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Map-Based Modeling of People’s Knowledge, Perceptions and Willingness to Participate in Green Infrastructure Alternatives to Traditional Storm-Water Management:

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Presentation on theme: "Map-Based Modeling of People’s Knowledge, Perceptions and Willingness to Participate in Green Infrastructure Alternatives to Traditional Storm-Water Management:"— Presentation transcript:

1 Map-Based Modeling of People’s Knowledge, Perceptions and Willingness to Participate in Green Infrastructure Alternatives to Traditional Storm-Water Management: A Case Study in Syracuse Wanjun Peng 1, A. Karen Baptiste 2 and Lindsay Speer 3 1. Master Candidate State University of New York College of Environmental Science and Forestry 2. Assistant Professor, Colgate University 3. The Partnership for Onondaga Creek November 17 th, 2010

2 A voice for the Midland Community and the environment advocating for better, nonpolluting solutions advocating for better, nonpolluting solutions for Onondaga Creek – Since 2000 Partnership for Onondaga Creek

3 Environmental Justice Partnership for Onondaga Creek Midland Sewage Plant Green Infrastructure means… Injustice of Midland plant will not be repeated Onondaga Creek & Harbor Brook will be cleaner Community investment and beautification instead of further disruption

4 Green Infrastructure Solution to capacity problems with underground storage – reduce the rain! Proposed by Onondaga Nation POC: “If you can stop the Armory Sewage Plant, you can stop the Phase III Pipeline too!” County Executive Mahoney has promised that the pipeline will not be built. Partnership for Onondaga Creek

5 Partnership for Onondaga Creek Map of land use / GI possibilities in the 077 sewershed, including University Neighborhood. Part of presentation by POC to DEC & Onondaga County,  Engaging Community Dr. April Baptiste

6 During 2008 and 2009 the POC, Syracuse University and SUNY-ESF cooperated to obtain over 200 surveys among five neighborhoods of the Midland and Clinton Sewershed to assess public attitudes toward Green Infrastructure (GI) Implementation.

7 Explore to what extent individual demographics influence environmental attitudes toward GI Explore at what level neighborhood contexts are statistically related to environmental attitudes toward GI Use maps to visualize environmental attitudes toward GI implementation across neighborhoods * Three building blocks of environmental attitudes: Environmental knowledge Environmental perception Environmental behavioral intention. Objective

8 Methods---At individual level Summarize responses using descriptive statistics in Minitab software Look for factors that explain responses using regression models in SAS software

9 Methods---At individual level Summarize responses using Descriptive Statistics in Minitab software Look for influence of demographics, knowledge, perception of benefits and cost on responses using Regression Models in SAS software

10 Divide survey responses by neighborhood Apply regression models in SAS software to explore the influence of neighborhood context Map predicted responses (from models) across the city using ArcMap Software Methods---At neighborhood level

11 RESULTS at the Individual Level: The effect of demographic background and perception of benefits and cost on behavioral intention to implement GI if provided for free (216 Individual Surveys) Overall GI (All), rain barrels (RB), trees (T), rain garden (RG), porous driveway/sidewalks (P) and curbside extensions (CE). Participation likelihood for free GI AllRBTRGPCE Residency Ownership Age Education Ethnicity * * Gender * * Knowledge The influence of benefit The influence of cost- -

12 RESULTS at the Individual Level: The effect of demographic background and perception of benefits and cost on behavioral intention to implement GI if savings on water bills ensued (216 Individual Surveys) Overall GI (All), rain barrels (RB), trees (T), rain garden (RG), porous driveway/sidewalks (P) and curbside extensions (CE). Participation likelihood for savings AllRBTRGPCE Residency Ownership Age-- - Education Ethnicity Gender Knowledge+++++ The influence of benefit+++++ The influence of cost -

13 RESULTS at the Neighborhood Level: The effect of neighborhood context on respondents’ behavioral intention to implement GI if provided for free (17 block groups with 136 Individual Surveys) Overall GI (All), rain barrels (RB), trees (T), rain garden (RG), porous driveway/sidewalks (P) and curbside extensions (CE). Participation likelihood for free GI AllRBTRGPCE Neighborhood Canopy Cover (%) ++ Neighborhood Imp. Surface (%) The percent of houses occupied by owner + The percent of African Americans The percent of females + Average age of neighbors +++ The percent below poverty level

14 RESULTS at the Neighborhood Level: The effect of neighborhood context on respondents’ behavioral intention to implement GI if they were to realize savings on their water bill (17 block groups with 136 Individual Surveys) Overall GI (All), rain barrels (RB), trees (T), rain garden (RG), porous driveway/sidewalks (P) and curbside extensions (CE). Participation likelihood for savings AllRBTRGPCE Canopy percentage Impervious percentage The percent of houses occupied by owner The percent of African Americans --- The percent of female Age ++ The percent of below poverty

15 Spatial Prediction Model estimation of participation likelihood in overall GI implementation, if free, in Syracuse, NY (10-25: low to high)

16 Spatial Prediction Model estimation of participation likelihood in overall GI implementation, if savings on water bills were to occur, in Syracuse, NY (10-25: low to high)

17 Conclusion At the individual level, the likelihood of participation is significantly related to knowledge and perceived benefit of GI. At the neighborhood scale, the variation in willingness to implement any GI, with the exception of curbside extension, can be explained primarily by a higher existing tree canopy cover, a lower percent of African American population, and an older population. The findings can provide valuable information to government officials working to find cheaper, publically acceptable, and environmentally friendly ways to control storm water management.

18 Acknowledge I would like to thank Myrna Hall and Stephen V. Stehman from SUNY ESF for their guidance and expertise during my research in spite of their tight schedule.

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