Evaluation of Durham City and County Greenhouse Gas Reduction Initiatives
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2014-04-25
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To combat climate change, local governments and communities have undertaken various initiatives to reduce greenhouse gas (GHG) emissions. Durham City and County created a GHG Emissions Reduction Plan in 2007, with a goal of 50% GHG reduction for government operations by 2030 from the 2005 baseline.
The purpose of this study is to examine various projects that the Durham local governments have undertaken since 2007, evaluate their energy savings and GHG reduction, and provide recommendations for further GHG reduction. The scope includes only projects associated with local government. Six different project types are examined: building upgrades, transportation, traffic signals, landfill methane, water and wastewater management. About 20 government officials from different departments were interviewed to collect information about projects and relevant data such as energy consumption and financial costs. Based on the data, the study analyzes the trend of energy use and GHG emissions through time and uses common metrics to measure energy intensity. Most of the GHG reduction projects were effective and are discussed in detail in the paper.
The study provides recommendations for each individual project as well as general overall recommendations. The overall suggestions are to 1) set quantifiable sub-goals for different projects to complement the current total 50% reduction goal, 2) offer training to facility management teams on the importance of adopting best practices prevalent in the relevant industries, 3) install better metering technologies for more accurate data, and 4) foster more collaborations and better communication between each government department as well as between the government and the private sector. These recommendations will also help other cities conduct similar GHG reduction initiatives.
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Xi, Wenyi, Gary Gao, Rubaina Anjum and Myeongyeon Son (2014). Evaluation of Durham City and County Greenhouse Gas Reduction Initiatives. Master's project, Duke University. Retrieved from https://hdl.handle.net/10161/8548.
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