science and Pollution Research.

    The analysis compared steady-state and dynamic mathematical modeling predictions with actual values of greenhouse gas emissions in wastewater systems. Both models gave accurate results of overall gas emissions. However, the dynamic model was able to estimate changes in emissions in response to a changing environment. The dynamic model could also be used to predict other outputs, such as energy consumption and generation. 

    "With dynamic modeling, we can better understand the behavior of the treatment plant over time," says senior author Fariborz Haghighat, professor in Concordia's Department of Building, Civil and Environmental Engineering and Concordia Research Chair in Energy and Environment. "With this knowledge, we can then recommend a strategy to reduce the emission of greenhouse gas and also improve energy efficiency."  

    "Models such as this are used to simulate the behavior of a particular management system either in the early stages of system design or in later development to incorporate changes," adds Yerushalmi. "We want to make sure that we use the most accurate method possible and the dynamic model is best predictor yet."