{"id":{"repo_id":"colostate","oai_identifier":"oai:mountainscholar.org:10217/219532"},"canonical_url":"https://search.dev.ndltd.org/etd/colostate/oai:mountainscholar.org:10217/219532","repository":{"repo_id":"colostate","name":"Colorado State University","base_url":"https://api.mountainscholar.org/server/oai/request"},"display":{"title":"Characterization of co-benefits of green stormwater infrastructure across ecohydrologic regions in the United States","abstract":"Green stormwater infrastructure (GSI) systems such as rain gardens, permeable pavement and bioswales are commonly used in municipalities to reduce urban flooding and water pollution. In conjunction with these direct benefits, GSI systems provide additional social and ecological \"co-benefits\". Our goal was to investigate the co-benefits of commonly used GSI systems in five cities in the United States, including Baltimore, Denver, New York City, Philadelphia, and Portland. Specifically, carbon storage, carbon sequestration, air pollution removal, UV reduction, and cooling effects of the trees used in GSI in the study cities were quantified. The i-Tree Eco urban forestry model was used to predict various co-benefits for individual tree species and total SGI tree inventories across the five study cities based on observed tree characteristic data. Aspects of SGI design, environmental factors, and model inputs were evaluated to find what influences the assessment of SGI co-benefits. SGI design types and utilization levels of those designs played a big role in determining the number of trees used in SGI projects, however there is more nuance to the evaluation of co-benefits of different cities' SGI trees than just the tree population. Climate was a large influence on co-benefits' estimation, with similar co-benefit responses for cities with similar climates, like the eastern seaboard. The inputs that influence co-benefit predictions the most were evaluated using global sensitivity analysis. We also found that the inputs that represent the tree growth and environmental factors heavily influenced the computation of co-benefits in i-Tree Eco. Our research supports current literature in developing SGI programs that provide the most amount of co-benefits for specific climates. This study aims to reveal more about the mechanisms and prevailing equations within i-Tree Eco by providing modelled datasets and assessment approaches to estimate the co-benefits of GSI at unit and city levels.","abstract_html":"Green stormwater infrastructure (GSI) systems such as rain gardens, permeable pavement and bioswales are commonly used in municipalities to reduce urban flooding and water pollution. In conjunction with these direct benefits, GSI systems provide additional social and ecological "co-benefits". Our goal was to investigate the co-benefits of commonly used GSI systems in five cities in the United States, including Baltimore, Denver, New York City, Philadelphia, and Portland. Specifically, carbon storage, carbon sequestration, air pollution removal, UV reduction, and cooling effects of the trees used in GSI in the study cities were quantified. The i-Tree Eco urban forestry model was used to predict various co-benefits for individual tree species and total SGI tree inventories across the five study cities based on observed tree characteristic data. Aspects of SGI design, environmental factors, and model inputs were evaluated to find what influences the assessment of SGI co-benefits. SGI design types and utilization levels of those designs played a big role in determining the number of trees used in SGI projects, however there is more nuance to the evaluation of co-benefits of different cities' SGI trees than just the tree population. Climate was a large influence on co-benefits' estimation, with similar co-benefit responses for cities with similar climates, like the eastern seaboard. The inputs that influence co-benefit predictions the most were evaluated using global sensitivity analysis. We also found that the inputs that represent the tree growth and environmental factors heavily influenced the computation of co-benefits in i-Tree Eco. Our research supports current literature in developing SGI programs that provide the most amount of co-benefits for specific climates. This study aims to reveal more about the mechanisms and prevailing equations within i-Tree Eco by providing modelled datasets and assessment approaches to estimate the co-benefits of GSI at unit and city levels.","abstract_has_math":false,"creators":["Rainey, William, author","Arabi, Mazdak, advisor","Sharvelle, Sybil, committee member","McHale, Melissa, committee member"],"institution":"Colorado State University. 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Our goal was to investigate the co-benefits of commonly used GSI systems in five cities in the United States, including Baltimore, Denver, New York City, Philadelphia, and Portland. Specifically, carbon storage, carbon sequestration, air pollution removal, UV reduction, and cooling effects of the trees used in GSI in the study cities were quantified. The i-Tree Eco urban forestry model was used to predict various co-benefits for individual tree species and total SGI tree inventories across the five study cities based on observed tree characteristic data. Aspects of SGI design, environmental factors, and model inputs were evaluated to find what influences the assessment of SGI co-benefits. SGI design types and utilization levels of those designs played a big role in determining the number of trees used in SGI projects, however there is more nuance to the evaluation of co-benefits of different cities' SGI trees than just the tree population. Climate was a large influence on co-benefits' estimation, with similar co-benefit responses for cities with similar climates, like the eastern seaboard. The inputs that influence co-benefit predictions the most were evaluated using global sensitivity analysis. We also found that the inputs that represent the tree growth and environmental factors heavily influenced the computation of co-benefits in i-Tree Eco. Our research supports current literature in developing SGI programs that provide the most amount of co-benefits for specific climates. 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In conjunction with these direct benefits, GSI systems provide additional social and ecological \"co-benefits\". Our goal was to investigate the co-benefits of commonly used GSI systems in five cities in the United States, including Baltimore, Denver, New York City, Philadelphia, and Portland. Specifically, carbon storage, carbon sequestration, air pollution removal, UV reduction, and cooling effects of the trees used in GSI in the study cities were quantified. The i-Tree Eco urban forestry model was used to predict various co-benefits for individual tree species and total SGI tree inventories across the five study cities based on observed tree characteristic data. Aspects of SGI design, environmental factors, and model inputs were evaluated to find what influences the assessment of SGI co-benefits. SGI design types and utilization levels of those designs played a big role in determining the number of trees used in SGI projects, however there is more nuance to the evaluation of co-benefits of different cities' SGI trees than just the tree population. Climate was a large influence on co-benefits' estimation, with similar co-benefit responses for cities with similar climates, like the eastern seaboard. The inputs that influence co-benefit predictions the most were evaluated using global sensitivity analysis. We also found that the inputs that represent the tree growth and environmental factors heavily influenced the computation of co-benefits in i-Tree Eco. Our research supports current literature in developing SGI programs that provide the most amount of co-benefits for specific climates. 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