1. Siting of Obnoxious Facilities in the City of Austin Jayanthi Rajamani Fall 2002 University of Texas at Austin

2. Project Objectives Identify a decision problem where a GIS- based decision support system may be useful Use GIS operations to transform raw data into meaningful information Design and implement a multi-criterion decision analysis scheme

3. Objectives (contd.)

4. Decision Problem Locating/siting an incinerator facility A municipal waste incinerator must be built in the city of Austin, composed of several areas. Objectives and Constraints: Dimensions Location subject to minimum operating cost Minimum nuisance due to transportation and air pollution

5. Why GIS? Locate several possible sites Study the population distribution pattern Analyze noise nuisance by informing us of proximity of roads with residential areas

6. Background Municipal Solid waste is non-toxic waste generated by households, commercial establishments, etc. - food and yard wastes - durable and nondurable - packaging material Waste Municipal Hazardous Medical

7. Maps! Maps! Maps! Austin ZipcodesLand Use ++ Public Parcels + Housing Industrial + + Parks and Facilities

8. Street Network

9. ArcGIS Steps

10. Buffer Analysis

11. Buffer Analysis (contd.)

12. The Optimization Problem C ij = unit transportation cost from zip code i to incinerator site j x ij = tonnage of waste transported from zip code i to site j F j = investment cost for site j y j = {0 if site j is not selected 1 if site j is selected} v i = waste generated by zip code i γ j = plant capacity at site j e j = population exposed to transportation nuisance at site j E = global nuisance indicator

13. Simplifying the Problem

14. The Transportation Matrix The Cost matrix ZIPCODEF7349F9692F28500F35764 7861054.5981.5330.0715.18 786132.5928.7518.7129.20 7861761.6376.8825.4223.66 7865224.3742.4220.7230.21 7870136.6953.046.2819.65 7870239.8755.254.6116.65 7870333.6349.758.7223.84 7870435.8957.0811.4517.31 7870537.7350.415.1621.95 7871718.0032.0220.7730.60 7871951.2272.5121.056.19 7872143.6755.563.9517.51 7872240.5951.512.3419.73 7872343.8050.883.1121.63 7872430.1357.516.3027.03 7872557.4268.6021.1819.94 7872631.7841.9519.4432.67 7872739.4136.3921.7939.39 7872823.2641.2013.5526.03 7872935.5532.5427.1444.74 7873017.0521.2222.2839.89 7873132.6342.0212.3129.92 7873216.2732.0632.8850.49 7873320.5028.9113.6836.20 787344.7539.0339.8551.14 7873523.0830.8013.8728.80 7873624.0232.7424.8954.84 7873729.6334.9037.5940.71 7873815.7627.1320.8948.21 7873932.0737.1229.8631.06 7874142.2159.999.3812.75 7874247.7762.0710.6114.38 7874447.6170.2418.786.57 7874533.7562.5117.9617.73 7874628.6152.1115.1627.59 7874747.5975.2226.4412.16 7874838.7145.6913.7121.17 7874928.6112.7223.0924.43 7875018.5130.5216.9627.22 7875139.9848.994.9422.55 7875224.9245.997.3324.95 7875343.5943.8814.2931.92 7875448.4849.9711.7128.59 7875636.8045.967.6925.30 7875736.4042.2410.9128.52 7875839.2939.8215.6733.27 7875920.6934.9619.8337.44

15. Optimizing in Solver

16. Results Nuisance and Cost are conflicting criteria We have computed trade-offs between the two criteria to find efficient compromise solutions

17. Results (contd.)  As the Nuisance Index reduces, the cost of installation and transportation of waste rises  As the Nuisance Index is decreased, the number of plants to be installed increases to better distribute the traffic in sensitive areas

18. Limitations Neglected criteria Proximity to airports, floodplains, active geologic faults Depth to groundwater Possible impacts on wildlife Political and Social Acceptance

19. Future Work Site Selection Economy Environment Social Acceptance Investment Transportation NOX Exposure Transportation Nuisance Neighborhood