The Tenacious Mappers Group Members: ROLANDO, THUY, AND CHARITY GIS 469 Workshop A King County Environment Justice Study: Demographic Analysis of Multi-family Housing in Proximity to Air and Noise Pollution from Major Arterial Roadways and Freeways

Problem Statement: Our Goals and Objectives Project Goal/Research Question Is there a strong correlation between minority lower-income residents of multi- family status and higher rates of exposure to air and noise pollution along high traffic arterial roadways?

Objectives: Satisfying the “need-to-know” question Which blockgroups in King County are more vulnerable to traffic pollution? Do Demographic Analysis to find out what segment of the population lives here.

King County’s Objectives: The goals of this project is to enhance the understanding of environmental equity considerations in housing conditions that King County has some control or influence over. The results of this analysis will help inform improvements to King County land use codes, service delivery, and perhaps, regional leadership. (Valenzuela, 2009).

Project Methods : Need-to-Know questions Questions:Software functions Needed What census blockgroups are more vulnerable to traffic pollution? Import data, select by attribute/location, Spatial Join, Raster-Vector conversions, Reclass, Weighted Overlay What is the racial makeup of those blocks, compared at different scalesImport shapefiles, import database fields, use field calculator, map symbology by quantity What are the poverty levels of those blocks; compared at different scales What is the primary language spoken in these blocks; compared at different scales

Resources Used for our Project King County’s Datasets  Road network data  Traffic data  Apartment points in King County WAGDA Data  US Census data on: Race Federal Poverty Level Primary language

Data Analysis: Blockgroup Vulnerability

Analysis of Data: Population Density

Analysis of Data: Traffic Counts

Analysis of Data: Apartment Units Count

Analysis of Data: Calculating Vulnerability Weighted Overlay Setup Raster VariableWeight Population Density33 Arterial Traffic18 Freeway Traffic15 Apartments within 25 meters16 Apartments within 50 meters10 Apartments within 75 meters8

Analysis Results: Blockgroup Vulnerability

Vulnerability01234 # of Blockgroups

VulnerabilityMoreLess # of Blockgroups226766

Data Analysis: Blockgroup Demographics

Analysis of Data: Demographic Calculation Join demographic table to King County Group the attribute into categories  English Only and Everything else  White Only and Everything else  Under 50%, 50% - 74% and 75% - 99% federal poverty level

Analysis Results: Blockgroup Demographics

Data Analysis Results Language English OnlyOther King County74.34%16.44% Vulnerable Area66.33%19.51% Block Group With Apt71.39%18.86% Block Group Outside of Vulnerable Area73.12%18.64% Language: Population Difference EnglishOther Vulnerable Area15%20% BG with Apt63%76% Outside Vulnerable48%56% Poverty Under 50% Level 50% to 74% Level 75% to 99% Level King County3.92%2.01%2.27% Vulnerable Area6.04%3.03%3.27% Block Group With Apt4.99%2.65%2.94% Block Group Outside of Vulnerable Area4.63%2.52%2.83% Poverty: Population Difference Under 50% % % Vulnerable Area26%25%24% BG with Apts84%87%86% Outside Vulnerable58%62%61% Race White OnlyOther King County73.33%26.67% Vulnerable Area67.59%32.41% Block Group With Apt69.03%30.97% Block Group Outside of Vulnerable Area69.52%30.48% Race: Population Difference White onlyOther Vulnerable Area16%20% BG with Apts62%77% Outside Vulnerable47%56%

Language Distribution

Poverty Distribution

Race Distribution

Conclusion Minorities are more likely to be affected by traffic pollution Poverty: there isn’t a specific pattern

Recommendations: Suggestions for Further Study Revisiting the reclassification step during vulnerability analysis for more meaningful rankings Laws or policies that affect the development of apartment Similar analysis at city level or other counties