Location Analysis for Outdoor Recycling Bin Placement Prepared for:

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Location Analysis for Outdoor Recycling Bin Placement Prepared for:

Municipal Solid Waste (MSW) and Recycling in the U.S. 26% of MSW recycled in 2011 MSW taken to landfills decreased from 89% to 54% in the last 30 years 45% of MSW that is recyclable is not recycled

Recycling Reduces greenhouse gas emissions Reduces other pollutants Reduces the need for landfills Conserves resources Produces economic benefit

Recycling and Texas State University Emerging Research University over 35,000 students in outdoor recycling bins on campus 8 purchased that have not been placed

Objectives Short Term: Aid Texas State University Waste and Management by identifying potential locations for outdoor recycling bins to maximize the collection of recyclable materials. Assist with determining traffic flow between campus buildings during different time periods of the day. Long Term: Texas State University Waste and Management will be able to maximize collection of recyclable materials, gain more outdoor recycling bins, and use and maintain a GIS that can assist with the growth and expansion of the recycling program.

Scope Final Recommendations by 2 May 2014

Literature Review Study One: Asturias, Spain, by B. Adenso-Días and P.L. Gonzáles-Torre (2005) Objective: Determine if walking distance to bins affects recycling habits. Process: Survey sample and Proximity Results: The citizens that have recycling bins in close proximity are more willing to dispose of recyclable materials more frequently and separate more often.

Literature Review Study Two: Australia, report by the Department of Environment and Conservation (2005) Objective: Determine where and how to place outdoor recycle bins. Process: Traffic Flow and Proximity Results: People will travel up to 12 meters (approximately 40 feet) to dispose of materials. Recycling bins and garbage bins should be clustered in areas of high traffic flow to negate contamination between bins.

Literature Review Study Three: Urban Modeling, by M. Batty (2009) Objective: Determine which factors cause the highest frequency of traffic flow between buildings and then determine their respective weight. Process: Spatial Interaction, Urban Modeling, and Urban Dynamics Results: Distribution of activity occurs according to urban gravity. Based on this study we have decided to model Texas State University as a small city.

Data Source Campus Base Map – sidewalks, buildings, current outdoor recycling bins Bob Stafford, Facilities Planning, Design, and Construction Department at Texas State University Foot Traffic NetworkTo be created by Dynamic Geo Solutions Campus Building PopulationsGeography Department W Drive Outdoor Recycle Containers Hardcopy Map – locations of new bins Mario Garza, Recycling and Waste Management Department at Texas State University GPS Data for New Outdoor Recycling Bins To be created by Dynamic Geo Solutions Software ArcMap Network Analyst Extension

Methodology 1.Create line map of walking routes 2.Plot points of origin and destination 3.Analyze network and identify frequent routes using campus population data 4.Assign weights to routes most frequently used 5.Identify areas of interest by relating weighted routes to location of current bins 6.Verify results through field work

Budget Data Collection (128 hours) $24.50/hour $3, Pre-Processing Data and Manipulation (128 hours) $24.50/hour $3, Data Analysis and Interpretation (172 hours) $28.00/hour $4, System Management (98 hours) $28.00/hour $2, Website Development (24 hours) $24.00/hour $ Software Licensing$ Total $15,354.50

Timeline Wk 1 Wk 2 Wk 3 Wk 4 Wk 5 Wk 6 Wk 7 Wk 8 Wk 9 Wk 10 Wk 11 Wk 12 Wk 13 Wk 14 Jan 27 Feb 3 Feb 10 Feb 17 Feb 24 Mar 3 Mar 10 Mar 17 Mar 24 Mar 31 Apr 7 Apr 14 Apr 21 Apr 28 Data Collection Pre-Processing Data Analysis Interpretation

Final Deliverables Final Report Professional Poster – Map of foot traffic and recycling bins – Map of potential areas for future bins Website CD containing: – Metadata – Final Report – Poster – PowerPoint Presentation Map of high foot traffic routes Map of high to low priority areas Map of most suitable locations for future bins

Conclusion Statistics Network Analysis Field Research