TY - JOUR
T1 - Cost/benefit assessment of green infrastructure
T2 - Spatial scale effects on uncertainty and sensitivity
AU - Heidari, Bardia
AU - Schmidt, Arthur R.
AU - Minsker, Barbara
N1 - We gratefully acknowledge financial support from the National Science Foundation (NSF) (grant numbers 1331807 and 1261582). We also appreciate the funding and support provided by the National Socio-Environmental Synthesis Center (SESYNC) (NSF grant number 1639145), which allowed national working and advisory groups (listed in Appendix C) from five cities to meet and provide valuable input to this work. We also thank Tetra Tech Inc. for providing us with the SWMM model for Dead Run 5. The supplementary data for this work can be accessed at Mendeley Data (Heidari, 2021).
We gratefully acknowledge financial support from the National Science Foundation (NSF) (grant numbers 1331807 and 1261582 ). We also appreciate the funding and support provided by the National Socio-Environmental Synthesis Center (SESYNC) (NSF grant number 1639145 ), which allowed national working and advisory groups (listed in Appendix C) from five cities to meet and provide valuable input to this work. We also thank Tetra Tech Inc. for providing us with the SWMM model for Dead Run 5. The supplementary data for this work can be accessed at Mendeley Data ( Heidari, 2021 ).
PY - 2022/1/15
Y1 - 2022/1/15
N2 - Green infrastructure (GI) is becoming a common solution to mitigate stormwater-related problems. Given the uncertain costs of GI relative to other stormwater management strategies, stakeholders investing in GI need performance-analysis tools that consider the full suite of benefits and the impacts of uncertainty to help justify GI expenditures. This study provides a quantitative and comparative analysis of GI benefits, including nutrient uptake from stormwater and air pollutant deposition. Economic costs and benefits of GI are assessed using two metrics, benefit-cost ratios (BCRs) and nutrient removal costs, at three scales: household, subwatershed, and watershed scale. Results from a case study in the state of Maryland show that the costs of nutrient uptake at the subwatershed scale can be lower than those at either the watershed or household scales. Moreover, rain gardens are far more efficient in stormwater treatment at the household scale in comparison to watershed scale, for which large-scale dry or wet basins are more efficient. Using a BCR metric, smaller subwatersheds show more promise, while using a nutrient removal cost metric indicates that upstream subwatersheds are more suitable for stormwater treatment. The results also show that implementation of GI at all potential pervious locations does not necessarily increase nutrient removal costs and that self-installation of rain gardens greatly reduces nutrient removal costs. Finally, the results show that using numerous small-sized rain garden practices in front of residential buildings yields lower nutrient removal costs in comparison to permeable pavements placed in parking lots and commercial buildings.
AB - Green infrastructure (GI) is becoming a common solution to mitigate stormwater-related problems. Given the uncertain costs of GI relative to other stormwater management strategies, stakeholders investing in GI need performance-analysis tools that consider the full suite of benefits and the impacts of uncertainty to help justify GI expenditures. This study provides a quantitative and comparative analysis of GI benefits, including nutrient uptake from stormwater and air pollutant deposition. Economic costs and benefits of GI are assessed using two metrics, benefit-cost ratios (BCRs) and nutrient removal costs, at three scales: household, subwatershed, and watershed scale. Results from a case study in the state of Maryland show that the costs of nutrient uptake at the subwatershed scale can be lower than those at either the watershed or household scales. Moreover, rain gardens are far more efficient in stormwater treatment at the household scale in comparison to watershed scale, for which large-scale dry or wet basins are more efficient. Using a BCR metric, smaller subwatersheds show more promise, while using a nutrient removal cost metric indicates that upstream subwatersheds are more suitable for stormwater treatment. The results also show that implementation of GI at all potential pervious locations does not necessarily increase nutrient removal costs and that self-installation of rain gardens greatly reduces nutrient removal costs. Finally, the results show that using numerous small-sized rain garden practices in front of residential buildings yields lower nutrient removal costs in comparison to permeable pavements placed in parking lots and commercial buildings.
KW - Benefit cost assessment
KW - Green infrastructure
KW - Sensitivity
KW - Spatial scale
KW - Uncertainty
KW - Watershed
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U2 - 10.1016/j.jenvman.2021.114009
DO - 10.1016/j.jenvman.2021.114009
M3 - Article
C2 - 34872175
AN - SCOPUS:85118530185
SN - 0301-4797
VL - 302
JO - Journal of Environmental Management
JF - Journal of Environmental Management
M1 - 114009
ER -