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Identifying Vulnerable Schools in High Risk Environmental Justice Communities

Identifying Vulnerable Schools in High Risk Environmental Justice Communities. Adam Dorr. Midterm Goals. Use pollution data to identify high-risk areas Use demographic data to identify vulnerable environmental justice communities Identify most vulnerable schools for priority intervention

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Identifying Vulnerable Schools in High Risk Environmental Justice Communities

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  1. Identifying Vulnerable Schools in High Risk Environmental Justice Communities Adam Dorr

  2. Midterm Goals • Use pollution data to identify high-risk areas • Use demographic data to identify vulnerable environmental justice communities • Identify most vulnerable schools for priority intervention • Geographic Area: Los Angeles County (by census tract)

  3. Sources and Methods • EPA National Air Toxics Assessment (NATA) 2002 data: • Cancer Risk • Neurological Risk • Respiratory Risk • Standardized Scales (0-1) • Composite Index (0-1)

  4. Sources and Methods • American Community Survey 5-Year Estimates 2005-2009 (US Census Bureau via Social Explorer) • Based on Massachusetts State Law and Atlanta City Code definitions of Environmental Justice Community: • 65% or more below median income (assumed: county) • 25% or more minority (assumed: ALL not “white alone”) • 25% or more foreign born • 25% or more under age 10 • 25% or more age 65 or older • Community Vulnerability Scale (0-5)

  5. Sources and Methods • ESRI/Microsoft: • California state boundary map • Los Angeles County census tracts boundary map • Shaded relief basemap • Major highways basemap • UCLA Mapshare: • Airports • Water bodies

  6. Final Project Goals • Use pollution data to identify high-risk areas • Use demographic data to identify vulnerable environmental justice communities • Identify most vulnerable schools for priority intervention • Buffer zones around EPA sites of concern • Develop a predictive model: • Risk  Environmental Justice Community • Test model in other cities

  7. GIS Skills Used • Inset map • Point graduated symbol (schools) • Aggregating attribute fields (scales and composite scores) • Creating Indices (EJ-Risk Combined Index) • Geoprocessing (clipping, multiple layers) • Buffering and dissolve (EPA sites of concern 0.5 mile buffer) • Attribute sub-sets selections (selected Los Angeles County EPA sites of concern from nationwide dataset) • Geocoding (EPA sites addresses)

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