LESSON 2: CHARACTERISTICS AND QUANTITY OF MSW

Goals  Determine why quantification is important  Understand the methodology used to quantify MSW  Become aware of differences among global production rates  Understand factors affecting waste generation rates  Become familiar with per capita generation rates

Goals, Cont’d  Explain why it is important to characterize MSW.  Become familiar with MSW descriptors.  Understand the methods used to characterize MSW  Describe the physical, chemical, and biological properties associated with MSW.  Perform calculations using waste composition and properties.

RCRA Subtitle D Wastes  MSW  Household hazardous wastes  Municipal sludge  Non-hazardous industrial wastes  Combustion ash  SQG hazardous waste  Construction and Demolition debris  Agricultural wastes  Oil and gas wastes  Mining wastes

MSW - RCRA Definition  Durable goods  Non-durable goods  Containers/Packaging  Food wastes  Yard wastes  Miscellaneous inorganics

MSW - Textbook Definition  Mixed household waste  recyclables  household hazardous waste  commercial waste  yard waste  litter  bulky items  construction & demolitions waste

What are the sources of RCRA Subtitle-D Wastes?  Residential  Commercial  Institutional  Industrial  Agricultural  Treatment Plants  Open Areas (streets, parks, etc.)

What is the Nature of Municipal Solid Wastes?  Organic  Inorganic  Putrescible  Combustible  Recyclable  Hazardous  Infectious

Importance of Generation Rates  Compliance with Federal/state diversion requirements  Equipment selection,  Collection and management decisions  Facilities design  Methodology –Materials Flow –Load Count

Factors Affecting Generation Rates  Source reduction/recycling  Geographic location  Season  Home food waste grinders  Collection Frequency  GNP trend, Per capita income  Legislation  Public attitudes  Size of households  Population density  Pay-As-You Throw Programs  Population increase

EU Waste Generation Study  Studied correlation between waste generation and: –Population –Population density –Age distribution –Employment –GDP –Infant mortality –Life expectancy –Average household size –Unemployment –Tourism  Waste generation has grown steadily in Europe for over 20 years

Strongest Correlation  Generation increases with: –Population –Age distribution (fraction in 15-39, employment) –The rate of increase in GDP (for example Poland, Spain and Slovakia  Generation decreases with average household size  Low income areas had low amounts of plastics, paper and cardboard, but not organics

Conclusions  Continued increase in MSW generation rate is expected –Because of economic grown –Improving health –Increasing urbanization –Offset by declining percent of year olds

Composition Studies  Materials Flow  Manual Sorting

Manual Sorting Methodology  Study Planning  Sample Plan  Sampling Procedure  Data Interpretation

Sample Plan  Load Selection  Number of Samples

Sampling Procedure  Vehicle Unloading  Sample Selection and Retrieval  Container Preparation  Sample Placement  Sorting

Waste contents are unloaded for sorting

Appropriate mass of material is selected randomly

Each load is separated manually by component example - Wood, concrete, plastic, metal, etc.

Components are separated

Each component is weighed and weights recorded

Data Interpretation  Weighted Average based on Generator Source Composition/Distribution  Contamination Adjustment

US MSW Composition

Terminology Generated Waste = Disposed (Collected) Waste + Diverted Waste

Specific Weight  Values: lb/yd 3 as delivered  Function of location, season, storage time, equipment used, processing (compaction, shredding, etc.)

Soil Phase Diagram V sample =V solids +V liquid +V gas V voids = V liquid + V gas W sample =W solids +W liquid (W gas ~0.00) V=volume, W=weight or mass

Moisture content (MC)  Weight or volume based  Weight: wt. of water/sample wt. MC wet = W water /(W water +W solids ) MC dry = W water /W solids  Volume: V water /V sample

Chemical Composition  Used primarily for combustion and waste to energy (WTE) calculations but can also be used to estimate biological and chemical behaviors  Waste consists of combustible (i.e. paper) and non-combustible materials (i.e. glass)

Proximate Analysis  Loss of moisture (temp held at 105 o C)  Volatile Combustible Matter (VCM) (temp increased to 950 o C, closed crucible)  Fixed Carbon (residue from VCM)  Ash (temp = 950 o C, open crucible)

Ultimate Analysis  Molecular composition (C, H, N, O, P, etc.)  Table in notes

Typical Data on the Ultimate Analysis - Example  Food Wastes –Carbon: 48% –Hydrogen: 6.5% –Oxygen: 37.6% –Nitrogen: 2.6% –Sulfur: 0.4% –Ash: 5%

Energy Content  Models are derived from physical composition and from ultimate analysis  Determined through lab calculations using calorimeters  Individual waste component energy contents

Empirical Equations  Modified Dulong formula (wet basis): BTU/lb = 145C +610(H2-02/8)+40S + 10N  Model based on proximate analysis Kcal/kg = 45B - 6W B = Combustible volatile matter in MSW (%) W = Water, percent weight on dry basis

Return to Home Page Last updated May 23, 2015 by Dr. Reinhart