Multi-criteria analysis for the identification of waste disposal areas Presentation by Eri Kudo and Olivier Mills

Identification of waste disposal areas For centuries unconcerned about waste Industrial revolution  Exponential increase in volume Today, one of the most crucial problems faced by urban centres is WHERE to dispose of it

Case study : Brazil - Disposing of marble and granite Marble and Granite Industry  large volumes of waste (up to 25% of rock in form of sludge) Discarded by tanks in ponds or rivers Silting (surface water), increase hardness, increased Aluminium (groundwater)

Waste disposal area identification Multi-criteria analysis : Method 1)Define criteria (factors and and restrictions)

Criteria Factors (degree of aptness) Restrictions (apt, inapt) Environmental Hydrography, flaws, pedology, geology, geomorphology Hydrography, geological, +200m buffer Operational Roads systemDeclinivity (allowed interval from 1% to 30%) Socio-economic Urban zone, districts, farms Urban zone, districts, farms, + 500m buffer Waste disposal area identification - Method 1) Define criteria, factors and restrictions

Waste disposal area identification Urban perimeter Hillshading Hydrography Hillshading, hydrography and urban perimeter

Waste disposal area identification Urban perimeter Farm District Urban perimeter, Farms, district and road system Road system

Waste disposal area identification Multi-criteria analysis : Method 1)Define criteria (restrictions and factors) 2) Standardize (normalize to same scale)

Waste disposal area identification Geologic Map

Waste disposal area identification Pedologic Map

Waste disposal area identification Multi-criteria analysis : Method 1)Define criteria (restrictions and factors) 2) Standardize (normalize to same scale) 3) Weight factors and criteria

Waste disposal area identification - Method 3) Factor Weighting Geology Road system

Waste disposal area identification - Method 3) Criteria weighting

Waste disposal area identification Multi-criteria analysis : Method 1)Define criteria (restrictions and factors) 2) Standardize (normalize to same scale) 3) Weight factors and criteria 4) Aggregate (put together)

Waste disposal area identification – Aggregation and output

Waste disposal area identification – Conclusion ADVANTAGES - Low cost (GIS) - Model multiple scenarios (high risk, low risk) - Graphical representation of options - Dynamic (GIS data) DISADVANTAGES - Careful choice of criteria and weighting functions - Coherence with reality - Doesn’t consider whole life of disposal site (time factor) GIS + Multi-criteria analysis