Transcript LESSON 2: CHARACTERISTICS AND QUANTITY OF MSW

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
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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?
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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:
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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 15-59 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: 600-900 lb/yd3 as delivered
Function of location, season, storage
time, equipment used, processing
(compaction, shredding, etc.)
Soil Phase Diagram
Vsample=Vsolids+Vliquid+Vgas
Vvoids = Vliquid + Vgas
Wsample=Wsolids+Wliquid
(Wgas~0.00)
V=volume, W=weight or mass
Moisture content (MC)
Weight or volume based
Weight: wt. of water/sample wt.
• MCwet= Wwater/(Wwater+Wsolids)
• MCdry= Wwater/Wsolids
Volume: Vwater/Vsample
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 105o C)
Volatile Combustible Matter (VCM)
(temp increased to 950o C, closed
crucible)
Fixed Carbon (residue from VCM)
Ash (temp = 950o 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
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Last updated July 17, 2015 by Dr. Reinhart