EPA 600/R-14/375 | September 2014 | www.epa.gov/ord
United States
Environmental Protection
Agency
Multimedia Environmental Assessment of
Existing Materials Management Approaches
for Communities
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Office of Research and Development
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EPA/600/R-14/375
September 2014
Multimedia Environmental Assessment of
Existing Materials Management
Approaches for Communities
US Environmental Protection Agency
Office of Research and Development
Land Remediation and Pollution Control Division
National Risk Management Research Laboratory
Cincinnati, OH, 45268
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EPA/600/R-14/375
September 2014
Foreword
The US Environmental Protection Agency (US EPA) is charged by Congress with
protecting the Nation's land, air, and water resources. Under a mandate of national
environmental laws, the Agency strives to formulate and implement actions leading
to a compatible balance between human activities and the ability of natural systems
to support and nurture life. To meet this mandate, US EPA's research program is
providing data and technical support for solving environmental problems today and
building a science knowledge base necessary to manage our ecological resources
wisely, understand how pollutants affect our health, and prevent or reduce
environmental risks in the future.
The National Risk Management Research Laboratory (NRMRL) is the Agency's
center for investigation of technological and management approaches for preventing
and reducing risks from pollution that threaten human health and the environment.
The focus of the Laboratory's research program is on methods and their cost-
effectiveness for prevention and control of pollution to air, land, water, and
subsurface resources; protection of water quality in public water systems;
remediation of contaminated sites, sediments and ground water; prevention and
control of indoor air pollution; and restoration of ecosystems. NRMRL collaborates
with both public and private sector partners to foster technologies that reduce the cost
of compliance and to anticipate emerging problems. NRMRL's research provides
solutions to environmental problems by: developing and promoting technologies that
protect and improve the environment; advancing scientific and engineering
information to support regulatory and policy decisions; and providing the technical
support and information transfer to ensure implementation of environmental
regulations and strategies at the national, state, and community levels.
This publication has been produced as part of the Laboratory's strategic long-term
research plan. It is published and made available by US EPA's Office of Research
and Development to assist the user community and to link researchers with their
clients.
Cynthia Sonich-Mullin, Director
National Risk Management Research Laboratory
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EPA/600/R-14/375
September 2014
Executive Summary
The Sustainable and Healthy Communities Program has a mission to develop
data and tools that enable community leaders to integrate environmental, societal,
and economic factors into their decision-making processes and thus foster
community sustainability. This report examines one key area of community
sustainability interest, the management of materials from the construction and
demolition of buildings, roads, and others structures at their end of life (EOL).
Life-cycle assessment (LCA) is an approach frequently used to examine the
environmental implications of the EOL management of materials, and while
much LCA research has focused on materials from household and commercial
community activities (e.g., municipal solid waste), very little effort has focused
on construction and demolition debris (CDD). Even though CDD constitutes a
substantial volume of material, the role that these materials play with respect to
human and ecological health has not been recognized in the same manner as other
wastes, and thus they have been less studied.
A meaningful LCA requires a strong database of information (e.g., material
makeup and magnitude, energy consumption, environmental emissions) from
throughout a material's life cycle. Compilations of such data - a life-cycle
inventory (LCI) - provide the backbone for conducting an LCA to examine
different materials management strategies. The primary objective of the work
presented here was to extensively assess the body of knowledge regarding CDD
life-cycle data and to compile US-specific LCI for distinct CDD material
categories from publicly available sources. These LCI datasets are intended to
complement the existing US EPA LCI database, which includes LCI for a variety
of processes and services such as natural resource extraction, manufacturing,
energy production, and transportation. An additional objective of this research
was to identify data gaps pertaining to CDD LCI and thus identify needed areas
of research and information gathering.
LCI were developed for the EOL management perspective of the following CDD
materials: asphalt pavement, asphalt shingles, gypsum drywall, CDD wood, land
clearing debris (LCD), Portland cement concrete, recovered screened material,
and clay bricks. Current EOL management practices were identified based on
published industry, government, and academic literature. LCI for each of the
CDD materials and several of the associated EOL practices were developed based
on input data used by US-specific waste LCA models (e.g., WARM, MSW-DST)
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EPA/600/R-14/375
September 2014
and information included in peer-reviewed and publically available
governmental and industry data. For some EOL processes, insufficient US-
specific data were available to develop the needed LCI category. For CDD
materials recycled in a closed-loop process (e.g., asphalt pavement, gypsum
dry wall), attempts were made to compile upstream LCI (i.e., those pertaining to
product manufacturing), if available.
Although the CDD LCI in this report represent the most comprehensive datasets
currently available on this material stream, they are limited because of the relative
unavailability of US-specific data; again, CDD has not been examined to the
same degree as other EOL materials. Some of the major limitations, and thus
identified data gaps, include the following:
i. Liquids emissions associated with the disposal of CDD materials are
estimated based on standardized leaching test data, which represent
leaching at a liquid-to-solid (L:S) ratio of 20 to 1. These estimates are
considered incomplete with respect to the number of constituents and the
magnitude of the total emission. Similarly, gaseous emissions are based on
methane generation potential data reported for various MSW constituents.
These data were used as a proxy to estimate methane and carbon dioxide
(biogenic) emission for several CDD materials due to lack of data for CDD
materials (e.g., data for branches were used to represent gaseous emission
for wood and LCD).
ii. The processing energy requirements for most of the CDD materials are
primarily based on equipment manufacturers' specifications compiled by
Cochran (2006) due to lack of data from operating processing facilities.
The processing LCI developed do not include liquids or particulate matter
emissions from handling of CDD materials at processing facilities as these
data are not available.
iii. The EOL LCI developed, in general, do not include capital equipment
burdens (i.e., emissions associated with the production of infrastructure
materials, equipment manufacturing, and energy associated with facility
construction) for CDD material management processes; these data were
not available in the publicly available literature.
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EPA/600/R-14/375
September 2014
iv. The transport distances between management processes for discarded and
processed CDD materials were set at a fixed assumed distance; these data
were not available in the publicly available literature.
To complement that data gap analysis, several recommendations for future data
gathering and research opportunities are identified and presented in the report.
VI
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Acknowledgements and Notice
The US Environmental Protection Agency (US EPA) through the Office of Research
and Development funded and managed the research described here under contract
order number: EP-C-10-060 to Computer Science Corporation, Inc. The research has
been subject to the Agency's review and has been approved for publication as a US
EPA document. Use of the methods or data presented here does not constitute
endorsement or recommendation for use. Mention of trade names or commercial
products does not constitute endorsement or recommendation.
Vll
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Table of Contents
Table of Contents viii
List of Figures x
List of Tables xi
List of Abbreviations, Acronyms, and Initialisms xv
1 Introduction 1-1
1,1 Background 1-1
1,2 Scope of Work and Objectives 1-2
1.2.1 Material Types 1-2
1,3 Report Organization 1-4
1,4 References 1-4
2 Materials and Management Approaches 2-1
2,1 Boundary Considered: EOL Phase 2-1
2.2 Geographic Area 2-1
2.3 Life-Cycle Inventory 2-1
2,4 Organization of Proposed LCI Datasets 2-3
2,5 Common Technosphere Inputs 2-3
2.5.1 Transportation 2-3
2.5.2 Electricity 2-5
2.5.3 Fuel Combustion in Equipment 2-5
2.5.4 Other Fuel Combustion Applications 2-5
2.5.5 O&M Consumables 2-5
2.5.6 Aggregates and Soil 2-6
2.5.7 Mixed CDD Processing 2-13
2.5.8 Landfilling 2-16
2.5.9 Landfill Leachate Emissions 2-21
2.5.10 Landfill Gas Emissions 2-29
2.6 Landfill Gas and Leachate Collection and Treatment 2-42
2.6.1 Data Gap Analysis of Landfill Gas and Landfill Leachate Collection and
Treatment 2-43
2.7 References 2-44
3 Asphalt Pavement 3-1
3,1 Introduction 3-1
3,2 Management at EOL 3-1
3,3 LCI Sources 3-3
3,4 LCI Related to HMA Pavement Production 3-4
3.4.1 Raw Materials Extraction 3-4
3.4.2 Transport 3-6
3.4.3 HMA Plants 3-7
3.5 LCI Related to Disposal 3-9
3,6 LCI Related to Recycling 3-11
3.6.1 RAP Processing 3-11
3.6.2 RAP Use in HMA 3-12
3.6.3 RAP Use as Aggregate 3-13
3,7 Data Gap Analysis and Opportunities for Additional LCI Data 3-14
3,8 References 3-16
Vlll
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Asphalt Shingles
4.1 Introduction
4.2 EOL Management
4.3 LCI Sources
4 4 Asphalt Shingles Manufacturing
4.5 LCI Related to Disposal
4.6 LCI Related to Recycling
461 Shingle Processing
4.6.2 HMA/WMA Production with Asphalt Shingles
4.7 Data Gaps and Future Opportunities
4.8 References
Gypsum Drywall
5 . 1 Introduction
5.2 EOL Management
5 3 LCI Sources
5.4 LCI Related to Material Manufacture
541 Raw Materials Extraction
542 Synthetic Gypsum Production
5.4.3 Gypsum Paper Manufacturing
544 Gypsum Drywall Manufacturing
5.5 LCI Related to Disposal
5.6 LCI Related to Recycling
5 . 7 Data Gap analysis and Opportunities for Additional LCI Data
5.8 References
Wood
6. 1 Introduction
6.2 EOL Management
6 3 LCI Sources
6,4 LCI Related to Wood Products Manufacturing
6.5 LCI Related to Disposal
6.6 LCI Related to Recycling
6.7 LCI Related to Combustion
6.7.1 Wood Ash
6,8 Data Gap analysis and Opportunities for Additional LCI Data
6.9 References
Land Clearing Debris
7. 1 Introduction
7 2 EOL Management
7.3 LCI Sources
7.4 LCI Related to On-site Burning
7 5 LCI Related to Landfill Disposal
7.6 LCI Related to Recycling
7 6 1 LCD Used as Mulch
7.6.2 LCD Used as Compost
7.6.3 LCD Combusted as Boiler Fuel
7.7 Data Gap analysis and Opportunities for Additional LCI Data
7,8 References
Portland Cement Concrete
8.1 Introduction
4-1
4-1
4-2
4-3
4-4
4-5
4-7
4-7
4-9
4-10
4-13
5-1
5-1
5-1
5-3
5-4
5-4
5-6
5-7
5-8
5-12
5-15
5-17
5-18
6-1
6-1
6-2
6-4
6-5
6-8
6-17
6-18
6-19
6-23
6-25
7-1
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7-2
7-3
7-7
7-8
7-8
7-10
7-11
7-12
7-14
8-1
8-1
IX
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8.2 EOL Management 8-1
8.3 LCI Sources 8-3
8.4 LCI Related to Removal/Demolition 8-4
8,5 LCI Related to Disposal 8-5
8.6 LCI Related to Recycling 8-7
8.6.1 Concrete Processing 8-7
8.6.2 RCA Use as Aggregate 8-9
8.6.3 Demolished Concrete Use as Soil Fill Replacement 8-10
8.7 Data Gap Analysis and Opportunities for Additional LCI Data 8-12
8.8 References 8-13
9 Recovered Screened Material 9-1
9,1 Introduction 9-1
9.2 EOL Management 9-2
9,3 LCI Sources 9-2
9,4 LCI Related to Production 9-3
9.5 LCI Related to Disposal 9-3
9.5.1 Leachable Emissions from RSM 9-4
9.5.2 Landfill Gas Emissions for RSM 9-4
9.6 LCI Related to Recycling 9-8
9.7 Data Gap Analysis and Opportunities for Additional LCI Data 9-9
9,8 References 9-10
10 Clay Bricks 10-1
10,1 Introduction 10-1
10.2 EOL Management 10-1
10,3 LCI Sources 10-2
10,4 LCI Related to Disposal 10-2
10.5 LCI Related to Recycling 10-3
10.5.1 Clay Brick Demolition 10-3
10.5.2 Clay Brick Sorting 10-3
10.5.3 Clay Brick Use as Aggregate 10-3
10,6 Data Gap Analysis and Opportunities for Additional LCI Data 10-4
10.7 References 10-4
11 Summary and Future Research Needs 11-1
11,1 Summary 11-1
11.2 Data Gaps and Future Research Opportunity 11-3
11,3 References 11-6
List of Figures
Figure 1-1. Composition of CDD (a) Landfilled, and (b) Recycled by Solid Waste Management
Facilities in the US 1-3
Figure 2-1. Total Fuel Energy Consumption per Kilogram Production of Aggregate and Soil
(developed from USCB 2001, Bolen 1997, and CAT 2006) 2-12
Figure 2-2. Weighted Average Mass Fraction of Materials Recovered or Discharged from Five
Florida CDD Processing Facilities (developed from Calhoun (2012)) 2-15
Figure 3-1. Materials Flow for HMA Production and EOL Phase Management 3-1
Figure 3-2. Distribution of RAP Uses in 2011 3-2
Figure 4-1. Asphalt Shingle EOL Management Processes 4-1
Figure 5-1. Gypsum Drywall Process Flow Diagram 5-1
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Figure 5-2. Sources of California-Discarded Gypsum Drywall (CIWMB 2007) 5-2
Figure 6-1. Life-Cycle Material Flows and Processes for Wood Product Manufacturing and EOL
Management 6-2
Figure 6-2. Distribution of Wood Products Manufactured in the US in 2011 6-6
Figure 7-1. Material Flows for LCD and EOL Phase Management 7-1
Figure 8-1. Materials Flow for Concrete EOL Phase Management 8-1
Figure 8-2. Distribution of Recycled Concrete Uses in the US (Deal 1997) 8-2
Figure 9-1. Material Flows for RSM Production and EOL Management 9-1
Figure 9-2. Composition of RSM (Townsend et al. 1998) 9-2
Figure 10-1. Material Flows for Production through EOL Management of Clay Bricks 10-1
List of Tables
Table 1-1. Estimated CDD Materials Generation Rate in 2011 1-4
Table 2-1. Basic Flow Categories 2-2
Table 2-2. Terminology for EOL CDD Material Management 2-2
Table 2-3. Estimated Transport Distances for Aggregate Materials (developed from USCB 2010) 2-5
Table 2-4. Fuel Consumption per Kilogram Mined and Quarried Aggregate (USCB 2001 and
Bolenl997) 2-8
Table 2-5. Uncontrolled Particulate Matter Emissions from Crushed Stone and Pulverized Mineral
Processing (US EPA 2004) 2-11
Table 2-6. Energy Consumption for Processing Demolished PCC and RAP 2-13
Table 2-7. Overview of Aggregate Production LCI Data Available 2-13
Table 2-8. Proposed LCI Dataset: Mixed CDD Processing Facility 2-15
Table 2-9. Proposed LCI Dataset: MSW Landfill Construction, for CDD Materials 2-17
Table 2-10. Proposed LCI Dataset: CDD Landfill Operations 2-19
Table 2-11. Proposed LCI Dataset: MSW Landfill Operations 2-19
Table 2-12. Proposed LCI Dataset: MSW Landfill Closure and Post-Closure, for CDD Materials 2-21
Table 2-13. Leachate-related Inflow and Outflows in LCA Models 2-29
Table 2-14. Summary of Landfill Gas and GCCS LCI Information Included in LCA Models 2-39
Table 2-15. Landfill Gas Production Properties for Different CDD Materials 2-40
Table 2-16. Methane and Carbon Dioxide Emissions for CDD and MSW Landfill Disposal of CDD
Materials 2-42
Table 3-1. Asphalt Pavement EOL Management Process Descriptions 3-2
Table 3-2. List of Sources Reviewed for LCI Data 3-3
Table 3-3. Transport Distances of Different Pavement Materials 3-7
Table 3 -4. Proposed LCI Dataset: Asphalt Pavement Production, Average Energy Mix 3-9
Table 3-5. Proposed LCI Dataset: Asphalt Pavement, at Unlined CDD Landfill 3-11
Table 3-6 Proposed LCI Dataset: Reclaimed Asphalt Pavement, at Processing Plant 3-12
Table 3-7. Proposed LCI Dataset: Reclaimed Asphalt Pavement, Use as Fill 3-13
Table 3-8. Overview of LCI Data Available 3-16
Table 4-1. LCI Needed for LCA of Asphalt Shingles EOL Management 4-2
Table 4-2. List of Sources Reviewed for LCI Data 4-3
Table 4-3. Proposed LCI Dataset: Asphalt Shingles, at Unlined CDD Landfill 4-6
Table 4-4. Proposed LCI Dataset: Asphalt Shingles, at Processing Plant 4-9
Table 4-5. Overview of LCI Data Available 4-12
Table 5-1. LCI Needed for LCA of Gypsum Drywall EOL Management 5-3
Table 5-2. List of Sources Reviewed for LCI Data 5-4
Table 5-3. Athena (2011) - Natural Gypsum Mining LCI (per kg of Mined Gypsum at
Mine/Quarry) 5-5
XI
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5-4. Materials, Energy, and Process: Related Emissions for 1 kg of Gypsum Paper, at Plant.
5-5. Proposed LCI for Gypsum Drywall, at Distribution Center
5-6. LCI Dataset: Gypsum Drywall Disposal, at Unlined CDD Landfill
5 -7. LCI Dataset: Recycled Gypsum Land Application as Agricultural Amendment
5-8. Overview of LCI Data Available
6-1. LCI Needed for LCA of Wood Products EOL Management
6-2. LCI Sources to Develop Wood Products LCI
6-3. Proposed LCI Dataset: Untreated Wood Waste, at Unlined CDD Landfill
6-4. Proposed LCI Dataset: CCA-Treated Wood Products, at Unlined CDD Landfill
6-5. Proposed LCI Dataset: ACQ-Treated Wood Products, at Unlined CDD Landfill
6-6. Proposed LCI Dataset: CBA-Treated Wood Products, at Unlined CDD Landfill
6-7. Proposed LCI Dataset: DOT-Treated Wood Products, at Unlined CDD Landfill
6-8. Proposed LCI Dataset: CCA-Treated Wood Products, at MSW Landfill
6-9. Proposed LCI Dataset: ACQ-Treated Wood Products, at MSW Landfill
6-10. Proposed LCI Dataset: CBA-Treated Wood Products, at MSW Landfill
6-11. Proposed LCI Dataset: DOT-Treated Wood Products, at MSW Landfill
6-12. Proposed LCI Dataset: Mulch Production and Land Application
6-13. Proposed LCI Dataset: Untreated Waste Wood Ash, at Unlined CDD Landfill
6-14. Proposed LCI Dataset: Untreated Waste Wood Ash, at MSW Landfill
6-15. Proposed LCI Dataset: CCA-Treated Wood Ash, 4 kg/m3 CCA Retention Level, at
MSW Landfill
6-16. Proposed LCI Dataset: CCA-Treated Wood Ash, 9.6 kg/m3 CCA Retention Level, at
MSW Landfill
6-17. Proposed LCI Dataset: CCA-Treated Wood Ash, 40 kg/m3 CCA Retention Level, at
MSW Landfill
6-18. Overview of Wood Product Specific LCI Data Available
7-1. LCD EOL Management Process Descriptions and Considerations for LCA
7-2. List of Sources Reviewed for LCI Data
7-3. Proposed LCI Dataset: Land Clearing Debris, Open Burning
7-4. Land Clearing Debris, at Air Curtain Incineration
7-5. Proposed LCI Dataset: Land Clearing Debris, at Unlined CDD Landfill
7-6. Proposed LCI Dataset: Ground LCD, Processed and Applied as Mulch
7-7. Composting Equipment Energy Consumption per Kilogram of LCD
7-8. Proposed LCI Dataset: Ground LCD, at Processing Facility
7-9. Overview of LCD Data Available
8-1. Concrete EOL Management Process Descriptions
8-2. List of Sources Reviewed for LCI Data
8-3. Proposed LCI Dataset: Concrete, at Unlined CDD Landfill
8-4. Proposed LCI Dataset: Crushed Concrete, at Processing Plant
8-5. Proposed LCI Dataset: Recycled Concrete Aggregate, Use as Aggregate
8-6. Proposed LCI Dataset: Concrete debris, Use as Soil Fill Substitute
8-7. Overview of LCI Data Available for Concrete
9-1. RSM EOL Management Process Descriptions
9-2. List of Sources Reviewed for LCI Data
9-3. Methane and Carbon Dioxide Emission Factors for CDD and MSW Landfill Disposal
of Different RSM Components (developed from US EPA (2012))
9-4. Proposed LCI Dataset: Recovered Screened Material, at Unlined CDD Landfill
9-5. Proposed LCI Dataset: Recovered Screened Material, at MSW Landfill
9-6. Proposed LCI Dataset: Recovered Screened Material, Use in Environment
9-7. Overview of LCI Data Available
10-1. Clay Brick EOL Management Process Descriptions
...5-7
.5-10
.5-14
.5-17
.5-18
...6-3
...6-4
.6-11
.6-12
.6-12
.6-13
.6-13
.6-14
.6-14
.6-15
.6-16
.6-18
.6-21
.6-21
.6-21
.6-22
.6-23
.6-25
...7-2
...7-3
...7-5
...7-6
...7-7
...7-9
.7-10
.7-12
.7-13
...8-3
...8-4
...8-7
...8-9
.8-11
.8-11
.8-13
...9-2
...9-3
...9-5
...9-6
...9-7
...9-9
.9-10
.10-2
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Table 10-2. List of Sources Reviewed 10-2
Table 11-1. Summary of CDD Material LCI Process Datasets and Flows Included in the Report 11-1
xin
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xiv
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List of Abbreviations, Acronyms, and Initialisms
ACQ
ADC
AP-42
ASMI
BDL
BOD
BTEX
BTS
BTU
C&D
CDD
CBA
CCA
CDRA
CFCs
CKD
CLT
COD
CORRIM
DCA
DOT
EAPA
EIA
EOL
ERG
FDEP
FGD
FHWA
FML
ft3
GCCS
GHG
GREET
HCFCs
HOPE
HHD
HMA
hr
IE
ILCD
IPCC
IVL
IWCS
kg
kJ
km
kWh
kWh/kg
Alkaline Copper Quarternary
Alternative Daily Cover
Compilation of Air Pollutant Emission Factors
Athena Sustainable Materials Institute
Below-Detection Limit
Biochemical Oxygen Demand
Benzene Toluene Ethylene Xylene
Bureau of Transportation Statistics
British Thermal Units
Construction & Demolition
Construction & Demolition Debris
Copper Azle
Chromated Copper Arsenate
Construction and Demolition Recycling Association
Chlorofluorocarbons
Cement Kiln Dust
Cross Laminated Timber
Chemical Oxygen Demand
Consortium for Research on Renewable Industrial Materials
Dense Concrete Aggregate
Disodium Octaborate Tetrahydrate
European Asphalt Pavement Association
Energy Information Administration
End of Life
Eastern Research Group, Inc.
Florida Department of Environmental Protection
Flue Gas Desulfurization
Federal Highway Administration
Flexible Membrane Liner
Cubic Foot
Gas Collection and Control Systems
Greenhouse Gas
Greenhouse Gases, Regulated Emissions and Energy Use
Hydrochlorofluorocarbons
High Density Polyethylene
Heavy Heavy-Duty
Hot Mix Asphalt
Hour
Impact Estimator
International Reference Life Cycle Data
Intergovernmental Panel on Climate Change
Swedish Environmental Institute
Innovative Waste Consulting Services, LLC
Kilogram
Kilojoule
Kilometers
Kilowatt-Hours
Kilowatt-Hours per Kilogram
xv
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L
Ib
LCA
LCD
LCI
LCS
LCRS
LEAF
LEED
LFG
LMOP
m
m2
m3
MDF
Mg
mg
MJ/m3
MMT
MOVES
MSW
MSW-DST
MT
n.d.
ng
n.r.
NAICS
NAPA
NCSU
ND
NMOC
NMVOC
NOAA
NOx
NRC
NREL
NRMRL
O&M
ORD
OSB
PAH
PAS
PCC
PE
PM
PVC
RAP
RCA
RCRA
RSM
SHC
Liter
Pound
Life Cycle Assessment
Land-Clearing Debris
Life Cycle Inventory
Leachate Collection System
Leachate Collection and Removal System
Leaching Environmental Assessment Framework
Leadership in Energy & Environmental Design
Landfill Gas
Landfill Methane Outreach Program
Meter
Square Meter
Cubic Meter
Medium-Density Fiberboard
Micrograms
Milligrams
Mega Joules per Cubic Meter
Million Metric Tons
Motor Vehicle Emissions Simulator
Municipal Solid Waste
Municipal Solid Waste-Decision Support Tool
Metric Tons
No Date
Nanogram
No Record
North American Industry Classification System
National Asphalt Pavement Association
North Carolina State University
Not Detected
Non-Methane Organic Carbon
Non-Methane Volatile Organic Carbon
National Oceanic and Atmospheric Administration
Nitrogen Oxides
National Resources Canada
National Renewable Energy Laboratory
National Risk Management Research Laboratory
Operation(s) and Maintenance
Office of Research and Development
Oriented Strand Board
Polycyclic Aromatic Hydrocarbons
Publicly Available Specification
Portland Cement Concrete
Polyethylene
Particulate Matter
Polyvinyl Chloride
Reclaimed Asphalt Pavement
Recycled Concrete Aggregate
Resource Conservation & Recovery Act
Recovered Screened Material
Sustainable and Healthy Communities
xvi
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SOx
SPLP
t*km
TCLP
TDS
TK
TNT
TOC
Tonne
TRPH
TSS
US
US EPA
USCB
USDA
USGS
VOC
WARM
WMA
WRATE
WWTP
XRF
Sulfur Oxides
Synthetic Precipitation Leaching Procedure
Tonne-Kilometer
Toxicity Characteristic Leaching Procedure
Total Dissolved Solids
Transfer Coefficient
Trinitrotoluene
Total Organic Carbon
Metric Ton
Total Recoverable Petroleum Hydrocarbon
Total Suspended Solids
United States
United States Environmental Protection Agency
United States Census Bureau
United States Department of Agriculture
United States Geological Survey
Volatile Organic Carbon
Waste Reduction Model (US EPA Model)
Warm Mix Asphalt
Waste and Resources Assessment Tool for the Environment
Wastewater Treatment Plant
X-ray fluorescence
XVII
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Multimedia Environmental Assessment Section 1 - Introduction
1 Introduction
1.1 Background
Decision-making processes used by communities to evaluate social, economic, and environmental
implications in a resource-constrained world are often not well characterized in terms of the interactions
among human health, ecosystem services, economic vitality, and social equity. The need for a decision-
making approach that accounts for all three pillars of sustainability (environment, society, and economy) is
widely recognized as a key component for transitioning to a more sustainable society (USGS 1998, US
EPA 2009, Pereira 2012). The US EPA's Sustainable and Healthy Communities Research Program (SHC)
strives to provide tools for community decision-makers to more effectively and equitably weigh and
integrate human health and socio-economic, environmental, and ecological factors into their decisions to
promote community sustainability. Decisions pertaining to waste and materials management have been
identified as one of the highest priorities by communities for implementing sustainable practices (US EPA
2012a). Life-cycle assessment (LCA), in which impacts across the life cycle of a material or process are
examined, can be used as a tool to comprehensively assess environmental and human health implications
of various available material management options. One of the critical underlying components of LCA are
life-cycle inventory (LCI) data, which are a compilation of quantitative inputs and outputs associated with
the management of a material (e.g., energy, material properties, and associated emissions and
transformations). As part of the SHC research program, the US EPA is developing tools and data that can
be used by communities to conduct an LCA for managing various waste and materials management streams
during the end-of-life (EOL) phase.
Although computer-based LCA tools have been developed to analyze waste materials and processes, the
overwhelming focus to date has been on municipal solid waste (MSW). Another large-volume, non-
hazardous materials waste stream, construction and demolition debris (CDD), has largely been excluded
from previously-developed models, perhaps owing to the perceived nature of CDD as "inert" or the lack of
available data since CDD is often regulated less stringently than MSW in the US. CDD originates from the
construction, renovation, repair, and demolition of structures such as residential and commercial buildings,
roads, and bridges. Although the composition of CDD materials depends on the nature of the activity (e.g.,
building construction, building demolition, pavement rehabilitation), wood, asphalt pavement, Portland
cement concrete (PCC), masonry, shingles and drywall represent the dominant fractions of CDD materials.
CDD materials also contain lesser amounts of such materials as metals, plastics, insulation, cardboard, and
soil. In addition, trace quantities of chemical products such as paints, solvents, and adhesives may be
present.
Recent estimates suggest that more than 220 MMT of CDD were generated in the US in 2011, and little
more than half of this amount of material was recycled. From the disposal perspective, approximately half
of the states in the US do not require CDD landfills to be constructed with bottom liners and leachate-
collection systems. In light of the large quantity of CDD materials generated annually, the potential for
environmental impacts from the disposal of CDD materials and the environmental benefits associated with
the recycling and recovery of CDD materials, the US EPA has identified the collection of information and
data regarding CDD management practices as a priority area to develop LCI and integrate the collected
information into new or improved LCA tools that include CDD management.
An LCA of a material at EOL would account for the energy and material inputs from various unit processes
associated with managing the material through final disposition and the associated emissions from that
material through management and after final disposition. For example, an LCA pertaining to the recycling
gypsum drywall recovered from a building demolition should include the materials (e.g., steel, lubricants)
and fuel (e.g., diesel) used by the equipment to grind and screen the drywall, the emissions associated with
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Multimedia Environmental Assessment Section 1 - Introduction
the production and use of these materials and energy, the emissions occurring during the recycling process
itself (e.g., dust emissions), as well as those associated with processing equipment and facility
decommission. The LCI data for this example would include the accounting of energy and raw material
inputs and emissions to various environmental compartments (i.e., air, water, and land) over the life cycle
of the process (i.e., construction, operation, and decommissioning).
1,2 Scope of Work and Objectives
The objective of the research presented in this report was to extensively assess the body of knowledge
regarding CDD life-cycle data and compile US-specific publicly-available LCI for the EOL phase for
various CDD materials and management processes. Peer-reviewed literature, government and private
industry publications, and various LCA modeling tools were reviewed to identify current management
practices and the available LCI datasets pertaining to these practices for a set of specific CDD materials. If
LCI data were not available, process description and documentation (e.g., included emission categories,
background data used to compile the dataset, geographic location, and time period of the data) were
reviewed to evaluate the completeness of the dataset. If available, the primary sources of information used
to develop the LCI datasets and information were reviewed.
If data on a process were lacking or a given CDD management practice was not in common use, LCI were
not compiled. If publicly-available information for a given unit process was not available (e.g., liquids
emissions from disposal of CDD), proxy information was reviewed and included as applicable (e.g., CDD
materials leaching data). Publicly-available LCI for upstream processes (raw material mining and product
manufacturing) were compiled for the materials that are currently recycled in a closed-loop system (i.e.,
recycled materials are used in the production of the same material). In cases where data gaps existed, LCI
developed for non-US conditions were reviewed to better understand the inputs and approaches used to
develop such LCI - the unit process LCI that were not available for the US were identified as data gaps in
need of further research.
A final objective of this research was to make available the compiled LCI data. The LCI that were
developed in this project were formatted to be compatible with the International Reference Life Cycle Data
(ILCD) System and were submitted for integration into the existing US EPA LCI database.
1.2.1 Material Types
Based on US EPA (2014) estimates, approximately 88 million metric tons (MMT) of construction and
demolition debris (CDD) were landfilled and 47 MMT were recycled by permitted or registered waste
management facilities in the US in 2011. Figure 1-1 presents the composition of the CDD landfilled and
recycled by solid waste management facilities in the US. The landfilled CDD composition is based on
multiple regional waste composition studies, whereas the recycled CDD composition is based on CDD
recycled material quantities tracked by Florida, Massachusetts, Nevada, and Washington.
The "other materials" categories mostly consist of indistinguishable and non-CDD materials (about 60%),
but also include paper, plastic, glass, carpet, and insulation. "Fines" include materials such as dirt and sand,
while "other aggregates" includes bricks, rock, and gravel.
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Section 1 - Introduction
A large fraction of asphalt pavement, Portland cement concrete (PCC), and land clearing debris (LCD) is
managed by facilities that do not require solid waste permits, so the composition shown in Figure 1-1 and
the previously-mentioned generation estimates do not include large quantities of asphalt pavement, PCC,
and LCD. For example, the National Asphalt Pavement Association (NAPA) reported that approximately
72 MMT of reclaimed asphalt pavement were managed by the asphalt pavement industry in 2011 (NAPA
2013). Based on an estimate reported by the Construction and Demolition Recycling Association (CDRA
2014), approximately 127 MMT of PCC is recycled annually in the US.
Organic s
1%
Metal
3%
Gypsum
8%
Other
Materials
15%
Wood
20%
Fines
Wood
13%
T pn Shingles/
_l_jv_._Lx -.-. f~
9% Roofing
Metal
Roofing
18%
Asphalt.
5% Other Aggrega'B
9%
Concrete
13%
Portland
Cement
Concrete
56%
(a)
(b)
Figure 1-1. Composition of CDD (a) Landfilled, and (b) Recycled by Solid Waste Management
Facilities in the US
When these additional quantities of asphalt pavement and PCC are considered, PCC, asphalt pavement,
wood, roofing materials, fines, gypsum, LCD, and other aggregates constitute more than 95% of the CDD
generated in the US. This report presents a compilation of life-cycle inventories (LCI) of various processes
needed to conduct an LCA of EOL phase management of the following major CDD constituents:
i. Asphalt Pavement
ii. Asphalt Shingles
iii. Gypsum Drywall
iv. Wood Products
v. Land Clearing Debris (LCD)
vi. Portland Cement Concrete (PCC)
vii. Recovered Screened Material (RSM)
viii. Clay Bricks
The estimate of the total quantity of each material that underwent EOL management in 2011 is presented
in each material's respective chapter. These estimates and the sources used to develop the estimates are
presented in Table 1-1. The quantities of stockpiled material (i.e., asphalt pavement, asphalt shingles) were
excluded from the table. For this report, temporary stockpiling is not considered EOL management.
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Section 1 - Introduction
Table 1-1. Estimated CDD Materials Generation Rate in 2011
Material
PCC
Asphalt Pavement
Wood Products
Asphalt Shingles
Gypsum Drywall
RSM
Clay Bricks
LCD
Estimated 2011 Quantity
Recovered for EOL
Management (MMT)
212-254
83.5
24
10
7.4
3.7-11.9
1.4-6.8
-
Sources
CDRA (2014), Turley (2002), Wilburn
and Goonan( 1998)
US EPA (2014), NAPA (2013), Bolen
(2013)
US EPA (20 14)
US EPA (2014), NAPA (2013)
US EPA (20 14)
US EPA (2014), Jang and Townsend
(200 la)
US EPA (2014), US EPA (2012b)
N/A
1.3 Report Organization
This report is organized into eleven chapters. Following Chapter 1, Chapter 2 summarizes important details
of the materials investigated in this report and then presents LCI information on unit processes that are
common to the management of multiple CDD materials targeted in this report, including transportation,
primary aggregate production, and environmental emissions (e.g., leachate and gas). Chapters 3 through 10
present material-specific details, including current EOL management practices, an estimate of the quantity
of the material managed at the EOL phase (if available), LCI needs and sources reviewed, LCI for the
different EOL management processes, and data gaps and opportunities for additional research. The
materials examined in these chapters are asphalt pavement, asphalt shingles, gypsum drywall, wood, land-
clearing debris, Portland cement concrete, recovered screened materials, and clay bricks. Finally, Chapter
11 summarizes the data gaps identified for the different CDD materials and presents additional research
opportunities that would allow the compilation of a complete LCI data search in the future.
1.4 References
Bolen, W.P. (2013). 2011 Minerals Yearbook - Sand and Gravel, Construction [Advance Release].
Published by the United States Geological Survey, May 2013. http://on.doi.gov/1 zpWK2z.
Accessed 12 March 2014.
CDRA (2014). Good Economic Sense. http://bit.lv/lo07BGV
Jang, Y.C., Townsend, T.G. (2001a). Occurrence of Organic Pollutants in Recovered Soil Fines from
Construction and Demolition Waste. Waste Management, 21, 703-715.
NAPA (2013). 2nd Annual Asphalt Pavement Industry Survey on Reclaimed Asphalt Pavement, Reclaimed
Asphalt Shingles, and Warm-Mix Asphalt Usage: 2009-2011. National Asphalt Pavement
Association, Information Series 138, April 2013.
Periera, E.G., da Silva, J.N., de Oliveira, J.L., Machado, C.S. (2012). Sustainable Energy: A Review of
Gasification Technologies. Renewable and Sustainable Energy Reviews, 16, 4753-4762.
Turley, W. (2002). Personal Communication between William Turley, Construction Materials Recycling
Association and Philip Groth of ICF Consulting, 2002. As cited in http://l .usa.gov/luDQzrG.
US EPA (2009). Sustainable Materials Management: The Road Ahead. EPA530R09009, June 2009.
https://www.fas.usda.gov/info/IATR/072011 Ethanol lATRpdf
US EPA (2012a). Landfilling. WARM Version 12, Documentation. http://l .usa.gov/UyBqY4. Accessed 21
April 2014.
US EPA (2012b). Basic Information. http://l.usa.gov/lmW4C77. Accessed 17 July 2014.
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US EPA (2014). Methodology to Estimate the Quantity, Composition, and Management of Construction
and Demolition Debris in the United States. A Report Prepared by Innovative Waste Consulting
Services, LLC and Pegasus Technical Services, Inc. for the US Environmental Protection Agency,
June 2014, Unpublished report.
USGS (1998). Materials Flow and Sustainability. USGS Fact Sheet FS-068-98, June 1998.
Wilburn, D.R., Goonan, T.G. (1998). Aggregates from Natural and Recycled Sources: Economic
Assessments for Construction Applications - A Materials Flow Analysis. US Geological Survey
Circular 1176, US Geological Survey and US Department of the Interior.
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2 Materials and Management Approaches
2. 1 Boundary Considered: EOL Phase
The EOL phase, which begins when the material is discarded after the use phase, is the primary focus of
the current study. Many LCA studies reported in the literature and from institutional efforts (e.g., LEED
Green Building efforts) have focused on building materials (among other CDD) from inception to the point
of sale (i.e., cradle to gate), or on the life cycle of their service phase (while in active use). However, the
EOL phase is often neglected in LCA studies.
Upstream processes (e.g., raw material extraction, raw material processing) were considered when the
material was recycled in a closed loop (e.g., RAP used for asphalt pavement production). However, for
materials which are not typically recycled through a closed-loop process, upstream processes were not
further explored since these processes would not impact the emissions from the EOL management of the
materials. Upstream processes were also considered in some open-loop-recycling cases. For example,
dimensional lumber recycled into particle board or PCC recycled as road-base aggregate would include
consideration of upstream processes associated with primary wood or aggregate production.
It is important to consider all life phases of facilities and associated equipment used in an EOL management
process. For example, while one may expect that the bulk of the environmental burdens from a CDD
recycling facility would occur during the operational phase, the emissions associated with construction and
decommissioning/demolition of the facility should also be taken into consideration as much as possible.
This is particularly important for EOL management-process-dedicated facilities/equipment.
2.2 Geographic Area
The LCI available/used by prominent models/databases were analyzed and discussed in this report but only
LCI for the US were compiled in this document.
2.3 Life-Cycle Inventory
An appropriate set of LCI data is needed to conduct an effective LCA, as the results of the LCA are closely
tied to the underlying data in the LCI dataset used. LCI datasets should include input and output flows
(materials, energy, emissions, etc.) for all processes identified within the materials life cycle (i.e., product
system). This section presents terminology frequently used in this report.
A fundamental aspect of a given product or process LCI is the stream of substances, which may be
categorized as elementary, product, or waste (see Table 2-1). For a given process, flows are represented
and quantified as either inputs or outputs. Flows must be quantified by at least one property, such as volume,
area, mass, time, or energy. Flows may be further broadly classified into either the technosphere (flows of
material into and from the supply chain or manufactured world) or ecosphere (i.e., belonging to nature)
(Schenck 2009). Particulate matter released to the air is an example of an ecosphere flow, whereas the
amount of high-density polyethylene (HOPE) needed for landfill construction is a technosphere flow Table
2-1 summarizes and provides examples of the different flow types.
Once a material reaches the EOL phase, the environmental burdens associated with a particular
management process are generally quantified by considering the inflows and outflows of energy, materials,
and process emissions. Emissions may either be fuel-related (e.g., emissions from fuel extraction,
processing, transport, combustion) or non-fuel-related (e.g. dust, leachate); they may originate during
facility construction, operation, or decommissioning and may be the result of the production and use of
materials that are ancillary to the process (i.e., operation and maintenance consumables) as presented in
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Table 2-2. Table 2-2 lists the technical terms used throughout this report to describe the different categories
of emissions and materials included in the LCI datasets.
Table 2-1. Basic Flow Categories
Flow Type
Elementary
Product
Waste
Description
Material or energy entering or exiting
the system without prior or subsequent
treatment (input or output)
Usable or desired material (inputs or
output) to another process
Material leaving the product system
(output only)
Flow Examples for an Example Product
System
Particulate matter emissions from heavy
equipment operation (ecosphere)
Input: Gasoline for combustion in heavy
equipment (technosphere)
Ouput: Softwood sawn and planed lumber
(technosphere)
Residuals from CDD processing
(technosphere)
Table 2-2. Terminology for EOL CDD Material Management
Term
Pre -combustion
Emissions
Manufacturing/
Construction
Emissions
Non-fuel Emissions
Operation and
Maintenance
(O&M)
Consumables
Decommissioning/
Demolition
Emissions
Primary Material
Recycled Material
Description
All emissions released as a result of
fuel or electricity production
Emissions released during the
manufacture of a product or piece of
equipment/construction of a facility
Emissions which are not associated
with fuel combustion. These
emissions are those emitted during a
processing step, not as a direct result
of energy use or fuel consumption
Those materials which are used by a
process but are not incorporated into
the product of interest.
Emissions released as a result of
removing or disposing of process
facilities or equipment.
Material produced from virgin
resources
Materials produced from processing
of discarded products
Example
Air emissions from crude oil
extraction, transport and processing
for diesel or gasoline fuel
production
Dust emissions from land clearing
activities for concrete plant
construction.
Emissions from stormwater run-off
or landfill leachate to surface or
groundwater
Lubricating oils for process
equipment
Particulates released as part of
material recovery facility demolition
Asphalt produced from petroleum
refining
Aggregate produced from crushing
discarded PCC
Airborne releases of carbon dioxide can either be considered fossil or biogenic. Biogenic carbon dioxide is
released due to transformation (e.g., biological decomposition or combustion) of biologically active carbon
(e.g., biomass), whereas fossil carbon dioxide is usually released from the combustion of carbon compounds
from a fossil origin (e.g., diesel fuel, plastics) or from mineral sources where carbon dioxide would not
have been otherwise liberated. Many models and datasets do not consider biogenic carbon dioxide
emissions for quantification of emissions associated with human activity as biogenic carbon dioxide
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emission would occur regardless of human activities (RTI International 2003, US EPA 2012a). However,
any anthropogenic-induced increase in greenhouse gas (GHG) emissions from biologically active carbon
above and beyond what would have naturally occurred is typically considered in LCA models. For
example, the landfill disposal of biomass results in methane emissions which have a substantially greater
GHG potency than carbon dioxide. Because it is unlikely that these methane emissions would have naturally
occurred without human activity, their impact on the environment would typically be considered in LCA
models.
LCI data on emissions to water vary based on assumed environmental controls (e.g., wastewater treatment)
and the associated pollutant removal efficiency, which may be quantified on a constituent-specific basis.
For example, the MSW-DST assumes removal rates of 97% and 21.6% for aqueous biochemical oxygen
demand (BOD) and phosphate, respectively (NC State and Eastern Research Group 2011). Leachate-
related emissions for landfill disposal of materials are an example of waterborne emissions considered for
material EOL management. LCI data are often available for chemicals normally required to be monitored
in leachate on a routine basis by regulations (e.g., BOD, arsenic). Material combustion ash, wastewater
treatment plant sludge, and solids collected in air-pollution-control devices are some examples of solid
wastes (from CDD materials processing) that should be accounted for in the EOL management of CDD
materials. While the amount of solid wastes may be quantified, environmental emissions from these solid
wastes and their management are not accounted for in various LCA models (ASMI2014).
2.4 Organization of Proposed LCI Datasets
All the LCI developed in this report were integrated with the US EPA LCI database using OpenLCA, an
open-source LCA program. The flows included in the proposed LCI datasets provided in this report are
quantified in terms of a reference flow. All the inputs and outputs included in a LCI are scaled with respect
to reference flow. The reference flow is always included under the output flows, but OpenLCA users can
switch reference flows for those processes that are producing multiple products of interest. For ease of
identification, the reference flow is in italic text in each of the LCI dataset tables presented in the report.
All the numbers in the range of 0.0001 to 10,000 are presented in decimal format and the numbers outside
this range are presented in engineering notation (e.g., 1.2E-08) for consistency with OpenLCA number
format. Also included within the proposed datasets is a column entitled "Category," which presents the
location of flows in the US EPA LCI database as accessible through OpenLCA. All the process LCI
developed and presented in this report and the associated elementary flows are included in a folder labeled
"Construction and Demolition Debris Management" for ease of identification and review. This folder was
created in the "Waste Management and Remediation Services" process folder.
2.5 Common Technosphere Inputs
2.5.1 Transportation
Emissions associated with transportation are often normalized with respect to the amount of material
multiplied by the shipment distance, typically expressed as ton-miles (or tonne-km). Ton-miles provide the
best single measure of the overall demand for freight transportation services; this measure in turn reflects
the overall level of industrial activity in the economy (Dennis 2005). Ton-miles have been historically used
by USCB to analyze the magnitude and modes of freight transportation at a national level for different
commodities (2007 Commodity Flow Survey by USCB (2010)).
Different LCA approaches and LCI databases quantify transportation-related emissions in different ways.
For example, the Municipal Solid Waste Decision Support Tool (MSW-DST), which is a waste-specific
LCA tool developed by Research Triangle Institute (RTI) International, North Carolina State University,
and the United States Environmental Protection Agency (US EPA), allows for estimates of emissions from
transportation for different waste management processes in units of grams of pollutant per ton of waste
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managed (Curtis and Dumas 2000). Because emission information is already stored in the program for
various vehicle types (i.e., grams released per mile traveled), the program requires information regarding
three input variables - user-specified material amount, user-specified transport distances, and the number
of vehicles necessary for the particular strategy. The total material amount managed is divided by the
transport vehicle capacity (which depends on the vehicle type selected) to calculate the number of vehicles
needed, which in turn is used to calculate cumulative transport distance. For example, if 1,000 MT of
material needed to be transported using trucks with 10 MT capacities, 100 truck trips would be necessary.
If each truck needed to travel 20 km per trip, this would result in a cumulative transport distance of 2,000
kilometers.
Similar to MSW-DST, other models estimate the contribution to emissions from both the distance over
which materials are transported and the total quantity of materials transported. However, the actual
structuring of these calculations is slightly different. Other LCA programs and LCI databases [e.g.,
WRATE, EASETECH, ECOINVENT, GABI, SIMA PRO, US LCI (2012)] include transportation process
units as the product of mass and distance (e.g., tonne-kilometers, ton-miles). For example, both
EASETECH and WRATE allow the user to specify the mass/weight of materials transported and the
distance that the vehicle travels. Using vehicle-specific default fuel consumption and emission factors,
EASTECH estimates the emissions resulting from fuel pre-combustion (i.e., those associated with fuel
extraction, mining, processing, transport to the fuel station), and combustion, respectively.
Numerous emissions data in the US LCI database developed by National Renewable Energy Laboratory
(US LCI (2012)) LCI database are estimated based on the US EPA's Motor Vehicle Emission Simulator
(MOVES). MOVES was developed by the Office of Transportation and Air Quality and uses information
from US EPA research; Census Bureau vehicle surveys; Federal Highway Administration travel data; and
other federal, state, local, industry, and academic sources (US EPA 2012b). MOVES can simulate time-
specific emissions from the operation of a variety of vehicles and vehicle operation stages (e.g. start-up,
idling) on a national, state, or county-wide basis. The Greenhouse Gases, Regulated Emissions, and Energy
Use in Transportation (GREET) model, developed by the Argonne National Laboratory, is also commonly
referenced for information concerning the pre-combustion emissions associated with fuel production from
initial crude oil extraction to provision at a fueling station.
For quantifying the emissions associated with the general transport of materials discussed in this report, the
"Truck transport, class 8, heavy heavy-duty (HHD), diesel, short-haul, load factor 0.75" process included
in the US EPA LCI database was used to simulate the one-way transport of materials between individual
EOL material management locations for distances less than 35 km. The same process, except distinguished
as long-haul instead of short-haul, was used to model transport for distances greater than 35 km. For those
process datasets where the transport distance is unknown, a distance of 20 km was assumed.
2.5.1.1 Primary Aggregate Transport
Several CDD materials may either contain primary aggregates (asphalt pavement, asphalt shingles, PCC)
or may be used as a substitute for the production and transport of primary aggregates as an EOL
management option. As a result, it is necessary to develop an estimate of the average nationwide modal
(i.e., road, rail, and ocean) distance that primary aggregates typically travel from production to end-use.
The US Census Bureau (USCB) Commodity Flow Survey provides the total amount, distance-amount, and
average miles per shipment for gravel and crushed stone in the US. However, the distances and quantities
provided are not organized by transport path or end-users (e.g., hot mix asphalt (HMA) plants, PCC plants).
Due to lack of end-user-specific data, the average distances for the commodity titled "Gravel and crushed
stone" presented in USCB (2010) are assumed to represent the average US-wide aggregate transport
distance from production sites to multiple primary (e.g., HMA Plants, PCC plants) end uses for various
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transport modes. The average distance for a mode was calculated by dividing the total ton-mile data for
the mode by the total amount (tons) for all modes combined. Only single-mode transport data provided by
the survey were used in the analyses presented in this report.
Table 2-3. Estimated Transport Distances for Aggregate Materials (developed from USCB 2010)
Material
Transport
Aggregate
Transport
from Mine
to Paving
Mix Plant
Source and
Representative
Commodity
USCB (2010)-
Gravel and
Crushed Stone
Total
Amount
Transported
by Single
Mode
(million tons)
1,930
Mode
Truck
Rail
Water
Ton-miles (in
millions)
80,600
23,400
15,500
Average
Transport
Distance
(miles)
41.7
12.1
8.01
Average
Transport
Distance
(km)
67.1
19.5
12.9
2.5.2 Electricity
Numerous CDD management processes require electricity for operation, and in many cases electricity
consumption is expected to be correlated with the amount of material handled by the process. The current
US EPA LCI database contains an "electricity, at industrial user" process, which was used to model the
environmental burdens associated with power generation based on the national average grid mix. All the
proposed LCI datasets developed as presented in this report use the output flow associated with this process
to model electricity consumption since all the datasets represent industrial user electricity demand.
2.5.3 Fuel Combustion in Equipment
Similar to electricity use, multiple CDD management processes require the use of heavy equipment for a
variety of tasks (e.g., material loading, unloading, sorting, on-site transport). The current US EPA LCI
database process "Diesel, combusted in industrial equipment," developed by Franklin Associates, was used
to simulate pre-combustion emissions and the emissions resulting from diesel combustion for heavy
equipment operation.
2.5.4 Other Fuel Combustion Applications
Several processes included in the US EPA LCI database simulate the combustion of other fuels (e.g.,
gasoline, natural gas, residual fuel oil) in various types of industrial equipment (e.g., boilers). Input flows
from these other processes were selected to approximate the emissions associated with combustion of
various fuels usage other than equipment operation. For example, the "Natural gas, combusted in industrial
boiler" was selected to model natural gas fired at an HMA plant.
2.5.5 O&M Consumables
In addition to direct emissions, LCI datasets should include the emissions associated with the production
and use of O&M consumables (e.g. lubricating oils, filters, drilling fluids, belts). While it may not be
possible to combine all environmental burdens associated with the production of each O&M consumable,
data on the quantity of these materials, if available, were compiled.
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2.5.6 Aggregates and Soil
2.5.6.1 Primary Aggregate Production and Fuel Consumption
Several CDD materials incorporate aggregates to increase load-bearing capacity (e.g., PCC, asphalt
pavement) and the practice of recycling these recycled materials eliminates the need to produce an
equivalent quantity of primary aggregates. It is therefore necessary to understand the fuel-related and non-
fuel-related emissions resulting from primary aggregate production.
The United States Geological Survey (USGS) has published annual primary aggregate production and use
statistics for crushed stone and construction sand and gravel since 1932 in the Minerals Yearbook. A large
fraction of these commodities is used in asphalt pavement and concrete production; limestone and dolomite
(i.e., calcium carbonate and calcium magnesium carbonate, respectively) are the most common crushed
stone aggregates - approximately 70% of all 1.2 billion MT of 2011 crushed stone was limestone and
dolomite. Together, bituminous and concrete aggregate account for nearly 65% of all limestone and
dolomite sold or used by producers categorized by major end use (Willet 2013). Also, approximately 82%
of the 327 MMT of sand and gravel produced in the US in 2011 was used for concrete aggregate and road-
related purposes (e.g., road base and coverings, stabilization, asphalt pavement aggregates) (Bolen 2013).
Natural rock is mined and commonly crushed and fractionated at the mining site before shipment (Wilburn
and Goonan 1998). Although underground mining of crushed stone is becoming more common due to
environmental concerns and better community acceptance, surface methods (e.g. open pit quarries) are the
predominant processes for aggregate production (Wilburn and Goonan 1998, USGS 2013). Numerous
stages of aggregate processing (e.g., blasting, crushing, screening, size classification, onsite storage) may
result in particulate matter emissions (US EPA 2004a). Water consumption information for aggregate
mining provided by USGS (2009) suggests that substantial amounts of aggregate mining process water are
discharged. Excavated rock is transported to crushers and screening equipment for size-reduction and
classification. Pre-combustion (i.e. those emissions released from fuels used for extracting,
refining/processing, and transporting) and exhaust emissions are associated with the use of energy for
processing equipment operation.
The 2012 US LCI database has a "Limestone, at mine" process developed by Franklin Associates from
information compiled from a variety of sources dated from 1998-2004. However, based on the process
inputs/outputs, it appears that only fuel consumption and particulate emissions associated with mining and
crushing were taken into account. As modeled, the process appears to be missing emissions from the
manufacturing and detonation of the explosives used for blasting and does not include any emissions to
surface water. The US EPA's Waste Reduction Model (WARM) uses information from this process from
the 2009 version of the US LCI (2012) database to develop the estimate for emissions related to aggregate
mining (US EPA 2012a). The GaBi LCI database appears to have a US-specific limestone production
process; however, it exclusively references German- and Swiss-published sources in its process
documentation page.
The US EPA's Compilation of Air Pollutant Emission Factors (AP-42) provides air emissions information
for crushed stone and sand and gravel processing and for quarrying/mining-specific explosives detonation
(US EPA 2004a, US EPA 1995b, US EPA 1980). Although AP-42 (US EPA 1983) includes emissions
associated with mining and quarrying blasting agent denotation, the emissions associated with
manufacturing blasting agents commonly used in quarrying/mining operations are not included. Persson et
al. (1993) reported that approximately 0.4 kg of explosives is needed for loosening a cubic meter of rock.
Mehrkesh and Karunanithi (2013) estimate the power consumption for the production of 2, 4, 6,-
trinitrotoluene (TNT) as 2.6 kWh/kg. While TNT is not typically used as a blasting agent in quarrying
operations, the magnitude of the energy requirement for TNT production demonstrates the importance of
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including emissions associated with manufacturing quarry-use-specific blasting agents in aggregate
production LCI.
Sand and gravel mining does not typically involve blasting. Unlike crushed stone production, sand and
gravel mining and processing has numerous sources of process water emissions (e.g., wet screening, log
washers, rotary scrubbers, water classification, wet dust suppression, dewatering) (US EPA 2004a, US EPA
1995b). AP-42 presents only air (particulate matter emissions) from sand and gravel processing (US EPA
1995b). The water requirement and the associated liquid emissions to surface and groundwater are not
included in any of the LCI sources reviewed. USGS (2009) estimates that 125 to 4,160 liters of water is
used for every MT of non-metallic crude ore produced from mining or quarrying; this suggests that
aggregate production has a significant water demand and releases substantial amounts of process water for
either treatment or discharge to surface water bodies.
Both Stripple (2001) and Ecoinvent contain LCI datasets simulating non-US aggregate production
processes, although Stripple (2001) only includes emissions associated with energy consumption and
maintenance vehicle operation. Similar to US LCI (2012), Ecoinvent has a limestone production process
to model aggregate production, but also includes processes for gravel and sand quarry operation, limestone
quarry construction, and gravel and sand quarry construction.
As none of the existing aggregate production LCIs evaluated includes all the emissions discussed above,
the "Limestone, at mine" process included in the US LCI (2012) database to model aggregate production
was selected for use in the LCI presented in this report, as needed. Future efforts should consider
quantification of emissions associated with blasting agents manufacturing and use in mining operations,
mining/processing equipment manufacturing and maintenance, surface water emissions, and water
consumption. As presented below, the energy requirements estimated from USCB (2001) for producing
different aggregates are similar in magnitude to the "Limestone, at mine" process.
Fuel-use LCI data for aggregate mining and quarrying were developed from the 1997 Economic Census
Mining Subject Series (USCB 2001) based on total fuel-consumption data for the production of crushed
and broken limestone, crushed and broken granite, other crushed and broken stone, and construction sand
and gravel. Industry data for the production of each of these aggregates are organized by the North
American Industry Classification System (NAICS) code within USCB (2001). The 1997 codes describe
the aggregate production industries for limestone, granite, and other crushed and broken stone to include
establishments primarily engaged in developing the mine site, mining and quarrying the specific aggregate
and related rocks, and preparing the raw ore for use (e.g., pulverizing, grinding) (USCB 2013). The 1997
NAICS code for construction sand and gravel describes the mining industry as including one or more of
the following: pit operations; dredging operations; and washing, screening, and other preparation operations
for material production (USCB 2013).
Limited data were available in the economic surveys of 2002 and 2007; the data reported in 1997 were used
for estimating fuel consumption per unit aggregate production. The total aggregate production for each of
the four aggregate categories reported by USCB (2001) for 1997 was used to estimate energy consumption
per kg of aggregate production (with the exception of construction sand and gravel). Construction sand and
gravel production data were instead taken from the 1997 USGS Minerals Yearbook because approximately
40% of the total value of shipments of construction sand and gravel as provided by USCB (2001) was not
provided for all categories of materials. In addition to electricity use and consumption of the five specific
fuels listed by USCB (2001), there are two other categories of unclassified fuel use: "other" (e.g., wood,
coke, liquefied petroleum gas) and "undistributed." Together these two fuel categories represent from 18%
(i.e., crushed and broken granite) to 59% (i.e., construction sand and gravel) of a specific aggregate's total
fuel delivery cost. However, the actual fuel quantity was not published for these two categories of fuels;
only the fuel delivered cost was provided. Distillate fuel makes up the majority (i.e., 64-75%) of the total
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categorized fuel delivery cost for each of the four aggregate categories. Therefore, "other" and
"undistributed" fuel consumption was quantified as distillate fuel oil. This was done by multiplying the
delivery cost of these fuels with the ratio of the distillate fuel oil consumption to the distillate fuel oil
delivery cost.
The approach for estimating material production fuel consumption LCI data outlined above was used by
the US EPA (2003) to estimate emission factors for primary aggregate production. Table 2-4 presents the
estimated fuel consumption per kg mined and quarried aggregate (by specific aggregate type). For
comparison purposes, Table 2-4 also lists the fuel consumption data used for the "Limestone, at mine"
process included in the US LCI (2012) LCI database.
Table 2-4. Fuel Consumption per Kilogram Mined and Quarried Aggregate (USCB 2001 and
Bolen 1997)
Fuel Category
Coal (kg)
Distillate Fuel Oil
(L)
Residual Fuel Oil
(L)
Natural Gas (m3)
Gasoline (L)
Electricity (kWh)
Fuel Consumption (fuel unit/kg aggregate production)
Granite
(Crushed
and Broken)
W1
0.000614
0.000117
W
3.10E-5
0.00323
Construction
Sand and
Gravel
W
0.000700
5.26E-5
4.16E-5
2.27E-5
0.00266
Other Stone
(Crushed
and Broken)
_2
0.000835
4.63E-5
0.000246
2.75E-5
0.00350
Limestone
(Crushed
and Broken)
4.49E-5
0.000752
5.65E-5
7.50E-5
4.93E-5
0.00365
US LCI (20 12)
"Limestone, at
mine" Process
3.58E-5
0.000584
NP3
0.000140
5.11E-5
0.00423
1 "W" denotes fuel consumption quantities were withheld to protect individual company data
2 "-" denotes a value of 0
3 "jsjp" Denotes that the value was not provided
The US LCI (2012) process was developed based on data provided in Franklin Associates. It can be seen
that USCB-based estimates for limestone distillate fuel and coal consumption were greater than those used
in the US LCI (2012) dataset. However, natural gas, gasoline, and electricity estimates were lower than the
respective US LCI (2012) estimates. For comparison purposes, diesel consumption as provided in the US
LCI (2012) process was listed as distillate fuel oil. The source document cited by Franklin Associates could
not be located to explore the causes of the differences between the estimates presented above and the US
LCI (2012)'s data. While coal consumption data were withheld for crushed granite and construction sand
and gravel production, the fact that this fuel category was withheld (which suggests that the use of this fuel
was limited to a small number of producers), coupled with the fact that this fuel category was not even
included in the 2002 Economic Census for these industries, suggests that coal consumption is insignificant
in the production of these aggregates. Natural gas consumption data for crushed granite production were
not found for other Economic Census years.
Energy content values from the US Energy Information Administration were used to translate fuel
consumption quantities (mass and volume) into a common energy unit (kJ) to compare the cumulative
energy demand for producing the different aggregate types. The total fuel energy consumption per kg mined
and quarried aggregate (by specific aggregate type) is presented in Figure 2-1.
The energy associated with blasting agent and water use is not quantified in the data presented in Figure 2-
1. The total fuel energy consumption for producing the different aggregates is similar across the different
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aggregate categories. As can be seen, the total fuel energy consumption per kg limestone production
developed from USCB (2001) is comparable with the US LCI (2012) "Limestone, at mine" process.
2.5.6.2 Natural Soil Production and Fuel Consumption
Similar to the use of recovered CDD materials as recycled aggregate, several of the materials analyzed (e.g.
RSM, concrete, asphalt pavement, clay bricks) may be recovered and beneficially used as general fill (i.e.,
a soil substitute). The LCIs for primary soil production are needed for a comparative LCA of EOL
management. The energy-related LCIs were developed for natural soil production using production rate
and fuel consumption data for the equipment commonly used for soil production.
CAT (2006) reported typical cycle times and bucket sizes for 12 excavator models. These cycle times and
bucket sizes were used to estimate volumetric soil production rates. The volumetric production rate was
converted to a mass-based estimate assuming a soil density of 1,330 kg/m3 soil (USDA 2013). These
production rates were used in conjunction with the median value of the medium diesel consumption rate
range for each excavator model to estimate the diesel consumption per ton of soil excavated. The average
diesel consumption rate among the models is approximately 6.54 x 10~5 L/kg excavated soil and was
estimated according to the following equation:
=
es
nps ^ \60Bt
Where,
Fes = average diesel consumption rate per unit weight of excavated soil (L/kg)
Ps = soil density (kg/m3)
Bj = the bucket volume of the ith excavator model (m3)
Ci = the cycle time of the 1th excavator model (minutes)
Fj = median diesel consumption rate for the ith excavator model (L/hour)
n = total number of excavator models
The amount of energy required to excavate natural soil is substantially less than the amount of energy
necessary to mine and process (e.g., crush, fractionate) different aggregates. As shown in Figure 2-1, soil
production energy is about 2.53 kJ per kilogram of soil, or approximately 5% of the energy needed for
aggregate production.
Ecobalance (1999) estimates that more than 80% of municipal solid waste landfill (MSW) sites that use
cover soil acquire it from on-site sources. Thus, it is necessary to develop an LCI process dataset that
simulates the on-site transport of primary cover soil for CDD materials disposed of at MSW landfills. Data
on the heaped capacity and diesel consumption rate for six articulated truck models included in CAT (2006)
were used in combination with the average excavator soil production rate approximated above to estimate
the diesel consumption resulting from on-site cover soil transport. The load time for each truck model was
summed with the round-trip travel time, assuming an average truck speed of 15 km/hr over a 2-km round-
trip distance. The average fuel consumption of all the articulated truck models was 1.88 x 10~7 L diesel per
kg of excavated soil and was estimated according to the following equation:
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Fts = average diesel consumption rate per unit weight of onsite transported soil (L/kg)
m = total number of articulated truck models
D = round-trip distance for onsite cover soil transport (km)
V= average truck speed (km/hr)
Bj = the bucket volume of the ith excavator (m3)
Ci = the cycle time of the ith excavator (minutes)
n = total number of excavator models
Fj = median diesel consumption rate for the jth articulated truck model (L/hour)
Hj = heaped capacity of the jth articulated truck model (m3)
ps = soil density (kg/m3)
Information on particulate emissions resulting from soil excavation and on-site transport was not found.
Ecobalance (1999) found that the average cover soil travel distance from off-site production to MSW
landfills within the US and Europe was approximately 8 km. This is the distance assumed for off-site cover
soil transport for CDD landfills in this report's analysis.
2.5.6.3 Primary Aggregate Production Particulate Emissions
The US EPA (1995a) published particulate matter emission factors for crushed stone and pulverized mineral
processing and sand and gravel processing. Particulate matter emission factors are provided for various
steps of aggregate processing; however, separate emissions factors are published for
controlled/uncontrolled processing steps (e.g., crushed aggregate screening (controlled) versus crushed
aggregate screening (uncontrolled)). Sand and gravel processing emission factors are only provided for
industrial sand and gravel (which is processed differently than construction sand and gravel); because of an
absence of additional data, US EPA (1995b) recommends applying the emission factors published in the
crushed stone and pulverized mineral processing section for modeling emissions from construction sand
and gravel processing. The sum of uncontrolled emissions from all steps in processing crushed stone was
used to provide a total conservative particulates air emission factor for both crushed stone and sand and
gravel production processes for the following reasons:
• No data were available for emissions from primary and secondary crushing - emission factors for
these steps are not published.
• Background documentation provided in US EPA (2004) does not discuss the distribution of
controlled versus uncontrolled steps in the crushed stone processing industry.
• Emission factor ratings for the processing steps as provided in US EPA (2004) are typically
identified as below average and poor.
US EPA (2004) also categorizes uncontrolled aggregate processing particulate emissions into particulates
smaller than 10 microns. This specific particulate category was separately used for developing particulate
emission factors (i.e., PM<10, PM>10). AP-42 does not quantify the particulate emissions resulting from
aggregate blasting, excavation, transport on haul roads, or emissions from aggregate stockpiles, and (in
addition to primary and secondary crushing as noted above) no data were available for particulate emissions
resulting from wet drilling and truck loading/unloading of aggregates, as shown in Table 2-5.
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Table 2-5. Uncontrolled Particulate Matter Emissions from Crushed Stone and Pulverized Mineral
Processing (US EPA 2004)
Source
Primary Crushing
Secondary Crushing
Tertiary Crushing
Fines Crushing
Screening
Fines Screening
Conveyor Transfer Point
Wet Drilling - Unfragmented Stone
Truck Unloading - Fragmented Stone
Truck Loading - Conveyor, crushed
Total
PM > 10 microns
(g/kg Crushed
Stone)
ND
ND
0.0015
0.012
0.0082
0.114
0.00095
ND
ND
ND
0.0870
PM < 10 microns
(g/kg Crushed
Stone)
ND
ND
0.0012
0.0075
0.0043
0.036
0.00055
4E-5
8E-6
5E-5
0.0496
4 "ND" denotes that no data were available.
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!™
i
0)
==5 40 -
P
g! 30 -
LLI
c
o
^ 20 -
•a
z
^ ID-
'S
n -
2.53
41.3
41.3
45.9
50.2
57.2
^6
/
/
Figure 2-1. Total Fuel Energy Consumption per Kilogram Production of Aggregate and Soil
(developed from USCB 2001, Bolen 1997, and CAT 2006)
2.5.6.4 Recycled Aggregate Production Fuel Consumption
Energy consumption for processing demolished PCC and reclaimed asphalt pavement (PvAP) is provided
by Wilburn and Goonan (1998), based on data from an energy audit of a material recovery facility in Denver
(Colorado). However, the energy requirements for these materials are not categorized by fuel type (e.g.,
electricity, diesel). Therefore, an energy feedstock mix as 50% diesel and 50% electricity (same as that
used by US EPA (2003) to develop the dataset for the production of recycled concrete aggregate) was
assumed. US EPA (2004) does not provide an estimate of particulate emissions resulting from the primary
or secondary processing of crushed stone; due to this lack of data, particulate emissions associated with
processing of these recycled materials could not be estimated. Energy consumption data for processing
both demolished PCC and RAP are provided in Table 2-6.
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Table 2-6. Energy Consumption for Processing Demolished PCC and RAP
Energy
Diesel
Electricity
Unit
L
kWh
Energy Consumption (per
kg Material)
Demolished
PCC
0.000440
0.00472
RAP
0.000213
0.00229
2.5.6.5 Data Gap Analysis of Primary Aggregate Production
Table 2-7 summarizes LCI data identified for primary aggregate production. Only the GaBi and US LCI
(2012) databases provide LCI datasets for at least one type of aggregate production. WARM and AP-42
only provide greenhouse gas and particulate matter emissions, respectively, while Wilburn and Goonan
(1998) only discuss the energy required for processing primary aggregates.
Table 2-7. Overview of Aggregate Production LCI Data Available
Process
Aggregate
Production
WARM
P
GaBi
X
AP-42
P
Wilburn and
Goonan (1998)
P
US LCI (2012)
X
"P" and "X" denotes partial, and most comprehensive dataset currently available, respectively. These
notations are used throughout the report.
The following data gaps were identified after reviewing the extent of available US-based LCI information
on primary aggregate production:
1. Emissions information associated with blasting agent manufacture and detonation at
quarries. AP-42 (US EPA 1980) data on emissions resulting from explosives detonation could be
combined with rock constant information (Persson et al. 1993) and a representative in-place density
of unmined aggregates to approximate blasting emissions on a per-mass-mined basis. However,
additional information from explosives manufacturers would be necessary to estimate the
emissions associated with the manufacture of quarry-specific explosives.
2. Emissions from mining/processing/grinding equipment manufacturing. For a complete LCI of
the environmental burdens associated with aggregate production, it is necessary to quantify the
material, energy, and emission burdens associated with manufacturing all cradle-to-gate aggregate
production equipment. These data do not appear to be available.
3. Water emissions/consumption information from quarry work. Although USGS (2009)
provides an estimate of the range of water necessary for producing raw aggregate ore, specific
process water emissions associated with the production of various aggregate types were not located.
Based on the range provided by USGS (2009) (125-4,160 L water per MT crude ore), it appears
the aggregate production process may result in substantial discharges of suspended and
(potentially) dissolved solids to surface water.
2.5.7 Mixed CDD Processing
Calhoun (2012) discusses the mass fraction of recovered materials and diesel consumption resulting from
the operation of five Florida CDD processing (i.e., recycling) facilities for 2011. Diesel consumption on a
per-kilogram-material-processed basis was estimated as 0.00199 liters by dividing the total amount of diesel
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used by all the CDD processing facilities by the total mass of material received by all the CDD processing
facilities according to the following equation:
,
2,i=i ™>i
Where,
DF = diesel consumption per kilogram of CDD processed (L/kg)
Di = total diesel consumption at the ith CDD processing facility for 201 1 (L)
Mj = total mass of material received at the ith CDD processing facility for 201 1 (kg)
Similar equations were used to estimate fossil fuel consumption for the management of different materials
throughout the report. The electricity consumption on a per-material -processed basis was estimated similar
to the diesel consumption, but the estimate only used electricity billing data from a single north Florida
CDD processing facility. The south Florida CDD processing facilities did not provide the purchased
electricity cost even though this information was requested by Calhoun (2012). The total amount of
electricity used by the north Florida facility was estimated using the total 2010 electricity purchase amount
(i.e. $109,272) and the average 2010 retail price of electricity sold to the Florida industrial sector from EIA
(2014) of $0.0885/kWh. Approximately 1.23 million kWh of electricity consumption is estimated for 2010.
Calhoun (2012) organizes processed material outputs into 7 categories: wood, RSM, yard waste, concrete,
metal, cardboard and miscellaneous (waste residuals are assumed as the difference between the total mass
of received material and the sum of the processed material outputs). However, the north Florida facility
provided 4 additional categories of recovered material instead of the "miscellaneous" category reported by
the south Florida facilities: shingles, plastic, glass and textiles. For the purpose of developing a CDD
processing facility LCI dataset, it was assumed that the "miscellaneous" material recovered by the south
Florida facilities included these four materials at the same percentages as the north Florida facility.
The estimated diesel and electricity consumption for CDD processing facilities is approximately 1.99
milliliters and 0.025 kWh per kilogram of processed material. Figure 2-2 shows the estimated mass-
fractional representation of materials recovered or discharged from a CDD processing facility. Compressed
gas is another fuel described in Calhoun (2012) which is used at the CDD processing facilities for forklifts
and floor-sweeping units, but a fuel consumption estimate was not provided. Because CDD processing
facilities are not operated to recover residuals or RSM, these two material output flows were assigned as
waste flows in the LCI dataset. Therefore, diesel and electricity consumption are not allocated to either
residuals or RSM, and these materials are produced burden free to downstream processes.
Based on these material fraction output and diesel consumption estimates, Table 2-8 presents the proposed
LCI dataset for a CDD processing facility. Although no electricity requirement estimate was found, this
input flow was included as a placeholder. No nationwide average transport distance was found for mixed
CDD movement between the point of generation and a mixed CDD processing facility; a distance of 20 km
was assumed.
In addition to US-data, additional LCI information was found in Ecoinvent documentation. Doka (2009)
discusses the fuel and electricity consumptions associated with sorting and crushing building materials,
which includes various CDD components (e.g., wood, glass, bricks, concrete). As described in Doka
(2009), building material sorting plants typically use an up-front screening/separation process to remove
fines and bulky items such as metals, wooden poles, and windows. This separation step is followed by a
crushing/sorting step for larger materials such as concrete and brick. Based on this review, Doka (2009)
assumes a total electrical usage of 3.7 kWh/MT of building material where 1.5 kWh is the electricity usage
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estimated solely for crushers alone while the remaining 2.2 kWh/MT was assumed to be the electricity
usage for other sorting machinery.
Diesel fuel consumption occurs at CDD processing facilities from heavy equipment used to unload, sort,
transport, and load waste at facility tipping floors. The Doka (2009) diesel fuel consumption estimate for
fuel usage was also based on literature-derived values corresponding to the fuel demand of a skid-steer
loader; values ranged from 2.95 - 5.9 MJ/m3 of sorted building waste with an average value of 4.4 MJ/m3.
Residuals
18.56%
Wood
22.21%
RSM
19.84%
Plastic
0.11%
Textiles
0.25°-
Glass
0.30% Shingles
0.75%
Yard Waste
16.24%
Cardboan
2.98%
-Metal
5.97%
Concrete
12.79%
Figure 2-2. Weighted Average Mass Fraction of Materials Recovered or Discharged from Five
Florida CDD Processing Facilities (developed from Calhoun (2012))
Table 2-8. Proposed LCI Dataset: Mixed CDD Processing Facility
Input Flow
Mixed C&D
Truck transport, class 8, heavy
heavy-duty (HHD), diesel,
short-haul, load factor 0.75
Diesel, combusted in industrial
equipment
electricity, at industrial user
Output Flow
Source
Calhoun
(2012)
Source
Category
Construction and Demolition
Debris Management
Flows
Flows
Category
Unit
kg
t*km
L
kWh
Unit
Amount
1
0.001*20
0.00199
0.0250
Amount
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Wood, from CDD processing
facility
Yard waste, from CDD
processing facility
Concrete, from CDD
processing facility
Metal, from CDD processing
facility
Cardboard, from CDD
processing facility
Shingles, from CDD
processing facility
Glass, from CDD processing
facility
Textiles, from CDD processing
facility
Plastic, from CDD processing
facility
RSM, from CDD processing
facility
Residuals, from CDD
processing facility
Calhoun
(2012)
Calhoun
(2012)
Calhoun
(2012)
Calhoun
(2012)
Calhoun
(2012)
Calhoun
(2012)
Calhoun
(2012)
Calhoun
(2012)
Calhoun
(2012)
Calhoun
(2012)
Calhoun
(2012)
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
0.222
0.162
0.128
0.0597
0.0298
0.00752
0.00299
0.00251
0.0011
0.198
0.186
2.5.8 Landfilling
2.5.8.1 Background
Although recycling rates have risen steadily based on increased consumer awareness, grants, and other
incentives to encourage recycling, landfilling is still the predominant EOL management of discarded
materials in the US, primarily attributed to reduced cost. While CDD disposal typically occurs at CDD or
inert debris landfills, some CDD materials are disposed of at MSW landfills at their EOL phase. US EPA
(2014) estimated that the average CDD mass fraction of incoming loads received at US MSW landfills was
10.5% based on the results of 12 large-scale waste characterization studies.
The materials disposal LCI should include materials and energy inputs and emissions associated with
landfill construction, waste placement and compaction, and closure and post-closure-care activities along
with the long-term liquids and gaseous emissions pertaining to biogeochemical decomposition of deposited
materials. The domain of disposal related inputs and outputs considered varies significantly among
different LCA models and LCI databases. For example, US EPA's WARM only consider GHG emission
from materials transport, waste placement and compaction activities, whereas WRATE includes materials
and inputs, and emissions associated with landfill construction, operation, closure. Several other LCA
models account for only a smaller subset of these emissions. This section presents LCI for landfill
construction, operation, closure and post-closure activities.
2.5.8.2 Construction
Landfill construction requires a variety of material and energy inputs. Landfills are built as containment
systems with the goal of minimizing direct (e.g., waste-related) emissions to the surrounding environment.
The bottom liner of landfill cells is generally constructed via a combination of low-permeability (typically
<10"7 cm/sec) compacted earthen material and geosynthetic materials (typically 60-mil-thick HOPE). The
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purpose of the bottom liner is to contain and collect leachate and remove it out of the landfill cell, generally
using porous drainage media (e.g., gravel), piping, and mechanical pumps to prevent build-up of liquid on
the liner system. Emissions resulting from landfill cell construction occur during liner material
manufacturing, transport and use of heavy equipment for on-site soil excavation and liner installation.
The fuel consumption and material resources required for landfill construction would depend on the level
of environmental controls installed at the site. Composite liner systems are frequently installed at MSW
landfills, which often include multiple layers of different geosynthetic materials for both leachate-collection
and leak-detection purposes. Geosynthetics may be placed in contact with underlying low-permeability
earthen material, which commonly will require compaction prior to the placement of the geosynthetics. In
addition to the energy consumption of equipment needed to transport, place, compact, and weld liner
components, the environmental burdens resulting from geosynthetic manufacturing should be taken into
account.
Ecobalance developed an LCI for US MSW landfills for the Environmental Research and Education
Foundation in 1999 based on a survey of more than 100 MSW landfills across the US and Europe. Part of
this survey included compiling the average characteristics and fuel demand necessary for the construction
of the liner system and other support infrastructure. Ecobalance (1999) provides the average thickness and
the density of each of the liner components and, based on survey results, presents the average airspace use
per MSW landfill footprint area. Ecobalance data were used as a primary input for developing landfill
construction LCI for MSW-DST and EASETECH.
The upper end of the literature-reported density range of CDD materials as reported by Jambeck (2004),
359 kg/m3, was used in this analysis to estimate the MSW landfill footprint required per mass of CDD
material accepted at MSW landfills. The upper end of the range was selected as these density values are,
probably, representative of uncompacted CDD; in-situ density of CDD placed in landfill is expected to
greater than uncompacted CDD. This allowed an estimate of the mass of individual materials needed per
mass of CDD material accepted at an average MSW landfill. Ecobalance (1999) also developed an estimate
for the amount of diesel fuel required for MSW landfill construction on a mass-acceptance basis. The report
details the average transport distances for each construction material; these distances were multiplied by
their respective masses and the resulting mass-distance amounts were organized and summed by whether
materials were transported more or less than 35 km. Material transport greater than 35 kilometers was
modeled as long-haul transport and all other transport was modeled as short-haul.
Ecobalance (1999) presented an estimate the quantity of steel required to manufacture the equipment used
for construction. This estimate was performed by assuming the average lifespan and weight of a wheeled
scraper as 17,000 operational hours and 49,837 kg, respectively. The equipment hours used per mass of
waste was divided by the total lifespan operation hours of the equipment and then multiplied by the total
weight of the equipment.
Table 2-9 presents the proposed LCI dataset for MSW landfill material and energy construction burdens
associated with the placement of CDD materials at an MSW landfill site. CDD landfills, typically, are not
lined as no federal requirements for liners and leachate collection systems exist for CDD landfills; some
states require liner construction for CDD landfills. Data that detail the energy and material burdens
associated with the construction of an unlined CDD or inert debris landfill were not found. Golder
Associates (2005) used MSW landfill construction LCI as a proxy for CDD landfill for WRATE model due
to lack of data. No construction LCI are developed for unlined CDD landfill construction due to lack of
data.
Table 2-9. Proposed LCI Dataset: MSW Landfill Construction, for CDD Materials
| Input Flow | Source | Category | Unit | Amount |
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Clay, at production
HDPE Liner, at production
Geotextile, at production
Sand, at production
HDPE, at production
Steel, at production
PVC, at production
Asphalt pavement, at
production
Concrete, at production
Truck transport, class 8,
heavy heavy-duty (HHD),
diesel, short-haul, load
factor 0.75
Truck transport, class 8,
heavy heavy-duty (HHD),
diesel, long-haul, load factor
0.75
Diesel, combusted in
industrial equipment
Output Flow
MSW landfill construction,
for CDD materials
Ecobalance
(1999)
Ecobalance
(1999)
Ecobalance
(1999)
Ecobalance
(1999)
Ecobalance
(1999)
Ecobalance
(1999)
Ecobalance
(1999)
Ecobalance
(1999)
Ecobalance
(1999)
Ecobalance
(1999)
Ecobalance
(1999)
Ecobalance
(1999)
Source
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Flows
Category
Construction and Demolition
Debris Management
kg
kg
kg
kg
kg
kg
kg
kg
kg
t*km
t*km
L
Unit
kg
0.15
0.00019
3.80E-05
0.063
2.60E-06
1.60E-05
2.00E-06
8.50E-05
9.00E-05
0.0032
0.00011
0.00022
Amount
;
2.5.8.3 Operations
Waste placement and compaction begins following construction of the liner/leachate collection system.
Waste is filled in designated cells and lifts in a sequenced filling plan. Landfill operations generally include
placing and compacting waste materials as well as periodically applying cover soil to the exposed waste
surface. MSW landfills will commonly install a daily cover over the active waste face while CDD sites
may install a weekly cover or no cover at all. Besides the diesel energy necessary to place and compact
incoming waste, electricity is necessary to power numerous site facilities and buildings (e.g., scalehouse,
workshop, offices, lighting). Cover soil is assumed to represent 10% of the volume of waste material placed
at MSW landfills. However, cover soil is assumed to only represent 1.43% of the volume of waste material
placed at CDD landfills (i.e., it is only placed once on a weekly basis or l/7th of the daily cover amount).
Literature-reported CDD material densities were used to estimate the corresponding mass of cover soil
necessary for material placement at either a CDD or MSW landfill site, assuming a soil density of 1,330
kg/m3 (USDA 2013). These densities were necessary in order to translate cover soil requirements from a
volumetric to a gravimetric basis.
Ecobalance (1999) provides operational diesel requirements with and without daily cover soil application.
However, no estimate of electricity consumption is provided. IWCS (2014b) compiled and analyzed
electricity consumption and waste acceptance data from a regional MSW landfill in north-central Florida
to estimate electricity consumption on a per kg waste mass basis. All electricity use was included in the
estimate for MSW landfills except for electricity required for the recycling center, leachate pumping (e.g.
sumps), and leachate treatment (e.g. leachate aeration ponds). Leachate collection and treatment will be
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handled in a separate LCI process dataset. Electricity consumption at a CDD landfill was estimated based
on IWCS (2014b) data, but only included the electricity demand from the site's office and workshop. The
nationwide average emissions from waste collection and transport to each landfill site category were not
found; however, a transport distance of 20 km was assumed and included in each CDD material's disposal
datasets. Table 2-10 and
Table 2-11 present LCI datasets that estimate energy consumption during the operation of CDD and MSW
landfills, respectively. CDD material-specific cover soil requirements depend on the density of the CDD
material and are therefore included in the material-specific disposal process datasets presented in the
subsequent chapters.
Ecobalance (1999) presents an estimate of the quantity of steel used for equipment used to place and
compact each unit mass of waste according to whether the site has daily or weekly/no cover soil
requirements. It was assumed that landfills with a daily cover soil requirement are reflective of MSW
landfill practices while sites with a weekly/no cover soil requirement would be representative of CDD
landfill practices. Steel requirement estimates were performed by assuming the average lifespan and weight
of a refuse compactor as 8,000 operational hours and 32,821 kg, respectively. The equipment hours used
per mass of waste was divided by the total lifespan operation hours of the equipment and then multiplied
by the total weight of the equipment.
It should be noted that these LCIs do not include emissions associated with operations equipment
decommissioning or for manufacturing/disposing service and maintenance consumables (e.g., lubricating
oil, rubber tires) due to lack of US-specific data. Golder Associates (2005) compiled material usage for
WRATE; the sources of data used to develop these estimates were not provided by WRATE.
Table 2-10. Proposed LCI Dataset: CDD Landfill Operations
Input Flow
Diesel, combusted in industrial equipment
Electricity, at industrial user
Steel, at production
Truck transport, class 8, heavy heavy-duty
(HHD), diesel, long-haul, load factor 0.75
Output Flow
CDD landfill operations
Source
Ecobalance
(1999)
IWCS (2014b)
Ecobalance
(1999)
Ecobalance
(1999)
Source
Category
Flows
Flows
Construction and
Demolition Debris
Management
Category
Construction and
Demolition Debris
Management
Unit
L
kWh
kg
t*km
Unit
kg
Amount
0.00077
0.00064
0.00011
4.4E-05
Amount
;
Table 2-11. Proposed LCI Dataset: MSW Landfill Operations
Input Flow
Diesel, combusted in industrial equipment
Electricity, at industrial user
Steel, at production
Source
Ecobalance
(1999)
IWCS (2014b)
Ecobalance
(1999)
Category
Flows
Flows
Construction and
Demolition Debris
Management
Unit
L
kWh
kg
Amount
0.0012
0.0013
0.00016
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Truck transport, class 8, heavy heavy-duty
(HHD), diesel, long-haul, load factor 0.75
Output Flow
MSW landfill operations
Ecobalance
(1999)
Source
Category
Construction and
Demolition Debris
Management
t*km
Unit
kg
6.4E-05
Amount
;
2.5.8.4 Closure and Post-Closure
Once a landfill has reached permitted capacity, it will undergo a closure process that usually involves
installing a low-permeability or impervious final cover system to minimize precipitation infiltration and
landfill gas emission. A gas collection and control system (GCCS) is typically installed at an MSW landfill
before closure to control fugitive LFG emission. Unlike MSW landfills, CDD landfills do not typically
have an active GCCS. LCI associated with closure include cap installation (material and energy usage),
construction of other site infrastructure (such as roads), and continued operation of leachate and gas
collection and management systems, environmental monitoring, and post-closure care activities.
Ecobalance (1999) summarizes the quantities of individual cap materials necessary to close an MSW
landfill, based on a "typical final closure cover profile," which includes layers of soil, geotextile, sand, clay,
and HDPE. Consumption of soil and clay materials is aggregated by Ecoblance (1999) into a single "soil"
material category to quantify fuel consumption for soil production- and transport-related emissions. This
material combination was preserved in the LCI dataset provided in Table 2-12. The materials necessary
for installing a GCCS and gas monitoring system are also provided for the closure phase of the MSW
landfill and are organized into the consumption of HDPE and PVC.
Ecobalance (1999) provides an estimate of the quantity of steel used for manufacturing of equipment steel
used to place and compact each unit mass of waste by assuming the average lifespan and weight of a
wheeled scraper as was assumed for landfill construction (i.e., 8,000 operational hours and 32,821 kg,
respectively). The equipment hours used per mass of waste was divided by the total lifespan operation hours
of the equipment and then multiplied by the total weight of the equipment.
During the post-closure-care period (assumed 30 years), Ecobalance (1999) assumes that 10% of the cap
will need to be replaced due to erosive wear. The proposed LCI includes the soil and fuel (diesel)
requirement for replacing 10% of the cap over the 30-year post-closure-care period. The soil and fuel
amounts provided by Ecobalance (1999) for closure were increased by 10% to account for this additional
soil needed over the post-closure care period. The fuel consumption resulting from site inspections (eight
inspections were assumed to occur annually) and site mowing is also estimated on an annual basis. These
emission factors were multiplied by the 30-year post-closure-care period and are included in Table 2-12 as
"Gasoline combustion, in industrial equipment."
From an LCI perspective, constructing and operating a GCCS entails emissions from producing and
transporting system components and energy demands from GCCS construction and installation. GCCS
commonly include a flare or other destruction device (e.g., an internal combustion engine) to oxidize
methane and other chemicals of concern to carbon dioxide. However, the LCI presented below do not
include materials and energy input for constructing a blower/flare station.
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Table 2-12. Proposed LCI Dataset: MSW Landfill Closure and Post-Closure, for CDD Materials
Input Flow
Soil, at production
HDPE geomembrane, at
production
Geotextile, at production
Sand, at production
HDPE, at production
PVC, at production
Steel, at production
Truck transport, class 8,
heavy heavy-duty (HHD),
diesel, short-haul, load
factor 0.75
Truck transport, class 8,
heavy heavy-duty (HHD),
diesel, long-haul, load
factor 0.75
Diesel, combusted in
industrial equipment
Gasoline, combusted in
industrial equipment
Output Flow
MSW landfill closure, for
CDD materials
Source
Ecobalance
(1999)
Ecobalance
(1999)
Ecobalance
(1999)
Ecobalance
(1999)
Ecobalance
(1999)
Ecobalance
(1999)
Ecobalance
(1999)
Ecobalance
(1999)
Ecobalance
(1999)
Ecobalance
(1999)
Ecobalance
(1999)
Source
Category
Construction and Demolition Debris
Management
Construction and Demolition Debris
Management
Construction and Demolition Debris
Management
Construction and Demolition Debris
Management
Construction and Demolition Debris
Management
Construction and Demolition Debris
Management
Construction and Demolition Debris
Management
Flows
Flows
Category
Construction and Demolition Debris
Management
Unit
kg
kg
kg
kg
kg
kg
kg
t*km
t*km
L
L
Unit
kg
Amount
0.42
0.00012
3.90E-05
0.13
8.20E-06
4.20E-06
6.20E-06
0.0077
7.20E-05
7.40E-05
6.20E-07
Amount
;
2.5.9 Landfill Leachate Emissions
Landfill leachate is generated as precipitation or waste-entrained moisture percolates through the waste
material and dissolves and retains various compounds. Unlined landfills or landfills with damaged bottom
liners have the potential to release landfill leachate to underlying soils and groundwater. In LCI databases
and models these are generally modeled as emissions to water, though leachate may contain dissolved
gaseous species that are ultimately released to the atmosphere. As mentioned previously, CDD landfills do
not carry a federal requirement for liners and leachate collection systems like MSW landfills. Leachate
emissions are caused by the release of compounds/elements in the waste materials themselves, resulting in
direct (i.e., waste-specific) emissions. Models and/or databases often do not handle leachate emissions on
a waste-specific basis but rather on assumptions of leachate composition from mixed waste streams (e.g.,
MSW leachate), due to the relative lack of data on emissions from individual waste components,
particularly over large spans of time. The timeframe over which leachate emission continues to occur after
the waste placement complicates estimations of long-term leachate emissions. The handling of leachate
emissions by different models is described below. It should be noted that most of these models are specific
to MSW and, in general, do not include data for CDD materials.
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2.5.9.1 WARM
WARM estimates the greenhouse gas (GHG) emissions associated with the EOL management of various
materials, including CDD constituents. Based on a screening analysis by Freed et al. (2004), US EPA
(2012a) recognized that an insignificant fraction (<1%) of the carbon input into a landfill dissolves into
leachate. Leachate carbon storage was not ultimately included in the model; emissions of other
contaminants such as heavy metals, anions, and cations are not considered as well. Leachate recirculation
to enhance the waste decomposition rate is recognized and the model provides LFG-specific GHG
emissions for four levels of moisture content (qualitatively specified as dry, average, wet, or bioreactor)
(US EPA 2012a). The GHG emissions from electricity and fuel use associated with leachate collection and
management are not included.
2.5.9.2 Athena's Building Impact Estimator
The Athena Impact Estimator for Buildings does not include emissions associated with leachate collection,
treatment, or discharge of untreated/treated leachate into the environment.
2.5.9.3 WRATE
The leachate-specific emissions description presented in this section is primarily based on a report by
Golder Associates (2005). The Waste and Resources Assessment Tool for the Environment (WRATE) uses
material-specific leachate emissions for 16 primary waste categories typical of MSW. While the majority
of the primary waste categories included in the model are specific to MSW, some CDD materials (e.g.,
wood, ferrous and non-ferrous metals) are also included (Golder Associates 2005, 2014). While the
documentation discusses leachate emissions associated with inert wastes, this waste stream is not included
in the current version of the model.
WRATE provides leachate emissions for three predetermined landfill sizes (2.25-, 5-, and 10-million MT
capacities) and three liner types (engineered clay, HDPE/clay composite, and dense asphaltic concrete) and
estimates emissions of several contaminants identified by Hall et al. (2001) using LandSim (version 2.5
was the most current version and in use by WRATE at the time of the publication of this report). LandSim
is a probabilistic model developed by Golder Associates for the United Kingdom (UK) Environment
Agency for modeling leachate emissions to groundwater using probability density functions for parameters
such as the number of pinholes and tears in the landfill liner (Drury et al. 2003; Golder Associates 2005).
WRATE models landfill-related emissions for a 20,000-year period. LandSim accounts for physical and
chemical deterioration of the flexible membrane liners over time and assumes that the leachate extraction
and treatment would cease following the post-closure-care period. The model does not consider
deterioration of mineral components (clay, geosynthetic clay liner, dense asphaltic clay liner) with time.
The total mass loading to the environment is the sum of the loading to groundwater through leakage in the
bottom liner and mass loading to surface water following treatment at a leachate treatment plant; only
leachate collected (remaining after leakage from the base of the site) is treated before being discharged into
the environment. The mass loading rates are estimated based on temporally-varying contaminant
concentrations, leachate collection/leakage rate, contaminant-specific leachate treatment efficiencies, and
waste amounts.
Leachate-related emissions for 30 inorganic and organic contaminants are modeled for MSW. The initial
contaminant concentrations are either based on LandSim default concentrations (primarily based on
Robinson (1995)) and data reported by Knox et al. (2000) and Robinson et al. (2004). The data published
by Robinson (1995) and Knox et al. (2000) could not be located for a detailed review. Robinson et al. (2004)
presented composition of leachate from different type of facilities accepting different waste types
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(incinerator ash, processed MSW, untreated MSW). For example, the leachate quality data for a landfill
accepting untreated MSW are based on limited numbers of samples collected from three landfill sites in
Europe.
The emissions of non-volatile and volatile species are assumed to exponentially decline with respect to L:S
ratio and time, respectively. The decline rates are contaminant specific and are based on a laboratory-scale
leaching test of four 20-kg samples collected from a landfill site in North Lincolnshire, UK. The
concentrations of various contaminants leached at multiple L:S ratio were measured.
LandSim estimates leachate generation based on effective rainfall, a parameter estimated using both
precipitation and an infiltration rate depending on cap. Leachate generation for the first 20 years is assumed
to occur instantaneously as the waste is exposed to the precipitation. The model assumes the presence of a
polyethylene flexible membrane liner (FML) cap after 20 years and considers FML degradation over time
for estimating the infiltration rate. The onset of degradation is assumed to begin in 250 years and the end
point is assumed to occur 1,000 years after landfilling ceases (when grassland infiltration rates are assumed
after the degradation endpoint).
Leachate leakage through the liner system is estimated assuming 1 m of head on the liner, the number of
tears and holes as well as liner oxidation, hydraulic conductivity and thickness of compacted clay or DCA,
and surface area of the liner (the regulatory limit for the UK). The performance of DCA, geosynthetic clay
liners and compacted clay is assumed to remain constant over time. HDPE liners are assumed to degrade
over time, similar to the landfill cap, where the area of defects doubles periodically (default time of 100
years) (Drury et al. 2003). Leachate emissions to groundwater are based on contaminant transport modeling
through the mineral part of the liner system and the unsaturated zone above the groundwater table.
WRATE assumes that collected leachate is pumped from the landfill to a leachate treatment plant, though
no emissions associated with electricity or fuel usage for leachate conveyance are included in the model
(Golder Associates 2005). Contaminant-specific treatment efficiencies are based on research by Robinson
and Knox (2004) and a (unreferenced) personal communication by Robinson (2004). The treatment
efficiencies range from 0% (e.g., C1-, K+, Na+) to 95.5% (NHs-N). The efficiency data for chemically
similar compounds or elements used for contaminant treatment efficiency were not available. The total
loading for each contaminant was allocated to individual waste streams by an "expert panel" of 14
individuals comprised of academic researchers, operators, consultants and regulators. Individuals within
the panel were allowed to present their thoughts to the group for those waste streams for which they had
specific knowledge. Additional details on the allocation process were not available. Although the
documentation discusses the estimation of a loading factor based on elemental content of various materials,
the role of this factor on the leachate emissions estimate is not clear. Moreover, it is not clear whether
loading factors include emissions associated with leachate treatment plant residuals management.
2.5.9.4 MSW-DST
MSW-DST leachate LCI datasets include the release of effluents from leachate treatment and the release
of uncollected leachate to the environment. The LCI also includes energy and materials required to transport
and treat leachate. The model calculates environmental contaminant loading rates based on an estimated
leachate generation rate, leachate collection efficiency and treatment efficiency, and contaminant
concentration for each waste constituent for three landfill types: traditional, bioreactor, and ash.
The leachate generation rate is estimated based on precipitation and a time-varying precipitation fraction
that enters the landfill. The model assume 20%, 6.6%, 6.5%, and 0.04% of the total precipitation enters the
landfill from 0-1.5, 1.5-5, 5-10, and after 10 years of waste placement, respectively, based on field data
reported for multiple sites (Ecobalance 1999). Landfill documentation by NCSU and ERG (2011) is not
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clear whether the same approach and time-varying precipitation fractions are used for estimating leachate
generation for all three landfill types. Also, it is not clear whether the model uses region-specific
precipitation for the leachate generation rate (selected from a total of nine US regions). The model assumes
a leachate collection and treatment time horizon of 100 years. The model assumes an insignificant leachate
generation in the post-closure period (after 100 years) due to the placement of a low-permeability cap at
the end of the operating period.
Some discrepancies were identified between the model documentation (NCSU and ERG 2011; Sich and
Barlaz 2000) and the current version of the software, which has been modified since publication of the
model documentation. For example, model documentation states that the timeframes for leachate collection
and treatment can be user-specified, however, the current version of the model does not offer this flexibility.
A leachate collection efficiency of 99.8% is used to estimate the leachate collection rate. The model
assumes that 100% of the collected leachate is sent to a treatment plant for the entire 100 years for all three
types of landfills except for the first 20 years for bioreactor landfills. The leachate collected from a
bioreactor landfill over the first 20 years is assumed to be recirculated. The model considers biochemical
oxygen demand (BOD), chemical oxygen demand (COD), ammonia (NHs), phosphate (PO.4), total
suspended solids (TSS), arsenic, cadmium, chromium, lead, mercury, selenium, and silver emissions for
MSW landfills. The model documentation also lists several hydrocarbons, but these do not appear to be
included in the model. The model considers COD, NHs, PO.4, arsenic, cadmium, chromium, copper, iron,
lead, mercury, selenium, silver, and zinc for leachate from ash monofills. A constant concentration
throughout the modeling period is assumed for ash monofill leachate.
The concentrations of all the contaminants except BOD and COD were assumed to be constant over time.
The BOD concentration was assumed to be 10,000 mg/L for the first 1.5 years (1 year for bioreactor
landfills), linearly declining from 10,000 mg/L to 1,000 mg/L from year 1.5 to year 10 (from year 1 to year
3 for bioreactor landfills), linearly decreasing from 1,000 mg/L to 10 mg/L from year 10 to year 50 (year 3
to year 10 year for bioreactor landfills), and a constant concentration of 10 mg/L after 50 years (10 years
for bioreactor landfills). The COD concentration is estimated based on BOD concentration and the
BOD/COD ratio is adjusted based on waste age. A COD concentration of 12,500 mg/L for the first 1.5
years (1 year for bioreactor landfills), linearly declining from 12,500 mg/L to 3,333 mg/L from year 1.5 to
year 10 (year 1 to year 3 for bioreactor landfills), linearly decreasing from 3,333 mg/L to 1,000 mg/L from
year 10 to year 50 (year 3 to year 10 for bioreactor landfills), and a constant concentration of 1,000 mg/L
after 50 years (10 years for bioreactor landfills).
TSS, NHs, PO.4, and metal concentrations in leachate for MSW landfills are reported as based on data
reported by Ecobalance (1999). The ash monofill leachate contaminant concentration data are based on the
leachate quality data from five ash monofills reported by US EPA (1990). US EPA (1990) reported ash
characterization data based on five individual composite ash samples collected from five incineration
facilities and one to seven leachate samples were collected from each of the landfill sites that accepted ash
from these facilities (where all but one of the landfill sites were ash monofills).
LCI emissions related to leachate transport to a wastewater treatment plant (WWTP) are based on travel
distance, leachate load, and the pre-combustion and combustion emissions of fuel used for transport.
However, the information source for these emissions was not available in the model documentation. The
emissions from treated leachate discharge are estimated based on treatment efficiencies in Robinson and
Knox (2003), US EPA (1989), and US EPA (1992) (as cited in NCSU and ERG 2011) for an average
WWTP. Treatment efficiencies range from 21.6 to 98% removal depending on the constituent- e.g., 21.6%
treatment removal for PO4 and 98% for NH3.
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The model also includes emissions associated with electricity use for leachate treatment and biogenic
carbon dioxide emissions associated with BOD removal. A user-specified regional energy mix can be used
for energy-consumption-related emissions (Dumas 1999). The model also estimates sludge production
associated with BOD, PO.4, metals, and TSS removal.
The model calculates the total amount of these contaminants released into the environment (referred to as
a contaminant yield) (mass of contaminant per unit waste mass) based on the model's leachate generation
and collection rates and post-treatment contaminant concentrations. The generic MSW contaminant yields
are allocated to different waste materials. The BOD, COD, and TSS yields are allocated based on the LFG
attributed to the waste components. NHs and PO4 are allocated to waste fractions based on the initial
concentration of these contaminants for different waste materials reported by Barlaz (1997). Grass and
food waste account for most of the NH3 and PO4. The generic MSW metal yields are allocated to individual
waste components based on the total metal content of specific waste components, as reported by AJ
Chandler & Associates Ltd. (1993) (as cited in NCSU and ERG 2011). A copy of the report by AJ Chandler
& Associates Ltd. could not be found through an extensive web search for further review. Minor organic
compounds, which are all hydrocarbons (11 in total), were reported to be considered in the model by older
MSW-DST documentation authored by Sich and Barlaz (2000), but these trace organics are not included
in the recent version of MSW-DST model documentation by NCSU and ERG (2011).
The emissions associated with electricity and materials (pipes, gravel, geotextile, pumps etc.) used for the
leachate collection system are not accounted for in the MSW-DST. Electricity used by leachate pumps and
ancillary equipment for the operational phase is not considered. The model calculates the amount of fuel,
PVC, and concrete (i.e., consumables) used in the leachate recirculation system (LRS) (for bioreactor
landfills) because the LRS is installed during waste filling. After the construction-phase, LCI financial and
environmental parameters associated with operational consumables are considered as part of the LCI for
the landfill. Horizontal trenches are assumed to be constructed with perforated PVC pipe and sand and the
vertical wells are assumed to be constructed with perforated concrete pipe filled with gravel. The model
does not account for sand and gravel used for constructing leachate recirculation devices. The model
includes emissions associated with the production of fuel, PVC, and concrete used for bioreactor landfills.
2.5.9.5 EASETECH
EASETECH estimates leachate generation based on user-specified site geometry, net infiltration, and
leachate collection efficiency that may be set differently for different time periods. EASETECH models
the release of 33 contaminants with leachate and assumes a default leachate composition for four time
horizons (0-2 years, 3-10 years, 11-40 years, and 41-100 years), which is independent of waste composition.
The concentrations of the leachate constituents decrease with each subsequent time period. The model
allows the user to assign unique leachate constituent concentrations for the different time periods.
Based on user-specified percentages, the model allocates leachate into collected and uncollected categories.
The uncollected leachate is assumed to be discharged to surface water. EASETECH allows the user to
simulate the quality/presence of a liner by specifying leachate collection efficiencies, which also may be
changed for different time periods. The model accounts for the discharge of the 33 constituents released
with either uncollected or with collected and treated leachate, where all the contaminants except COD are
allocated to the surface water compartment; COD is allocated to an unspecified air compartment as fossil
carbon dioxide.
Although the model does not include emissions associated with collecting and transporting leachate to a
WWTP, a leachate transport process can be readily inserted into the model. The model accounts for energy
and the associated emissions for leachate treatment; the model assumes 9 kWh of electricity consumption
for the treatment of each 1,000 kg leachate. The total direct emissions associated with leachate release to
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the environment are estimated by summing the emissions from uncollected leachate with emissions from
treatment plant discharged effluent; the contaminant loading within the effluent are based on user-specified
treatment efficiencies. The model's default leachate composition is based on the data reported by Reinhart
and Grosh (1998) and Kjeldsen and Christophersen (2001). Reinhart and Grosh (1998) reviewed Florida
Department of Environmental Protection (FDEP) leachate composition data from 39 lined Florida MSW
landfills to characterize Florida MSW leachate. Kjeldsen and Christophersen (2001) characterized leachate
at 106 old MSW landfills and at one modern, lined Danish MSW landfill. Leachate samples from the old
landfill sites were taken from either within the waste mass or within 50 meters of the landfill border. The
timespan over which leachate samples were taken was not provided for these studies. The model cites the
use of the data reported by Reinhart and Grosh (1998) for developing the pollutants discharged from the
wastewater treatment plant, but no such data were found in Reinhart and Grosh (1998).
2.5.9.6 GaBi
Twelve of the 59 datasets identified to include landfill leachate are specific to the US in GaBi. Five of these
landfill process datasets are for landfilling multi-component (i.e., heterogeneous) waste streams:
biodegradable waste and MSW (under average, arid, moderate, and wet climatic conditions, for four total
MSW datasets). Seven US landfill disposal datasets are related to specific wastes: ferrous metals, glass/inert
waste, paper waste, plastic waste, textiles, untreated wood, and wood products (e.g., oriented strand board,
particleboard). Landfill leachate parameters and processes described in the metadata for each US process
dataset were identical and are described in this section.
Leachate-related emissions for the US process datasets consider leachate generation, collection,
recirculation, and treatment. Leachate generation is determined based on precipitation. The US annual
average precipitation is assumed for the process datasets except those specific to arid, moderate, and wet
climatic zones. For climate-specific process datasets, the US states within those zones are identified and
the zone-specific annual average precipitation is used. The US precipitation data were reported in the
metadata to originate from the National Oceanic and Atmospheric Administration's (NOAA's) climatic
data center.
The GaBi databases for the US are developed to be representative of national/regional data and the amount
of waste landfilled assumed is based on research from US EPA and Levis and Barlaz (2011). Landfill
characteristics are based on US national averages, attributed to Ham et al. (1999) and Themelis and Ulloa
(2005). Themelis and Ulloa (2005) report quantities of waste landfilled (for 42 US states), operational US
landfills, mean waste depth, density, and other characteristics.
The leachate collection efficiency in the US process datasets was reported in the metadata as 70% (though
no reference was cited for this information). The leachate recirculation rate (i.e., % of leachate generated
which is recirculated) was based on Benson (2007), where five field bioreactor sites that were examined
showed 68.4% of leachate recovered and recirculated. Metadata states that 80% of US Landfills have some
recirculation program (attributed to personal communication with Craig Benson (2012)). The product of
these rates gives the total recirculation rate of 54.7%, which is used in the US landfill process datasets.
Benson (2007) selected sites representative of contemporary US bioreactor practices, and conventional
landfills were not examined.
The only leachate constituents US GaBi process datasets appear to include are COD and BOD. Metadata
cites Kjeldsen et al. (2002) as the source for the COD/BOD ratio in MSW leachate (0.1). However, Kjeldsen
et al. (2002) reports the long-term BOD/COD ratio in MSW leachate as 0.1, a ratio consistent with other
sources. Kjeldsen et al. (2002) reports leachate data for many other constituents along with temporal
variation characteristics; it is unclear whether any of this additional data are included in the GaBi datasets
and if BOD/COD emissions are waste-specific.
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Leachate treatment for US landfill process datasets occurs via activated carbon adsorption and flocculation
(unreferenced in the metadata). Leftover sludge from the leachate treatment process is disposed of in the
landfill and is assumed to be dried through combustion of natural gas. No information on the time period
considered by US process datasets is included. There are other landfill process datasets containing leachate
processes for areas outside the US; 47 landfill process datasets were found in GaBi for areas outside the US
(typically countries within the EU). Similar to the US data, it is not clear whether leachate emissions are
waste-material specific.
Non-US MSW landfill datasets include 60% transpiration/runoff of precipitation, no leachate recirculation,
and 70% leachate collection efficiency (all unreferenced). Finnveden (n.d.) is cited in the metadata for
assumptions of exponential solubility of fluids used for leachate-related solubility calculations. All non-US
datasets use a landfill with fixed dimensions for a 100-year period. Leachate treatment includes activated
carbon and flocculation with sludge disposal in a landfill.
Non-US CDD process datasets that include a "landfill leachate" process are as follows: construction rubble
on inert matter landfill, landfill for inert matter (construction waste), and landfill for inert matter (with
separate datasets for individual CDD components such as aluminum, steel, glass, glass/inert waste). The
leachate technology descriptions for the non-US inert matter landfill process datasets match those of non-
US MSW landfill process datasets, with changes to the transpiration rate and leachate collection efficiency
to 50% and 60%, respectively.
2.5.9.7 Ecoinvent
Ecoinvent includes LCI for four types of landfills: inert, residual, slag, and sanitary (i.e., MSW). CDD
materials are disposed of only in inert and sanitary landfills (Doka 2003a). Ecoinvent does not consider the
environmental effect of leachate from inert landfills and residual and slag compartment landfill units do not
accept CDD materials (e.g., they only accept ash, desulfurization residues, and industrial waste). Therefore,
only sanitary landfill LCI dataset information is discussed in this section. Materials-specific emissions of
41 chemical elements are included for various waste constituents. The following waste constituents can be
used as proxy for CDD materials: wood, wood ash, gypsum, and cardboard.
Leachate-related emissions are divided into short- (<100 yr) and long-term (year 100 to year 60,000)
emission periods. Doka (2003a) addresses this temporal distinction as a somewhat arbitrary choice,
inclusive of the time periods studied by Zimmermann et al. (1996) (as cited in Doka 2003a). The Ecoinvent
model assumes that all the leachate produced over the short-term period is collected and treated at a WWTP
and that the liner and leachate collection system remain intact throughout that period (Doka 2003a). At the
WWTP, treatment sludges are incinerated at a municipal incineration facility and the incineration residuals
are placed in a residual material or slag compartment landfill. After treatment at the WWTP, the effluent
is modeled as discharged to surface water (Doka 2003c). Long-term leachate management assumes that
after 100 years the collection system fails and all leachate produced is released to groundwater (Doka
2003a).
Theoretical emission potential of various elements is estimated based on the material-specific degradability
rate and elemental content along with waste composition. Degradability refers to decomposition and
mineralization of materials in landfill. Material-specific degradability is calculated based on the fraction
of carbon released from individual materials during the first 100 years, based on data presented by Micales
and Skog (1997). The degradability rate for cardboard, wood, and gypsum is estimated to be 32%, <3.3%,
and 100%, respectively. In other word, 100% of gypsum is estimated to mineralize within 100 years. It is
assumed that all the elements release from material with the same rate. For example, 100% of both calcium
and sulfate in gypsum will mineralize. Some fraction of the elements once released from the waste matrix
may undergo chemical transformation and be retained in the landfill, while the rest exit the landfill with
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gas or leachate. For example, a portion of sulfate (from gypsum) is reduced to hydrogen sulfide and leaves
the landfill as a gaseous emission, another fraction of the sulfate may transform to metal sulfide and
precipitate out, and the rest would be released with leachate. The amount of elements released with gas
and leachate are estimated based on release factors, which are specific to elements.
An average release factor representing the expected release after taking into account elemental re-
precipitation within the landfill for the different elements is calculated as the ratio of the actual to the
theoretical leachate emissions of the element. The "actual" leachate emissions are estimated as the product
of the leachate volume released over the first 100 years and the average leachate concentration of that
element (assumed constant over the first 100 years) as estimated from eight studies analyzing MSW landfill
leachate.
Total emissions for each element are estimated based on the degradability rate, the elemental concentration,
release rate, and the fractional representation in MSW for each specific waste material. This estimate is
partitioned into gaseous and leachate emission using % gas factors reported by Belevi and Baccini (1989).
The elemental concentration of the different contaminants is assumed to be constant for the first 100 years.
Long-term leachate emissions in sanitary landfills are divided into two time periods; the first occurs
following year 100 to year 4,500 and the second occurs following year 4,500 to year 60,000. A first-order
decay model is used to estimate the long-term decrease in elemental concentration in leachate and to
estimate the long-term leachate emission; as described above, Ecoinvent LCIs assume 100% of leachate
over long-term is emitted into the environment without treatment.
Some emissions related to the construction of a leachate control infrastructure are considered by Ecoinvent.
Sanitary landfills are modeled at a set size with a liner consisting of gravel, bituminous concrete, and
polyethylene, and the energy demand for the liner as a whole is approximated as 0.5 L/m2 of sealed surface
(Zimmermann et al. 1996, as cited in Doka 2003). Eight concrete leachate tanks connected to the sewer are
assumed. Consumables (e.g., PVC, cast iron, diesel fuel use) associated with the construction of the tanks,
sewer pipe, and leachate collection pipes are inventoried in Ecoinvent. Doka (2003a) provides the LCI data
(e.g., energy demand) of the infrastructure required for completing the Ecoinvent modeled sanitary landfill,
which has a 1.8-million-ton capacity.
2.5.9.8 Leachate Modeling Summary
Table 2-13 summarizes the leachate-related flows, which are considered in these models. An "X" indicates
that the consideration of that flow is built into the model. A "P" indicates that only partial information was
available for that flow. As shown in the table, only limited information is available on emissions to
groundwater as a result of the leaching of waste materials. However, it should be noted that no information
was found which estimated CDD material leachability in a CDD landfill or land-applied beneficial use
application. Therefore, for the purposes of developing a landfill disposal management LCI for the different
CDD materials presented in this report, literature was reviewed to identify sources of material-specific
Synthetic Precipitation Leaching Procedure (SPLP) and Toxicity Characteristic Leaching Procedure
(TCLP) data. SPLP data was selected as representative of leaching which occurs as a result of precipitation
infiltration through CDD materials in either a CDD landfill or a beneficial use land application (e.g., use as
a fill material). TCLP data was used to estimate leachability of CDD materials in an MSW landfill. The
majority of the CDD materials were only modeled with respect to disposal in an unlined CDD landfill or
land-applied beneficial use application. Due to an absence of information, the MSW landfill disposal LCIs
of materials for which TCLP data were found (i.e. wood, RSM) do not include emissions information with
respect to leachate collection, treatment and treated residual discharge; emissions to groundwater are
presented as if no leachate collection/interception occurs.
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Table 2-13. Leachate-related Inflow and Outflows in LCA Models
Flow
Electricity (Pipe Welding)
Emissions - LCS
Installation (Piping,
Gravel, Geotextile)
Inputs - LCS Pipes and
Fittings
Inputs - Gravel/Geotextile
Inputs - Leachate
Pumps/Storage Tanks
Electricity (Pumps and
Ancillary Equipment)
Electricity - Leachate
Treatment
Fuel - Leachate Transport
to Treatment
Emissions - Post-
Treatment Discharge of
Leachate
Emissions - Leakage to
Groundwater
Construction Phase
EASETECH
WARM
Ecoinvent
X
X
X
MSW-
DST
WRATE
GaBi
ASMI IE
Buildings
BEES
Operation and Closure/Post-Closure Phase
X
X
X
p
X
X
X
X
X
X
X
X
X
X
X
2.5.10 Landfill Gas Emissions
Landfill gas emissions result from the decay of landfilled organic materials and depend on the landfilled
waste composition. In an anaerobic MSW landfill environment, LFG tends to be comprised of
approximately 55% methane and 45% carbon dioxide with trace amounts of other gases for the majority of
the landfill's active and post-closure life. The CDD stream typically contains smaller quantities of readily
biodegradable wastes (generally the largest biodegradable component of CDD is wood and paper); thus a
lower total bulk gas production is observed (Doka 2003a). However, at CDD landfill sites, F^S, a
malodorous compound produced typically from decay of sulfur-containing wastes (e.g., gypsum drywall),
can be produced. Since gas-production rates are expected to be low at CDD landfills, there is no federal
requirement for active GCCS at CDD, and employing combustion-based treatment systems can be
challenging at CDD sites because of the small amount of gas produced.
Gas production at MSWs is typically assumed to follow a first-order decay relationship, and the production
rates can be estimated using computer modeling tools (e.g., the US EPA's Landfill Gas Emissions Model)
(US EPA 2005). Since a GCCS is rarely used at CDD landfill sites, the temporal modeling or estimation of
gaseous emissions from CDD landfills (either controlled or uncontrolled) may be challenging because of
the lack of data collected on gas composition and quantities at operating facilities. Several researchers have
used field surface emissions monitoring and laboratory columns to quantify sulfur gas release from CDD
landfills (Lee et al. 2006, Eun et al. 2007, Xu et al. 2014).
The generation, composition, and controlled/uncontrolled emissions of LFG are based on the gas-
production properties of the landfilled material (e.g., decay rate, total gas production potential), GCCS
operation and coverage area, and cover soil and cap installation and characteristics. Gas treatment or
inhibition mechanisms (e.g., co-disposal of drywall with ash or lime) employed will also impact
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environmental emissions (Plaza et al. 2007, Panza and Belgiorno 2010, Xu et al. 2010, Sungthong and
Reinhart2011).
2.5.1'0.1WARM
The Waste Reduction Model (WARM) estimates greenhouse gas (GHG) emissions associated with LFG
from biodegradation of a variety of materials; dimensional lumber, wood flooring, medium-density
fiberboard, yard trimmings (typical of land clearing debris), corrugated containers, and drywall are the CDD
materials considered by the model to produce methane in a landfill. The model calculates material-specific
emission factors for a variety of landfilling scenarios based on the measured initial carbon content, methane
yield, LFG collection scenario, electricity generation from the collected and combusted methane, and
carbon storage for 14 materials over 100 years. The initial biogenic carbon content and stored carbon
contents used in the model are based on the material-specific data published by Barlaz (1998). Barlaz
(1998) reported biogenic carbon contents and carbon storage factors of various materials in 2-L reactors in
quadruplicate under anaerobic conditions. The carbon content of waste materials was measured at the
beginning and end of the experiment to estimate the initial and stored carbon content, respectively (Barlaz
1998). The model uses data reported by Eleazer et al. (1997) to estimate the material-specific methane
yield as a percent of the initial carbon content for various materials. Barlaz (1998) and Eleazer et al. (1997)
used the data collected from the same set of experiments.
Adjustments to the methane yield reported by Eleazer et al. (1997) were made to account for 100% of the
initial carbon if the methane and carbon dioxide yield and stored carbon did not add up to 100%; the
volumetric carbon dioxide yield was not measured and was assumed to be equal to that of methane. For
example, the methane yield for gypsum board was increased from 16% to 18% of the initial biogenic carbon
content so that the methane and carbon dioxide yield, when added to the stored carbon content of 64%,
accounted for 100% of the initial biogenic carbon. US EPA (2012a) identified proxies for the materials
that were not included in the Barlaz (1998) study. For example, dimensional lumber and phone books were
assumed to have the same characteristics as branches and newspaper, respectively. Water content of the
different materials was adjusted as needed (US EPA 2012a).
The model provides emission estimates for three types of landfill operation: landfills without LFG recovery
systems, landfills that flare LFG, and landfills that combust LFG for energy recovery. For the national
average the model assumes that LFG is not collected for CDD landfills and that 28%, 38%, and 34% of the
total methane generated is vented to the atmosphere, recovered and flared, and used for electricity
generation, respectively, for landfills other than CDD landfills. CDD materials are assumed to be disposed
of in a CDD landfill and therefore LFG collection from these materials is not considered by the model.
The fugitive methane emission is dependent on the time-varying methane generation rate and collection
efficiency for the options with LFG collection and combustion. The model calculates LFG generation for
four material-specific decay rates, using a first-order decay model. The material-specific decay rates
reported by De la Cruz and Barlaz (2010) were used to estimate the LFG generation rate. De la Cruz and
Barlaz (2010) used the data collected in the experiments reported by Eleazer et al. (1997) to estimate
material specific-decay rates and compared the composite k value (calculated based on waste composition
and measured material-specific k values) with the field k values (0.04 yr1 and 0.12 yr1) to calculate a
correction factor. The model uses the correction factor to adjust the lab-measured k-values to material-
specific field-relevant decay rates of 0.02 yr"1, 0.04 yr"1, 0.08 yr"1, and 0.12 yr"1 for dry, average, wet, and
bioreactor landfill moisture conditions, respectively. Temporally varying collection efficiencies are applied
to the generation rate to estimate the LFG collection rate for three LFG collection scenarios (typical, worst-
case, and aggressive gas collection scenarios). However, the collection efficiency is the same for 6 to 100
years for all LFG collection scenarios (75% for the 6th and 7th year and 95% for the 8th - 100th). The LFG
collection efficiency annually varies from 0 to 75% for the first 5 years and depends on the collection
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scenario. A temporally-averaged LFG collection efficiency, defined as the total methane collected over 100
years divided by the total methane produced over 100 years, is calculated for each material based on the
total estimated LFG generation and annual collection rates.
The model assumes an oxidation rate of 10% for methane that is not collected by the LFG collection system.
The oxidation rate is based on the data reported by Liptay et al. (1998) and Czepiel et al. (1996) and the
IPCC (2006) in US EPA (2012a). Further investigation of these sources showed that this rate was based on
work by Czepiel et al. (1996), who reported the methane oxidation rate based on methane flux
measurements through laboratory-scale soil columns under varying temperature, soil moisture, and 62
mixing ratios; soil samples were collected from a landfill cover in New Hampshire. Subsurface LFG
migration is not mentioned by US EPA (2012a). The model also does not consider emissions of other
gaseous contaminants.
The offset associated with LFG beneficial use is estimated only for electricity generation; offsets associated
with other beneficial use applications such as direct use of LFG is not considered. The model calculates the
offsets based on methane's energy content of 1,012 BTU per cubic feet, a methane density of 20 g/ft3, an
LFG-to-electricity heat rate of 11,700 BTU per kWh electricity, and a capacity factor of 85% (to account
for system downtime). Regional (for nine regions in the US) utility mixes can either be user-specified or
the US average utility emission factors can be used. The model provides material-specific offsets for non-
baseload electricity generation. The model appears to assume 100% destruction efficiency for LFG
combustion via flare and electricity generation. The model accounts for sequestering biogenic carbon,
which is not degradable in an anaerobic environment. WARM does not account for emissions or materials
consumed from manufacturing, installing, or operating the GCCS, energy recovery equipment, or LFG
condensate-management devices.
2.5.10.2Athena's Building Impact Estimator
Athena's Impact Estimator for Buildings (version 4.5, released in January 2014) includes an assessment of
LFG produced from wood decomposition (Athena Institute 2013). LFG calculations are performed by the
model to determine the biogenic carbon sequestration of wood during EOL management, where the amount
of carbon in the product which is not released as LFG provides an environmental carbon storage benefit
(Athena Institute 2013). The methodology for the biogenic carbon accounting was reported as based on the
Publicly Available Specification (PAS) 2050 carbon footprint standard (BSI 2011). The model assumes
80% of waste for landfilling, 10% for recycling, and 10% for combustion. Emissions associated with LFG
in the Impact Estimator for wood products are estimated based on LFG generation, LFG collection,
uncontrolled LFG release, and the discharge of combusted LFG through flaring or energy recovery (though
there is no accounting for energy offsets resulting from power production) (Athena Institute 2013).
The model uses a first-order decay model to estimate gas generation from anaerobic and aerobic landfills
for 100 years. It is assumed that 23% of the wood decomposes to produce LFG. A decay rate of 0.04 year"
1 is used for both aerobic and anaerobic landfill cases. LFG from aerobic landfilling is assumed to be
constituted of only carbon dioxide, whereas LFG from anaerobic landfill is assumed to be constituted of
50% methane and 50% carbon dioxide by volume. The model assumes a collection efficiency of 82% and
oxidation through cover material of 10%. The collected LFG is assumed to be combusted. The model does
not offer credit for energy recovery from LFG combustion. The documentation does not provide sources of
the inputs used for the LFG emission estimate and does not describe the methodology for estimating carbon
stored from LFG emission estimates. It appears that the model does not consider emissions associated with
GCCS equipment and material manufacture, installation, maintenance, or any consumables from GCCS
operation.
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2.5.1'0.3 EASETECH
EASETECH uses the Intergovernmental Panel on Climate Change's first-order decay model to estimate
LFG generation (DTU 2013). EASETECH estimates total anaerobically degradable carbon for each waste
material constituent based on its hydrogen, oxygen, nitrogen, and volatile solids content, as well as its
methane generation potential (total methane volume produced per MT of volatile solids). The model
calculates the methane fraction of the total gaseous emissions for each material constituent based on
elemental composition (i.e. hydrogen, oxygen, nitrogen, and anaerobically degradable carbon). The model
only allocates gaseous emissions to methane and carbon dioxide based on first-order decay of the
anaerobically degradable carbon for each waste material fraction. The model adopts the first-order decay
rates reported by De la Cruz and Barlaz (2010), who performed lab-scale decomposition studies to estimate
material specific decay rates of 12 MSW components. Although similar, the decay rate constants do not
exactly match those reported by De la Cruz and Barlaz (2010). While EASETECH provides decay rates
for 22 material fractions, only eight unique decay rate constants are used in the model - similar material
fractions were assigned the same rate constant (e.g. animal and vegetable food waste both have a constant
of 0.137 year1). The model provides details on the chemical composition and amount of anaerobically
degradable carbon within wood, concrete stones, cardboard, soil, and metal waste materials.
For each year that waste degradation is modeled, EASETECH calculates the total amount of anaerobically
degradable carbon converted into LFG based on the material-specific first-order decay rates; the user may
specify a different value for any or all of the material fractions. In addition to methane and carbon dioxide,
21 minor LFG constituents are added to the LFG on a g/m3 concentration basis independent of waste type.
The model allows concentration modifications or addition/subtraction of constituents as needed. While
methane, carbon dioxide, and trace gas emissions will decrease over time according to the decay rate
constants, EASETECH models the concentration of all gas constituents as independent of time.
The model includes a default 100-year period for the evaluation of LFG management, but the user may
modify this time horizon. The model allows the user to specify LFG collection efficiencies for different
time periods. The default collection efficiencies include 0% for the first two years, 80% for the next 43
years, and 0% for the remaining 55 years. The 20% of the LFG that is not collected from years 2-43 is
further modeled according to "early" oxidation (i.e. the first 8 years during which LFG is collected) and
late oxidation (i.e. the last 35 years during which LFG is collected) while the 100% of the LFG that is not
collected for the last 55 years is modeled as undergoing late oxidation. A unique default
oxidation/transformation rate is specified for 23 default organic and inorganic compounds, but these rates
may be modified and additional substances may be added or subtracted. Methane is one example of a
carbonaceous gas which is oxidized differently during the early/late oxidation periods - it is oxidized at
60% to carbon dioxide during the early phase and at 80% during the late phase.
The model does not account for subsurface gas migration process - LFG is either collected or released
through the final cover. While documentation for LFG production, collection, and treatment within the
EASETECH model is not explicit, it appears that Deipser et al. (1996) and Scheutz et al. (2004) were used
to estimate the oxidation of methane and non-methane organic compounds (NMOC) in landfill cover soils
for the different time periods. Scheutz et al. (2004) assessed the methane oxidizing potential of soil samples
from a location bordering an unlined Danish landfill; offsite methane migration was observed at the
sampling location. Soil samples from depths ranging from 0 to 90 cm were collected. Samples were placed
in air-tight glass containers from which the air was evacuated and were subsequently incubated with gas
mixtures consisting of 15% methane, 35% oxygen, and 50% nitrogen. Gas samples were routinely
withdrawn from the containers after incubation for chemical analysis by gas chromatography to estimate
oxidation of a variety of organic compounds.
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EASETECH can model the collected portion of LFG as either utilized within an LFG-to-energy project or
as sent to a flare for destruction. Power produced as a result of a gas-to-energy project is used to offset the
power (and corresponding emissions) from a Danish coal-fired utility. The model estimates electricity
generation from methane combustion using an estimated methane collection rate, an energy content of 37
MJ/m3, and an efficiency of 30%. The model default gas-to-energy project also includes a heat-recovery
process, which captures an additional 50% of the methane energy content. The model assumes a default
energy recovery efficiency of 80% for combining heat and power processes. However, the user can change
any of these efficiencies and remove either/both energy-recovery process(es). A methane and NMOC
destruction efficiency of 97% is used for the flare and gas-to-energy processes. Again, while not explicitly
stated within the model, it seems likely that flare emissions data from Frost et al. (1997) were used and
potentially from NSCA (2002). The project team could not find a copy of these sources for additional data
evaluation. The model does not account for emissions or materials associated with manufacturing,
installing, or operating the GCCS, energy recovery equipment, or LFG condensate management devices
(e.g., electricity used to operate gas mover equipment, pilot gas used for flare operation, lubricating oil
needed for gas-to-electricity internal combustion generator sets). Only emission offsets associated with
power production from energy recovery are included.
2.5.10.4 MSW-DST
The MSW-DST is focused on MSW materials; however, some LFG-generating MSW wastes in the model,
such as cardboard and components of land-clearing debris (i.e., branches, grass, leaves), could be
considered CDD materials. Gaseous emissions are not considered for ash landfills. The model estimates
total LFG gas emissions and offsets for traditional and bioreactor landfills based on generation rate,
collection efficiency, oxidation through landfill cover, electricity generation, and carbon sequestered (or
stored). The LFG emission methodology used by the model is very similar to that used by WARM. The
MSW-DST, however, offer more flexibility for user inputs. For example, DST allows users to specify the
LFG collection efficiency for each year LFG is collected, where WARM does not offer such flexibility.
The model uses a material-specific methane generation potential and decay constant to estimate LFG
generation for a user-specified MSW composition using a first-order decay model for a 100-year time
frame. Similar to WARM, the material-specific decay rate and methane generation potentials used by the
model are adopted from De la Cruz and Barlaz (2010) and Eleazer et al. (1997), respectively. LFG from
anaerobic landfilling is assumed to be constituted of 50% methane and 50% carbon dioxide by volume. The
model provides temporally-averaged default collection efficiencies for typical collection (national average)
and state-of-the-art systems for traditional and bioreactor landfills. The model, however, allows users to
select collection efficiency for each year from year 1 through year 100. The model does not account for
landfill carbon sequestration - the justification given in the model documentation was that carbon storage
was not included in other parts of the model outside of landfilling.
The model allows the user to select gas management methods for any year from year 1 through year 100.
The management methods include venting to the atmosphere, combustion via flare, and combustion for
energy recovery. The options for LFG combustion with energy recovery include combustion in internal
combustion engines, turbines, and boilers. The energy generated by the LFG-to-energy system is calculated
based on the volume of collected methane, conversion technology efficiency, and methane energy content
(1,012 BTU/dry standard ft3 methane). The emission offset LFG-to-energy emission offsets include
precombustion and combustion emissions from fossil fuel use. The energy mix is then used by the model
to determine the offset based on the emissions per kWh or MJ of the particular energy fuel in the energy
mix. The fuels included in the energy mix are (with model default values shown in parentheses) coal
(56.45%), natural gas (9.75%), residual oil (2.62%), distillate oil (0.23%), nuclear (22.13%), hydroelectric
(8.59%), and wood (0.24%) (Dumas 1999).
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The fugitive surface emissions are estimated based on the remainder of LFG, which is not collected by the
GCCS or converted through oxidation in the cover soil. LFG soil migration or dissolution to groundwater
is not considered in the MSW-DST landfill modeling process. The oxidation rate through the landfill cover
can be specified as temporally varying (i.e., the user may specify different oxidation rates for each year of
the entire 100-year time horizon).
The other trace constituents in LFG included by the model are benzene, chloroform, carbon tetrachloride,
ethylene dichloride, methylene chloride, trichloroethene, tetrachloroethene, vinyl chloride, toluene, and
xylenes; concentrations of these constituents are based on AP-42 values (US EPA 2008) and are modeled
independently of MSW waste composition. Destruction of these organic compounds is generally modeled
as >90% for all technologies (including flaring) and destruction efficiencies were based on research by
Ecobalance (1999).
The MSW-DST includes emissions from LFG treatment/energy recovery, emissions which are solely based
on the quantity of LFG combusted (NCSU and ERG 2011). Exhaust constituents emitted by LFG
combustion/energy recovery equipment are as follows (reported in Ib per dry ft3 methane going through the
equipment): carbon monoxide (CO), nitrogen dioxide (N2O), particulate matter (PM), sulfur dioxide (802),
hydrogen chloride (HC1), and dioxins. These emission factors are also based on AP-42 values (US EPA
2008).
The gas collection and monitoring systems are assumed to be placed at landfill closure (NCSU and ERG
2011). The model calculates the materials necessary for installing a GCCS as well as the emissions from
producing, transporting, and placing the materials by heavy equipment (e.g., fossil carbon dioxide released
by fuel combustion in heavy equipment); the GCCS was assumed to be comprised of HOPE and PVC and
installed at respective rates of 0.016 Ib and 0.0081 Ib per ton MSW forthe gas collection system and 7.3x10"
5 Ib PVC per ton of MSW for the gas monitoring system. Rates of HDPE and PVC use for the gas collection
and gas monitoring system were reported to be based on landfill site survey information gathered by
Ecobalance (1999). The MSW-DST also estimates emissions from the final cover installation when refuse
in cells reaches final grade (NCSU and ERG 2011).
The MSW-DST does not account for emissions from operating or maintaining the GCCS nor does it
consider emissions associated with producing GCCS operation and maintenance consumables (e.g.,
lubricating oils, pilot gas). The model does not appear to consider emissions from electricity use by the gas
collection system operation, emissions due to fuel use in the pilot light, or emissions associated with
consumables used during flare station operation and maintenance activities.
2.5.10.5WRATE
The Waste and Resources Assessment Tool forthe Environment (WRATE) LCA model uses pre-developed
output data from the software tool GasSim v2.0 to estimate LFG-related emissions for a series of landfilling
scenarios. WRATE is primarily focused on MSW, though some materials which are commonly discarded
in CDD debris also appear in the model as options for waste fractions and a modeling scenario could be run
which focuses on specifically managing CDD debris. These materials include wood, combustibles
(unspecified, carpet/underlay), non-combustibles (bricks, blocks, plaster), household hazardous waste
(paint/varnish), ferrous metal, and several paper products. GasSim is a probabilistic performance
assessment model that can be used to estimate gas (methane, carbon dioxide, and hydrogen) generation,
partitioning between collection, migration, surface emissions, biological oxidation through cover,
combustion plant, and atmospheric dispersion.
The rate of LFG generation is affected by the landfill size and waste composition (Golder Associates 2009).
The emissions associated with the LFG collection are affected by the modeled collection efficiency and the
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different operational conditions and engineering practices such as LFG used for energy production, flaring,
or lost due to surface emissions or subsurface migration (Golder Associates 2009). A key modeling
parameter used in GasSimv2.0 is the "source term" for LFG (Golder Associates 2009). The source term for
bulk gases is the LFG generation rate of that waste fraction (i.e., a total LFG yield) (Gregory et al. 1999);
therefore, modifying the landfilled waste stream will affect the LFG generation rate (Golder Associates
2009).
In WRATE, there are three set landfill sizes based on filling rates of 125,000 MT/year, 250,000 MT/year,
or 500,000 MT/year over a 20-year period. The period of gas collection is based on the LFG generation
rate (i.e., there are threshold levels of LFG flow into the flare or LFG-to-energy which trigger their
employment in the model), although LFG emissions are modeled over a 150-year period (Golder Associates
2009). Landfill gas generation follows a first-order decay model (deemed multi-phase, because of
consideration of waste moisture content); thus it is time dependent (Gregory et al. 1999; Golder Associates
2009). The degradation rate (k) can be changed in WRATE and there are three options for decay rates.
Decay rates are dependent on waste type and the moisture content of the landfill. The default WRATE
setting is "normal" degradation, which combines slow, moderate, and rapid decay (due to the waste
composition being a mixture of components, each of which has its own decay rate) (Golder Associates
2009). GasSimv2.0 includes lateral migration of LFG and trace constituents through the subsurface by
advection and diffusion. Methane oxidation is assumed to occur through the landfill cap/cover at a rate of
10%, unchanging with time, and this estimate is based on a recommendation by the IPCC (2006). Specific
information on the field or laboratory studies considered by IPCC (2006) for this estimate are not provided.
No carbon storage is considered by the WRATE model (Golder Associates, n.d.). The model assumes a 20-
year active lifespan of 10 cells, each filled in a 2-year period and progressively capped to optimize gas
collection (Golder Associates 2009).
The primary gas constituents modeled by the first-order decay model are methane, carbon dioxide, and
hydrogen (Golder Associates 2009). Total LFG production is equivalent to the sum of the hydrogen, carbon
dioxide, and methane produced by landfilled waste. The generation of both bulk and trace LFG constituents
is waste-material specific in GasSimv2.0. However, the gases are not simply allocated1 to the waste
fractions based on assumed generation rates; rather, bulk gas generation is estimated by GasSimv2.0 and a
first-order decay function, based on the waste inputs and their characteristics (e.g., degradation rate), and
detailed in Gregory et al. (1999), as reported by Golder Associates (n.d.). GasSimv2.0's bulk LFG
calculation is based on work by Gregory et al. (1999), where waste fractions were grouped into waste which
degrades slowly, at a moderate rate, and rapidly and by Barlaz et al. (1989) where cellulose, hemi-cellulose,
lignin, and moisture contents of different waste streams are reported from a study which used 56 laboratory-
scale lysimeters with shredded refuse to investigate decomposition (Gregory et al. 1999).
Golder Associates (n.d.) reports that trace gas emissions were based on multiple studies conducted from
1987 through 1997 (seven total studies), which examined VOCs in LFG at actual landfill sites. Trace gas
constituents considered by WRATE are grouped into the following classes: alcohols, aldehydes, aliphatics,
BTEX, CFCs, chlorinated solvents, chlorinated solvent degradation products, chloro-benzenes, HCFCs,
hydrocarbons, partial combustion products, substituted aromatics, sulphurous compounds, and terpenes (for
a total of 57 trace compounds, not counting isomers of these compounds). Waste-specific trace gas
emissions were developed for GasSimv2.0 using a "top-down" approach. Concentrations of trace LFG
constituents from research by Parker (2002) were assigned to the degradation of specific waste material
1 Allocation refers, in the case of WRATE, to taking the total amount of a constituent (e.g., CFCs) calculated or
assumed and then using waste composition data to allocate what portion of that quantity is attributable to the given
waste fractions.
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fractions by an "expert panel" of industry professionals. This panel considered the amount of degradable
carbon available in each of the waste materials when performing trace LFG constituent allocations.
Golder Associates (2009) developed linear equations relating gas emissions to the environment (kg/ton
waste) to gas collection efficiency for each bulk and trace gas component. These linear equations, coupled
with the reduction factors, were used to develop emission allocation tables in WRATE. WRATE users can
edit these allocation tables, including changing the gas collection efficiency for a year when gas collection
occurs (Golder Associates 2009).
LFG collection efficiency affects emissions, and there are six available gas collection efficiencies in
WRATE: 0%, 30%, 65%, 75%, 90%, and 100%. These collection efficiencies only apply when gas is being
collected and do not represent the total LFG collected over the landfill's lifetime. The fraction of LFG
which is not collected is considered an uncontrolled release to the atmosphere through the landfill surface
or through subsurface migration.
LFG treatment in WRATE can be specified as either occurring through combustion by flaring or in an LFG-
to-energy project through the use of internal combustion engines (Golder Associates 2009). Because of the
use of GasSimv2.0 to model a limited number of design scenarios, only a limited number of scenarios may
in turn be modeled in WRATE (since the two programs are not coupled). For example, a WRATE user
only has two modeling options for specifying a "flare-only" scenario: a 10-MT total landfill capacity, 30%
collection efficiency, and slow degradation of biodegradable waste components; or a 5-MT total landfill
capacity, 75% collection efficiency, and normal waste decay (Golder Associates 2009).
WRATE includes emission offsets resulting from an LFG-to-energy project by assuming a generating
efficiency of 33% and 50 MJ/kg calorific value (for methane) (Golder Associates 2009). Discharge of
treated LFG through an LFG-to-energy project (i.e., the "combustion plant") will partially destroy some
pollutants and oxidize various LFG compounds.
WRATE accounts for raw materials (e.g., clay, concrete, steel) and fuel use during landfill construction, as
detailed in Golder Associates (2005). Capping related materials and emissions are dealt with separately
from construction-related emissions. Materials (e.g., cover soil) and fuel usage during landfill construction,
operation, and closure are dependent on the landfill size selected. Golder Associates (2005) does not specify
whether these emissions and materials for LFG construction and operation are related to the GCCS.
2.5.10.6It GaBi
LCI background documentation was reviewed for GaBi processes which model the disposal of various
waste streams and which include LFG emissions data. US-specific GaBi datasets broadly include
information on LFG generation, collection, uncontrolled release to the environment, and energy recovery.
Several US-based landfilling processes for a variety of individual and mixed waste streams were identified
for different climatic conditions (e.g., arid, moderate, wet).
These US-specific datasets rely on national average data for their LFG modeling parameters, however,
regional precipitation information is mentioned within the process datasets (i.e., the ability to select arid,
moderate, or wet climates). Landfill waste density, height, and area are attributed to Ham et al. (1999) and
Themelis and Ulloa (2005). Themelis and Ulloa (2005) provide information on the quantities of waste
landfilled for 42 states, the number of operational landfills, the area of the working face, average waste
depth, density, and other parameters. Ham et al. (1999) was not available online for additional review. It
is not clear from Gabi dataset documentation whether methane generation is waste-specific or time
dependent, however, since the dataset considers the total methane generated and collected at US landfills
(with data utilized from US EPA's Landfill Methane Outreach Program (US EPA 2013, LMOP 2013)), the
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temporal aspect may be included by assuming that the percent of landfill gas collected and managed by the
process is the same as the nationwide average. A full citation for US EPA (2013) was not provided within
GaBi process documentation; this information was unavailable for further review.
Numerous details regarding nationwide average LFG collection and combustion are summarized from US
EPA (2013) and LMOP (2013) including the percent of methane collected for flaring, the percent collected
for energy recovery, the percent released as fugitive emissions, LFG combustion efficiency and the
fractions of energy recovered from combusted LFG available as electricity and thermal energy. LMOP
(2013) information is based on field data representing 782 operational MSW landfill gas beneficial use
projects. GaBi process documentation discusses the energy generated by LFG-to-energy systems at
landfills, but the processes do not appear to include or consider the offsets associated with energy
generation. Oxidation of methane in landfill covers was not discussed in any process datasets. All US
datasets examined for LFG consideration are part of the GaBi Extension Database XVII: Full US (PE
International 2013).
Emissions related to construction of a GCCS are not considered in US (or European) datasets, although the
datasets do include emissions for producing and transporting materials to cover and line the landfill as well
as fuels used for landfill operations (e.g., diesel emissions for compactors). No emissions associated with
operation and maintenance consumables or energy use of the GCCS were included.
2.5.10.7Ecoinvent
Doka (2003a) presented a methodology to estimate LFG generation, collection, uncontrolled release to the
atmosphere, and emissions from LFG combustion. Model documentation specifically discusses the
individual parameters of waste materials that uniquely influence their decomposition in a sanitary (i.e.,
MSW) landfill. Insufficient information was available in the documentation to provide a detailed discussion
of gas modeling from non-MSW landfills.
Short-term (i.e., within the first 100 years) LFG generation is the only phase during which LFG emissions
are modeled; air emissions after this period are considered negligible (Doka 2003a). Similar to the total
emission of an element as leachate, the total emission of an element as LFG is dependent on the total
fraction of the element in the waste stream of interest and the time- (i.e., short term, long term) and phase-
(i.e., gas, liquid) specific transfer coefficient for that waste. Doka (2003a) developed waste-material-
specific transfer coefficients for materials received at sanitary landfills, but uses an average transfer
coefficient for wastes placed at inorganic landfills (e.g., residual and inert material landfills).
Transfer coefficients are estimated from an element's theoretical emissions potential, its release factor
(estimated based on simplifications to leachability predictions which include consideration of element
precipitation) and the fraction of the element emitted in LFG. The theoretical emissions potential is related
to the carbon content of agiven waste material; the carbon conversion and degradability rate for 13 different
waste materials is provided in Doka (2003a) and carbon conversion rates are cited from Micales and Skog
(1997). The fraction of the quantity of 19 different elements emitted in LFG is estimated from Belevi and
Baccini (1989) (included in an appendix to Doka (2003a)).
Information on the quantity of LFG collected and combusted at a sanitary landfill was averaged from five
literature sources reviewed and summarized in Zimmermann et al. (1996), however, this document was not
available for review. In addition to methane and carbon dioxide (present at concentrations of 47% and 37%
by volume), Doka (2003a) assumes that some amount of air intrudes into the waste mass and is collected
along with LFG by the GCCS; oxygen and nitrogen are assumed to represent 2.5 and 13% of collected LFG
(by volume). Besides carbon dioxide and nitrogen, combusted LFG is assumed to include quantities of
carbon monoxide, non-methane volatile organic compounds, particulate matter (<2.5 microns), nitrogen
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dioxide and a relatively small amount of non-combusted methane. Emissions related to installation and
operations of the GCCS, as well as consumables (e.g., fuel, oil) are not discussed. Subsurface gas migration
and oxidation of methane through the landfill cover are not reported by Doka (2003a), however, hydrogen
sulfide is assumed to partially oxidize in the top layer of the landfill and then appears to be inventoried
completely as sulfur dioxide due to atmospheric oxidation.
The presence of hydrogen sulfide in LFG is assumed to be a result of gypsum disposal, where the
concentration is dependent on the transfer coefficient for sulfur and the quantity of sulfur placed in the
landfill. Gypsum decomposition for a 100-year period was assumed to be 100% (Doka 2003b). The sulfur
transfer coefficient was estimated based on four hydrogen sulfide measurements from building waste
landfill cells (Belevi and Baccini 1987) and an estimated 3% gypsum concentration in construction waste
(Doka 2003b).
2.5.10.8Landfill Gas Modeling Summary
Table 2-14 summarizes the LFG-related flows presented in the different LCA models. An "X" indicates
that information with respect to that flow was identified in the model or in documentation for the model.
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Table 2-14. Summary of Landfill Gas and GCCS LCI Information Included in LCA Models
Phase
Construction
Operation and
Closure/Post-
Closure
Flow
Fuel (Well Installation/Pipe
Placement)
Electricity (Pipe Welding)
Inputs - GCCS Pipes and
Fittings
Inputs - Gravel/Geotextile
Inputs - Gas Mover and
Ancillary Equipment
Emissions - GCCS Installation
Electricity (Gas Mover and
Ancillary Equipment)
Fuel (Pilot Gas)
Inputs - O&M Consumables
Emissions - Gas-to-Energy
Equipment
Emissions - Gas-to-Energy
Emissions Offset
Emissions - Flaring
Emissions - Gas
Cleanup/Treatment Equipment
Emissions - Surface
Emissions/Venting
Emissions - Cover Oxidation
Emissions - Subsurface
Migration/Dissolution into GW
Emissions - Carbon Storage
Offset
EASETECH
X
X
X
X
X
X
WARM
X
X
X
X
X
X
Ecoinvent
X
X
X
X
MSW-
DST
X
X
X
X
X
X
X
X
WRATE
X
X
X
X
X
X
GaBi
X
X
X
X
ASMI IE
Buildings
X
X
X
X
X
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The methodology used by the US EPA (2012b) fors WARM landfilling process was selected for estimating
the gas emissions from the landfill disposal of CDD materials. US EPA (2012b) provides LFG production
properties for numerous waste materials placed in landfills. While the specific focus of the documentation
is MSW materials, several materials are also part of the CDD waste stream including dimensional lumber
(selected to represent CDD wood), branches (selected to represent LCD), cardboard and gypsum drywall.
The data presented in US EPA (2012b) used for estimating the LFG emissions for CDD and MSW landfill
disposal of the different organic CDD materials discussed in this report is presented below in Table 2-15.
Table 2-15. Landfill Gas Production Properties for Different CDD Materials
Material
Dimensional
Lumber/Branches1
Cardboard
Gypsum Drywall
Initial %
Carbon of Dry
Mass (Barlaz
1998)
0.49
0.47
0.05
Methane Carbon
as portion of initial
carbon (%) (Barlaz
1998)
0.12
0.22
0.18
Ratio of
Dry to
Wet
Mass
0.9
0.95
0.94
MSW Landfill Gas Collection
Efficiency - Average Typical
Landfill Scenario Moisture
Conditions (Barlaz et al.
2009)
0.9
0.89
0.872
1 US EPA (2012b) used the experimental gas production results from branches as a proxy for dimensional lumber. The Project
Team uses branches gas production results as a proxy for LCD gas production in this report. A moisture content of 50% was used
for LCD instead of 10% used by US EPA (2012b) for branches The methane and carbon dioxide emissions estimate for branches
were adjusted for this moisture content difference.
2 A gas collection efficiency for LFG produced from the decomposition of gypsum drywall was not provided, however, the gas
collection efficiency for waste paper was assumed since this is the organic portion of the drywall which will produce
methane/carbon dioxide.
The total amount of methane emitted from a landfill after the placement of any of the materials listed in
Table 2-15 in a CDD landfill was calculated using the following equation:
= C
Di
16
—
Where,
MGI = methane generated from landfill disposal of 1 kilogram of the ith material (kg)
CM = initial carbon mass fraction of the dry ith material (%)
MCI = methane carbon as a fraction of the initial carbon (%)
Wi = ratio of dry to wet mass
16/12 = conversion factor methane to carbon mass
Assuming that LFG is not collected at CDD landfills, the total amount of methane emitted from CDD
landfills was assumed to be 90% of the amount generated due to an assumed cover soil oxidation rate of
10% (as discussed previously in the WARM landfill gas emission section). The amount of degraded carbon
is equally allocated to methane and carbon dioxide (based on results from Barlaz et al. 1989). Therefore,
the amount of carbon dioxide generated from the placement of one of the CDD materials in a CDD landfill
prior to cover soil oxidation may be approximated according to the following equation:
= C
Di
44
—
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Where,
CGI = carbon dioxide generated from landfill disposal of 1 kilogram of the ith material (kg)
44/12 = conversion factor of the molecular ratio of carbon dioxide to carbon
The carbon dioxide emission estimated from equation above was multiplied with 1.1 to account for the
carbon dioxide from the oxidation of methane in the cover soil.
US EPA (2012b) also presents information which allows an estimate of the amount of methane and carbon
dioxide emitted from the MSW landfill disposal of the CDD materials presented in Table 2-15. US EPA
(2011) reported that approximately 72% of all landfill-produced methane is generated at landfills with a
GCCS. Methane emissions would result from fugitive LFG at MSW landfills without as well as with GCCS.
The methane emissions from the disposal of the CDD materials at an average nationwide MSW landfill
was estimated using the following equation:
MEMSWI = MGi x 0.9 x (LGCCS x (1 - I]c£) + (1 - LGCC5))
Where,
MEMSWI = mass of methane emitted from the disposal of 1 kilogram of the ith material at an MSW
landfill (kg)
LGCCS = percentage of methane from MSW landfills with a GCCS (i.e. 72%)
HCI = gas collection efficiency for the ith material (see Table 2-15)
0.9 = factor accounting for cover soil oxidation of uncollected methane. Other variables as defined
above.
In addition to the carbon dioxide generated from organic material decomposition, carbon dioxide would
also result from the combustion of methane collected in an MSW landfill GCCS and from the oxidation of
uncollected methane emitted through the landfill cover soil. Carbon dioxide emissions from the disposal of
the CDD materials at an average nationwide MSW landfill may be estimated according to the following
equation:
CEMSWI = CGi + MGi x — x ((LGCCs^cL> + 0.1 x ((LGCC5)(1 - He.) + (1 - icccs)))
Where,
CEMSWI = mass of carbon dioxide emitted from the disposal of 1 kilogram of the ith material at an
MSW landfill (kg)
0.1 = factor accounting for the carbon dioxide produced from cover soil oxidation of uncollected
methane
44/16 = conversion factor of the molecular ratio of carbon dioxide to methane. Other variables as
defined above.
Table 2-16 presents a summary of the estimated methane and carbon dioxide emissions for the CDD and
MSW landfill disposal of the organic CDD materials discussed in this report based on the calculation
methodology presented above.
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Table 2-16. Methane and Carbon Dioxide Emissions for CDD and MSW Landfill Disposal of CDD
Materials
Material
Dimensional
Lumber and
Engineered
Wood
Cardboard
Gypsum
Dry wall
LCD
CDD Landfill Emissions
Methane (kg/kg
material)
0.064
0.12
0.010
0.036
Carbon Dioxide
(kg/kg material)
0.21
0.40
0.034
0.12
MSW Landfill Emissions
Methane (kg/kg
material)
0.022
0.042
0.0038
0.012
Carbon Dioxide
(kg/kg material)
0.33
0.60
0.052
0.183
2.6 Landfill Gas and Leachate Collection and Treatment
Because the majority of US CDD landfills do not have a GCCS, an LCI process dataset that models the
environmental burdens associated with gas collection and management at a CDD landfill was not
developed. However, a complete MSW disposal LCI process dataset should include the materials and
energy used and the emissions resulting from the construction, operation, and eventual decommissioning
of the average nationwide GCCS installed at MSW landfills, since MSW landfills also accept CDD
materials. An MSW landfill GCCS typically includes a flare station, which houses gas movers (i.e.,
blowers), destruction/treatment (e.g., flares, reciprocating internal combustion engines), and monitoring
equipment. At the present time, data on the average amount of electricity necessary to extract and treat the
LFG appear to be unavailable. Furthermore, no estimates of the specific composition of flare station
materials and the energy required to install/decommission the components of a GCCS were found. The
Project Team was unable to develop a generic process that models the average nationwide energy
consumption per unit volume of LFG handled by GCCS equipment due to lack of data.
As of 2012, 17 states required that CDD landfills have liners and leachate collection systems (IWCS 2012).
It was assumed that the typical US CDD landfill is unlined. However, the emissions resulting from
installing, operating, and decommissioning a leachate collection and removal system (LCRS) at an MSW
landfill need to be considered for CDD materials placed in MSW landfills. Two subcategories of emissions
result from leachate collection and treatment: those based on the total volume of leachate handled (e.g.,
emissions resulting from electricity used to pump leachate) and those based on the treatment of specific
leachate constituents (e.g., amount of energy necessary for aeration of leachate to reduce the concentration
of BOD below regulatory limits).
While Ecobalance (1999) provides an estimate of the average leachate collected per ton of MSW deposited
in MSW landfills at different intervals after placement (i.e., 20, 100, and 500 years), it does not estimate
the average amount of electricity necessary to collect and transport leachate; the only energy consumption
estimate provided is for the WWTP treatment of BOD, given as 0.001 kWh/g BOD removed. While WWTP
removal efficiencies are provided for seven leachate constituents/parameter categories (i.e., COD, BOD,
ammonia, phosphate, total suspended solids, heavy metals, and trace organics), the specific energy required
for the removal of each of these is not provided. While the emission path for each parameter is specified
(e.g., BOD treatment will release carbon dioxide to air, emit biomass sludge), an additional complicating
factor is the potential for the sludge from the WWTP to be disposed of at the MSW landfill from which the
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leachate came. Furthermore, it does not appear that the removal efficiencies are temporally weighted to
account for the average LCRS operational period (estimated as 40 years); to estimate the mass of a particular
contaminant (or treatment byproducts of a particular contaminant) released to surface water or to air as a
result of WWTP treatment, it would be necessary to estimate the mass emissions of the contaminant through
MSW leachate over time. Because of these limitations and the data gaps identified in the next section, it
was not possible to create an LCI dataset for the collection and treatment of leachate produced from
disposing of CDD materials in an MSW landfill.
2.6.1 Data Gap Analysis of Landfill Gas and Landfill Leachate Collection and
Treatment
To develop an LCI dataset that simulates emissions resulting from the use of an MSW landfill GCCS to
collect gas produced from CDD materials, the following data gaps need to be addressed:
1. Average energy required to construct and manufacture the components of a GCCS. Based on
the experience of the Project Team, significant quantities of steel are used in the manufacturing the
flare stations used for a MSW landfill GCCS; the quantity of steel and other components used in
manufacturing flare stations is important for developing a representative LCI for GCCS
construction. Furthermore, determining the average energy associated with gas well
drilling/trenching and GCCS pipe welding would allow for a more accurate estimate of the
emissions associated with GCCS construction and installation.
2. Average energy required to collect a unit volume of LFG. Electricity is necessary to power
GCCS equipment; therefore, emissions associated with powering GCCS equipment should be
allocated to organic CDD materials on a gas-collected-per-mass-disposed-of basis.
3. Data on common practices for decommissioning GCCS equipment. Information on the EOL
management of GCCS equipment is necessary to estimate the complete environmental burdens
associated with its serviceable life. Depending on whether the flare station or other GCCS
components are recovered or simply disposed of will have an impact on the total emissions resulting
from the MSW landfill disposal process dataset.
Besides the leachate data limitations presented for each of the materials in its respective chapter, the
following additional information would be necessary to develop a representative dataset for leachate
emissions resulting from the placement of CDD in an MSW landfill:
1. Volume of leachate collected over the serviceable life of an MSW landfill LCRS. This volume
would be necessary to estimate the average emissions associated with collecting and transporting
MSW leachate, irrespective of leachate quality.
2. Mass fraction of different C&D-material-produced leachate constituents, which may be
expected to be released in leachate during the service life of the LCRS. Currently, it is not
possible to estimate the total mass fraction of different leachate parameters that will be collected
and treated at a WWTP. Therefore, it is not possible to assign emissions to the correct
environmental bins (e.g., air, surface water, groundwater). For example, it is expected that calcium
would leach from the placement of demolished concrete in an MSW landfill environment. There
currently appears to be no information that specifically predicts the total amount of calcium that
will leach out from concrete placed in an MSW landfill over the operational life of an LCRS.
Therefore, it is not possible to estimate the quantity of calcium removed or energy consumption
associated with WWTP calcium removal. Similar to LFG production, it is likely that individual
leachate contaminants will be released at different rates depending on the specific CDD material.
Long-term leaching data specific to each CDD material will likely be necessary before an LCI
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Multimedia Environmental Assessment Section 2 -Materials and Management Approaches
dataset representing the emissions resulting from collecting and treating leachate from MSW-
landfill-placed CDD can be created.
3. Energy necessary to collect, transport and treat leachate on a per-volume basis. As mentioned
previously, it is anticipated that a certain baseline electricity demand will be necessary for leachate
collection, transport, and some treatment processes, independent of leachate quality.
4. Energy and materials necessary to treat specific leachate constituents. Different sub-processes
of WWTPs are designed to remove different categories of contaminants (e.g., aeration for BOD,
clarification for suspended solids, activated carbon filtration for metals and organic compounds).
The energy and (as applicable) operation and maintenance consumables for each treatment sub-
process need to be quantified on a per-mass-contaminant basis before a suitable MSW leachate
treatment dataset can be developed to simulate the emissions associated with the treatment of
individual contaminants. This estimate is necessary to be able to estimate the specific emissions
resulting from treating leachate resulting from the placement of specific CDD materials in an MSW
landfill environment.
5. End location of contaminants removed from MSW leachate at a WWTP. Ecobalance (1999)
discusses three process emission categories from WWTPs: air emissions, surface water emissions,
and solid (i.e. sludge) emissions. Once leachate is treated, it is necessary to know what fraction of
the contaminants (or contaminant treatment byproducts) was emitted into which emission category.
While removal efficiencies refer to the fraction of the contaminant removed from the leachate, data
pertaining to partitioning of contaminant into sludge and air are not available. This is particularly
important for those contaminants that may be removed through multiple treatment processes (e.g.
BOD removal through suspended solid clarification versus aeration to carbon dioxide).
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Section 3 - Asphalt Pavement
3 Asphalt Pavement
3, 1 Introduction
Asphalt pavement is constructed in multiple layers: top surface, intermediate, and base. The top two layers
typically consist of approximately 95% aggregate and 5% asphalt (FHWA 2011). Asphalt (also referred to
as bitumen), which is a product of petroleum refining and includes the denser fraction of crude oil
hydrocarbons, is used as an aggregate binder. Aggregates used for asphalt pavement production may
include gravel, sand, and crushed stone; crushed stone may include various rock types such as limestone,
dolomite, and granite. Aggregate and bitumen are commonly combined at HMA plants at elevated
temperatures prior to transport to a job site for pavement surface application. While there are numerous
processes for paving mix production (e.g. hot mix, warm mix, cold mix), HMA production is the most
commonly used process; approximately 94% of US roads are paved with HMA (US EPA 2012, Kelly
2011). NAPA (2013a) estimated that approximately 325 MMT of asphalt pavement were produced and
used for road construction, rehabilitation, restoration, and resurfacing in the US in 2012.
Asphalt pavements are routinely rehabilitated, resurfaced, and reconstructed due to surface wearing over
time. Asphalt pavement is removed by either road milling or demolition through excavation. Milling
involves grinding the road surface using a machine which has a toothed rotary drum that can be lowered or
raised to adjust the milling depth. Road pulverization and excavation may be used in instances where the
road base is compromised and no longer provides sufficient structural support for the overlying layers or
for instances where milling is not feasible or economically justified (e.g., parking lots, small road stretches).
Pavement removed via milling is typically referred to as RAP; all pavement removed after service life is
herein referred to as RAP.
Once removed, RAP may be recycled or disposed of. Recycling most commonly includes introduction into
new HMA or use as an aggregate in a fill application (e.g., road base, embankment). Figure 3-1 identifies
the flow of materials and processes that should be considered for conducting an LCA of asphalt pavement
EOL management. Upstream processes such as primary material extraction, crude oil refining, aggregate
production, and HMA production are also needed for an EOL LCA, as a majority of RAP is recycled in a
closed loop to produce paving mix.
Structural Fill
Aggregate
Mining, Crushing
& Sorting
Bitumen
Production
Crushing/
Sorting
HMA Production
Retail/
Wholesale
In Service
1
End-of-Life
Product Removal
(Milling/
Excavation)
Landfilling
Figure 3-1. Materials Flow for HMA Production and EOL Phase Management
3,2 Management at EOL
A significant amount of RAP generated in the US results from pavement resurfacing, rehabilitation, and
reconstruction operations (Copeland 2011). Based on a nationwide survey in 2011 of the asphalt pavement
industry, NAPA estimated that approximately 65.7 MMT of RAP were used by the asphalt pavement
producers (NAPA 2013b). In an independent survey for the same year, the USGS estimated that
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Multimedia Environmental Assessment
Section 3 - Asphalt Pavement
approximately 13.4 MMT of RAP were recycled by construction aggregate mining companies (e.g.,
construction crushed stone and sand and gravel producers) and construction and demolition companies
(Bolen 2013). US EPA (2014a) estimated that approximately 4.3 MMT of RAP was disposed at permitted
or registered solid waste management facilities. Together, it appears that nearly 83.5 MMT of RAP was
generated in 2011.
Figure 3-2 presents the distribution of RAP used in different applications in the US in 2011 based on the
US EPA (2014a) estimate of RAP landfilled by permitted or registered solid waste disposal facilities and
surveys by NAPA (2013b) and Bolen (2013). As Figure 3-2 shows, more than 70% of RAP generated in
the US in 2011 was used in HMA/WMA production. Approximately 12% of the pavement produced in
2010 was warm mix asphalt (WMA) (FFiWA 2012), so it is anticipated that the bulk of RAP was used in
HMA applications. As presented in Figure 3-2, "Other uses" of RAP include cold mix production and
untracked use. Aggregate uses may include application as a road base course, fill material for road
embankments, and other fill applications.
Landfilled
5%
HMA/WMA
72%
Aggregate
22%
Figure 3-2. Distribution of RAP Uses in 2011
Table 3-lTable 3-1 lists the processes that should be considered to conduct an LCA of EOL management
of asphalt pavement. The emissions associated with energy and materials requirements and process non-
energy emissions (e.g., fugitive dust, liquid emissions associated with disposal of RAP in a landfill) were
taken into account for compiling the different LCI datasets.
Table 3-1. Asphalt Pavement EOL Management Process Descriptions
Process
Crude Oil Extraction
Asphalt Production and
Storage
Aggregate Production
Description
Extracted crude oil is separated from water and transported to a refinery
typically by means of tankers or pipelines.
Asphalt is produced as a co-product of petroleum refining. Following
production, asphalt is typically stored at elevated temperatures for it to
remain a liquid.
Aggregate production generally includes the mining and processing of
stone, gravel, and sand. These materials are typically ground and
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Section 3 - Asphalt Pavement
Process
HMA Production
Transport
Asphalt Pavement
Removal
Landfill Disposal
RAP Processing
RAP Use as Aggregate
Description
fractionated at the mining site before shipment to the end-user.
Additional information on aggregate production is provided in Chapter 2
of the report.
Aggregates, asphalt, and sometimes RAP are mixed at elevated
temperatures to produce HMA. Because asphalt solidifies at ambient
temperatures, it is typically stored hot at the plant until added with
aggregates to produce HMA.
While transport LCI are generally presented in units of mass-distance
(kg-km), regional average distances between processes is necessary for
the development of a regional -level LCA.
Pavements are removed either through milling or excavation at the end
of their serviceable life. A milling machine has a rotating drum with
studded teeth that grind down the surface of the pavement to a pre-
determined depth. The ground-up material is discharged as millings.
Pavement excavation involves the use of heavy equipment to break up
the pavement into chunks prior to removal.
Following removal, asphalt pavement may be disposed of at a CDD,
inert, or sanitary (MSW) landfill.
RAP processing may include additional crushing and fractionation (i.e.,
sorting into different size categories). The extent of RAP processing is
dependent on many factors such as end use, amount of RAP used
relative to primary materials for HMA, production method, and the
duration of RAP storage in a stockpile.
RAP may be used as a primary aggregate substitute in a variety of fill
applications.
3.3 LCI Sources
Peer-reviewed literature, government and private industry publications, and various LCA modeling tools
were reviewed to identify available LCI datasets pertaining to asphalt pavement EOL management
processes. Table 3-2 lists data sources reviewed to develop the LCI presented in this chapter. If LCI data
were not available, process metadata and documentation (e.g., included emission categories, background
data used to compile the dataset, geographic location and time period of the data) were reviewed to evaluate
the completeness of the dataset. If available, the primary sources of information used to develop the LCI
datasets and information were reviewed.
Table 3-2. List of Sources Reviewed for LCI Data
LCI Source
Athena
(2001)
US LCI
(2012)
Description
Franklin and Associates developed LCI for Road and Roofing Asphalt, which include
emissions associated with crude oil extraction and processing at a petroleum refinery
for asphalt production (i.e., cradle to gate). The LCI data were compiled for the report
presented to Athena in 1999 and are representative of asphalt production in the US.
The National Renewable Energy Laboratory has published an LCI database which
includes datasets for a wide variety of services and material, component, and
assembly production processes within the US.
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LCI Source
Wilburn and
Goonan
(1998)
NRC (2005)
Stripple
(2001)
Eurobitume
(2012)
WARM
AP-42 (US
EPA 1995a)
NIST BEES
ASMI IE
GaBi
Ecoinvent
Description
The authors provide energy requirements associated with crushing/sorting stone, sand
and gravel, and RAP. These data were taken from the Portland Cement Association
and an energy audit of a recycling facility in Denver, Colorado.
Natural Resources Canada developed a Road Rehabilitation Energy Reduction Guide
for Canadian Road Builders based on a survey of pavement producers. This report
provides fuel-use data at asphalt pavement plants in the Canadian context.
Stripple (2001) presents LCI for a wide variety of road construction, pavement
production, maintenance, and demolition activities (e.g., land clearing activities for
road placement, installation of signs). Emissions are based on information gathered
from 1990-1994 for numerous road manufacturing and upkeep processes taken from a
variety of industry and heavy equipment manufacturer sources.
The European Bitumen Association provides LCI of the bitumen (i.e., asphalt)
production process from crude extraction to hot storage of bitumen at the refinery site.
EPA's Waste Reduction Model presents data on GHG emissions associated with
source reduction, transport, recycling, and landfilling (i.e., collection and placement)
of asphalt pavement.
Provides air emissions data for blasting agent detonation (for aggregate mining),
HMA plants, sand and gravel and crushed stone processing (PM emissions only), and
petroleum refinery processes
The National Institute of Standards and Technology Building for Environmental and
Economic Sustainability model allows for an economic and environmental impact
comparison among various building materials.
The Athena Sustainable Materials Institute developed the Impact Estimator for
Highways, which is LCA software for the evaluation of the environmental
implications of different roadway designs.
GaBi includes an LCI database developed by PE international that contains US-
specific datasets related to crude oil, aggregate (i.e., limestone), and asphalt
production.
Ecoinvent is an LCI database developed by the Swiss Centre for Life Cycle
Inventories, which includes specific processes related to the EOL management of
numerous individual materials. It includes processes related to the disposal of waste
asphalt pavement.
3.4 LCI Related to HMA Pavement Production
3.4.1 Raw Materials Extraction
3.4.1.1 Aggregate Mining, Crushing and Sorting
Crushed rock and gravel and sand are the most commonly used aggregates in asphalt pavement production,
although a wide variety of industrial byproducts (e.g., glass, crumb rubber, ash, steel slag) are also
occasionally used (NAPA and EAPA 2011). According to Willett (2013), approximately 80% of crushed
stone consumption (which was tracked by use) was used "mostly for highway and road construction and
maintenance." Also, approximately 13% of the 810 MMT of sand and gravel produced in the US in 2011
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which was categorized by end use was used for asphalt pavement aggregates (Bolen 2013). Additional
information on the development of LCI datasets for the production of different aggregates is included in
Chapter 2 of the report.
3.4.1.2 Asphalt Production
Asphalt is a co-product of the petroleum refining process and is used as the binding agent to provide
aggregate cohesion. Approximately 85% of the asphalt produced worldwide is used for asphalt pavement
production (NAPA and EAPA 2011). Approximately 21 MMT of asphalt and road oil were produced in
the US in 2012 (US EIA 2014). The LCI for the asphalt production process include emissions associated
with crude oil extraction, transportation, and refinery processing.
The US LCI (2012) database already includes a "crude oil, at production" process which cites 2003
information developed by Franklin Associates. However, this source document was not found. Franklin
Associates also developed the crude oil LCI dataset used in Athena (2001), which uses information from
11 sources dated between 1962 and 1996. The GaBi database references 76 individual sources for its US-
specific "Crude Oil Mix" process dataset. While LCI datasets with information on crude oil production
were available in other publications and LCA models, these were representative of international crude
mixes.
Crude oil refineries use a number of physiochemical processes to refine crude into a variety of petroleum
products; however, the production of asphalt usually consists of desalting, atmospheric and vacuum
distillation, and deasphalting (Athena 2001). Desalting involves water washing the crude to remove any
water-soluble constituents. Atmospheric distillation classifies crude into those constituents that have a
boiling point higher than 650 degrees Fahrenheit. These constituents pass to the vacuum distillation process.
Vacuum distillation allows a lower temperature classification of the residuals from atmospheric distillation.
Deasphalting occurs when the residuals from vacuum distillation are removed through the use of a liquid
hydrocarbon solvent. The steam that is stripped from this solvent is asphalt (Athena 2001).
Athena (2001) and US LCI (2012) provide LCI information for asphalt production in the US; information
in Athena (2001) was used to assess the greenhouse gas emissions and energy requirements corresponding
to asphalt production as modeled by WARM. GaBi also contains a US-based asphalt production process
titled "Bitumen at refinery" which also includes inventory data resulting from crude oil extraction.
Eurobitume (2012) and Stripple (2001) provided asphalt production LCI for Europe and Sweden,
respectively. The US LCI (2012) LCI database includes a "Petroleum refining, at refinery" process which
produces asphalt and uses inventory emissions information from LCI datasets published by Franklin
Associates in 2010.
Eurobitume (2012) provides a detailed LCI of numerous sub-processes within the asphalt production
industry of Europe, citing source materials obtained from industry contacts, a Eurobitume survey, and other
sources from 2008-2010. LCI data include the emissions and energy consumption from crude oil extraction
to the hot storage of asphalt onsite. It is important to note that Eurobitume (2012) includes emissions from
the construction/manufacturing of asphalt production infrastructure.
Asphalt is generally stored hot at the refinery until it is either transported to an asphalt terminal (often by
rail) or by tanker truck (depending on distance) to an HMA plant for use. Transportation distances and
timeframes are critical in order to keep the asphalt at a high enough temperature to ensure a sufficiently low
viscosity so that the material can be pumped from the transport vehicle into heated storage tanks at the
HMA plant (Walker and Davis 2008, Astec 2009). In addition to hot storage at HMA plants, some major
petroleum companies and asphalt pavement producers store hot asphalt at asphalt terminals (e.g., BP, Shell,
Marathon, Associated Asphalt, C.W. Matthews). Terminals have large heated storage tanks that are used
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as a centralized location to hold asphalt until delivery to individual HMA plants. Some asphalt terminals
use steam to heat rail car asphalt tanks so that the solidified material can be withdrawn and stored at the
terminal (Walker and Davis 2008, Astec 2009). However, it does not appear that the US asphalt production
LCI discussed above includes the process energy and process non-energy emissions from the hot onsite
storage of asphalt at terminals. Depending on typical asphalt storage practices and durations, the absence
of this information may have major limitation with the use of the "Petroleum refining, at refinery" dataset
for quantification of environmental impacts of this process.
The US EPA (2006) provided equations for determining emission factors for the storage of organic liquids
based on numerous parameters such as liquid properties, environmental conditions, tank type, and tank
dimensions. However, it would be difficult to develop an average nationwide value for each of these
variables to create a representative LCI dataset including emissions from the asphalt terminal storage,
especially considering the absence of information with respect to the quantity of asphalt stored at terminals
and the duration of storage. Also, the US EPA (2006) does not provide procedures for estimating emissions
resulting from fuel consumption to keep asphalt storage tanks at elevated temperatures. Since the US LCI
(2012) dataset includes publicly-available LCI for crude oil extraction and asphalt production, these LCI
for asphalt pavement EOL management LCA are proposed for use in this report.
3.4.2 Transport
A wide variety of transportation modes, including ocean, road, and rail, are used to move numerous
materials, including crude oil, asphalt, aggregate, pavement mix, and RAP. The emissions associated with
crude oil transport are accounted for in US LCI (2012) petroleum refining processes. The LCI data for fuel-
related emissions from various pieces of transport equipment are included in the US LCI (2012) database.
However, the emissions associated with the manufacturing/building of transport equipment do appear to be
included in these LCI. The transport distances associated with the different stages of asphalt pavement
production, which would be region specific, are needed to estimate the emissions associated with the
transport of other materials (besides crude oil). Wilburn and Goonan (1998) provide transport energy
requirements for aggregate, sand and gravel, and reclaimed asphalt pavement in terms of joules per kg-km.
The Athena Sustainable Materials Institute (ASMI) Impact Estimator for Highways model allows the user
to specify distances between various cradle-to-gate processes in the complete pavement production and
placement process, or the user may choose default values. The model uses a database with numerous pieces
of road-manufacturing equipment, each of which includes default operating specifications such as primary
and secondary fuel consumption rates, production rates, load factors, and daily operational time. However,
model defaults are specific to Canada - the opening input page for a new project only allows selection of a
Canadian province for the project location. The model and accompanying documentation do not provide
the sources of transport LCI due to LCI's proprietary nature.
In its environmental impact assessment of product use, the National Institute of Standards and Technology
(NIST) Building for Environmental and Economic Sustainability (BEES) model considers the transport of
products between the product manufacturer and the end-user. The model allows the user to input
information for the distance between the product manufacturer and the use of the material, although the
model already has a default value included for this distance. However, NIST (2011) does not provide details
on the source of these default distances already included in BEES.
The US EPA (2012) uses crude oil transport information from the US LCI (2012) database and NRC (2005)
for transport-related emissions of HMA pavement materials (e.g., asphalt and aggregates to the HMA plant,
HMA to the road site) for the WARM model. NRC (2005) provides average distances (in Canada) from
aggregate and asphalt production locations to HMA plants and the distance from HMA plants to road sites.
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Distances for asphalt transport were calculated in the same way they were estimated for primary aggregates
in Chapter 2 of this report, using transport data provided in USCB (2010) for the "Coal and Petroleum
Products" commodity. Table 3-3 summarizes the US-wide average transportation distances of asphalt,
HMA, and RAP materials.
Table 3-3. Transport Distances of Different Pavement Materials
Material
Transport
Asphalt
Transport
from
Refinery to
Paving Mix
Plant
Paving Mix
Transport
from Paving
Mix Plant to
Road Sites
Source and
Representative
Commodity
USCB (2010)-
Coal and
Petroleum
Products
Total
Amount
Transported
by Single
Mode
(million tons)
459
Mode
Truck
Rail
Water
Ton-miles
(in
millions)
33,900
52,600
18,600
Average
Transport
Distance
(miles)
73.9
115
40.6
Average
Transport
Distance
(km)
119
185
65.3
20
3.4.3 HMA Plants
HMA plants accept asphalt and specific gradations of aggregate (e.g. sand, gravel), heat and mix the
ingredients using a drum or batch process, and store the mix at a sufficiently elevated temperature until it
can be loaded for transport and laid as pavement at the roadway j ob site. Different gradations of aggregate
are fed into HMA plant rotary dryers that operate at approximately 300 ° F. Aggregates are dried and mixed
with asphalt in the same rotary drum used for drying in continuously mixed plants, whereas aggregates
dried in a rotary drum are discharged, screened, weighed, and then mixed with asphalt in a pug mill in a
batch mix process (NAPA and EAPA 2011).
The environmental emissions from HMA production include particulate emissions from on-site aggregate
handling, aggregate drying, RAP crushing/screening, process energy emissions (e.g., aggregate drying,
asphalt storage tank heating, HMA storage heating), air emissions from the storage of hot asphalt and
pavement mix (e.g., VOCs), and liquid emissions (e.g., stormwater run-off).
Stripple (2001) provides LCI data for HMA plant operation in Sweden, but it appears that only emissions
associated with electricity and energy consumption are included in the dataset. Fuel-use data are reported
to be based on operational information from a single HMA plant, and additional information is not provided.
HMA energy requirements are also provided by NRC (2005), which surveyed five Canadian road builders
to gather information on the energy requirements for pavement manufacturing and road rehabilitation. The
US EPA (2012) used data reported by NRC (2005) to develop energy and emission factors for HMA plants
in WARM.
The Manufacturing Energy Consumption Survey conducted by the US Energy Information Administration
provides US-wide energy used by the asphalt paving mixture and block manufacturing industry (NAICS
code 324121) by fuel type. The survey is conducted every 4 years and the most recent survey presents
energy consumption data for 2010 (US EIA 2013a).
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AP-42 (US EPA 2004) provides air emissions (gaseous and participate matter) from HMA plants specific
to plant type (i.e., drum versus batch mix) and in some cases fuel use (e.g., No. 2 fuel oil, No. 6 fuel oil,
natural gas). The majority of emissions are provided per ton of HMA produced. However, emissions as a
result of truck load-out, silo filling, and asphalt storage are based on equations that use the input of site-
specific factors, such as asphalt volatility and HMA temperature, though default values for these parameters
are provided in the document.
Asphalt paving industry fuel consumption data, asphalt pavement production data, HMA plant particulate
emissions data, and aggregate and asphalt transport data were analyzed to develop an HMA production
process LCI dataset as presented in Table 3-4. Emissions are provided per kilogram "Asphalt pavement, at
production" flow. The industry-wide fuel-specific energy consumption data for the asphalt paving mixture
and block industry (NAICS 324121) compiled for 2010 by the US EIA (2013a) along with the total
pavement production data for 2010 compiled by NAPA (2013a) were used to estimate the energy
requirement for producing one kilogram of pavement. The energy associated with the "Other" fuel category
was assigned to natural gas because on an equal-energy (btu) basis, natural gas constituted 72% of the total
fuel consumed by the asphalt paving mixture and block manufacturing industry.
Particulate emissions data were taken from AP-42, Hot Mix Asphalt Plants (US EPA 2004) since HMA
production constitutes the majority (-80%) of national asphalt pavement production (NAPA 2013b).
Particulate emissions were modeled as the average uncontrolled emissions from a drum mix plant dryer and
a batch mix plant dryer, hot screens, and mixer. AP-42 only provides particulate matter emission factors
for the dryer, hot screening, and mixing process and does not account for particulate matter emissions from
aggregate stockpiles, aggregate loading, aggregate conveyance, and onsite equipment movement. Due to
this limitation, uncontrolled particulate emission factors reported by AP-42 were selected for modeling
particulate emissions from the HMA plant. While particulate emissions do result from dryer fuel
combustion, it is expected that these only make a minor contribution to the overall particulate emissions
released from drying and mixing, particularly since natural gas is the primary fuel used by HMA plants, as
described above.
Polycyclic aromatic hydrocarbons (PAHs) have been reported to be one of the major classes of air pollutants
emitted from HMA facilities (US EPA 2000). Based on a US EPA estimate, approximately 13 Ib of PAHs
are emitted annually from a typical batch mix HMA facility with an annual production rate of 100,000 tons
of HMA (US EPA 2000). Lee et al. (2004) conducted a study to quantify PAHs emissions from batch
HMA plants. Gas samples were taken from batch mixers, preheating boilers, and discharging chutes. The
reported PAH emission factor for batch mix plants was 139 mg/ton (30.6 Ib per 100,000 tons) of product
(Lee et al. 2004). Lee et al. (2004) also reported that approximately 90% of carcinogenic PAHs were
removed by air-pollution-control equipment at the HMA plants studied.
AP-42 does provide equations for estimating non-fuel related VOCs emissions from HMA silo filling and
load-out based on site-specific variables such as temperature and asphalt volatility data. However, the
individual VOC emissions could not be estimated using the procedure outlined in AP-42 without making a
variety of assumptions. The VOC emissions were, therefore, not estimated and included in Table 3-4. The
absence of VOC emissions information in the dataset may be a major limitation in assessing the
environmental impacts associated with the asphalt pavement production process. It should also be noted
that due to lack of data, stormwater emissions associated with aggregate and RAP stockpiles and emissions
from plant construction and component manufacture were not included in Table 3-4.
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Table 3-4. Proposed LCI Dataset: Asphalt Pavement Production, Average Energy Mix
Input Flow
Limestone, at mine
Bitumen, at refinery
Electricity, at industrial user
Diesel, combusted in
industrial boiler
Natural gas, combusted in
industrial boiler
Transport, barge average
fuel mix
Truck transport, class 8,
heavy heavy-duty (HHD),
diesel, long-haul, load
factor 0.75
Transport, train, diesel
powered
Output Flow
Asphalt pavement, at
production
Particulates, < 2.5 um
Particulates, > 10 um
Particulates, > 2.5 um, and
< lOum
Source
US EPA (20 12)
US EPA (20 12)
USEIA(2013a)
USEIA(2013a)
USEIA(2013a)
USCB (2010)
USCB (2010)
USCB (2010)
Source
US EPA (2004)
US EPA (2004)
US EPA (2004)
Category
Flows
Flows
Flows
Category
Construction and
Demolition
Debris
Management
air/unspecified
air/unspecified
air/unspecified
Unit
kg
kg
kWh
L
m3
t*km
t*km
t*km
Unit
kg
kg
kg
kg
Amount
0.95
0.05
0.0033
0.001
0.0042
0.0155
0.0697
0.0277
Amount
;
0.000443
0.0123
0.00228
3.5 LCI Related to Disposal
Various literature sources suggest different rates of landfill disposal of asphalt pavement. Wilburn and
Goonan (1998) estimated that about 20% of asphalt pavement is disposed of in landfills. A 2011 NAPA
(2013b) survey of RAP use, which included 203 asphalt mix producing companies from 49 states
representing 1091 plants, suggested that less than 1% of all RAP is disposed of in a landfill. A compilation
of the data from the USGS, NAPA and permitted CDD materials processing and disposal facilities compiled
by US EPA (2014a) from across the US suggests that approximately 5% of RAP is landfilled.
Air emissions from landfill disposal of asphalt pavement will result from the operation of landfill equipment
during material and cover soil compaction and placement, including both fuel-related and pre-combustion
emissions. RAP exposure to precipitation or other liquids (e.g., landfill leachate) is expected to result in
leached emissions and the emissions are expected to depend on the biogeochemical environment (e.g.,
MSW landfill, CDD landfill). Only a single Ecoinvent LCI dataset (2014) appears to include leached
emissions from waste pavement.
Leachable emissions from RAP were estimated using the SPLP (batch test) and leaching column data
reported by Townsend and Brantley (1998). Townsend and Brantley (1998) conducted batch and column
leaching tests on asphalt pavement samples collected from six sites. Batch test data were used for
contaminants except heavy metals. Batch test concentrations were multiplied by the total solution volume
and divided by the sample mass to estimate leachability on a per-kilogram-asphalt pavement basis.
Contaminant emissions were not estimated for parameters below the detection limit in more than half (i.e.,
three) of the samples; bromide, sodium, and potassium were excluded. The detection limit was used as the
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concentration for measurements below detection for samples in which the contaminant emission was
quantified. Nitrate and sulfate data reported by the study were not used since the SPLP extraction fluid
contains these anions. The emissions of non-purgeable organic compound were not estimated as this
compound is not included as an elementary flow in US LCI (2012). Total dissolved solid (TDS) data
reported by the study were also not included to avoid double counting of emissions as some of the
contaminants listed in Table 3-5 are included in the TDS measurement.
None of the measured heavy metals and organic compounds leached above the detection limits in batch
leaching tests. Therefore, column test data were used to estimate heavy metals and organics emissions. All
the organic compounds (VOCs and PAHs) and heavy metals except lead targeted in this study were below
detection in the column tests. The total lead leached in saturated column test was greater than that of the
unsaturated column test; the lead emission was estimated based on the saturated column test data, which
corresponds to a L:S ratio of 0.257. Lead emission was estimated for each of the six samples by dividing
the total amount of lead leached from RAP sample by the total RAP amount used for the test. The average
lead leached from six samples was estimated to be 6.58 microgram per kg of RAP.
Azah (2011) conducted batch and (saturated and unsaturated SPLP) column leaching tests on RAP samples
collected from five Florida locations to assess PAH leaching. Leaching data were selected from column
tests for PAHs which were detected in over half of the samples. Four PAH's were detected in over half of
the samples during unsaturated column testing (i.e., fluoranthene, pyrene, benzo(k)fluoranthene,
benzo(a)pyrene) while three PAHs were detected in over half of the samples during saturated column testing
(i.e., pyrene, benzo(g,h,i)perylene, benzo(b)fluoranthene). Because the final L:S was higher for saturated
column testing compared to unsaturated column testing (i.e., approximately 2 versus 1.2, respectively)
saturated column leaching results were selected over unsaturated column testing results for pyrene since
this compound was detected in over half of the samples for both column testing conditions. Data were used
to estimate liquids emissions from the disposal of RAP in CDD material landfills. Column leaching data
were used to estimate the total leachable amount of PAHs - all below-detection-limit (BDL) measurements
subsequent to detected concentrations were excluded from the analysis. The other BDL measurements
were included at the detection limit concentration. Temporal column PAH concentrations (ng/L) were
multiplied by the L:S ratio (L/kg) of the solution and values were summed for each PAH to estimate the
PAH's total leachability on a per-kilogram-asphalt-pavement basis.
The energy use and the associated emissions from landfill operation (e.g., waste placement, compaction)
include diesel use in heavy equipment and electricity use in landfill buildings (e.g., administrative buildings,
workshop). In the absence of additional data, it was assumed that asphalt pavement would be transported
20 km for landfill disposal. Diesel consumption from landfill operations and electricity consumption from
landfill administrative offices and workshop areas were estimated from Ecobalance (1999) and IWCS
(2014b), respectively, and these flows are included as the "CDD landfill operations" input flow, as detailed
in Chapter 2. Details on how cover soil was assigned for the placement of demolished asphalt pavement in
a CDD landfill is also included in Chapter 2, and is based on the bulk density of asphalt pavement as
provided in CCG (2006). RAP leaching data, energy consumption data from landfill operations, and the
assumed transport distance were used to develop an LCI process dataset for the disposal of RAP at an
unlined inert debris landfill, as presented in Table 3-5. Emissions are provided per kilogram "Asphalt
pavement, at unlined CDD landfill" flow.
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Table 3-5. Proposed LCI Dataset: Asphalt Pavement, at Unlined CDD Landfill
Input Flow
Asphalt pavement,
recovered from
milling
Truck transport, class
8, heavy heavy-duty
(HHD), diesel, short-
haul, load factor 0.75
CDD landfill
operations
Cover soil, from
offsite source
Output Flow
Asphalt pavement, at
unlined CDD landfill
Calcium, ion
Chloride
COD, Chemical
Oxygen Demand
Fluoride
Lead
Magnesium
Fluoranthene
Pyrene
Benzo(k)Fluoranthene
Benzo(a)pyrene
Benzo(g,h,i)perylene
Benzo(b)fluoranthene
Source
Assumed
See Chapter 2
See Chapter 2
Source
Townsend and
Brantley (1998)
Townsend and
Brantley (1998)
Townsend and
Brantley (1998)
Townsend and
Brantley (1998)
Townsend and
Brantley (1998)
Townsend and
Brantley (1998)
Azah(2011)
Azah(2011)
Azah(2011)
Azah(2011)
Azah(2011)
Azah(2011)
Category
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Category
Construction and Demolition
Debris Management
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Construction and Demolition
Debris Management/
Groundwater
Construction and Demolition
Debris Management/
Groundwater
Construction and Demolition
Debris Management/
Groundwater
Construction and Demolition
Debris Management/
Groundwater
Construction and Demolition
Debris Management/
Groundwater
Construction and Demolition
Debris Management/
Groundwater
Unit
kg
t*km
kg
kg
Unit
kg
mg
mg
mg
mg
ug
mg
ng
ng
ng
ng
ng
ng
Amount
1
0.001*20
1
0.0414
Amount
;
273
70.3
2230
23.9
6.58
26.7
49.3
34.6
2.55
5.74
54.9
3.07
3,6 LCI Related to Recycling
3.6.1 RAP Processing
RAP may need to be processed prior to recycling as an aggregate or for the production of new paving mix.
The extent of RAP processing would be dependent on a number of factors, such as the pavement-removal
method (i.e., milling, demolition and excavation), duration it is stockpiled, and end-use specifications. For
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those instances where RAP is produced as a result of road demolition and excavation, RAP must be size-
reduced before it can be recycled into new HMA or for most aggregate applications. Additional processing
is also likely to be required when RAP constitutes greater than 20% of the new paving mix for the mix to
meet specified fractionation requirements. According to Brock and Richmond (2007), many continuously
fed HMA plants will have a closed-circuit crushing system on the front end of the aggregate feeder where
oversized milled material and aggregate is screened away from the feed, crushed, and then returned to the
screen. Emissions from crushing and screening RAP millings could in this case be considered part of the
total emissions released from the HMA plant. However, it is possible that RAP produced as a result of
pavement demolition and excavation may be crushed offsite from an HMA plant.
The emissions from crushing/sorting equipment include those associated with materials (e.g., equipment,
consumables), energy (fuel) inputs, and particulate matter released during processing. While particulate
emissions information for asphalt pavement crushing/sorting was not located, Wilburn and Goonan (1998)
reported energy requirement of 16.5 MJ for crushing/sorting 1 MT of recycled asphalt pavement based on
data from the Portland Cement Association and data from a recycling facility in Colorado. In the absence
of additional data, electricity and diesel consumption were each assumed to constitute 50% of the total
energy requirements. A similar approach was used by the US EPA (2003) for estimating emission factors
for demolished PCC processing for WARM. Energy units were converted into electricity and diesel
quantities assuming 3,412 btu/kWh and 138,690 btu/gallon diesel, as provided by US EIA (2013b).
Table 3-6 presents the proposed LCI dataset for RAP processing. Similar to aggregate crushing and sorting
during production, it is expected that particulates would be a source of emissions released from RAP
crushing and sorting operations. However, due to a lack of data, fugitive dust emissions released during the
grinding process and emissions from manufacturing, maintaining, and disposing of/dismantling the
grinding equipment are not included in Table 3-6. If recovered pavement is not processed prior to use, the
diesel and electricity consumption should be excluded from the LCA. In the absence of national average
data on the distance from the road demolition site to RAP processing, a distance of 20 km was assumed
with transport by a single-unit, short-haul, diesel-powered truck.
Table 3-6 Proposed LCI Dataset: Reclaimed Asphalt Pavement, at Processing Plant
Input Flow
Asphalt pavement, from road
demolition
Diesel, combusted in
industrial equipment
electricity, at industrial user
Truck transport, class 8,
heavy heavy-duty (HHD),
diesel, short-haul, load factor
0.75
Output Flow
Reclaimed asphalt pavement,
at processing
Source
Wilburn and Goonan
(1998)
Wilburn and Goonan
(1998)
Source
Category
Construction and
Demolition Debris
Management
Flows
Flows
Category
Construction and
Demolition Debris
Management
Unit
kg
L
kWh
t*km
Unit
kg
Amount
1
0.000213
0.00229
0.02
Amount
;
3.6.2 RAP Use in HMA
Because RAP contains valuable asphalt binder and aggregate, its use in new HMA to replace primary
aggregates and binders has been perceived as the most economical use of RAP (Copeland 2011); this use
also avoids the environmental impacts from the primary production and transport of both materials. Milled
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Section 3 - Asphalt Pavement
RAP, about 75% of which has a typical diameter less than 0.5 in., may often be added without any further
processing besides screening and crushing of oversized material (Brock and Richmond 2007). However,
mixes using more than 20% RAP need additional RAP crushing and sorting to fractionate the material
according to the mix design.
Aurangzeb et al. (2014) and COLAS (2003) suggest that the energy necessary for HMA production is not
related to RAP content for mixtures using less than or equal to 50% RAP. However, information on whether
RAP content has an effect on HMA plant non-fuel emissions was not discovered. Additional information
from a couple of French studies suggests that RAP content may impact air (e.g., volatile organic
compounds, polycyclic aromatic hydrocarbons, odor) and liquid (e.g., total hydrocarbons and polycyclic
aromatic hydrocarbons) emissions from pavement (Jullien et al. 2006, Legret et al. 2005).
3.6.3 RAP Use as Aggregate
RAP produced from road demolition and excavation activities will likely need to be crushed prior to use in
structural fill applications; however, it is possible that millings may be used without additional processing.
The primary emissions resulting from the use of RAP as a fill material include leaching to groundwater
(Townsend and Brantley 1998, Azah 2011). The use of RAP as aggregate would avoid the emissions
resulting from the production and transport of primary aggregates as presented in Chapter 2. Table 3-7
presents LCI for RAP transport and use as aggregate. It was assumed that the processed RAP will be
transported 20 km from the processing site to the end-use site.
Table 3-7. Proposed LCI Dataset: Reclaimed Asphalt Pavement, Use as Fill
Input Flow
Reclaimed asphalt pavement, at
processing
Truck transport, class 8, heavy
heavy-duty (HHD), diesel,
short-haul, load factor 0.75
Output Flow
Reclaimed asphalt pavement,
use as fill
Calcium, ion
Chloride
COD, Chemical Oxygen
Demand
Fluoride
Lead
Magnesium
Fluoranthene
Pyrene
Source
Source
Townsend and
Brantley (1998)
Townsend and
Brantley (1998)
Townsend and
Brantley (1998)
Townsend and
Brantley (1998)
Townsend and
Brantley (1998)
Townsend and
Brantley (1998)
Azah (20 11)
Azah (20 11)
Category
Construction and Demolition
Debris Management
Category
Construction and Demolition
Debris Management
water/groundwater
water/groundwater
water/groundwater
water/groundwater
water/groundwater
water/groundwater
Construction and Demolition
Debris Management/
groundwater
Construction and Demolition
Debris Management/
groundwater
Unit
kg
t*km
Unit
kg
mg
mg
mg
mg
lig
mg
ng
ng
Amount
1
0.001*20
Amount
;
273
70.3
2230
23.9
6.58
26.7
49.3
34.6
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Section 3 - Asphalt Pavement
Benzo(k)Fluoranthene
Benzo(a)pyrene
Benzo(g,h,i)perylene
Benzo(b)fluoranthene
Azah(2011)
Azah(2011)
Azah(2011)
Azah(2011)
Construction and Demolition
Debris Management/
groundwater
Construction and Demolition
Debris Management/
groundwater
Construction and Demolition
Debris Management/
groundwater
Construction and Demolition
Debris Management/
Groundwater
ng
ng
ng
ng
2.55
5.74
54.9
3.07
3.7 Data Gap Analysis and Opportunities for Additional LCI Data
The Project Team reviewed LCA software models, government and industry publications, and peer-
reviewed literature to determine the availability of US-based asphalt pavement management LCI data.
Three models and three publications were identified that contained at least partial emissions data for some
portion of asphalt management. With the exception of WARM and NREL (WARM uses information from
a limestone mining process included in the 2009 NREL database), each of these data sources is independent
of each other, (i.e., the same primary data are not being used in multiple sources). As shown in Table 3-8,
WARM process data are partial because WARM only analyzes GHG emissions. Similar to WARM, AP-
42 only includes partial data because the datasets only include process air emissions. Wilburn and Goonan
(1998) only provide energy requirements for RAP processing, without distinguishing what fuels are used
to provide this energy. Townsend and Brantley (1998) used SPLP batch and column testing to estimate the
leachability of numerous organic, inorganic, and metal parameters. However, the leaching data are only
considered partial because testing occurred in 1997-1998, and it appears that some laboratory detection
limits have significantly decreased since that time; for example, Azah (2011) reports the leachable amount
of PAHs from RAP, where the detection limit for these tests ranged between 0.0001 and 3.5 (ig/L while the
detection limit for Townsend and Brantley (1998) ranged between 0.5 and 5 (ig/L. Also, Townsend and
Brantley (1998) column testing occurred over 40 days while column testing by Azah (2011) occurred over
35 days. Additional extended runs would be necessary to observe concentration trends to estimate the total
leachable concentrations from RAP placed in a fill or unlined landfill. Data from Azah (2011) are partial
because Azah only presents the leachable amounts of PAHs. All identified models and publications that
include environmental burdens with respect to some portion of asphalt pavement management are presented
in Table 3-8. The table shows that LCI data are better documented for primary material extraction and HMA
production processes than for pavement removal and EOL management.
Based on a review of these sources, the following needs for additional US-specific LCI data with respect
to the EOL management of asphalt pavement were identified:
1. A complete inventory of environmental burdens associated with constructing, operating, and
decommissioning an HMA plant. AP-42 estimates emissions for a number of sub-processes at
HMA plants, where emission factors are categorized by plant type and fuel type (US EPA 2004).
Specific air emission datasets could be developed for batch and drum mix plants, categorized by
whether they operate on natural gas, No. 2 fuel oil, No. 6 fuel oil, or waste oil. However,
information on total HMA production from each of these plant types would be necessary to develop
individual datasets representative of nationwide average emissions. Furthermore, information on
participate emissions from HMA plants is limited to actual measurements of a very small fraction
of HMA plant processes. It appears that particulate emissions from onsite aggregate loading,
discharging, conveyance, and stockpiles have not been assessed. Also, LCI data associated with
HMA plant construction and component manufacture, as well as data related to plant
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decommissioning were not found in literature. Besides air emissions provided by AP-42, air
emissions are compiled by the US EPA Office of Air Quality Planning and Standards every three
years for a variety of industries and are organized by NAICS code (US EPA 2014b). The most
recent (2011) point source emissions inventory has nearly 1.9 million air emission
measurements. It would be possible to aggregate the total emissions of each parameter for all point
sources within an industry across the nation and correlate these emissions with national asphalt
production data to develop an additional alternative average US HMA plant air emissions inventory
for each ton of HMA produced. However, a portion of these emissions is associated with energy
use, which is accounted for using such EPA LCI processes as "diesel combustion in industrial
equipment" and "natural gas combustion in industrial boiler" included in the proposed LCI for
HMA.
2. Milling/Excavation equipment fuel consumption, operation, and manufacturing emissions.
The US EPA NONROAD model simulates air emissions from non-road equipment, including
milling and excavation equipment, on a per-horsepower-operating-hour basis. Published
equipment-specific loading capacities (e.g., from equipment manufacturer performance
handbooks) could be used to estimate a conservative loading rate to project emissions on a mass-
emission-per-mass-pavement-removed basis by using these emission factors as provided in
NONROAD. This is a similar approach to that taken by the Washington State Department of
Transportation in an LCA they undertook to compare PCC road rehabilitation alternatives (Weiland
and Muench 2010). However, while this information would allow for estimating fuel-related air
emissions due to equipment operation, no estimates of particulate matter emissions from road
abrasion or environmental burdens associated with milling/excavation equipment manufacturing
were found in the literature. Also, while it appears that water spray is used to suppress particulate
emissions from milling, no estimates were found on the quantity or quality of the water released
from spraying.
3. Fuel-related and particulate matter emissions from RAP processing. Only Wilburn and
Goonan (1998) estimated the amount of energy necessary to process RAP. This energy was not
categorized by fuel type (e.g. electricity, diesel). An estimate of the average quantity and mix of
fuels used for RAP processing is necessary to develop a more accurate LCI dataset. Also, we found
no source of data for particulate matter emissions released as a result of RAP processing. No
information on the environmental burdens associated with the manufacture or decommissioning of
RAP processing equipment was identified.
4. Leachable emissions from the landfill disposal or use of RAP as aggregate. Although an
estimate of liquid emissions from RAP disposal in unlined and inert debris landfills and for use as
aggregate is included in the proposed LCI datasets and was developed based on available batch and
column RAP leaching test data, these estimates are probably lower than the actual emission due to
partial leaching of contaminants attributed to the L:S ratio of these tests. Future research should
consider estimating the long-term leaching of RAP.
Although the discussion presented in this chapter focuses on HMA, there has been significant growth
in the use of WMA in recent years; approximately 12% of the asphalt pavement produced in 2010 was
WMA (FHWA 2012), while approximately 24% of the asphalt pavement produced in 2012 was WMA
(NAPA 2013a). While the percentages of asphalt and binder are generally the same for HMA and
WMA, WMA production requires the use of an additive to reduce the viscosity of the asphalt so that it
can be mixed and applied at a lower temperature than HMA. The resulting (28°C or more) temperature
reduction impacts air emissions from the pavement production and application process (FHWA 2012).
While RAP may be incorporated into WMA, it appears that standard practices for this beneficial use
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Section 3 - Asphalt Pavement
are not yet well established (TRB 2011). Development of LCI datasets for WMA production and EOL
management should be considered as additional data on this technology become available.
Table 3-8. Overview of LCI Data Available
Process
Crude Oil
Extraction
Asphalt
Production
HMA
Production
Asphalt
Pavement
Removal
Transport
Landfill
Disposal
RAP
Processing
RAP Use
as
Aggregate
WARM
P
P
P
P
P
GaBi
X
X
Athena
X
X
X
AP-
42
P
Wilburn and
Goonan
(1998)
P
P
US LCI
(2012)
X
X
X
Townsend
and Brantley
(1998)
P
P
Azah
(2011)
P
P
3.8 References
Astec Industries (2009). Rockmart Asphalt Terminal. Hot-Mix Magazine, Astec Industries, Inc.
http://bit.ly/lojDuuU. Accessed 10 March 2014.
Athena (2001). A Life Cycle Inventory for Road and Roofing Asphalt. A Report Prepared by Franklin
Associates, A Service of McLaren-Hart/Jones for the Athena Sustainable Materials Institute, March
2001. http://bit.lv/VVYcuA. Accessed 19 February 2014.
Aurangzeb, Q., Al-Qadi, I.L., Ozer, H., Yang, R. (2014). Hybrid Life Cycle Assessment for Asphalt
Mixtures with High RAP Content. Resources, Conservation and Recycling, 83, 77-86.
Azah, E.M. (2011). The Impact of Fob/cyclic Aromatic Hydrocarbons (PAHs) on Beneficial Use of Waste
Materials. Ph.D. Dissertation. University of Florida, Gainesville, FL, USA.
Bolen, W.P. (2013). 2011 Minerals Yearbook - Sand and Gravel, Construction [Advance Release].
Published by the United States Geological Survey, May 2013. http://on.doi.gov/1 zpWK2z.
Accessed 12 March 2014.
Townsend, T.G., Brantley, A.S. (1998). Leaching Characteristics of Asphalt Road Waste. Report #98-2.
State University System of Florida, Florida Center for Solid and Hazardous Waste Management.
Brock, J.D., Richmond, J.L., Sr. (2007). Technical Paper T-127: Milling and Recycling. ASTEC, Inc., An
Astec Industries Company, Chattanooga, TN, USA. http://bit.ly/lnJwHyl. Accessed 21 February
2014.
CCG (2006). Targeted Statewide Waste Characterization Study: Waste Disposal and Diversion Findings
for Selected Industry Groups. A Report Prepared by Cascadia Consulting Group for the California
Integrated Waste Management Board, June 2006.
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COLAS (2003). The Environmental Road of the Future, Life Cycle Analysis. Energy Consumption &
Greenhouse Gas Emissions, COLAS Group September 2003. http://bit.ly/loCjkhf Accessed 4
April 2014.
Copeland, A. (2011). High Reclaimed Asphalt Pavement Use. FHWA Publication No.: FHWA-HRT-11-
057, McLean, VA, USA. September 2011.
Ecobalance (1999). Life Cycle Inventory of a Modern Municipal Solid Waste Landfill. A Report Prepared
by Ecobalance, Inc. for the Environmental Research and Education Foundation, June 1999.
Ecoinvent (2014). Swiss Center for Life Cycle Inventories: Ecoinvent Centre. Dataset Information (UPR):
Treatment of Waste Asphalt, Sanitary Landfill, CH, (Author: Roland Hischier inactive).
http://bit.ly/ltRWFED. Accessed 2 June 2014.
Eurobitume (2012). Life Cycle Inventory: Bitumen. 2nd Edition, The European Bitumen Association,
Brussels, Belgium, July 2012. http://bit.lv/lkEJqO5. Accessed 20 February 2014.
FHWA (2011). Reclaimed Asphalt Pavement in Asphalt Mixtures: State of the Practice, Publication No.
FHWA-HRT-11-021. The Federal Highway Administration, US Department of Transportation at
the Research, Development, and Technology Turner-Fairbank Highway Research Center, McLean,
VA, USA, April 2011.
FHWA (2012). Warm Mix Asphalt (WMA). Federal Highway Administration, US Department of
Transportation, January 2012. http://l .usa.gov/lqKulOH. Accessed 11 June 2014.
IWCS (2014b). Personal Communication between Pradeep Jain, P.E., Innovative Waste Consulting
Services, LLC with a Confidential Client.
Jullien, A., Moneron, P., Quaranta, G., Gaillard, D. (2006). Air Emissions from Pavement Layers
Composed of Varying Rates of Reclaimed Asphalt. Resources, Conservation and Recycling, 47,
356-374.
Kelly, W.M. (2011). Mineral Industry of the State of New York 2007-2010. New York State Museum
Record 3, Published with a Report on the Economic Impact of the New York State Mining and
Construction Materials Industry by Rochelle Ruffer and Kent Gardner. http://bit.ly/loCp2Q5.
Accessed 12 March 2014.
Lee, W., Chao, W., Shih, M., Tsai, C., Chen, T.J., Tsai, P. (2004). Emissions of Fob/cyclic Aromatic
Hydrocarbons from Batch Hot Mix Asphalt Plants. Environmental Science & Technology, 38 (20),
6274-6280.
Legret, A., Odie, L., Demare, D., Jullien, A. (2005). Leaching of Heavy Metals and Fob/cyclic Aromatic
Hydrocarbons from Reclaimed Asphalt Pavement. Water Research, 39, 3675-3685.
NAPA (2013a). Annual Asphalt Pavement Industry Survey on Recycled Materials and Warm-Mix Asphalt
Usage: 2009-2012, Information Series 138. National Asphalt Pavement Association, Lanham, MD,
USA, December 2013.
NAPA (2013b). 2nd Annual Asphalt Pavement Industry Survey on Reclaimed Asphalt Pavement, Reclaimed
Asphalt Shingles, and Warm-Mix Asphalt Usage: 2009-2011, Information Series 138. National
Asphalt Pavement Association, Lanham, MD, USA, April 2013.
NAPA, EAPA (2011). The Asphalt Paving Industry: A Global Perspective, 2nd Edition. European Asphalt
Pavement Association and the National Asphalt Pavement Association, February 2011.
Natural Resources Canada (2005). Road Rehabilitation Energy Reduction Guide for Canadian Road
Builders. Canadian Construction Association, Issued by the Canadian Industry Program for Energy
Conservation, Ottawa, ON, Canada. http://bit.ly/ln87bxS. Accessed 19 February 2014.
NIST (2011). Inventory Analysis. A Report Prepared by the National Institute for Safety and Technology
for the Building for Environmental and Economic Sustainability Software.
http://l.usa.gov/lto21r3. Accessed 3 April 2014.
PE International (n.d.). Gabi Software. Search GaBi Databases. http://bit.ly/ln7njQ5. Accessed May 2014.
Stripple, H. (2001). Life Cycle Assessment of Road - A Pilot Study for Inventory Analysis, 2nd Revised
Edition. A Report Prepared by the FVL Swedish Environmental Research Institute for the Swedish
National Road Administration, March 2001. http://bit.ly/lk623dN. Accessed 20 February 2014.
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TRB (2011). NCHRP Report 691: Mix Design Practices for Warm Mix Asphalt. A Report Prepared by
Ramon Bonaquist of Advanced Asphalt Technologies, LLC for the National Cooperative Highway
Research Program, Transportation Research Board of the National Academies, Washington, B.C.,
USA.
US EIA (2013a). 2010 Manufacturing Energy Consumption Survey Data. US Energy Information
Administration, Washington, B.C., USA. http://l .usa.gov/U4guIv. Accessed 6 June 2014.
US EIA (2013b). Energy Units and Calculations Explained. US Energy Information Administration,
Washington, B.C., USA. http://l.usa.gov/ljeper3. Accessed 13 June 2014.
US EIA (2014). Petroleum and Other Liquids, Supply and Bisposition: Asphalt and Road Oil. US Energy
Information Administration, Washington, B.C., USA. http://l .usa.gov/lnePIsv. Accessed 24
March 2014.
US EPA (1995a). Compilation of Air Pollutant Emission Factors - 5th Edition, Volume I: Stationary Point
and Area Sources. Office of Air Quality Planning and Standards, Office of Air and Radiation, US
http://l.usa.gov/lmgxh6jUS.
US EPA (2000). Hot Mix Asphalt Plants Emission Assessment Report. A Report Prepared by Emissions
Monitoring and Analysis Bivision of the US Environmental Protection Agency for Midwest
Research Institute and Eastern Research Group, Inc., Becember 2000.
US EPA (2003). Background Bocument for Life-Cycle Greenhouse Gas Emission Factors for Clay Brick
Reuse and Concrete Recycling. EPA530-R-03-017, US Environmental Protection Agency, 7
November 2003.
US EPA (2004). Section 11.19.2 - Crushed Stone Processing and Pulverized Mineral Processing. AP 42,
Fifth Edition, Volume I, Chapter 11: Mineral Products Industry, US Environmental Protection
Agency. http://l .usa.gov/ljerheN. Accessed 4 April 2014.
US EPA (2006). Section 7.1 - Organic Liquid Storage Tanks AP 42, Fifth Edition, Volume I, Chapter 7:
Liquid Storage Tanks, US Environmental Protection Agency. http://l .usa.gov/lqkteVT. Accessed
2 June 2014.
US EPA (2012). Asphalt Concrete. US EPA for the Waste Reduction Model, Version 12, US Environmental
Protection Agency, February 2012. http://l .usa.gov/VLedB3. Accessed 19 February 2014.
US EPA (2014a). Methodology to Estimate the Quantity, Composition, and Management of Construction
and Bemolition Bebris in the United States. A Report Prepared by Innovative Waste Consulting
Services, LLC and Pegasus Technical Services, Inc. for the US Environmental Protection Agency,
June 2014, Unpublished report.
US EPA (2014b). The 2011 National Emissions Inventory - Technology Transfer Network Clearinghouse
for Inventories & Emission Factors. http://l .usa.gov/lxTkdaE. Accessed April 2014.
US LCI (2012). US Life Cycle Inventory Batabase. National Renewable Energy Laboratory.
http://www.nrel.gov/lci/. Accessed 20 February 2014.
USCB (2010). 2007 Economic Census, Transportation, Commodity Flow Survey, EC07TCF-US. United
States Bepartment of Transportation, Research and Innovative Technology Administration, Bureau
of Transportation Statistics and the United States Bepartment of Commerce, Economics and
Statistics Administration, United States Census Bureau. April 2010.
Walker, B., Bavis, J. (2008). An Overview of Storage and Handling of Asphalt. Asphalt: The Magazine of
the Asphalt Institute. 13 August 2008. http://bit.lv/loCCPX4. Accessed 10 March 2014.
Weiland, C.B., Muench, S.T. (2010). Life Cycle Assessment of Portland Cement Concrete Interstate
Highway Rehabilitation and Replacement, WA-RB 744.4. WSBOT Research Report Published by
the Washington State Bepartment of Transportation, Office of Research and Library Services,
February 2010.
Wilburn, B.R., Goonan, T.G. (1998). Aggregates from Natural and Recycled Sources: Economic
Assessments for Construction Applications - A Materials Flow Analysis. US Geological Survey
Circular 1176, US Geological Survey and US Bepartment of the Interior.
Willett, J.C. (2013). 2011 Minerals Yearbook - Stone, Crushed [Advance Release]. US Geological
Survey, March 2013. http://on.doi.gov/lxTlZZo. Accessed 12 March 2014.
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Section 4 - Asphalt Shingles
4 Asphalt Shingles
4,1 Introduction
Asphalt shingles are more commonly used over other roofing alternatives (e.g., wood, tile, slate, and metal)
due to their relatively lower material and installation cost and their durability (ARMA 2014). Four out of
five homes in the US are covered with asphalt shingles (ARMA 2014). More than 12 MMT (12.5 billion
ft2) of shingles are manufactured in the US annually; approximately 65% are used for re-roofing projects
and 35% are for new roofs (Brock 2007). The sources of discarded shingles are post-manufacturing and
post-consumer (i.e. from construction, renovation, and demolition activities). Post-consumer shingles
generated from construction, renovation, and demolition activities are commonly referred to as tear-offs.
Although old shingles may be overlain by new shingles during reroofing, most building codes limit
maintenance of one reroof without removing the existing shingles. The shingles, therefore, are removed at
some point after their service life, which typically is 20 years (NCHRP 2013).
Approximately 10 MMT of asphalt shingles are discarded annually in the US; in 2011, approximately 9
MMT were disposed of at permitted or registered solid waste disposal facilities (US EPA (2014)) and nearly
1.3 MMT were recovered for use in pavement production NAPA (2013). Roughly 90% of recovered asphalt
shingles are comprised of tear-off shingle scrap and 10% represent post-manufacture scrap (VANR 1999,
Sengoz and Topal 2005). Post-manufacture scrap tends to be more uniform (relative to tear-offs) and
typically consists of shingles and packaging material (e.g., paper or plastic). However, tear-off shingles
contain other roofing debris (e.g., wood, paper, metal, etc.) and have variable properties since different
loads of shingles may have different asphalt composition and may have been subject to varying degrees of
weathering or outdoor exposure.
The discarded shingles are transported either to a landfill for disposal or to a processing facility and
eventually used for asphalt pavement production as depicted in Figure 4-1 While not an established practice
in the US, the use of discarded shingles as a fuel source in an industrial application (e.g., cement
manufacturing) has been explored on a limited scale (OCC 2008, Lee 2011). Figure 4-1 identifies the flow
of materials and processes that should be considered for LCA of asphalt shingles EOL management.
Asphalt Shingles
End-of-Life
Product Removal
Shingle Recovery
and Processing
HMA/WMA
Production Unit
Process
Bitumen
Production
Aggregate
Production
Cement Kiln Fuel
Sustitutue
Ash Landfilling
Landfilling
Figure 4-1. Asphalt Shingle EOL Management Processes
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Multimedia Environmental Assessment Section 4 - Asphalt Shingles
4.2 EOL Management
Several regional composition studies suggest that composition roofing (which consists of asphalt shingles
and attached roofing tar and tar paper), comprises 2.1 to 18.3% (by weight) of CDD materials received at
landfills (CCG 2006, CCG 2008, CCG 2009, COM 2009, COM 2010, and RWB et al. 2010). Based on the
88.1 MMT total amount of CDD materials disposed of at permitted or registered solid waste management
facilities in 2011 (US EPA 2014), this suggests that approximately 2.4 to 16 MMT of composition roofing
were placed in landfills.
As identified in Figure 4-1, three potential EOL management pathways for asphalt shingles are HMA
production, combustion in a cement kiln, and disposal. Closed-loop recycling of asphalt shingles into new
asphalt shingles is not a viable recycling option at present due to challenges in meeting stringent
manufacturer feedstock specifications (Snyder 2001, OCC 2008). Consequently, applicable closed-loop
recycling option and the associated LCI data (i.e., raw material extraction and product manufacturing data
for asphalt shingles) are not discussed in this report.
Due to their substantial asphalt content (approximately 20% in fiberglass shingles), the use of asphalt
shingles in asphalt paving mix production has increased significantly in recent years from 0.64 MMT in
2009 to 1.7 MMT in 2012 (NAPA 2013). In addition to asphalt, shingles also provide aggregate needed
for paving mix production. Apart from paving mix production, paving mix producers recycled
approximately 66,000 MT of asphalt shingles as aggregates in 2012 (NAPA 2013).
Asphalt shingles, due to their significant energy content, present a potential opportunity for energy
recovery, including use as a supplemental fuel in cement kilns. Combustion of discarded asphalt shingles
for energy is still under development in the US (OCC 2008, Lee 2011). The US EPA (2012) used emissions
from the combustion of oil and lubricants as a proxy for the emissions from shingles combustion due to a
lack of shingles-specific combustion emissions data and assumed that shingles combustion in cement kilns
would offset emissions associated with refinery fuel gas combustion for assessing emission factors for the
use of shingles in a cement kiln for the WARM model. As shingles combustion in a manufacturing
application is not widely practiced, data needed to develop LCI for this process are lacking and shingles
combustion is not further discussed in this report.
Using paving industry recycling estimates and the approximate amount of asphalt shingle waste produced
annually, it is estimated that more than 80% of waste asphalt shingles are disposed of in landfills, typically
within CDD landfills (Sengoz and Topal 2005, CIWMB 2007, CMRA 2007a, and NAPA 2013). Some
landfill facilities may separate incoming loads of asphalt shingles for use as road base material for
temporary access roads or for truck pads. Table 4-1 presents LCI needed to conduct an LCA of asphalt
shingle EOL management.
Table 4-1. LCI Needed for LCA of Asphalt Shingles EOL Management
Process
Description
Asphalt Shingle
Processing
The emissions associated with processing shingles for contaminant (e.g., nails)
removal and size reduction include materials and energy input as well as process
non-energy emission such as particulate matter emission from shingles grinding.
Landfilling
The material (e.g., equipment, soil, water) and energy (fuel, electricity) inputs for
placement and compaction of discarded shingles in a landfill along with the
associated process energy and non-energy emissions (e.g., dust emissions from
equipment operation and liquids emission associated with physiochemical
degradation of shingles in landfill) should be considered in developing a
representative dataset for the landfill disposal of asphalt shingles.
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Multimedia Environmental Assessment
Section 4 - Asphalt Shingles
Bitumen Production
The use of asphalt shingles for paving mix production displaces the production of
primary bitumen. The material burdens, energy requirements, and process
emissions related to the production of primary bitumen should be considered for an
LCA of asphalt shingles used for paving mix production. LCI for this process are
described in Chapter 3.
Aggregate
Production
The use of asphalt shingles for paving mix production displaces the production and
use of primary aggregate. The material burdens, energy requirements, and process
emissions related to primary aggregate production should be considered for an
LCA of asphalt shingles used for paving mix production. LCI for this process are
described in Chapter 2.
Transportation
The emissions associated with transporting discarded asphalt shingles to recycling
facilities or landfill, primary materials (for bitumen and aggregate production) to
paving mix production plant, and processed shingles to respective end uses for the
material should be included in the LCA.
4.3 LCI Sources
Peer-reviewed literature, government and private industry publications, and LCA modeling tools were
reviewed to identify available LCI datasets pertaining to asphalt shingles EOL management processes. If
LCI data were not available, process metadata and documentation were reviewed to evaluate the
completeness of the dataset (e.g., emissions categories were included, background data were used to
compile the dataset, and the geographic location and time period of the data were considered). The primary
sources of information used to develop the LCI datasets and information identified, if available, were
reviewed. Table 4-2 presents the data sources reviewed to compile LCI for shingle EOL management
options.
Table 4-2. List of Sources Reviewed for LCI Data
LCI Source
Athena (2000)
Athena (2001)
US LCI (20 12)
Cochran (2006)
Trumbore etal.
(2005)
US EPA
(2012)
Description
The report presents cradle-to-gate LCI for manufacturing various types of asphalt
roofing products such as organic felt asphalt shingles and fiberglass mat asphalt
shingles in Canada.
Franklin and Associates developed LCI for Road and Roofing Asphalt, which
includes emissions associated with crude oil extraction and processing at a
petroleum refinery for asphalt production (i.e., cradle to gate) in the US.
The National Renewable Energy Laboratory has published LCI for a wide variety
of materials, products, and processes used in the US.
Cochran (2006) presented diesel energy requirements for asphalt shingles
processing.
Trumbore et al. (2005) presented air emissions based on measurements from more
than 20 asphalt roofing manufacturing facilities and one pilot plant in the US.
Emission factors were developed using these measurements and proposed to update
the older US EPA AP-42 asphalt roofing manufacturing emission factors.
EPA's Waste Reduction Model presents data on GHG emissions associated with
source reduction, transport, recycling, and landfilling (i.e., collection and
placement) of asphalt shingles.
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LCI Source
AP-42 (US
EPA 1995)
NIST(2011)
BEES
GaBi (PE
International
n.d.)
Ecoinvent
(2014)
Description
Provides emission factors of filterable particulate matter (PM), total organic carbon
(TOC), and carbon monoxide (CO) for asphalt roofing manufacturing processes.
The National Institute of Standards and Technology Building for Environmental
and Economic Sustainability model allows an economic and environmental impact
comparison between various building materials. Documentation suggests that the
model uses data from SimaPro, US LCI (2012) and Trumbore et al. (2005) for
estimating LCI for asphalt shingles manufacturing. No LCI specific to
EOLmanagement of shingles are provided.
GaBi includes US-specific LCI for crude oil, aggregate (i.e., limestone), and
asphalt production; the database does not contain asphalt-shingles-specific LCI.
Ecoinvent is an LCI database developed by the Swiss Centre for Life Cycle
Inventories, which includes specific processes related to the EOL management of
numerous individual materials. Asphalt shingles are not addressed by Ecoinvent.
4,4 Asphalt Shingles Manufacturing
As discarded asphalt shingles are not used for manufacturing new asphalt shingles (closed-loop recycling),
asphalt shingles manufacturing LCI do not impact the EOL management of discarded shingles. This section
provides a brief overview of shingle manufacturing and references to available LCI data relevant to this
process.
Asphalt shingles are typically comprised of four main constituents: aggregates, asphalt, an asphalt-
impregnated mat, and a fine mineral base. The six major sequential operations used for asphalt shingle
manufacturing are felt saturation, coating, mineral surfacing (top and bottom), cooling and drying, product
finishing, and packaging. The shingle fabrication process begins with coating a layer of organic (cellulose
or wood fiber) or fiberglass fiber mat with asphalt by passing it through a tank filled with hot "blown"
asphalt. Asphalt, prior to use in shingles manufacturing, is oxidized by bubbling oxygen into the liquid
asphalt until the desired properties (e.g., viscosity) are achieved; this process is referred to as "blowing"
(NIOSH 2001, Blachford and Gale 2002, and Wess et al. 2004).
The mat material supports the other components while the asphalt provides weather resistance and
waterproofing. The organic or fiberglass mat makes up 2-15% of the shingle and the asphalt binder
comprises from 19-36% of the mass of an asphalt shingle. Fiberglass and organic felt are the two types of
mats used for asphalt shingles manufacturing in the US. Organic felt is made of cellulose fibers, while the
fiberglass mat is generally made by chopping fine glass filaments and mixing them with water to form a
pulp, which is then formed into a sheet (Blachford and Gale 2002). Fiberglass asphalt shingles are most
commonly used shingle type in the US (Athena 2000).
Once coated with the appropriate thickness of asphalt, one side of the mat is then surfaced with granules.
The surface granules consist of crushed rock coated with ceramic metal oxides for protection against
physical damage and sun-exposure. The granules add a desired color to the product and may also contain a
chemical such as copper to inhibit algae growth during the shingle's service life (3M 2014). Granular
aggregates comprise from 20-38 % of the weight of an asphalt shingle. A light coating of fine sand, talc,
or fine particles of mica is applied to the back surface of the shingle, which represents the bottom surface
of the shingles, to prevent the individual shingles from adhering to each other during packaging and
transport (Blachford and Gale 2002; Grodinsky et al. 2002; Willett 2013). Mineral fillers comprise 8-40 %
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(by mass) of an asphalt shingle. The final steps in the production of asphalt shingle are the finish, cutting,
and packaging of the shingles (NIOSH 2001, CMRA 2007a).
Asphalt shingle manufacturing LCI data are available through several sources. Athena (2000) presents
materials and energy use, and air, water and solid waste emissions from the asphalt shingle manufacturing
process based on data from facilities in Canada. AP 42 presents filterable particulate matter, total organic
carbon, and carbon monoxide emissions factors developed for a range of different asphalt blowing and
shingle saturation processes based on air pollution emissions tests from five asphalt roofing manufacturers
in the US during the 1970s. Due to limited or poor test data, these emission factors are rated as below
average (D) to poor (E) by the US EPA. Trumbore et al. (2005) proposed emissions factors for particulate
matter, volatile organic compounds, sulfur oxides, carbon monoxide, nitrogen oxide, and 22 hazardous air
pollutants based on measurements from more than 20 shingles manufacturing facilities in the US. As the
discarded asphalt shingles are not currently recycled to produce new shingles, the emissions and LCI data
presented by these sources were not further evaluated and considered as these upstream processes do not
impact EOL management.
4.5 LCI Related to Disposal
Emissions associated with shingles disposal in a landfill include air emissions from equipment used for
placing shingles in the landfill, emissions associated with landfill construction and operation, and liquids
and gaseous emissions from material decomposition in the landfill environment. Asphalt shingles are not
expected to significantly degrade biologically and, therefore, not expected to produce gaseous emissions
(US EPA 2012). There are various sources which provide landfilling emission factors related to equipment
use and landfill construction and operation; however none are specific to asphalt shingle landfilling.
Generalized landfill construction and operations LCI data were presented in Chapter 2.
Leaching may be a potential environmental concern with asphalt shingles because asphalt products contain
PAHs (Kriech et al. 2002, CMRA 2007a). Asphalt shingles are typically disposed of with other discarded
CDD materials and not in a monofill; field-scale leachate-quality data specific to asphalt shingles disposal
in a landfill are not available. The available laboratory-scale shingles leaching studies data were reviewed
for developing an estimate of liquids emission from shingles disposal in landfills. Kriech et al. (2002)
measured the total and leachable (leached using a TCLP solution) concentration of 29 PAHs in four primary
roofing asphalt samples from a commercial source of roofing asphalt for built-up roofs. The total PAH
results indicated concentrations in the roofing shingles ranging from 4.0 to 23 mg/kg. None of the 29 PAHs
analyzed were detected in TCLP leachate, suggesting that PAHs do not readily leach from different asphalt
materials.
Commercial Recycling Systems (Scarborough, Maine) reported leaching (TCLP) results for ground
shingles (CDRA 2010). The results indicated that the VOCs, Semi-VOCs, PAHs, and metals were not
readily leachable. Low concentrations of some metals (eight RCRA metals) were reported. Some
constituents of ground shingles, most notably cPAHs, were reported to exceed the concentration standards
for state de minimis risk levels (Appendix A of Chapter 418 Maine Solid Waste Rules [MDEP 2012]). The
data were not available for further evaluation.
Azah (2011) conducted batch and column leaching tests (SPLP) on a shingle sample collected from a
recycling facility in Florida to assess PAHs leaching from shingles. These data were used to estimate PAHs
emissions from disposal of shingles in CDD materials in landfills. Batch test data were used for PAHs that
were measured above the method detection limits. Batch test concentrations were multiplied by the total
solution volume and divided by the sample mass to estimate leachability on a per-kilogram-asphalt-
pavement basis (Table 4-3). The column leaching test (under saturated conditions) data were used to
estimate leaching emission of PAHs (acenaphthene, phenanthrene, anthracene, and dibenzo(a,h)anthracene
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) that were not detected in batch leaching tests. The column leaching test was conducted under saturated
conditions until a L:S ratio of 3.08 (L of liquids per kg of shingles) was achieved. PAHs concentrations
were measured at liquids-to-solid ratios (0.62, 1.23, 1.85, 2.47, and 3.08 L of liquid per kg of shingles).
The contaminant mass released between two sampling events was estimated by multiplying the L:S ratio
increment from the previous sampling event to measured PAH concentration. The cumulative leaching
amount was estimated by adding the leaching amount from each sampling interval.
Jang (2000) conducted batch and column leaching tests of several individual CDD materials, including
asphalt shingles using the SPLP extraction fluid to assess leaching of conventional water-quality
parameters. These data were used to estimate liquids emissions of calcium, chloride, and sodium with
asphalt shingles disposal in an unlined inert materials landfill; the parameter measured below detection
were not used. The concentrations were multiplied by the total solution volume and divided by the sample
mass to estimate leachable mass per kilogram of shingles (Table 4-3). The results for nitrate and sulfate
were not included due to the presence of nitric acid and sulfuric acid in the SPLP leaching solution, the
influences of which are not entirely known.
The asphalt shingles leaching data and energy consumption data from landfill operations were used to
develop an LCI process dataset for disposal of asphalt shingles at an unlined CDD landfill, as presented in
Table 4-3. Emissions are provided per kilogram "Asphalt shingles, at unlined CDD landfill" flow.
Although the actual liquids emissions are expected to be greater than the estimated liquids emission, as the
material would be subjected to leaching a higher L:S ratio than that used by Azah (2011) and Jang (2000)
for the batch leaching tests, using these emissions for LCA until the total emission estimates become
available would be more accurate than excluding liquids emission altogether. Details on diesel and
electricity consumption as a result of landfill operations (included in the "CDD landfill operations" flow)
and details on the calculation for cover soil requirements for placement of asphalt shingles at an unlined
CDD landfill are provided in Chapter 2. Tthe bulk density of asphalt shingles provided by CCG (2006) was
used to estimate cover soil requirements. In the absence of average nationwide distance data, the site of
asphalt shingle removal was assumed to be 20 km from the CDD landfill disposal site.
Table 4-3. Proposed LCI Dataset: Asphalt Shingles, at Unlined CDD Landfill
Input Flow
Asphalt shingles, from
roof removal
Truck transport, class 8,
heavy heavy-duty (HHD),
diesel, short-haul, load
factor 0.75
CDD landfill operations
Cover soil, from offsite
source
Output Flow
Asphalt shingles, at
unlined CDD landfill
Acenaphthene
Phenanthrene
Anthracene
Source
Assumed
See Chapter 2
See Chapter 2
Source
Azah (20 11)
Azah (20 11)
Azah (20 11)
Category
Construction and
Demolition Debris
Management
Construction and
Demolition Debris
Management
Construction and
Demolition Debris
Management
Category
Water/Groundwater
Water/Groundwater
Water/Groundwater
Unit
kg
t*km
kg
kg
Unit
kg
mg
mg
mg
Amount
1
0.001*20
1
0.0438
Amount
;
0.00171
1.03E-05
0.00210
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Fluoranthene
Pyrene
Benzo(k)fluoranthene
Chrysene
Benzo(g,h,i)perylene
Benzo(a)pyrene
Benzo(a)anthracene
Dibenzo(a,h)anthracene
Benzo(b)fluoranthene
Calcium
Chloride
Sodium
Azah(2011)
Azah(2011)
Azah(2011)
Azah(2011)
Azah(2011)
Azah(2011)
Azah(2011)
Azah(2011)
Azah(2011)
Jang (2000)
Jang (2000)
Jang (2000)
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
0.0147
0.011
0.00102
0.00135
0.00673
0.00333
0.0065
8.6E-06
0.00207
102
146
108
4,6 LCI Related to Recycling
4.6.1 Shingle Processing
Asphalt shingle processing includes removing contaminants (e.g., nails, metal flashing, plywood) from
discarded asphalt shingles and reducing their size. The emissions and energy requirements for processing
equipment should be considered for asphalt shingle processing LCI. Asphalt shingles, once removed, may
be segregated from other CDD materials at the construction site or they may be commingled with other
demolition waste. While some asphalt shingle processing facilities receive only source-separated asphalt
shingles, others may not require source separation and perform all sorting operations to segregate asphalt
shingle from other materials. Source separation places the burden on the construction/demolition contractor
to remove non-shingle materials from the discarded shingles.
The degree and methods of processing asphalt shingles depend on the quality of materials received and
facility design; post-consumer shingles require more intensive sorting due to the higher level of
contamination compared with post-manufacture scrap shingles;. Post-consumer asphalt shingles may also
have variable properties due to variation in degree of weathering and age among loads of asphalt shingles
(NAHB 1998). Asphalt shingles that arrive at a mixed CDD facility are typically manually picked from
the CDD debris and stockpiled until an appreciable amount of material has been acquired for processing.
Once the shingles have been sorted and all the undesirable materials removed, the shingles are size-reduced
using various grinding and screening methods to obtain the size necessary for the intended recycling
application (CMRA 2007b).
Various grinding and screening methods have been used to grind shingles for recycling, including
shredders, hammer mills, and different screen arrangements. A grinder typically consists of a loading
hopper, feeding drum, grinding chamber, size screen, and an exit conveyer. Water is sometimes added
during shredding to keep the grinder and shingles cool and to control dust (CMRA 2007b, TRB 2013). The
ground-up shingles are typically screened. The fraction that does not pass through the screen may be used
for a process with larger size specifications or they may be fed back into the grinder for further size
reduction (Marks and Gerald 1997, VANR 1999, and Grodinsky et al. 2002). Screenings that are greater
than % of an inch can typically be used as an aggregate; in most HMA applications the shingles must be
reduced to a size smaller than 1A an inch (CMRA 2007b). Sand may be added to the ground shingles to
prevent agglomeration of the materials during storage (IWCS 2010, TRB 2013).
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The typical fraction of recovered shingles for an asphalt shingles processing facility (not requiring source
separation) ranges from 15 to 90%. The recovery rate is dependent on the quality of the feedstock shingles
and the efficiency of the sorting equipment. Facilities achieving the highest recovery rates are those that
target loads comprised mostly of just asphalt shingle waste; facilities that accept and sort mixed CDD
materials would have much lower asphalt shingle recovery rates (CMRA 2007b).
Particulate matter generation from the grinding process and the potential release of asbestos are potential
non-energy air emission sources from asphalt shingles processing. Similarly, liquids emissions to surface
and groundwater from short-term storage of unprocessed and processed shingles in stockpile should be
considered for quantifying LCI. Asbestos, a known health hazard, was used in roofing products up until the
1970s. Although asbestos is not used as frequently today in roofing products (e.g., cements, mastics and
other products may still contain asbestos), post-consumer shingle waste removed from older housing may
potentially contain residual asbestos from when asbestos products were more commonly used (NAHB
1998, USGS 2010). An important goal for CDD recycling facilities when processing asphalt shingles is to
ensure compliance with asbestos regulations (typically accomplished by following an approved sampling
protocol) and to minimize processing asphalt shingles containing asbestos (CMRA 2007a). One practice
that is employed at CDD recycling facilities in states that require asbestos testing on asphalt shingles is to
have a staging area where incoming roofing waste loads are held while asbestos analytical results are
obtained (CMRA 2007a). Once analytical results indicate that the shingles do not contain asbestos, they
are then moved from the staging area to the processing area; asbestos-containing shingles are diverted to
disposal.
Based on an evaluation of approximately 28,000 shingles samples analyzed for asbestos content, CMRA
(2007a) reported that 0.06% and 1.46% of samples has asbestos detected as less than l%and more than 1%
of asbestos content, respectively. These measurements quantify the total asbestos content of shingles and
not the fraction that would be released into the air with grinding and screening. The asbestos emissions and
amount of particulate matter, in general, from shingles processing and liquids emission from short-term
storage of processed and unprocessed shingles are not available.
Energy inputs and emissions associated with asphalt shingle processing include those related to the
manufacturing and use of sorting, grinding, and screening equipment. For shingles that are processed for
use in HMA applications, Cochran (2006) reported diesel equipment energy requirements of 41 MJ per MT
of asphalt shingle processed, which is equivalent to the combustion of 1.06 L of diesel per MT of shingles.
US EPA (2012) used the energy requirement reported by Cochran (2006) to estimate shingles processing
emission factors for WARM. Table 4-4Table 4-4 presents process energy requirements for shingles
grinding based on the total diesel consumption estimated for these processing equipment data reported by
Cochran (2006). It was assumed that the shingles will be transported 20 km from the point of generation to
the processing plant. The energy requirement does not include energy needed to segregate shingles from
mixed CDD materials. Process non-energy emissions (e.g., particulate matter emission and asbestos
emission to air and leachate emission to surface and groundwater from asphalt shingles stockpile) and the
emissions from manufacturing, maintaining, or disposing of/dismantling the grinding equipment are not
included due to a lack of available information. Grinding and screening of post-consumer shingles also
produces ferrous metals (nails) (IWCS 2010). IWCS (2010) visually estimated separation of approximately
2.5 cubic feet of nails with the grinding and screening of 90 MMT of post-consumer asphalt shingles. As
the mass of the nails was not measured by IWCS (2010), the data were not used for the LCI presented in
Table 4-4.
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Table 4-4. Proposed LCI Dataset: Asphalt Shingles, at Processing Plant
Input Flow
Asphalt shingles
Truck transport, class 8, heavy
heavy-duty (HHD), diesel,
short-haul, load factor 0.75
Diesel, combusted in industrial
equipment
Output Flow
Ground asphalt shingles, at
processing plant
Source
Assumed
Cochran
(2006)
Source
Category
Construction and
Demolition Debris
Management
Flows
Category
Construction and
Demolition Debris
Management
Unit
kg
t*km
L
Unit
kg
Amount
1.0
0.001*20
0.00106
Amount
1.0
4.6.2 HMA/WMA Production with Asphalt Shingles
Use of asphalt shingles for producing paving mix has significantly increased in recent years due to the
shingles' asphalt content and the increase in asphalt prices. The benefits of using asphalt shingles for paving
mix production include reduced demand on primary asphalt cement and aggregate, reduced paving mix
production cost, and improved resistance to pavement cracking and rutting due to the reinforcement
provided by fibers contained in shingles (Brock and Shaw 1989, Grzybowski 1993, Ali et al. 1995, Button
et al. 1995, NAHB 1998, Foo et al. 1999, Mallick 2000, and Sengoz and Topal 2005). Several state
departments of transportation (e.g., Georgia, Minnesota, Montana, and South Carolina) have specifications
allowing from 3 to 8% of HMA to be replaced by tear-off shingles; other laboratory experiments have
acknowledged that up to 7% of HMA material can be replaced by tear-off shingles without adverse effects
(Mallick 2000, OCC 2008).
Another potential environmental concern, apart from asbestos release from shingle grinding, with the
recycling of asphalt shingles is the emission of PAHs during the production of HMA. Since asphalt is a
mixture of paraffinic and aromatic hydrocarbons, heating of asphalt can result in the emission of PAHs
(ARMA 1998; US EPA 2000; Lee et al. 2004). PAHs are one of the major classes of air pollutants emitted
from HMA facilities (US EPA 2000). While the quantity of PAH emissions from HMA facilities has been
fairly well documented, the impact of using recycled asphalt shingles on PAH emissions is not well
understood. Currently, there are no available data to suggest that emissions of PAHs during HMA
production with recycled asphalt shingles would be different from emissions from production without
asphalt shingles. TRB (2013) reported that HMA plants may require more frequent cleaning and
adjustments may need to be made to temperature settings to melt the more hardened shingle asphalt,
suggesting greater energy demand for HMA production using asphalt shingles. However, data are not
available to estimate the additional energy and material demand associated with using shingles for HMA
production.
Asphalt and aggregates constitute approximately 19-36% and 20-38% (by weight) of shingles, respectively
(NAHB 1998, CPvVMB 2007). Therefore, asphalt shingles supplements the use of primary asphalt and
aggregates in paving mix production. The US EPA (2012) assumed that asphalt shingles provide 22% and
38% (by weight of shingles) of asphalt and aggregate, respectively, for estimating emission offsets
associated with avoiding primary asphalt and aggregate production. The US EPA (2012) also assumed a
loss of 7.2% of the product during recycling. Based on the procedure used by the US EPA (2012), recycling
1 kg of asphalt shingles for HMA production is estimated to replace 0.2 kg and 0.35 kg of primary asphalt
and aggregates, respectively. It is assumed that there are no differences in emissions associated with use of
asphalt shingles in HMA production (e.g., particulate matter, liquid, and the energy requirements) as
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compared to those from the use of primary materials in the production process. It is assumed that there
would be additional avoided emissions resulting from the prevention of the transport of primary aggregates
and asphalt to the HMA plant; additional details on the transport distances for these primary materials are
provided in Chapters 2 and 3.
US EPA (2013) conducted LCA of recycling asphalt shingles into asphalt pavement. While the report
discussed the collection of energy data from shingles processing facilities, these data are not provided in
the report and could not be used for the development of an LCI specific to shingle processing for recycling
in asphalt pavement application.
4.7 Data Gaps and Future Opportunities
Table 4-5 summarizes the type of data presented by various sources reviewed for compilation of asphalt
shingle EOL management LCI. Only WARM (US EPA 2012), Athena (2001), AP-42 (US EPA 1995),
MSW-DST, Azah (2011), Wilburn and Goonan (1998), and GaBi provide information with respect to US-
based processes. Some sources used data from the other sources presented in Table 4-5. For example, the
US EPA (2012) used data from NREL database and Cochran (2006). As shown in the table, many sources
present only part of the data/information needed for compiling LCI. For example, WARM uses only GHG
emissions associated with equipment fuel consumption to estimate landfill emission. Similarly, Ecoinvent
only has partial landfill leachate emissions data because leachate from inert materials landfills are not
considered.
A majority of LCI information available on asphalt shingles pertains to the manufacturing aspects of the
life cycle. Only limited EOL-specific LCI are available. Based on a review of the available information,
the following data gaps were identified for compilation of a more comprehensive LCI dataset for asphalt
shingles EOL management:
1. Long-term leachable emissions from asphalt shingles placed in a landfill. As described earlier,
the liquid emissions presented in this study are based on SPLP tests, which simulate leaching from
land-application or disposal in inert debris landfills. Although references to results of batch test (TCLP)
data mimicking leaching from shingles disposed of in MSW landfills are found (CDRA 2010), the
actual data could not be located for developing liquids emissions estimates pertaining to shingles
disposal in MSW landfills. Moreover, the batch leaching data used for estimating liquid emissions
correspond to liquid to a solid ratio of 20 and, therefore, do not represent complete liquid emission. As
asphalt shingles are typically disposed of with other discarded materials and not disposed of in a
monofill, field-scale leachate quality data specific to asphalt shingles disposal in landfill are not
available and probably will not be available in the future. The liquids emissions from asphalt shingles
placement in an inert materials as well as MSW landfills would, therefore, need to be based on
laboratory-scale studies simulating long-term liquids emissions. Leaching studies have been published
on asphalt shingles as a component in the CDD debris waste stream and on asphalt binder used for
built-up roofs, which are a type of asphalt roofing but different from asphalt shingles (Townsend and
Kibert 1998, Townsend et al. 1999, Kriech et al. 2002, and Jang and Townsend 2003).
Leaching or air emissions data have been collected by facility operators and submitted to the state
environmental agencies for compliance with state rules and present the opportunity to develop asphalt
shingle leaching LCI based on actual operations. For example, Commercial Recycling Systems
(Scarborough, Maine) reported asphalt shingles leaching (TCLP) results and asbestos analysis to the
Maine Department of Environmental Protection for permitting of an asphalt shingles processing
facility.
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2. Materials and energy input and emission from asphalt shingles processing. The shingles
processing LCI presented in this report are based on the energy requirements reported by one data
source (Cochran 2006). Cochran (2006) identified the energy requirements of shingles processing
based on a survey of a handful of equipment manufacturers. Some of the data (e.g., consumables, fuel
and electricity usage, water consumption, material throughput) tracked by the facility owner from
financial accounting perspective can readily be used for developing more comprehensive LCI for
shingle processing.
The process non-energy emission (e.g., particulate matter and asbestos emissions to the atmosphere)
associated with asphalt grinding are lacking. Future research should focus on collecting and compiling
these data.
3. Data pertaining to shingles use in pavement mix production. The use of asphalt shingles in
HMA production has shown a significant increase in recent years. Similar to the US EPA (2012), the
LCI presented in the report for shingles use for HMA production are based on the assumption that
shingles do not impact emissions associated with HMA production. Data are not available to estimate
the additional energy and material demand and emissions associated with using shingles for HMA
production. Future research should consider assessing the impact of shingles on energy and materials
input and emissions associated with HMA production. The impact of using shingles in HMA on the
quality and service life of the pavement should also be assessed. The discussion presented in this
chapter focused on recycling asphalt shingles in HMA. However, there has been significant growth in
the use of WMA in recent years. There are insufficient data pertaining to the use of shingles in WMA.
4. Data pertaining to asphalt shingles use as fuel source in industrial applications. The LCI data
for asphalt shingles use as a supplemental fuel in cement kiln are lacking due to the rarity of this practice
in the US (OCC 2008). The cement industry has experimented with the use of asphalt shingles in cement
kilns [e.g., Lafarge cement plant, Brookfield, Nova Scotia, and St. Mary's Cement, Charlevoix,
Michigan (Lee 2011)]; however, there is very little research data available on the subj ect. A Department
of Energy-sponsored project conducted in 2007 investigated the feasibility of using asphalt shingles
(post-manufacture and post-consumer) in the manufacture of cement and in circulating fluidized bed
boilers (OCC 2008). OCC (2008) presented emissions from the combustion of the shingles and the
potential impacts on the quality of the products and the cement kiln dust (CKD); however, the data
were interpreted as being rudimentary. None of the existing US-specific data sources listed in Table 4-
5 except WARM (US EPA 2012) included emissions associated with shingles in cement kiln
manufacturing. The WARM model does consider GHG associate with combusting shingles in a cement
kiln; however, GHG were estimated using lubricants as a proxy to estimate emissions from the
combustion of fiberglass asphalt shingles. Future research into this potential recycling application is
recommended.
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Table 4-5. Overview of LCI Data Available
Process
Aggregate
Production
Asphalt
Production
Transport
Landfill
Construction &
Operation
Landfill Leachate
Emissions
Shingle
Processing
HMA Production
Shingles in
Cement
Manufacturing
WARM
P
P
P
P
P
P
MSW-
DST
X
Ecoinvent
X
P
GaBi
X
X
X
Athena
(2001)
X
X
AP-42
P
P
US LCI
(2012)
X
X
Wilburn and
Goonan
(1998)
P
P
Jang
(2000)
P
Azah
(2011)
P
Cochran
(2006)
P
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Multimedia Environmental Assessment Section 4 - Asphalt Shingles
4.8 References
3M Corporation (2014). Scotchguard Algae Resistant Roofing System. http://bit.rv/VVUlyL. Accessed 8
July 2014.
Ali, N., Chan, J., Potyondy, A., Bushman, R., Bergen, A. (1995). Mechanistic Evaluation of Asphalt
Concrete Mixtures Containing Reclaimed Roofing Materials. In: Proceedings of the 74th Annual
Meeting of Transportation Research Board, Technical University of Nova Scotia and University of
Saskatchewan, Saskatoon, SK, Canada, pp. 28-36.
ARMA (1998). Polyaromatic Hydrocarbon Emissions from Asphalt Processing and Roofing
Manufacturing Operations. A Report Prepared by the Asphalt Roofing Manufactures Association
Environmental Task Force, Rockville, MD. September 1998.
ARMA (2014). Asphalt Shingles: Raising the B.A.R. Fast Facts. http://bit.ly/lznnRLM. Accessed 6 June
2014.
Athena (2000). Life Cycle Analysis of Residential Roofing Products. A Report Prepared by Venta, Glaser
& Associates and Jan Consultants for the Athena Sustainable Materials Institute, Ottawa, Canada,
March 2000.
Athena (2001). A Life Cycle Inventory for Road and Roofing Asphalt. A Report Prepared by Franklin
Associates, A Service of McLaren-Hart/Jones for the Athena Sustainable Materials Institute,
Ottawa, Canada, March 2001.
Azah, E. M. (2011). The Impact of Fob/cyclic Aromatic Hydrocarbons (PAHs) on Beneficial Use of Waste
Materials. Ph.D. Dissertation, University of Florida, Gainesville, FL, USA.
Blachford, S. L., Gale, T. (2002). Shingle: How Products are Made. http://bit.lv/lrOi43R. Accessed 8 July
2014.
Brock, J. D., Shaw, D. (1989). From Roofing Shingles to Road. Astec Industries, Technical Paper T-120.
Brock, J.D. (2007). From Roofing Shingles to Roads. Technical paper T-120, Astec Industries, Inc.,
Chattanooga, TN. Revised 2007. http://bit.lv/VWOvcL. Accessed 5 June 2014.
Button, J. W., Williams, D., Scherocman, J. A. (1995). Shingles and Toner in Asphalt Pavements. FHWA
Research Rep. FHWA/TX-96/1344-2F, Austin: Texas Department of Transportation, Research,
and Technology Transfer Office.
CCG (2006). Targeted Statewide Waste Characterization Study: Waste Disposal and Diversion Findings
for Selected Industry Groups. A Report Prepared by Cascadia Consulting Group for the California
Integrated Waste Management Board, June 2006.
CCG (2008). 2007 Construction & Demolition Waste Composition Study. A Report Prepared by Cascadia
Consulting Group, Inc. for the Seattle Public Utilities Staff, July 2008.
CCG (2009). 2007/2008 Construction and Demolition Materials Characterization Study. Department of
Natural Resources and Parks, Solid Waste Division, King County Waste Monitoring Program,
February 2009.
COM (2009). Illinois Commodity/Waste Generation and Characterization Study. A Report Prepared by
COM Smith Commissioned by Illinois Department of Commerce & Economic Opportunity and
Contracted by the Illinois Recycling Association, 22 May 2009.
COM (2010). Waste Characterization Study. A Report Prepared by COM Smith for the Chicago
Department of Environment, 2 April 2010.
CDRA (2010). Maine Case Study: Case Study of Successful Asphalt Shingle Recycling. Commercial
Recycling Systems. http://bit.lv/lrOxvQY. Revised 8 March 2010. Accessed 20 June 2014.
CIWMB (2007). Asphalt Roofing Shingles Recycling: Introduction. http://bit.ly/lxOj loZ. Accessed 24
March 2014.
CMRA (2007a). Environmental Issues Associated With Asphalt Shingles Recycling.
http://bit.lv/lmG9TjW. Accessed 24 March 2014.
CMRA (2007b). Recycling Tear - Off Asphalt Shingles: Best Practices Guide. A Report Prepared by Dan
Krivit and Associates for the Construction Materials Recycling Association, October 2007.
http://bit.lv/lnbU2Zr. Accessed 18 March 2014.
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Multimedia Environmental Assessment Section 4 - Asphalt Shingles
Cochran, K. M. (2006). Construction and Demolition Debris Recycling: Methods, Markets and Policy.
Ph.D. Dissertation, University of Florida, Gainesville, FL, USA.
Ecoinvent (2014). Swiss Center for Life Cycle Inventories: Ecoinvent Centre. http://bit.ly/ltRWFED.
Accessed 2 June 2014.
Foo, K. Y., Hanson, D. I., Lynn, T. A. (1999). Evaluation of Roofing Shingles in Hot Mix Asphalt. Journal
of Materials in Civil Engineering, (11), 15-20.
Grodinsky, C., Plunkett, N., Surwilo, J. (2002). Performance of Recycled Asphalt Shingles for Road
Applications. Final Report, State of Vermont's Agency of Natural Resources. September 2002.
http://bit.ly/loFiBOk. Accessed 24 March 2014.
Grzybowski, K.F. (1993). Recycled Asphalt Roofing Materials—A Multi-Functional, Low Cost Hot-Mix
Asphalt Pavement Additive: Use of Waste material in Hot-Mix Asphalt, ASTM STP 1193, ASTM
West, H. Fred Waller, Ed., American Society for Testing and Materials, Philadelphia, PA.
IWCS (2010). Beneficial Use of Asphalt Shingles from Construction and Demolition Debris in Hot Mix
Asphalt Plant. A report prepared by Innovative Waste Consulting Services, LLC, Polk County
Waste Resource Management Division, and Jones Edmunds & Associates, Inc., submitted to the
Florida Department of Environmental Protection. http://bit.ly/lrOB3XS. Accessed July 3, 2014.
Jang, Y.C. (2000). A Study of Construction and Demolition Waste Leachate from Laboratory Landfill
Simulators. Ph.D. Dissertation, University of Florida, Gainesville, FL, USA.
Jang, Y. C., Townsend, T. G. (2003). Effect of Waste Depth on Leachate Quality from Laboratory
Construction and Demolition Debris Landfills. Environ. Eng. Sci., (20-3), 183-196.
Kriech, A. J., Kurek, J. T., Osborn, L. V., Wissel, H. L., Sweeney, B. J. (2002). Determination of Fob/cyclic
Aromatic Compounds in Asphalt and in Corresponding Leachate Water. Polycyclic Aromatic
Compounds, 22, 517-535.
Lee, M. (2011). Successful Supply Marketing Shingles-to-Fuel to the Portland Cement Industry. In:
Proceedings of the Shingle Recycling Conference, Dallas, TX, USA, 28 October 2011.
Lee, W. J., Chao, W. H., Shih, M. L., Tsai, C. H., Chen, T. J. H., Tsai, P. J. (2004). Emissions of Polycyclic
Aromatic Hydrocarbons from Batch Hot Mix Asphalt Plants. Environmental Science &
Technology, 38 (20), 5274-5280.
Mallick, R. B., Teto, M. R., Matthew R, Mogawer, W.S. (2000). Evaluation of Use of Manufactured Waste
Asphalt Shingles in Hot Mix Asphalt. Technical Report #26, Chelsea Center for Recycling and
Economic Development, University of Massachusetts Lowell, Chelsea, MA, USA.
Marks, V. J., Petermeier, G. (1997). Let Me Shingle Your Roadway. Research Project HR-2079, An Interim
Report Prepared by Vernon Marks and Gerald Petermeier for the Iowa DOT, Iowa Department of
Transportation, Ames, IA, USA.
MDEP (2012). Maine Solid Waste Management Rules: Chapter 418 Beneficial Use of Solid Wastes.
Revised 8 February 2012.
NAHB (1998). From Roofs to Roads: Recycling Asphalt Roofing Shingles into Paving Materials. National
Association of Home Builders Research Center, Upper Marlboro, MD, USA.
http://l.usa.gov/lpZhSL8. Accessed 24 March 2014.
NAPA (2013). Annual Asphalt Pavement Industry Survey on Recycled Materials and Warm-Mix Asphalt
Usage: 2009-2012. Information Series 138, National Asphalt Pavement Association, Lanham, MD,
USA. December 2013.
NCHRP (2013). Recycled Materials and Byproducts in Highway Applications. Volume 6: Reclaimed
Asphalt Pavement, Recycled Concrete Aggregate, and Construction Demolition Waste. NCHRP
Synthesis 435, National Cooperative Highway Research Program, Transportation Research Board
of the National Academies, Washington, D.C., USA.
NIOSH (2001). Asphalt Fume Exposure During the Manufacture of Asphalt Roofing Products. No. 2001
127, National Institute for Occupational Safety and Health, Cincinnati, OH, USA.
NIST (2011). Inventory Analysis. A Report Prepared by the National Institute for Safety and Technology
for the Building for Environmental and Economic Sustainability Software.
http://l.usa.gov/lto21r3. Accessed 3 April 2014.
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Multimedia Environmental Assessment Section 4 - Asphalt Shingles
OCC (2008). Asphalt Roofing Shingles into Energy Project Summary Report. Revised Report, Department
of Energy, Award Number DE-FG36-06GO86009. http://www.osti.gov/scitech/biblio/927606.
PE International (n.d.). Gabi Software. Search GaBi Databases. http://bit.ly/ln7njQ5. Accessed May 2014.
RWB, CCG and IWCS (2010). Statewide Construction and Demolition Debris Characterization Study. A
Report Prepared by R.W.Beck, Inc., Cascadia Consulting Group, Innovative Waste Consulting
Services, lie. for Georgia Department of Natural Resources, Sustainability Division. June 2010.
Sengoz, B., Topal, A. (2005). Use of Asphalt Roofing Shingle Waste in HMA. Construction and Building
Materials, 19, 337-346.
Snyder, R. (2001). 21st Century Recycling: ARMA and other industry organizations are leading the way
for waste-reduction and recycling programs, http://bit.ly/lnemz01. Accessed 24 March 2014.
Townsend, T. G., Kibert, C. (1998). The Management and Environmental Impacts of Construction and
Demolition Waste in Florida.Report #97-7, Florida Center for Solid and Hazardous Waste
Management.
Townsend, T. G., Jang, Y.,Thurn, L. G. (1999). Simulation of Construction and Demolition Waste
Leachate. Journal of Environmental Engineering, 125, 1071-1081.
TRB (2013). Recycled Materials and Byproducts in Highway Applications. Volume 8: Manufacturing and
Construction Byproducts. NCHRP Synthesis 435, National Cooperative Highway Research
Program, Transportation Research Board of the National Academies, Washington, D.C., USA.
Trumbore, D., Jankousky, A., Hockman Jr., E. L., Sanders, R., Calkin, J., Szczepanik, S., Owens, R. (2005).
Emissions Factors for Asphalt-Related Emissions in Roofing Manufacturing. Environmental
Progress 24 (3), 268-278.
US EPA (1995). AP 42, Fifth Edition, Volume I, Chapter 11: Mineral Products Industry, Section 11.2 -
Asphalt Roofing. US Environmental Protection Agency, http://Lusa.gov/lr8s2WR. Accessed 8
July 2014.
US EPA (2000). Hot Mix Asphalt Plants Emission Assessment Report. EPA-454/R-00-019, Emissions
Monitoring and Analysis Division, Office of Air Quality Planning and Standards, US
Environmental Protection Agency, Research Triangle Park, NC, USA. December 2000.
US EPA (2012). Asphalt Shingles. WARM model: Version 12. US Environmental Protection Agency,
February 2012. http://l.usa.gov/lk5pPGA. Accessed 5 June 2014.
US EPA (2013). Analysis of Recycling of Asphalt Shingles in Pavement Mixes from a Life Cycle
Perspective. EPW07020, 24 July 2013.
US EPA (2014). Methodology to Estimate the Quantity, Composition, and Management of Construction
and Demolition Debris in the United States. A Report Prepared by Innovative Waste Consulting
Services, LLC and Pegasus Technical Services, Inc. for the United States Environmental Protection
Agency, June 2014, Unpublished report.
US LCI (2012). US Life Cycle Inventory Database. National Renewable Energy Laboratory.
http://www.nrel.gov/lci/. Accessed 20 February 2014.
USGS (2010). Minerals Commodity Summary 2010, Asbestos, Page 22. US Geological Survey and US
Department of the Interior, January 2010. http://on.doi.gov/UzBZRR. Accessed 29 July 2014.
VANR (1999). Recycled Asphalt Shingles in Road Application: An Overview of the State of Practice.
Vermont Agency of Natural Resources, September 1999. http ://bit.ly/VKeXbP. Accessed 24
March 2014.
Wess, J. A., Olsen, L. D., Sweeney, M. H. (2004). Asphalt (Bitumen). Concise International Chemical
Assessment Document 59, A Report Prepared by Joann Wess, Dr. Larry Olsen, and Dr. Marie
Sweeney for the National Institute for Occupational Safety and Health, World Health Organization,
Geneva, Switzerland.
Wilburn, D.R., Goonan, T.G. (1998). Aggregates from Natural and Recycled Sources: Economic
Assessments for Construction Applications - A Materials Flow Analysis. US Geological Survey
Circular 1176, US Geological Survey and US Department of the Interior.
Willett, J.C. (2013). 2011 Minerals Yearbook - Stone, Crushed [Advance Release]. US Geological Survey,
March 2013. http://on.doi.gov/lxTlZZo. Accessed 12 March 2014.
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Section 5 - Gypsum Drywall
5 Gypsum Drywall
5. 1 Introduction
Gypsum drywall (also referred to as gypsum board, wallboard, or plasterboard), typically manufactured
and sold as 4-ft-by-8-ft or 10-ft-by-12-ft sheets or panels, is widely used as an interior wall and ceiling
finishing in residential, commercial, and institutional structures. Although there are a variety of drywall
products, including many varieties of fire-resistant and water-resistant product, !/2-inch-thick regular and
Type X (fire-resistant) gypsum boards combined constitute over 80% (by weight) of the prefabricated
gypsum products (Crangle 2014). In 2013, approximately 19.5 million ft2 of gypsum drywall products were
sold in the US (Crangle 2014).
Primary mined gypsum, flue gas desulfurization (FGD) byproduct gypsum, and recycled gypsum are all
input streams used for gypsum drywall manufacture. In 2013, approximately 90% of the 24 MMT of
gypsum consumed in the US was used by manufacturers of drywall and plaster products (Crangle 2014).
In combination with other additives, a gypsum slurry is made that is deposited on paper facing and backing
to create sheets of drywall. These sheets are dried and cut to specific sizes and distributed for use in
construction and renovation projects. Once delivered to the jobsite, drywall sheets are attached to the
interior frames of the building using drywall screws and are cut to fit the various structures in the building.
Drywall sheet-fitting generates scraps that are often free of tarnish or paint. Figure 5-1 presents the various
gypsum drywall processes, including production and EOL management; processes upstream of the EOL
removal are depicted because some of the post-consumer gypsum is recovered and used in lieu of mined
gypsum (i.e., recycling of waste drywall to new drywall or agricultural use). Such uses of the recovered
drywall results in energy and emission offsets associated with avoidance of gypsum mining and production.
Paper Backing
Production
Landfilling
Gypsum Mining, 1
Processing,
Stacking I
Drywall
Manufacturing
Retail/
Wholesale
In Service
End-of-Life
Product
Removal
'Agricultural |
Drywall Recycling,
Grinding & Paper
Screening
Amendment
Paper Recovery |
Other
Recovered
Paper Use
Figure 5-1. Gypsum Drywall Process Flow Diagram
5.2 EOL Management
US EPA (2014) estimated that nearly 7.4 MMT of waste gypsum drywall was handled by permitted or
registered solid waste management facilities in the US in 2011; approximately 6.9 MMT was disposed of
in C&D and MSW landfills and about 0.5 was recovered through CDD processing facilities. CPvVMB
(2007) reports the fractions of (California) waste drywall which are produced from new construction,
demolition, manufacturing, and renovation activities; these fractions are presented in Figure 5-2.
Distinguishing between these waste drywall sources is important because the drywall quality is substantially
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Multimedia Environmental Assessment Section 5 - Gypsum Drywall
different among these streams; manufacturing and construction waste drywall are relatively clean, while
demolition and renovation drywall typically has contaminants such as paint, joint compounds, nails, and
any other material that may have been applied to the drywall during installation and use.
Renovation
10%
Manufacturing
12%
Demolition.
14%
_New Construction
64%,
Figure 5-2. Sources of California-Discarded Gypsum Drywall (CIWMB 2007)
Due to its relatively high quality (e.g., absence of nails, paint), the drywall discarded from drywall
manufacturing and new construction activities accounts for the bulk of the drywall waste stream recycled
(Venta 1997, WRAP 2008, US EPA 2012). Gypsum drywall that is not recycled (representing the majority
of waste drywall) is disposed of in landfills. Drywall is estimated to account for approximately 8% of the
landfilled CDD materials based on several regional waste composition studies (Barnes 2000, Sandier 2003,
CCG 2006, COM 2009, RWB et al. 2010). MSW landfills may have restrictions on the amount of drywall
material that is disposed of and where it is disposed of, or it may be banned from disposal altogether (e.g.,
Massachusetts) often due to anticipated or actual problems related to the generation and release of hydrogen
sulfide gas. However, it appears that the majority of demolition drywall is still landfilled. RSM may contain
significant amounts of gypsum and may be used as daily cover in landfills. The fate and the associated
environmental impacts of gypsum in a landfill in either case (disposed of as waste or used as daily covers)
would, potentially, be the same.
Drywall which is recovered for recycling is typically taken to drywall processing facilities where processing
removes contaminants and separates gypsum from the paper backing (WRAP, n.d.). The processed drywall
can be recycled in closed loop (e.g., new drywall manufacturing) or open loop (e.g., soil amendment)
application. Closed-loop recycling and some open-loop recycling applications result in avoiding primary
gypsum mining and production and associated emissions. Drywall scrap recovered from construction sites
can be ground and reused in a variety of agricultural purposes, such as a soil conditioner and liming agent
(Marvin 2000). The recycled gypsum is applied directly to the ground in this application; reuse permits or
regulations, if applicable, may dictate the application rate (e.g., allowable application, typically expressed
in tons per acre per year). Concerns with drywall land application include dust and liquids emissions from
processing and spreading gypsum drywall (Marvin 2000). Open-loop recycling of gypsum drywall may
also include use as an additive to compost, acting as a bulking agent. The gypsum absorbs moisture in the
pile and adds calcium, sulfur, and some carbon to the compost (Marvin 2000).
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Section 5 - Gypsum Drywall
Table 5-1 presents processes that should be considered for LCA of EOL management options for gypsum
drywall. For all the applications, where discarded drywall is processed to produce gypsum (referred to
herein as recycled gypsum) and used as a substitute for primary gypsum, production of primary gypsum
was identified as an end point for LCI compilation. The production and use of the recycled gypsum
potentially would result in avoiding an equivalent amount of primary gypsum production and the associated
emissions. Emissions downstream of the primary gypsum production (e.g., those associated with drywall
manufacturing from primary gypsum), however, were assumed to occur irrespective of whether
downstream processes used primary or recycled gypsum unless the available data indicated otherwise. As
available, LCIs were developed for the processes listed in Table 5-1.
Table 5-1. LCI Needed for LCA of Gypsum Drywall EOL Management
Process
Gypsum Mining and
Production
Paper Backing
Production
Drywall Manufacturing
Landfilling
Drywall Grinding and
Paper Screening
Paper Recovery and
Recycling
Transportation
Description
The process entails mining and processing (size reduction via grinding and
crushing) of primary gypsum for use in drywall manufacturing, cement
production, or agricultural use.
The process includes manufacturing paper backing using current mix of
primary and recycled sources for eventual use as facing and backing for
gypsum drywall.
The process entails processing and calcining gypsum to produce stucco, stucco
slurry production, and forming, cutting, and drying gypsum drywall.
The process entails placing and compacting drywall and long-term physical,
chemical, and biological decomposition of drywall in a landfill.
Processing includes grinding waste drywall and screening paper and other
contaminants that may be present in the drywall waste to produce ground-up
gypsum.
The process includes recovering paper for reuse as input for new paper
backing production for use in new drywall manufacturing or other uses.
The fuel requirements and emissions from transporting primary materials and
discarded drywall to recycling facilities and respective end uses for the
material or to landfill should be considered in the LCA.
5.3 LCI Sources
Peer-reviewed literature, government and private industry publications, and various LCA modeling tools
were reviewed to identify available LCI datasets pertaining to gypsum drywall EOL management processes.
Table 5-2 lists data sources reviewed to compile LCI presented in this chapter. If LCI data were not
available, process metadata and documents were reviewed to evaluate the completeness of the dataset (e.g.,
emissions categories, background data used to compile the dataset, and geographic location and time period
of the data were included). The primary sources of information used to develop the LCI datasets and
information identified, if available, were reviewed.
Although gypsum management LCI data were located in many of the sources listed below (Venta (1997),
WRAP (2008), Ecoinvent, WRATE, GaBi), non-US-specific data are presented and discussed for a better
understanding of the inputs used to develop LCIs for this material.
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Section 5 - Gypsum Drywall
Table 5-2. List of Sources Reviewed for LCI Data
LCI
Source
Description
Athena
(2011)
Athena Institute developed this report for the Gypsum Association. The report presents
cradle-to-gate LCI of 1/2-inch regular and 5/8-inch Type X gypsum drywall. It also
presents US-specific LCI for raw gypsum extraction, gypsum paper manufacture, and
drywall assembly based on the data from seven quarries/mining sites, three paper plants,
and 17 drywall board plants to develop the LCI datasets with the intent of uploading them
to the US LCI (2012) database.
Venta
(1997)
The report presents cradle-to-gate LCI of different types of gypsum boards and associated
finishing products. These LCI appear to be used by the Athena Impact Estimator for
Buildings, an LCA model which evaluates the environmental impacts for structures created
from a variety of building materials. The data used for LCI development were primarily
specific to Canada. US-specific data such as distribution of different type of boards
produced were used for developing the LCI.
EPA
WARM
The US EPA's WARM presents energy and GHG emissions associated with source
reduction, recycling, and landfilling of drywall. The data presented by Venta (1997) were
used for developing emission factors for raw material extraction and drywall and paper
manufacturing. The energy requirements provided by WRAP (2008) were used for
developing emission factors for processing discarded drywall.
Cochran
(2006)
Cochran provided an estimate of the energy requirements of equipment for processing
gypsum drywall for recycling (in MJ/hour) based on a survey of equipment manufacturers.
This Swiss-based LCI database presents industrial LCA and management data. The
database contains individual international gypsum production/management processes,
including gypsum board production, gypsum quarry operation, recycling of waste gypsum
board, and disposal of waste gypsum at sanitary and inert debris landfills.
Ecoinvent
WRAP
(2008)
This report presents the results of an LCA, including the LCI used, of Type A plasterboard
in the United Kingdom. Data considered are representative of industry practices and waste
management for drywall (referred to as plasterboard) in the United Kingdom. Individual
LCI datasets were developed using a combination of data from Ecoinvent, UK gypsum
industry data, and primary information from manufacturing facilities.
GaBi
This LCA software contains its own database developed for specific processes similar to
the Ecoinvent database. Data related to internationally representative processes
corresponding to gypsum board production, gypsum board paper production, gypsum
extraction (i.e. mining), and FGD gypsum production at a coal-fired power plant are
presented in this database.
5.4 LCI Related to Material Manufacture
5.4.1 Raw Materials Extraction
Gypsum is mined or quarried in 17 states, of which Oklahoma, Nevada, California, and Indiana account for
62% of the total gypsum mined in the US (Crangle 2014). Approximately 16 MMT of gypsum were mined
in 2013 and 90% was used by drywall and plaster product manufacturers (Crangle 2014). Additional uses
of mined gypsum include cement production, agricultural applications, and other industrial applications
(Crangle 2014). Gypsum is extracted from underground mines, open pits, and quarries of natural gypsum
rock. The natural deposit of gypsum rocks are drilled and blasted loose for extraction after removing
overlying deposits of soil (Athena 2011). The use of heavy equipment such as front-end loaders, mechanical
shovels, and traxcavators and blasting agents require the bulk of the energy demand for gypsum extraction
(Venta 1997). Mined gypsum undergoes primary grinding and crushing, typically on-site, into particles of
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Multimedia Environmental Assessment
Section 5 - Gypsum Drywall
2 to 5 inches or less (Venta 1997, Athena 2011). Additional processing of the natural gypsum such as
screening and drying may be necessary depending on end-use requirements of the material (e.g., cement
manufacture, agricultural gypsum).
Table 5-3 presents the inputs and outputs of materials, energy, and emissions from gypsum mining based
on data compiled by Athena (2011) from six quarries and one underground mining operation for raw
gypsum ore production. Although two of these quarrying operations were located in Canada, a sensitivity
analysis conducted by Athena (2011) reported that the source location of natural gypsum had less than a
1% impact on the overall drywall production process LCA. These data, along with additional data (e.g.,
chemical inputs, fuel and electricity consumption data for processing materials) from the US LCI database
and Ecoinvent were used to develop a US gypsum drywall production LCI dataset (Athena 2011). The
outbound transport distance of the mined gypsum to the drywall manufacturing plant is not included in
Table 5-3. Several sources of international energy and emission data for gypsum mining and processing
were also identified (Venta 1997, WRAP 2008, Kellenberger et al. 2004). The process exchange LCI titled
"Gypsum Quarry Operation" in the Ecoinvent database presents LCI for gypsum mining and crushing
activities for the production of raw material for stucco in Switzerland. Although data for a global context
are presented, these data appear to originate from the same source (i.e., Kellenberger et al. 2004). The
infrastructure input and mining activity emissions (e.g., particulate matter emissions) are estimated based
on information for limestone mining. Waste Resources Action Programme (WRAP) conducted a cradle-to-
grave LCA of gypsum plasterboard in the United Kingdom (UK) (WRAP 2008). LCI for imported mined
gypsum were obtained from the same source (i.e., Kellenberger et al. 2007) that was used for developing
the LCI for Ecoinvent's gypsum quarry operation.
Table 5-3. Athena (2011) - Natural Gypsum Mining LCI (per kg of Mined Gypsum at
Mine/Quarry)
Input
Explosives
Lubricants
Hydraulic Fluid
Greases
Engine Oil
Antifreeze
Diesel, combusted in
industrial equipment
Gasoline, combusted in
industrial equipment
Propane, combusted in
industrial boiler
Electricity, at industrial
user
Natural gas, combusted in
industrial boiler
Fresh Water
Recycled Water
Transport, truck
Transport, Barge
Output
Source
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Source
Category
Construction and Demolition Debris
Management
Construction and Demolition Debris
Management
Category
Unit
kg
kg
kg
kg
kg
kg
L
L
L
kWh
m3
L
L
t*km
t*km
Unit
Amount
0.000274
1.75E-05
1.65E-05
3.50E-06
9.50E-06
3.50E-06
0.00168
3.33E-05
2.46E-06
0.00133
0.00182
0.15
0.142
0.000316
0.0343
Amount
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Section 5 - Gypsum Drywall
Gypsum, at mine
Overburden (for quarried
gypsum)
Other solid rock sold to
other industries
Particulates, < 2.5 um
Particulates, > 10 um
Particulates, > 2.5 um,
and < lOum
Total suspended solids
Total suspended solids
Oil and Grease , hexane
Chloride
Sulfate
Solid waste
Waste oil
Athena (2011)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Athena (20 11)
Construction and Demolition Debris
Management
Air/Unspecified
Water/Stormwater
Water/Groundwater
Construction and Demolition Debris
Management
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
1
1.94
0.033
9.85E-05
3.9E-05
6.50E-06
l.OOE-06
1.15E-09
9.00E-10
5.50E-08
2.65E-07
3.75E-05
1.60E-06
5.4.2 Synthetic Gypsum Production
Synthetic gypsum is also used as a raw material in addition to the mined gypsum for drywall production.
Currently, mined and synthetic (FGD) gypsum constitute 41% and 57% of the total amount of gypsum used
for drywall production in the US, respectively (Athena 2011). The use of synthetic gypsum has increased
dramatically in the US from 0.9 MMT in 1993 to 12.3 MMT in 2013 (Balazik 1995, Crangle 2014). Of the
synthetic gypsum sold and used in the US, 81% is accounted for in drywall production (Athena 2011,
Crangle 2014). Even with the significant increase in the use of synthetic gypsum, approximately 47% of
synthetic gypsum produced was landfill in the US in 2013, suggesting significant potential for further
growth in recovery and use of synthetic gypsum.
Although a byproduct of many chemical processes such as acid neutralization, citric acid production, sugar
production from sugar beets, and titanium dioxide production, synthetic gypsum is predominantly produced
from an FGD wet process in coal-fired power plants (Crangle 2013). Calcium bisulfate is produced from
the reaction of sulfur dioxide with a calcium-based sorbent used for sulfur dioxide scrubbing in FGD stack.
The calcium bisulfate is subsequently oxidized to sulfate dihydrate (i.e., FGD gypsum) by natural or forced
oxidation (WRAP 2008). The materials from natural oxidation processes are generally disposed of due to
their partial oxidation, while forced oxidation results in a marketable product (WRAP 2008). The oxidation
process produces gypsum crystals, which are fractionated using a hydrocyclone to separate larger crystals.
The rest of the gypsum crystal suspension is filtered or centrifuged and washed to remove water-soluble
substances (Athena 2011). Vacuum filter beds are used to dewater and reduce the moisture content of the
FGD to less than 10%.
Although Athena (2011) acknowledges dewatering (to reduce moisture content to less than 10%) as the
process that differentiates waste FGD from marketable FGD, WRAP (2008) recognizes oxidation as the
process for this distinction. As a result, Athena (2011) attributes inputs for dewatering and transportation
of FGD to end-user to synthetic gypsum production, whereas WRAP (2008) assigns inputs and the
associated emissions for forced oxidation of calcium bisulfate and the subsequent processing to FGD
production. FGD gypsum is not included in the Ecoinvent inventories as only a small quantity of FGD is
used in Switzerland (Kellenberger et al. 2007). LCI data reported by Athena (2011) for FGD processing
should be used as these are specific to the US. Although Athena (2011) considered FGD dewatering and
processing LCI information for conducting an LCA of different drywall products, specific LCI data were
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Multimedia Environmental Assessment
Section 5 - Gypsum Drywall
not reported. Therefore, because of an absence of any US-specific information, it was not possible to
develop an LCI for FGD gypsum production.
5.4.3 Gypsum Paper Manufacturing
Paper layers (facing and backing) sandwich the gypsum core of the drywall. The US-specific and
international energy and emission data for gypsum paper production were identified (Athena 2011, Venta
1997, Kellenberger et al. 2007, WRAP 2008). Athena (2011) compiled US-specific energy and materials
input for paper production based on data from three gypsum paper plants for 2010. The description of the
paper manufacturing processing and the associated LCI presented in this section are based on information
and data presented in Athena (2011). Recycled paper sources are exclusively used for manufacturing the
paper used for drywall production. Although various paper types (e.g., post-manufacture and post-
consumer newspaper, Kraft clippings, mixed waste papers, and old corrugated containers (OCC)) are used
for manufacturing facing, backing is exclusively made from OCC.
The process of producing gypsum paper is similar to other paper manufacturing processes. The recycled
papers are blended in a pulper to create a slurry of paper fibers. The slurry is cleaned to remove wires,
staples, and glue. The pulp is then made into multiple-ply sheets using either rotating cylinders or
Fourdrinier flat wire machines. The sheets are pressed together to remove excess water and the residual
water is subsequently removed in high-temperature driers. The dried paper is treated with chemicals (e.g.,
retention chemicals and sizing agents). The treated paper is rolled, trimmed, and packaged. Electricity and
natural gas are the major forms of energy used in the production of gypsum paper. Athena (2011) presented
materials, energy, and process emission data for 1000 square feet of paper. These values were divided by
the weight of 1000 square feet of paper provided by Athena (2011) to estimate data on a mass basis. Table
5-4 presents the materials, energy, and process-related emissions for manufacturing 1 kg of facing and
backing paper based on the data compiled by Athena (2011). The outbound transport distance of the finish
paper to the drywall manufacturing plant is not included in Table 5-4.
Table 5-4. Materials, Energy, and Process: Related Emissions for 1 kg of Gypsum Paper, at Plant
Input Flow
Old Corrugated Cardboard (OCC)
Kraft Clippings
Mixed waste papers/flyleaves,
signature/white news blank, magazine
blank, coated fly
Starch
Retention chemical (flocculant/coagulant)
Sizing agents
Polymer emulsifier
Other chemicals (defoamers,
dyes/fungicide)
Chemicals used for on-site water
treatment (P &N based)
Packaging materials
Lubricants
Hydraulic fluid
Category
Construction and
Demolition
Debris
Management
Unit
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
Amount
(Facing Paper)
0.58
0.143
0.395
9.77E-05
0.00196
0.00569
0.000245
0.000299
0.000605
0.00238
9.16E-05
3.51E-06
(Backing Paper)
1.12
0
0
0.000102
0.00202
0.00552
0.00026
0.000313
0.000583
0.00231
8.94E-05
3.73E-06
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Section 5 - Gypsum Drywall
Greases
Total electricity (purchased and on-site
co-generated)
Total natural gas (excluding electricity
production)
Diesel fuel oil
Propane
Fresh well water
Fresh water from "municipality city water
system"
Recycled water re-entering the paper
production system
Water discharged
Transport, truck
Transport, rail
Outputs
Gypsum paper, at plant
Co-products - downgraded and side rolls
Non-Methane VOCs
Total suspended solids
Biological oxygen demand
Lead
Zinc
Copper
Total nitrogen
Total phosphorus
Lead
Non-hazardous solid waste
Hazardous solid waste
Wastewater
Sludge waste
Solvent mixture waste
Construction and
Demolition
Debris
Management
Category
Construction and
Demolition
Debris
Management
Construction and
Demolition
Debris
Management
Air/Unspecified
Water
Water
Water
Water
Water
Water
Water
Soil
Waste
Waste
Waste
Waste
Waste
kg
kWh
m3
L
kg
L
L
L
L
t*km
t*km
Unit
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
L
kg
L
3.63E-06
0.69
0.173
0.000304
0.000311
7.71
1.58
2.16
8.95
0.203
0.0199
Amount
(Facing Paper)
;
0.0295
8.75E-06
0.000637
0.000794
5.90E-09
1.62E-07
6.19E-08
1.24E-06
1.02E-07
1.32E-09
0.101
8.73E-06
5.4
0.0451
6.42E-06
3.78E-06
0.681
0.176
0.000287
0.000323
7.39
1.53
2.26
8.52
0.183
2.02E-05
Amount
(Backing Paper)
;
0.0294
9.16E-06
0.000619
0.000819
6.24E-09
1.72E-07
6.58E-08
1.30E-06
1.07E-07
1.38E-09
0.101
9.28E-06
5.18
0.0424
6.82E-06
5.4.4 Gypsum Drywall Manufacturing
The mined and synthetic gypsum is further processed (e.g., secondary crushing, drying, and screening) to
produce finely ground gypsum (particle size less than 150 (im) with very low moisture content (Venta
5-8
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Multimedia Environmental Assessment Section 5 - Gypsum Drywall
1997). This gypsum stream is calcined (i.e., dehydrated) to produce stucco; calcium sulfate dihydrate
transforms to calcium sulfate hemihydrate in the presence of heat (Athena 2011). Stucco may undergo
further grinding, after cooling, if necessary. Stucco is mixed with several additives (depending on drywall
type), foaming agent, and water to prepare a slurry. The slurry is spread on the paper facing and covered
by the paper backing. An automatic knife slices the boards to their desired sizes. The hydrated boards are
then transported to a drying kiln to remove the excess water.
While many types of gypsum drywall are produced, as previously described, the two most common
products are 1/2" regular and 5/8" Type X gypsum drywall. In 2011, these two types of drywall represented
over 80% of all drywall consumed in the US (Crangle 2013). Type X gypsum board is made using
noncombustible fibers and is a fire-resistant board (National Gypsum 2013). Athena (2011) compiled
materials and energy requirements and process non-energy emissions for 1/2" regular and 5/8" Type X
gypsum drywall production from 17 plants in the US. These plants included a mix of small, medium, and
large operations as well as a geographical spread of at least one plant in each US census region and
represented one-third of the total drywall output in the US in 2010 (by all the 60 plants in the US).
Athena (2011) presented materials, energy, and process emission data for 1000 square feet of 1/2" regular
and 5/8" Type X gypsum drywall production. These values were divided by the respective weight of 1,000
square feet of drywall provided by Athena (2011) to estimate data on mass basis. Table 5-5 presents the
materials, energy and process related emissions for manufacturing of 1 kg of 1/2" regular and 5/8" Type X
gypsum drywall based on the data compiled by Athena (2011). Based on the data presented in Table 5-5, it
can be seen that synthetic, mined, and recycled gypsum represented approximately 57%, 41%, and 2% of
the gypsum used for drywall production in the US in 2010. Electricity is used at all stages in gypsum board
production. Natural gas is primarily used during raw gypsum drying, calcination, and the final product
drying (Athena 2011). Particulate matter represents a majority of process non-energy emissions. Athena
(2011) also present transport distances of various material inputs and output that can be used to estimate
transport-related emissions. Weighted average transport distances for various transport modes were
estimated based on the amount and transport distance of various materials provided by Athena (2011). The
weighted average one-way distance for each transport mode is also provided in Table 5-5. It should be
noted that the outbound transport distance of finished drywall from plant was not included in the cradle-to-
gate LCA presented by Athena (2011). The destination of the finish drywall from plant was not provided
by Athena (2011). As the gypsum-drywall-manufacturing-related data presented by Athena (2011) are
mostly based on surveys of the manufacturers, the outbound distances are probably representative of the
average distances to the distribution centers from the plants. The LCI presented in Table 5-5 correspond to
the manufacturing and delivery of the drywall to distribution centers.
The materials and energy inputs and emissions data for drywall production process and sub-process (e.g.,
stucco production) for other countries are available (Venta 1997, Kellenberger et al. 2007, WRAP 2008).
The US EPA (2012) used the data reported by Venta (1997) for estimating emission factors for source
reduction and recycling of gypsum drywall; Venta (1997) compiled LCI for types of drywalls and
associated finishing products based on data collected from drywall manufacturers in Canada.
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Section 5 - Gypsum Drywall
Table 5-5. Proposed LCI for Gypsum Drywall, at Distribution Center
Input Flow
Mined/quarried natural gypsum ore (US
source)
Mined/quarried natural gypsum ore
(imported from Canada/Mexico)
Synthetic gypsum (FGD)
Post-consumer gypsum
Transport, barge
Transport, truck
Transport, rail
Transport, conveyor
Starch
Vermiculite
Fiberglass
Dispersant
Retarder
Potassium Sulfate
Dextrose
Clay, kaolin
Boric Acid
Land Plaster
Foaming agent (soap)
BM Accelerator
Ammonium Sulfate
Edge Paste
STMP
Shredded Paper
Talc
Paper End tape
Ink (water based)
Ink (oil based)
Ink (alcohol based)
Shrink-wrap
Plastic slip sheets
Rail bags
Other Plastics
Cardboard Edge Protectors
Plastic Banding
Steel Banding
Zip tape
Dunnage/Bunks/Sleutters
Adhesive for Dunnage/Bunks/Sleutters
Motor Oils
Gear Oil (Transmission)
Lubricants
Hydraulic Fluid
Greases
Antifreeze
Category
Construction and
Demolition Debris
Management
Construction and
Demolition Debris
Management
Construction and
Demolition Debris
Management
Unit
kg
kg
kg
kg
t*km
t*km
t*km
t*km
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
Amount
1/2" Regular
Gypsum
Wallboard
0.265
0.119
0.544
0.0177
0.381
0.496
0.216
0.00128
0.00459
0.00495
0.000447
0.00311
0.000576
0.000218
0.000724
0
0.00014
0.00151
0.000791
0.00107
7.02E-05
0.000402
7.66E-05
0.000357
2.49E-07
0.000451
3.10E-06
1.98E-07
2.32E-06
2.87E-05
2.78E-05
4.16E-05
1.72E-05
1.37E-06
5.92E-07
1.44E-06
1.05E-05
0.0161
2.63E-07
1.23E-06
1.66E-06
3.57E-06
4.66E-08
1.38E-07
8.10E-07
5/8" Type X
Gypsum
Wallboard
0.263
0.123
0.549
0.0186
0.393
0.493
0.218
0.00127
0.00324
0.00438
0.00246
0.00244
0.000368
0.000115
0.000407
0.000572
5.86E-05
0.000689
0.000595
0.000622
4.50E-06
0.000288
5.41E-05
0.000189
1.76E-07
0.000449
3.09E-06
1.95E-07
2.32E-06
2.86E-05
2.82E-05
4.10E-05
1.74E-05
1.37E-06
6.04E-07
1.47E-06
1.05E-05
0.016
2.65E-07
1.18E-06
1.61E-06
3.56E-06
4.64E-08
1.26E-07
8.11E-07
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Multimedia Environmental Assessment
Section 5 - Gypsum Drywall
Input Flow
Locomotive Oil
Electricity
Natural gas
Diesel fuel oil
Propane
Gasoline
Fresh water (process)
Reclaimed water (process)
Fresh water used for cooling or steam
production
Output Flow
Gypsum Drywall
Internal gypsum waste -recycled back
into the production system
Off-spec GWB used as BDS
Total Paniculate Matter (PM)
as PM10
as PM2.5
voc
Lead
Mercury
Total suspended solids
Total Organic Carbon
Lead
Zinc
Copper
Sulfates
Sulfide
Oil & Grease
Ammonia
Wastewater to waste treatment facility
Solvent mixture waste to incinerator
Sludge waste to landfill
Non-hazardous solid waste (including
packaging) to landfill
Other(s) solid waste
Paper to recycler
Plastic to recycler
Wood to recycler
Steel scrap to recycler
Hazardous solid waste to incinerator
Category
Construction and
Demolition Debris
Management
Construction and
Demolition Debris
Management
Category
Construction and
Demolition Debris
Management
Waste
Construction and
Demolition Debris
Management
Air/Unspecified
Air/Unspecified
Air/Unspecified
Air/Unspecified
Air/Unspecified
Air/Unspecified
Water/Unspecified
Water/Unspecified
Water/Unspecified
Water/Unspecified
Water/Unspecified
Water/Unspecified
Water/Unspecified
Water/Unspecified
Water/Unspecified
Construction and
Demolition Debris
Management
Unit
kg
kWh
m3
L
kg
L
kg
kg
L
Unit
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
L
L
kg
kg
kg
kg
kg
kg
kg
kg
Amount
1/2" Regular
Gypsum
Wallboard
1.71E-06
0.0661
0.0723
0.000233
0.00617
0.0514
0.576
0.0252
0.537
Amount
;
0.027
0.00977
6.45E-05
4.67E-05
1.78E-05
3.25E-06
1.77E-08
9.70E-09
2.39E-08
1.06E-08
2.61E-14
1.24E-11
2.07E-12
3.89E-09
1.19E-10
8.49E-09
1.31E-09
9.30E-05
2.94E-05
1.42E-05
0.00174
0.00185
0.00019
3.62E-06
8.93E-05
3.41E-05
1.70E-06
5/8" Type X
Gypsum
Wallboard
1.56E-06
0.0663
0.0723
0.000236
0.00623
0.0519
0.566
0.0248
0.533
Amount
;
0.0273
0.00977
6.49E-05
4.73E-05
1.77E-05
3.39E-06
1.76E-08
9.91E-09
2.26E-08
1.09E-08
2.68E-14
1.12E-11
1.87E-12
3.51E-09
1.08E-10
8.33E-09
1.34E-09
9.15E-05
2.95E-05
1.44E-05
0.00173
0.00182
0.000194
3.67E-06
9.10E-05
3.42E-05
1.66E-06
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5.5 LCI Related to Disposal
The emissions from gypsum drywall landfill disposal result from operating landfill equipment during
material and cover soil compaction and placement, including both fuel-related and pre-combustion
emissions, as well as those associated with the physical, chemical, and biological decomposition of gypsum
drywall in landfill. The exposure to precipitation or other liquids (e.g., landfill leachate) is expected to result
in leaching emissions. The liquids and gaseous emissions to the environment are expected to depend on the
biogeochemical environment of the landfill (e.g., MSW landfill, CDD landfill), as well as in-place
environmental controls employed at the landfill.
WARM estimates landfilling emission factors related to drywall, which include GHG emissions from
transportation and the operation of the landfill, carbon sequestration, and methane generation from
biological decomposition of the facing and backing paper. WARM does not consider liquid emissions from
landfills. In addition to emissions from heavy equipment, US EPA (2012) included fugitive methane
emission associated with drywall paper decomposition from drywall disposed of in a CDD landfill site
without GCCS. US EPA (2012) used methane generation potential reported by Staley and Barlaz (2009) to
assess methane generation from drywall. Staley and Barlaz (2009) estimate the methane generation
potential of drywall by multiplying the methane generation potential of OCC/Kraft bag reported by Eleazer
et al. (1997) by 0.1 to account for the relative mass of paper (approximately 10% of drywall by mass based
on the data reported by National Gypsum Company (2008)) and adjusted for the paper-specific moisture
content (6% by mass reported by Tchobanoglous et al. (1993)); the drywall methane generation potential
was estimated to be 15.2 m3 per dry MT of drywall. The US EPA (2012) assumed a methane oxidation rate
of 10% in the landfill cover based on work by Czepiel et al. (1996) to estimate fugitive emissions from
methane generation. Additional details on the information used in US EPA (2012) to estimate methane and
carbon dioxide emissions from the disposal of drywall in a CDD and MSW landfill are presented in Section
2.5.10.8. The CDD landfill methane and carbon dioxide emissions are estimated as 0.010 and 0.034 kg,
respectively.
The US EPA (2012) considered only methane emissions from drywall decomposition in anaerobic landfill
environments for estimating GHG impacts. The production of hydrogen sulfide from the biological
decomposition of organic matter in anaerobic conditions in the presence of dissolved sulfate (primarily
from gypsum) has been reported to be a major environmental concern associated with gypsum drywall
disposal in landfills (Jang 2000, Xu 2005). Several factors, including moisture content, organic content,
pH, and temperature, may contribute to the production of hydrogen sulfide in landfills (Elsgaard et al. 1994,
Knoblauch and Jorgensen 1999, Koschorreck 2008). Several studies have indicated that the amount of
organic matter present in CDD landfills, although significantly lower than in MSW landfills, is not a
limiting factor for hydrogen sulfide production; the paper backing on drywall is sufficient to sustain a viable
microbial community that produces hydrogen sulfide (Hardy Associates 1978, Townsend 2002, New
Hampshire Department of Environmental Services 2004). Tolaymat et al. (2013) reported a decay rate
constant for drywall decomposition and the associated hydrogen sulfide production. Xu (2005) assessed the
impact of different cover materials in reducing hydrogen sulfide emissions from CDD landfills and reported
the hydrogen sulfide concentration in gaseous emissions from drywall decomposition based on laboratory
experiments.
Anderson et al. (2010) evaluated hydrogen sulfide emission and sulfur content of CDD fines from nine
landfills in the US to estimate the potential for and rate of hydrogen sulfide generation from disposal of
CDD fines, based on sulfur content. Anderson et al. (2010) emission of 5,360 ft3 of H2S per ton of sulfur
disposed of in landfill. From stoichiometry, sulfur represents 18.6% of the gypsum (by weight) and
assuming that drywall is comprised of 92% gypsum (Marvin 2000), this approximately equates to 0.041 kg
of hydrogen sulfide release per kg of drywall disposal (using a density of about 1.42 grams per liter of
hydrogen sulfide at 20° C and 1 atm pressure). Plaza et al. (2007) estimated the attenuation of hydrogen
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Multimedia Environmental Assessment Section 5 - Gypsum Drywall
sulfide by different landfill cover materials, included clayey and sandy soils; the average attenuation of
these two soils was 47.5%. Additional details on the studies conducted by Anderson etal. (2010) and Plaza
et al. (2007) are provided in the RSM chapter, Section 9.5. Using the same assumptions listed in Chapter
9, and in the absence of other US-data, the average estimated hydrogen sulfide release rate based on these
studies (including the estimated average cover soil removal efficiency) is 0.021 kg hydrogen sulfide per
kilogram of drywall disposed of in a CDD landfill.
Ecoinvent provides LCI which are gypsum specific for disposal in inert material landfills and sanitary
(MSW) landfills. Although the database includes LCI for Switzerland as well as the global case, the LCI
sets appear to be based on the data published by Doka (2009) based on the management practices in
Switzerland. Doka (2009) presented LCI for three EOL management options for building materials. In the
first option, the building materials are source segregated and recycled; no disposal is assumed to occur in
this option. In the second option, the building materials are transported and processed at a material recovery
facility and the materials that cannot be recycled are disposed of in a landfill. The fine fractions recovered
in this option are assumed to be disposed of at a sanitary landfill; the gypsum content of the recovered fines
appears to be primary reason for the requirement of fines disposal in a sanitary landfill. In the third option,
building materials are assumed to be disposed of in an inert debris landfill without resource recovery. Liquid
emissions are considered only for sanitary landfills and not for inert debris landfills. For disposal in sanitary
landfills, Doka (2003) estimated that although 100% of gypsum will decompose, 56.2% of the dissolved
sulfate reduces and precipitates as sulfides and eventually 6.5% of the sulfur is emitted to the air. Although
not specifically mentioned by Doka (2009), it seems that the balance of sulfur (37.3%) is assumed to exit
the landfill with leachate. Doka (2009) does not provide emission factors for hydrogen sulfide.
The GaBi database contains processes for three separate landfill exchanges (three separate LCI datasets)
for CDD material disposal. These are not specific to the drywall product and the processes are based on
data from countries within the EU-27 region. WRAP (2008) uses the emissions data presented by Golder
Associates (2007) for gypsum drywall disposal in landfill. Golder Associates (2007) compiled liquids and
gaseous emission from gypsum drywall disposal in monofill as well as co-disposal with MSW in UK based
on LandSim and GasSim2 modeling results, respectively. Leachate is assumed to be treated before
discharge into the environment. The emissions from landfill construction, operation, and closure were based
on those used by WRATE. No interaction between the MSW and drywall was assumed for leachate and
landfill construction and operation were assumed. The impact of MSW on gas generation from drywall in
co-disposal scenario was modeled; hydrogen sulfide emissions from drywall co-disposed of with MSW
was estimated to be more than four times that from a monofill. A time horizon of 150 years with active gas
collection for the MSW landfill model was assumed. Based on GasSim modeling, Golder Associates (2007)
reported emission estimates of 0.5 g and 2.4 g of hydrogen sulfide per MT of plasterboard disposed of in a
monofill and co-disposal, respectively.
Jang (2000) conducted batch and column leaching tests of several individual CDD materials, including new
gypsum drywall, using SPLP extraction fluid (and US EPA SW-846 Method 1312). Drywall material was
cut into square pieces approximately 5 cm on each side. Results from these experiments were used to
estimate liquids emissions that would result from disposing of gypsum drywall in an unlined landfill.
Unlined landfill disposal may occur due to the classification of CDD type wastes as more chemically inert
than MSW components and in some areas the term inert material landfill is used for CDD sites (Doka
2003). Batch test data were used for the constituent with concentrations measured above detection limits
due to the greater L:S ratio in batch tests (20:1 vs. 5.3:1 for column tests); higher L:S ratios are designed
for and are generally capable of leaching a higher quantity of the total constituent mass from the solid
material (i.e., drywall). Batch test concentrations were multiplied by the total solution volume and divided
by the sample mass to estimate leachability on a per-kilogram-drywall basis (Table 5-6).
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Section 5 - Gypsum Drywall
Column leaching test data were used to estimate the leaching emission of potassium and magnesium, as
these were not detected in batch leaching tests. The column leaching test entailed percolation of
approximately 160 L of SPLP extraction fluid through a 3 0-cm-diameter polyvinyl chloride column
containing 3Okg of drywall over a 3-month period; anL:S ratio of 5.3 was achieved in this test. The amount
of potassium and magnesium leached between two sampling events was estimated by multiplying the
leachate volume collected since the previous sampling event with the measured concentration. The
cumulative leaching amount was estimated by adding the leaching amount for each sampling intervals.
Batch test results for nitrite and nitrate solution concentrations were not included due to the presence of
nitric acid in the SPLP leaching solution. Although sulfate is present in the SPLP leaching fluid, the sulfate
concentrations in drywall leachate from batch tests were approximately one to three orders of magnitude
greater than those observed for all other CDD materials (e.g., levels of 1.9, 125, and 1,430 mg/L were found
in leaching fluid for aluminum, insulation, and drywall, respectively). Therefore the sulfate contributed by
the leaching fluid was considered insignificant compared to the amount leached from drywall. High levels
of calcium in comparison to other CDD materials are likely attributable to the dissolution of calcium and
sulfate present in drywall; the mass ratio of SOVCa found in the SPLP fluid after batch tests (approximately
2.6) approximately matched that of the SCVCa mass ratio in raw gypsum molecules of 2.4 (CaSC>4 -H2O).
The gypsum drywall leaching data and energy consumption data from landfill operations were used to
develop an LCI process dataset for disposal of drywall at an unlined CDD landfill, as presented in Table 5-
6. Emissions are provided per kilogram "Gypsum drywall, at unlined CDD landfill" flow. Although the
actual emissions are expected to be greater than the estimated liquids emission as the material would be
subjected to leaching a higher L:S ratio than used by Jang (2000) for the batch leaching test, using these
emissions for LCA until the total emission estimates become available would be more accurate than
excluding liquids emission altogether. The methane emission rate estimate presented earlier in the section
is included in Table 5-6. Details on the diesel and electricity consumption included in the "CDD landfill
operations flow" and on how the cover soil requirement was determined are provided in Chapter 2. The
density of bulk gypsum drywall for the cover soil requirement estimation was provided by CCG (2006). In
the absence of average nationwide distance data, the site of gypsum drywall removal was assumed to be
located 20 km from the CDD landfill disposal site.
Table 5-6. LCI Dataset: Gypsum Drywall Disposal, at Unlined CDD Landfill
Input Flow
Gypsum drywall, from
building removal
Truck transport, class 8,
heavy heavy-duty (HHD),
diesel, short-haul, load factor
0.75
CDD landfill operations
Cover soil, from offsite
source
Output Flow
Gypsum drywall, at unlined
CDD landfill
Methane
Carbon dioxide
Hydrogen sulfide
Source
Assumed
See Chapter 2
See Chapter 2
Source
Staley and
Barlaz (2009)
US EPA (20 12)
Anderson et al.
(2010)
Category
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Category
Air/Unspecified
Air/Unspecified
Air/Unspecified
Unit
kg
t*km
kg
kg
Unit
kg
kg
kg
kg
Amount
1
0.001*20
1
0.0686
Amount
;
0.010
0.034
0.021
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Section 5 - Gypsum Drywall
COD
Chloride
Sulfate
Sodium
Potassium
Magnesium
Calcium
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
mg
mg
mg
mg
mg
mg
mg
1,160
152
2.86E4
214
21
66
1.1E4
5.6 LCI Related to Recycling
Drywall recycling has been gaining momentum as landfills place more restrictions on drywall disposal due
to actual or potential odor issues. Drywall scrap can be processed and reused in a variety of applications,
such as a soil conditioner and liming agent and production of new drywall. Discarded drywall sources
include off-spec drywall generated at the gypsum board plant as well as scraps from new construction or
renovation or material produced from structural demolition. However, because of the quality issues
described previously, the majority of waste gypsum used for recycling comes from the plant off-spec
material and scraps from construction and renovation projects. At drywall manufacturing plants, scrap
drywall generated from off-spec boards is recycled back into the manufacturing process for new drywall
material. The drywall generated from demolition activities is not recycled as commonly as drywall from
other sources due to possible contamination from other CDD materials such as nails, paint, and joint
compound (Venta 1997, Cochran 2006). For developing emission factors for drywall recycling for the
WARM model, the US EPA (2012) assumed that 19% and 81% of the recycled drywall is recycled for new
drywall manufacturing and soil amendment production, respectively. However, the US EPA (2012) only
considered recycling of new drywall scraps generated from construction sites.
Drywall discarded during installation of the interior wall in new construction or renovation can be more
readily recycled due to ease of separation from other CDD materials. Processing consists of size reduction,
where initial size reduction may occur during material handling with heavy equipment while further size
reduction occurs through crushing and grinding. Based on a review of the operation of a few drywall
processing facilities and trial of various methods, Townsend et al. (2001) reported that the rotating action
of a trommel screen is sufficient to separate paper and pulverize the gypsum core. A material recovery rate
of approximately 70% was reported for this processing method based on trial operation in Florida. As paper
constitutes approximately 5.5% (by weight) of new drywall, the rest (30%) of the residue primarily consists
of unrecovered gypsum. The separated paper can be recovered for the production of new paper for drywall
manufacturing, and the recovered gypsum is directly used as raw material for new drywall manufacturing
(Venta 1997, WRAP 2008).
Energy requirements for various equipment used for drywall processing have been presented by Cochran
(2006). However, the throughput rate for this equipment was not provided by Cochran (2006) to estimate
the energy requirement per unit weight of drywall processed. WRAP (2008) presented energy requirement
and recovery rates for processing post-manufacture and post-consumer drywall based on data provided by
three plasterboard manufacturers and four recyclers in the UK. The electricity and diesel demand of 9.9
kWh and 0.9 L per MT of post-consumer drywall processing was reported, respectively. The electricity and
diesel requirement for post-manufacture drywall processing was reported to be 9.6 kWh and 1.3 L per MT
drywall, respectively. The processing of 1 MT of post-consumer drywall was reported to yield 930 kg, 68
kg, and 2 kg of recycled gypsum, reclaimed paper, and waste. Details on the process used are not provided
by WRAP (2008). The US EPA (2012) used the post-consumer drywall processing electricity and diesel
requirement and recovery rate for developing emission factors for drywall recycling for WARM.
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The emission associated with the transport of gypsum and paper recovered from processing gypsum drywall
should be considered for LCA. The US EPA (2012) reported that it used the transport distance of the
finished drywall transport compiled provided by the US Census Bureau (2004) as a proxy for the transport
distance of discarded drywall to a recycling facility and recycled gypsum to a drywall manufacturing
facility. However, the commodity flow survey does not provide transport distances specific to drywall. The
commodity closest to drywall that this survey provides distances for is "lumber and other construction
materials."
Doka (2009) (Ecoinvent) presented LCI for three EOL management options for building materials. In the
first option, the building materials are source segregated and recycled; no disposal is assumed to occur in
this option. In the second option, the building materials are transported and processed at a material recovery
facility and the materials that cannot be recycled are disposed of in a landfill. In the third option, building
materials are assumed to be disposed of in an inert debris landfill without resource recovery. These
processes include burdens associated with the dismantling process (e.g., energy used and participate matter
from the process). The second option includes burdens associated with waste sorting. None of these options
includes the burden associated with processing recovered building materials to produce a recycled product.
For example, burdens associated with the processing of drywall to produce recycled gypsum and paper are
not included in these LCI.
In addition to use in new drywall manufacturing, recycled gypsum could be land-applied in agricultural
applications or used for cement production. The liquids emissions presented in Table 5-6 can be used as a
proxy for the liquid emissions from land application of recycled gypsum. As recycled gypsum offsets
production and use of natural gypsum in these applications, emissions from natural mined gypsum should
be considered as well for LCA. Isaac and Morris (2012) conducted Leaching Environmental Assessment
Framework (LEAF) leaching tests on four mined gypsum samples to assess metals leaching associated with
the use of recycled gypsum as soil amendment. Energy and materials inputs and particulate matter emission
associated with land application of recycled gypsum are lacking; the "Diesel, combusted in industrial
equipment" input flow is included in the dataset as a placeholder until this energy input can be quantified.
Table 5-7 presents liquid emissions LCI associated with land application of recycled gypsum. It is assumed
that the recycled gypsum is transported 20 km from processing facility for agricultural application.
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Table 5-7. LCI Dataset: Recycled Gypsum Land Application as Agricultural Amendment
Input Flow
Gypsum Drywall
Truck transport, class 8, heavy
heavy-duty (HHD), diesel, short-
haul, load factor 0.75
Diesel, combusted in industrial
equipment
Output Flow
Recycled gypsum- land applied as
agricultural amendment
COD
Chloride
Sulfate
Sodium
Potassium
Magnesium
Calcium
Source
Source
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Category
Construction and
Demolition Debris
Management
Flows
Category
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Unit
kg
t*km
L
Unit
kg
mg
mg
mg
mg
mg
mg
mg
Amount
1
0.001*20
0
Amount
;
1,160
152
2.86E4
214
21
66
1.1E4
5.7 Data Gap analysis and Opportunities for Additional LCI Data
Table 5-8 summarizes the type of data presented by various sources reviewed for compilation of drywall
EOL management LCI. Only Cochran (2006), Athena (2011), and the US EPA (2012) provide information
with respect to US-based processes. Some sources used data from the other sources presented in. For
example, the US EPA (2012) used data from Venta (1997) and WRAP (2008). As shown in the table, many
sources present only part of the data/information needed for LCI compilation. For example, WARM
presents only GHG emissions and uses emissions only associated with fuel consumption in equipment to
estimate the landfill emission factor. Similarly, Ecoinvent only has partial landfill leachate emissions data
because leachate from inert materials landfills are not considered.
A majority of LCI information available on drywall pertains to the manufacturing aspects of the life cycle.
Only limited EOL-specific LCI are available. Based on a review of the available information, the following
data gaps were identified for compiling a more comprehensive LCI dataset for drywall EOL management:
1. Long-term leachable emissions from drywall placed in a landfill. As described earlier, the
liquid emissions presented in this study are based on SPLP tests, which simulate leaching from
land-application or disposal in an inert debris landfill. The batch leaching data used for estimating
liquid emissions correspond to L:S ratio of 20 and, therefore, do not represent complete liquid
emission. As gypsum drywall is typically disposed of with other discarded materials and not
disposed of in a monofill, field-scale leachate quality data specific to gypsum drywall disposal in
landfill are not available and probably will not be available in the future. The liquid emissions from
gypsum drywall placement in an inert materials as well as MSW landfills would, therefore, need to
be based on laboratory-scale studies simulating long-term liquids emissions. Published leaching
studies have been conducted on gypsum drywall as a component in the CDD debris waste stream
(Jang 2000, Jang and Townsend 2003).
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2. Materials and energy input and emission from gypsum drywall processing. Only one source
(Cochran 2006) identified energy requirement (MJ/hour) of drywall processing equipment based
on a survey of a handful of equipment manufacturers. Due to the lack of throughput data (MT/hour),
energy requirement per unit mass of drywall could not be estimated. Some of the data (e.g.,
consumables, fuel and electricity usage, water consumption, material throughput) tracked by the
facility owner from financial accounting perspective can be readily used for developing more
comprehensive LCI for drywall processing.
The process non-energy emission (e.g., particulate matter emission from drywall grinding, water
consumption for dust control) associated with drywall grinding are lacking. Future research should
focus on collecting and compiling these data.
3. Long-term gaseous emissions from drywall placement in landfills. The disposal of gypsum
drywall in inert debris and MSW landfills is expected to produce methane and hydrogen sulfide.
Staley and Barlaz (2009) used the methane generation potential of OCC/Kraft paper as a proxy for
the methane generation potential of gypsum paper. The US EPA (2012) used the methane
generation potential estimate provided by Staley and Barlaz (2009). Although some sources
presented the gypsum drywall decay rate, the hydrogen sulfide generation estimates are lacking.
Table 5-8. Overview of LCI Data Available
Process
Gypsum Mining
Paper Backing
Production
Drywall Manufacturing
Landfilling
Drywall Grinding and
Paper Screening
Paper Recovery and
Recycling
Transportation
Venta
(1997)
X
X
X
Athena
(2011)
X
X
X
X
US EPA
(2012)
WARM
P
X
P
X
X
Cochran
(2006)
P
5.8 References
Anderson, R., Janbeck, J.R., McCarron, G.P. (2010) Modeling of Hydrogen Sulfide Generation from
Landfills Beneficially Utilizing Processed Construction and Demolition Materials. A Report
Prepared for the Environmental Research and Education Foundation, Alexandria, VA. February
2010.
Athena (2011). A Cradle-to-Gate LCA of 1/2" Regular and 5/8" Type X Gypsum Drywall. A Report
Prepared by Dr. Lindita Bushi and Mr. Jamie Meil for the Gypsum Association, Inc., December
2011.
Balazik, R. (1995). Gypsum. USGS Minerals Yearbook 1995. United States Geological Survey, US
Department of the Interior.
Barnes, A.H. (2000). Feasibility of Recycling Scrap Gypsum Drywall from New Construction Activities in
Florida. Master's Thesis, University of Florida, Gainesville, FL, USA. May 2000.
CCG (2006). Targeted Statewide Characterization Study: Detailed Characterization of Construction and
Demolition Waste. A Report Prepared by Cascadia Consulting Group for the California
Environmental Protection Agency Integrated Waste Management Board. June 2006.
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CDM (2009). Illinois Commodity/Waste Generation and Characterization Study. A Report Prepared by
Camp, Dresser, and McKee (CDM) for the Illinois Department of Commerce and Economic
Opportunity and contracted by the Illinois Recycling Association. 22 May 2009.
CIWMB (2007). Construction and Demolition Recycling: Wallboard (Drywall) Recycling.
http://www.calrecvcle.ca.gov/conDemoAVallboard/. 26 July 2007.
Cochran, K.M. (2006). Construction and Demolition Debris Recycling: Methods, Markets, and Policy.
Ph.D. Dissertation, University of Florida, Gainesville, FL, USA.
Crangle, R.D. (2013). Gypsum. Produced by the US Geological Survey, United States Department of the
Interior. US Geological Survey Minerals Yearbook-2011. June 2013.
Crangle, R. (2014). Mineral Commodity Summaries 2014. Produced by the US Geological Survey, United
States Department of the Interior. Mineral Commodities Profile, Gypsum Industry Profile.
February 2014.
Czepiel, P.M., Mosher, B., Harriss, R.C. (1996) Quantifying the Effect of Oxidation on Landfill Methane
Emissions. Journal of Geophysical Research, 101, 16, 721-16, 729.
Doka, G. (2009). Life Cycle Inventories for Waste Treatment Services, Part V: Building Material Disposal.
Ecoinvent Report No. 13,Swiss Centre for Life Cycle Inventories, Dubendorf. December 2009.
Eleazer, W.E., Odle III, W.S., Wang, Y.S., Barlaz, M.A. (1997). Biodegradibility of Municipal Solid Waste
Components in Laboratory-Scale Landfills. Environmental Science & Technology, 31, 911-917.
Elsgaard, L., Prieur, D., Mukwaya, G.M., Jorgensen, B.B. (1994). Thermophilic Sulfate Reduction in
Hydrothermal Sediment of Land Tanganyika, East Africa. Applied Environmental
Microbiology, 60 (5), 1473-1480.
Golder Associates. (2007). Life Cycle Assessment of Plasterboard, PBD014, Landfill Emissions Inventory.
A Report Prepared by Golder Associates (UK) Ltd. for Environmental Resources Management
Ltd., October 2007.
Hardy Associates Ltd. (1978). Investigation of means to control sulphide production in drywall landfill
disposal operations. Gypsum Subcommittee of the Lower Mainland Refuse Project, 19 December
1984.
Isaac, C., Morris, A. (2012). Evaluation of Metal Leaching from Contaminated Soils, FGD, and oth Coal
Combustion Byproducts in Ruse Scenarios. Mined Gypsum LEAF Methods 1313 and 1316. Draft
Report.
Jang, Y.C., Townsend, T.G. (2003) Effect of Waste Depth on Leachate Quality from Laboratory
Construction and Demolition Debris Landfills. Environmental Engineering Science, 20 (3), 183-
196.
Jang, Y. (2000). A Study of Construction and Demolition Waste Leachate from Laboratory Landfill
Simulators. Ph.D. Dissertation, University of Florida, Gainesville, FL, USA.
Kellenberger, D., Althaus, H.-J., Jungbluth, N., Kiinniger, T. (2004). Life Cycle Inventories of Building
Products. Final Report ecoinvent 2000 Published by Swiss Centre for LCI, EMPA-DU, Dubendorf,
CH.
Kellenberger, D., Althaus, H., Kiinniger, T., Lehmann, M. (2007). Life Cycle Inventories of Building
Products. Ecoinvent Report No. 7, Swiss Centre for Life Cycle Inventories, Dubendorf. December
2007.
Knoblauch, C., Jorgensen, B.B. (1999). Effect of Temperature on Sulphate Reduction, Growth Rate and
Growth Yield in Five Psychrophillic Sulphate-Reducing Bacteria from Arctic Sediments.
Environmental Microbiology, 1 (5), 457-467.
Koschorreck, M. (2008). Microbial sulphate reduction at a low pH. FEMS Microbial Ecology, 64, 329-342.
Marvin, E. (2000). Gypsum Wallboard Recycling and Reuse Opportunities in the State of Vermont. Waste
Management Division, Vermont Agency of Natural Resources. August 2000.
National Gypsum Company. (2008). National Gypsum Company: Drywall, cement board, gypsum board.
www.nationalgypsum.com. Accessed January 9, 2008.
National Gypsum (2013). Gypsum Board Frequently Asked Questions. http://bit.ly/lruLiOO. Accessed
April 2014.
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New Hampshire Department of Environmental Services. (2004). Interim best management practices
Approved for Co-Disposal of Construction and Demolition Process Fines with Municipal Solid
Waste. November 22, 2004.
Plaza, C., Xu, Q., Townsend, T.G., Bitton, G., Booth, M. (2007). Evaluation of Alternative Landfill Cover
Soils for Attenuating Hydrogen Sulfide from Construction and Demolition Debris Landfills.
Journal of Environmental Management, 84 (3), 314-322.
RWB, CCG and IWCS (2010). Statewide Construction and Demolition Debris Characterization Study. A
Report Prepared by R.W.Beck, Inc., Cascadia Consulting Group, Innovative Waste Consulting
Services, lie. for Georgia Department of Natural Resources, Sustainability Division. June 2010.
Sandier, K. (2003). Analyzing What's Recyclable in C&D Debris. Biocycle, 44 (11), 51-54.
Staley, B.F., Barlaz, M.A. (2009). Composition of Solid Waste in the United States and Implications for
Carbon Sequestration and Methane Yield. Journal of Environmental Engineering, ASCE, 135, 901-
909.
Tchobanoglous, G., Theisen, H., Vigil. S. 1993. Integrated Solid Ewaste Management: Engineering
Principles and Management Issues. McGraw Hill. ISBN 0-07-063237-5
Tolaymat, T.M., El Badawy, A. M., Carson, D.A. (2013). Estimate of the Decay Rate Constant of Hydrogen
Sulfide from Drywall in a Simulated Bench-Scale Study. Journal of Environmental Engineering,
ASCE, 139, 538-544.
Townsend, T.G., Barnes, A.H., Cochran, K.M., Carlson, J.J. (2001). Recycling of Discarded Gypsum
Drywall in Florida. A Report Prepared by University of Florida Department of Environmental
Engineering Sciences submitted by Citrus County Government, The New River Solid Waste
Association, and Okaloosa County Government for the Florida Department of Environmental
Protection. January 2001.
Townsend, T.G. (2002). Gypsum Drywall Impact on Odor Production at Landfills: Science and Control
Strategies. Florida Center for Solid and Hazardous Waste Management, University of Florida,
Gainesville, FL.
US Census Bureau. (2004). 2002 Commodity Flow Survey. US Economic Census. US Departmetof
Commerce, Economics and Statistics Administration. Washington, D.C. December 2004.
US EPA (2012). EPA Waste Resources Model, Drywall, WARM Version 12. United States Environmental
Protection Agency. February 2012.
US EPA (2014). Methodology to Estimate the Quantity, Composition, and Management of Construction
and Demolition Debris in the United States, WA 3-79, Tools for Improving Materials Management.
A Draft Report Prepared by Innovative Waste Consulting Services, LLC Under Subcontract to
Pegasus Technical Services, Inc for United States Environmental Protection Agency Office of
Research and Development. June 2014, Unpublished report.
US LCI (2012). US Life Cycle Inventory Database. National Renewable Energy Laboratory.
http://www.nrel.gov/lci/. Accessed 20 February 2014.
Venta, G.J. (1997). Life Cycle Analysis of Gypsum Board and Associated Finishing Products. Prepared by
George J. Venta of Venta, Glaser & Associates for The Athena Sustainable Materials Institute.
March 1997.
WRAP (2008). Life Cycle Assessment of Plasterboard: Quantifying the environmental impacts throughout
the product life cycle, building the evidence base in sustainable construction, Technical Report.
Report written by Karen Fisher, Senior Consultant, Environmental Resources Management Ltd for
the Waste Resources Action Programmme. April 2008.
Xu, Q. (2005). Hydrogen Sulfide Emissions and Control Strategies at Construction and Demolition Debris
Landfills. Ph.D. Dissertation, University of Florida, Gainesville, FL, USA.
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6 Wood
6.1 Introduction
Wood is the third most widely used construction material in the US after asphalt concrete and PCC (Cochran
and Townsend 2010). Softwood and hardwood lumber constituted approximately 58% (by weight) of 60
MMT of the solid wood products manufactured in the US in 2011 (Howard and Westby 2013).
Approximately 46% and 14% of the total solid wood products consumed in the US in 2009 were used for
residential (single family, multifamily, mobile home) and non-residential building construction and
renovation, respectively (McKeever and Howard 2011). Light wood framing utilizing dimensional lumber
and engineered wood is employed heavily in residential construction (Wacker 2010, McKeever and Howard
2011). This section covers the following solid wood product wastes, which commonly appear in CDD,
including dimensional lumber and engineered wood products:
• plywood and oriented strandboard (OSB),
• particleboard,
• medium-density fiberboard (MDF),
• structural laminated veneer lumber,
• glue laminated timber
• wood I-joists
Woody wastes from land clearing debris (LCD) activities are covered in Chapter 7 of this report. Paper
products, although representing the largest wood-derived product stream, represent a very small fraction of
discarded CDD materials by weight and, therefore, are not included in the scope of CDD materials
investigated in this report. A large amount of wood waste (wood residues) is also generated during
manufacturing and more than 98% of these are used by the wood products manufacturing industry as fuel
or as a feedstock for other products such as particle board. In an LCA context, the management of these
residues and the associated environmental impacts are typically attributed to the product manufacturing
phase (Puettmann and Wilson 2005). The LCI associated with the management of this portion of the wood
waste stream are not presented in this report.
Figure 6-1 depicts the processes in the life cycle of wood products, beginning with raw materials production
and extraction from forestry and silviculture (active management of forest resources) operations and
harvesting, through processing into product, use, and EOL management. The production phase consists of
multiple sub-processes. The nature and complexity of sub-processes depend on the type of wood used and
the desired end product.
The wood products used for construction are discarded at the end of their service life, which is reported to
range from 50 to 100 years (Cochran and Townsend 2010). As depicted in Figure 6-1, the EOL management
options of discarded wood products include landfill disposal (either in MSW or dedicated CDD landfills),
combustion, recycling, and composting. Although not a common practice, the discarded wood products can
be used for the production of new wood products (MGE 1997, Cochran 2006, US EPA 2012).
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Multimedia Environmental Assessment
Section 6 - Wood
^\ f "^
Silviculture Engineered
Operations & Wood Adhesive
Harvesting Production J
L
1
1
Sawmill/
Engineered
Wood
Production
V J
1
r i r i
Retail/ ^ , . .
Wholesale
«, j V >
^ *•
L . .. I
1
Size Reduction/
-»• Chipping & Nail
Removal
End-of-Life
Product Removal /
\~ J
*-> Landtilling
Mulch Use
Composting
J Combustion with
^| Energy Recovery
i-> Ash Landfilling
Ash Agricultural 1
Use/Soil
Amendment J
Figure 6-1. Life-Cycle Material Flows and Processes for Wood Product Manufacturing
and EOL Management
6.2 EOL Management
Wood, along with other construction materials, is discarded during construction, renovation, demolition
and/or deconstruction of the built environment. Based on a review of the data from 11 state-level waste
composition studies, Staley and Barlaz (2009) reported that lumber comprised approximately 40% of
discarded CDD by mass. Several estimates of discarded CDD wood materials have been published (Wiltsee
1998, Cochran an Townsend 2010, Falk and McKeever 2012). Wiltsee (1998) conducted telephone surveys
of demolition and land clearing contractors in 30 metropolitan areas in the US with populations ranging
from approximately 100,000 to 3.9 million to estimate the wood generation rate and management options
(including CDD wood waste); CDD wood was defined to include LCD. Wiltsee (1998) estimated the
weighted-average CDD wood waste generation rate to be 0.069 MT per capita per year, which is equivalent
to an annual generation rate of approximately 22 MMT for the US.
Falk and McKeever (2012) reported that CDD debris generated in 2010 included approximately 33 MMT
of wood; approximately 80% of the CDD wood was attributed to demolition activities. These estimates
were based on economic metrics (e.g., population change, housing completions) and construction activities
and unit generation rates (debris per capita per year). Cochran and Townsend (2010) estimated generation
of 36 to 55 MMT of CDD wood waste in 2002 based on a materials-flow analysis approach. Based on a
compilation of disposal and recycling data from individual states and regional-scale composition studies of
CDD debris landfilled, US EPA (2014) estimated that approximately 24 MMT of CDD wood was managed
by disposal and CDD processing facilities in the US in 2011; approximately 74% and 26% of the discarded
CDD wood (excluding LCD) was landfilled and recycled (including combustion), respectively. Several
other studies have published data pertaining to EOL management of discarded CDD materials. Wiltsee
(1998) estimated that approximately 70%, 15%, and 11% of the CDD waste wood was landfilled or
incinerated, mulched, and used as biomass fuel, respectively; the fraction of wood incinerated with energy
recovery was not provided. Approximately 4% of the CDD wood waste was estimated to be used for
production of pulp chips, color mulch, pressed fire logs, and fuel pallets.
The type of modification to the built environment (e.g., construction, renovation, or demolition) impacts
the relative fraction of wood waste present in the waste stream, which in turn impacts the viable EOL
management processes. The fraction of wood in CDD waste generated from construction, renovation, and
demolition of residential structures has been reported to be higher than for nonresidential structures
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Multimedia Environmental Assessment Section 6 - Wood
(Cochran et al. 2007). Cochran et al. (2007) also reported a greater wood fraction in the waste stream from
renovation than from demolition of residential and non-residential buildings.
The material handling at the point of generation (e.g., segregation from other CDD materials) impacts the
quality and in turn EOL management options. For example, the recovery and recycling of wood
commingled with other CDD materials may not be economically viable because of the extensive processing
that would be required. In addition to contamination by other materials, the presence of treated wood may
also dictate the EOL management options.
Landfilling of wood wastes appears to be the most common EOL management strategy employed in the
US. Combustion of discarded CDD wood seems to be practiced on a limited scale and is often considered
a form of recycling (MGE 1997, Falk and McKeever 2004, Cochran 2006). Creosote, used extensively for
treating wood used for railroad ties, has been reported to increase the wood energy content (Smith and Bolin
2010). The presence of treated wood affects all EOL management options. For example, ash from the
combustion of wood that includes treated wood may be limited in viability as a soil amendment (Solo-
Gabriele and Townsend 1999).
Discarded CDD wood is not commonly reused in the US. Building deconstruction as an alternative to
demolition has been proposed and practiced on very small scale to enhance material recovery and reuse
(NAHB 1997, Denhart 2010). Closed loop recycling of wood, unlike many other waste materials, is
severely limited (MGE 1997). Although engineered wood products can be manufactured using discarded
dimensional lumber, dimensional wood cannot be manufactured using engineered wood products due to
the processes wood undergoes when engineered wood products are manufactured. Recycling dimensional
lumber may also involve processing to smaller pieces of lumber or size reduction (i.e., chipping) to produce
engineered wood products (Merrild and Christensen 2009). This downcycling has been referred to as a
wood cascade chain (Sathre and Gustavsson 2006, Hoglmeier et al. 2013) and entails energy and carbon
balances considering land use, primary material substitution, transit, and manufacturing considerations.
Open-loop recycling generally involves size reduction for the production of mulch or chips. Mulch can be
used in erosion control, as a bulking agent in composting, as a boiler fuel, or for decorative purposes and
to assist in soil moisture retention in landscaping and gardening. Composting, although used for other
woody wastes (i.e., LCD discussed in Chapter 7), is rarely practiced for CDD wood materials (US EPA
2012). Table 6-1 presents processes that should be considered for LCA of EOL management options for
wood products.
Table 6-1. LCI Needed for LCA of Wood Products EOL Management
Process
Description
Wood Products
Manufacturing
Major operations of wood products manufacturing include forestry operations,
timber harvesting and processing timber at a mill. A variety of wood products
are manufactured in the US; cradle-to-gate materials and energy inputs and
emissions depend on the type of wood processed and the type of end product.
Transport
The fuel requirements and emissions associated with the transport of CDD wood
from the point of generation to a recycling facility or a landfill, and from a
recycling/processing facility to end users (e.g., for the use of mulch or wood
chips for combustion) should be considered for LCA of wood products.
Landfilling
The materials (e.g., equipment, soil, water) and energy (fuel, electricity) inputs
for placement and compaction of CDD wood in a landfill along with process
non-energy emissions (e.g., particulate emissions from equipment operation,
gas emissions from the decomposition of wood, and liquids emissions
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associated with biogeochemical degradation of CDD wood in a landfill) should
be included in LCA. Energy recovery from the collection and combustion of
landfill gas should also be accounted for.
Recycling
CDD wood is typically recycled into either mulch or biomass fuel; materials
(e.g., equipment), fuel consumption, and fuel and non-fuel emissions from
processing CDD wood in a chipper or grinder and storing the processed
materials should be considered. Land application of mulch, similarly to
landfilling of CDD wood, is expected to generate leachate influenced by
precipitation.
Combustion
Fuel and non-fuel emissions from combusting biomass fuel produced from CDD
wood include those generated during the drying of biomass fuel and blending
with other woody materials prior to combustion, and from combustion.
Ash Management
Wood ash produced from the combustion of CDD wood in a boiler is typically
managed by landfilling, although land application and other uses may occur.
Materials and emissions from management of the ash landfill will include
similar considerations as landfilling CDD wood, however gaseous emissions are
not expected.
6.3 LCI Sources
Peer-reviewed literature, government and private industry publications, and various LCA modeling tools
were reviewed to identify available LCI datasets pertaining to CDD wood EOL management. Table 6-2
lists data sources reviewed to compile LCI presented in this chapter. If LCI data were not available, process
metadata and documents were reviewed to evaluate the completeness of the dataset (e.g., emissions
categories included, background data used to compile the dataset, geographic location and time period of
the data). The primary sources of information used to develop the LCI datasets and information identified,
if available, were reviewed. Although LCI from many information sources listed in Table 6-2 may not
pertain specifically to the US, these sources are presented and discussed for better understanding of the
inputs used to develop these LCI and the LCI information available globally.
Table 6-2. LCI Sources to Develop Wood Products LCI
LCI Source
Description
AP-42 (US
EPA 1995a)
US EPA (1995a) provides air emissions factors for plywood manufacturing, reconstituted
wood products (OSB, particleboard, medium density fiberboard or MDF, hardboard and
fiberboard) manufacturing, wood preservation, and manufacture of engineered wood
(including glulam, laminated veneer lumber, and others).
US LCI
(2012)
The US LCI (2012) database contains US-specific LCI data for solid wood products related
to extracting raw materials, logging, and manufacturing wood products. The wood LCI
primarily originate from the Consortium for Research on Renewable Industrial Materials
(CORRIM) publications. CORRIM's work included LCI development for different wood
products in different geographic areas within the US, reflected in the unique inputs/outputs
for each process.
Cochran
(2006)
Cochran (2006) compiled energy requirements for recycling waste wood into mulch and
incineration as boiler fuel, identified as the primary EOL management option employed in
the US.
Dubey et al.
(2010)
Dubey et al. (2010) presents leaching data for four types of pressure-treated wood simulating
contaminant leaching under a variety of recycling and disposal scenarios.
GaBi
GaBi presents wood product manufacture related datasets that are primarily the same as those
in the US LCI (2012) database. Wood-specific elemental data for untreated and treated wood
are provided on a mass basis within the GaBi process datasets related to wood product
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landfilling.
Hasan et al.
(2010)
Hasan et al. (2010) present arsenic, copper, and chromium leaching data for untreated,
weathered chromated copper arsenate (CCA)-treated, and ACQ-treated wood subjected to
natural precipitation.
Jambeck
(2004)
Batch tests conducted on CCA-treated wood at different L:S ratios with deionized water as
the leaching fluid were undertaken and metals leached were quantified.
Jang (2000)
Jang (2000) reported anions, cations, and metals leaching from individual CDD materials
subjected to synthetic precipitation.
MSW-DST
This model's primary focus is the MSW stream and the environmental implications of its
management. Wood is recognized as a major component of MSW; EOL LCI data for leachate,
and LFG specific to branches are contained in the model.
Townsend
etal. (1999,
2004, 2005)
These studies reported column and batch leaching tests data on new as well as weathered
untreated and treated wood. Batch leaching tests utilized multiple set-up protocols to evaluate
the impact on metal leachability.
US EPA
(2012)
US EPA (2012) presents GHG emissions factors pertaining to source reduction, recycling,
combustion, and disposal of dimensional lumber, MDF, and hardwood flooring for WARM
model.
Athena
The Athena Impact Estimator (IE) for Buildings life-cycle model includes the energy
requirement for demolishing wood-framed structures. The Athena Sustainable Materials
Institute (ASMI) has developed cradle-to-gate LCI for the following wood products: cross
laminated timber (CLT), Glulam (glue laminated timber), wood I-joists, laminated veneer
lumber, MDF, OSB, particle board, softwood plywood sheathing, and softwood lumber.
EASETECH
EASETECH presents the LCI data associated with windrow composting of source separated
organic waste which may include several wood products. LCI data specific to composting
wood and SSOs in general is contained in the composting processes.
Ecoinvent
Doka (2009) presents elemental compositions of wood, which are used in conjunction with
transfer coefficients to estimate contaminants emissions to different media.
WRATE
WRATE presents the emissions data of various constituents associated with landfilling
unspecified wood, wood packaging, and non-packaging wood.
6.4 LCI Related to Wood Products Manufacturing
As discussed in Section 6.2, the reuse of recovered CDD wood in new construction or renovation or for
manufacturing new wood products is limited in the US. Assuming a constant wood products demand, the
reuse of discarded CDD wood products would offset production and the associated emissions of the same
wood product from primary inputs. This section discusses the cradle-to-gate wood products manufacturing
process and the associated LCI. Through CORRIM, several US wood products manufacturers, researchers,
associations, and government agencies have collaboratively developed LCI for multiple wood products
manufacturing unit processes, including forest management, harvesting, and manufacturing for various
geographical regions (Northwest, Southeast, Inland Northwest, and Northeast-North Central) in the US
(Oneil et al 2010, Puettmann et al. 2010). The LCI data discussed in this section are based primarily on the
work of CORRIM. The LCI developed by CORRIM are included in the US LCI and EPA databases.
The major operations for manufacturing wood products include forestry operation, timber harvesting, and
processing timber at a mill. Forestry operation includes activities such as site preparation for planting,
planting seedlings or promoting natural regeneration or sprouting, fertilization, thinning, and reducing wild
fire hazards (Oneil et al. 2010). Plants take up, convert, and store the atmospheric carbon until harvested.
Timber harvesting entails cutting the trees (felling); removing limbs and tops and cutting the tree into
merchantable and transportable log lengths, moving logs from the felling point to a loading point near a
haul road; and loading and transporting logs from the forest to a process point (e.g., mill) (Oneil et al. 2010).
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The LCI associated with the individual unit processes of forestry and harvesting operations are included in
the forestry and logging process category of the US LCI (2012) database. The LCI for two major wood
types (softwood and hardwood), multiple geographic regions of the US, and various management intensities
(low, medium, and high) are included in these databases. The management intensity is a measure of the
level of undertaking and spending on forest/land management (Arano and Munn 2006). The forestry LCI
include plant uptake of the atmospheric carbon dioxide.
The harvested timber is debarked (i.e., exterior bark is removed) to produce "roundwood." Roundwood is
used to produce a variety of wood products. As discussed earlier, approximately 60 MMT of solid wood
products were manufactured in the US in 2011. Figure 6-2 presents a relative distribution of different wood
products manufactured in the US (Howard and Westby 2013). It can be seen that lumber (hardwood and
softwood), OSB, softwood plywood, and particleboard constituted 58%, 10%, 7%, and 5% of the total
wood products manufactured in the US in 2011, respectively. These four products represented 80% of the
total solid wood products manufactured in the US in 2011. Other industrial products include poles, piling,
fence posts, and cooperage logs (Howard and Westby 2013). These wood products can be broadly classified
into two categories: sawn lumber and composite or engineered wood products. Sawn lumber (including
poles, piling, fence posts) is a single wood piece, whereas engineered wood products are made from lumber,
veneers, strands of wood, or from other small wood elements that are bonded together with structural resins
to form lumber-like structural products (US EPA 1990).
Oriented Strandboard
Softwood Plywood 10%
7%
Particlebard Production
5%
Other Industrial,
Production and
.Consumption
11%
Medium Density
Fiberboard Production
3%
Insulating Board
1%
Softwood Lumber
40%
Hardwood Plywood
and Veneer
2%
Lumber made
at Pallet Plant
1%
Laminated Veneer
Lumber
1%
Figure 6-2. Distribution of Wood Products Manufactured in the US in 2011
Sawn lumber is manufactured by sawing the roundwood to produce "green lumber," which is dried in kilns
to produce rough dry lumber. After drying, wood is shaped into final lumber form by planing rough dry
lumber. As can be seen from Figure 6-2, plywood, OSB, particle board, and medium-density fiberboard
are the most commonly manufactured engineered wood products. This section describes the manufacturing
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of these major engineered products based on process descriptions provided in the US EPA AP-42
documents.
For the manufacturing of softwood or hardwood plywood, debarked logs are cut to appropriate lengths and
heated in hot water baths or via steam or hot spray or a combination of the three to around 93 °C. The heated
logs are processed using a slicer or veneer lathe to generate veneer. The veneer is dried in kilns or driers.
Formaldehyde-based resins are applied on both sides of the dried veneer using glue spreaders and covered
with veneers with no glue. Multiple layers of veneers are laid together, with the grains of adjacent veneer
layers perpendicular. The laid-up assembly is consolidated under heat and pressure in a hot press to press
the glue into a thin layer over each veneer sheet and to activate thermosetting resins. The temperature and
time depend on the wood species, the resin and the press design. The plywood is trimmed at the edges and
the face and back may or may not be sanded smooth.
For OSB manufacturing, debarked logs are cut and placed in hot ponds (18-43 °C). The logs are the sliced
into wafers (1.5 inches wide and 3 to 6 inches long) using a waferizer. The wafers may be passed through
screens to remove fine and differentiate core and surface materials. Wafers are dried in rotary or conveyor
driers, normally fired with wood residues from the plant. The dried wafers are processed to remove fines
and segregate wafers by surface area and weight using a cyclone; undersized materials are used as fuel for
the dryer burner or boiler. The dried wafers are blended with resin, wax, and other additives in a blender;
thermosetting phenol-formaldehyde and isocyanate resins are the most commonly used binders. The resin-
coated wafers are metered out on a moving screen. The wafers are mechanically oriented in one direction
as they fall to the screen below. Wafers in the subsequent layer are oriented perpendicular to those in the
previous layer. The continuous formed mat is cut into desired lengths. The trimmed mat is pressed under
heat and pressure to activate the resign and bond the wafers. After cooling, bonded panels are trimmed to
final dimensions, finished as necessary, and packaged.
MDF is typically made from wood chips (residues from other wood processing steps or from primary
wood). The chips are cleaned and mechanically pulped to produce fibers. The fibers are blended with
bonding resins (urea-formaldehyde is the most commonly used resin) and other additive. The resinated
fibers are dried in single- or multi-stage dryers. The drying and blending sequence depends on the fibers-
resins (along with other additives) blending method. The dried resinated fibers are deposited on a
continuously moving belt to form a mat. The mats are prepressed and trimmed. The mat is pressed under
heat and pressure to activate the resin and bond the fibers into solid boards. The boards are cooled, sanded,
trimmed, and sawed to final dimensions; the boards may be painted or laminated as well.
Particleboard incorporates small particles typically in the form of a panel or other shapes. The source for
the particles may be residues (e.g., wood shavings, sawdust) from other wood products manufacturing
processes or harvested logs. After general size reduction (i.e., milling), the particles are screened and
classified by size, using an air classifier. After the particle size equals the specifications, the particles are
dried (at about 1600 °F for raw, greenwood particle inputs) to the desired moisture content (about 2 to 8%
by mass). Screening may occur after this step for further fines removal. The particles are then combined
with synthetic resin or other adhesive (e.g., wax) via spray nozzles. Wax may also be added to the boards'
outer layers for protection. To form the solid end product, the resinated particles are formed into the desired
shape. A press can be used to activate the resin and bond the fibers (for about 2.5 to 6 minutes) into boards.
The boards are then cooled, sanded, and trimmed.
The cradle-to-gate materials and energy inputs and the emissions depend on the wood (softwood,
hardwood) and product type (lumber, plywood, medium-density fiberboard) (Puettmann et al. 2010).
Dimensional lumber processing involves only saw and planing mill operation (i.e., planed dried lumber),
with the possible application of treatment chemicals (Wagner et al. 2009). Engineered wood products
require a greater degree of processing and treatment (e.g., resin production/application and heating) than
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dimensional lumber products, often including the use of adhesives and chemicals. The manufacturing phase
is reported to consume 90-92% of the total cradle-to-gate energy consumption for wood products
manufacturing (Puettmann et al. 2010). The harvesting and material transport phases combined consume
less than 10% of the total production energy. Drying has been reported to be the most energy-intensive step
in lumber production (Puettmann and Wilson 2005). Drying and final pressing of composite products have
been reported to be the most energy-intensive steps in engineered wood products manufacturing (Puettmann
and Wilson 2005).
The US LCI (2012) and US EPA LCI databases provide multiple unit processes pertaining to softwood and
hardwood lumber and various engineering products manufacturing; additional LCIs for wood product
manufacturing were not developed as part of this project. In addition to US LCI and US EPA databases, the
US EPA (1995a) reports air emissions [particulate matter (<2.5 and 10 microns), carbon monoxide, carbon
dioxide, nitrous oxides and volatile organic compounds] from wood product manufacturing. GaBi contains
US-specific LCI data for wood product reduction, which in large part overlap with US EPA and US LCI
(2012) datasets; however, several unique process datasets were developed by PE International related to
wood product manufacture (e.g., production of CCA containerboard (not a CDD wood product considered
in this report)). The CCA production LCI dataset includes material inputs of chromic acid, lead, and copper
sulfate to the process and electricity and steam use and transport for the US. Emissions to the environment
are not provided within the accessible metadata for the dataset. The US EPA's WARM model presents
GHG emission data pertaining to source reduction, recycling, and landfilling of dimensional lumber, MDF,
and hardwood flooring from 100% primary inputs based on emissions from process and transport energy
use and the elimination of forest carbon storage (due to the cessation of CCh sequestration by the trees when
they are harvested). Athena (2012) provides Canada-specific LCI data for the manufacture of wood
products. Several inputs used for developing these LCI are based on US LCI and CORRIM data.
6.5 LCI Related to Disposal
Disposal of CDD wood product waste in landfills is the most commonly encountered management practice
in the US (Falk and McKeever 2012). Due to generally lower tipping fees, CDD wood disposal in MSW
landfills is less common than disposal in CDD materials landfills. The potential for leachate and LFG
release to the environment is dependent on the biogeochemical environment of the landfill and the
environmental controls, as discussed in Chapter 2. The emissions associated with production and use of
different materials and energy inputs for landfill construction, operation, and closure as well as those
associated with leachate and gas should be included in LCI for wood disposal. The details of leachate and
gas emission LCI are presented in this section. More details on landfill operation LCI are presented in
Chapter 2.
Due to its organic nature, the decay of wood wastes in an anaerobic (i.e., oxygen-poor) environment
produces methane, which may be collected by a GCCS and converted to biogenic CO2 via flaring or energy-
conversion technology. Most of the waste LCA models (WARM, MSW-DST, EASETECH) account for
methane as the only gaseous emission associated with wood decomposition in a landfill. Moreover,
WARM, and MSW-DST adopted material-specific methane yield and decay rates reported by the same
sources (i.e., Eleazer et al. 1997, Barlaz 1998, Staley and Barlaz 2009, De la Cruz et al. 2010) for estimation
of methane emissions. Eleazer et al. (1997) collected branches (<5 cm in length), from a compost facility
in North Carolina and conducted bioassay tests in quadruplicate in 2-L reactors to estimate methane yield
per unit of dry weight; no information on the tree species was provided.
The MSW-DST contains LCI data for leachate emissions from the landfill disposal of an array of waste
materials contained in MSW, including branches, a component of yard waste. CDD wood product is not
included as a material category in the model. The US EPA (2012) used methane yield of branches (reported
on dry weight of branches) as a proxy for developing emission factors for dimensional lumber, medium-
density fiberboard, and wood flooring. The methane yield was adjusted for moisture content to estimate
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methane emission per unit wet weight of the material. The moisture content used for dimensional lumber
and medium density fiberboard was the same as that of branches. The moisture content used for wood
flooring was greater than that of branches resulting in approximately 15% lower methane emission factors
for wood floor than the other wood products. WRATE provides wood-specific emissions of approximately
30 gaseous constituents for disposal scenario. The materials-specific gaseous emissions of various
constituents are not based on actual material-specific measurements, but rather are based on a theoretical
allocation of the total emissions to individual waste components (Golder Associates 2005).
The LFG production properties of branches was used as a proxy for estimating gas generation as a result of
the landfill disposal of CDD wood. Additional information on calculations used to estimate CDD wood
LFG emissions is provided in Section 2.5.10.8. The methane and carbon dioxide emissions from the landfill
disposal of CDD wood is respectively estimated as 0.064 and 0.21 kg for placement in a CDD landfill.
A significant fraction of methane is captured and combusted to carbon dioxide at the landfills with GCCS
(e.g., MSW landfills). The methane and biogenic carbon dioxide emission from landfills with GCCS would
be lower and higher, respectively, than from landfills with no GCCS. Using the average nationwide
statistics for the percentage of landfills that have GCCS and assuming a 90% average gas collection
efficiency as provided for dimensional lumber in US EPA (2012), the methane and carbon dioxide
emissions from the landfill placement of one kilogram of wood in an MSW landfill are estimated to be
0.022 kg, and 0.33 kg, respectively. Wood treatment chemicals were assumed not to have an impact on gas
generation.
Wood products are often treated with preservative chemicals for protection from the weathering elements
and biota. Chemicals may either be applied to the wood's surface and/or impregnated (requires pressure
treatment to infuse the chemical) into the wood itself (Haverty and Micales-Glaeser 2004, US EPA 1999).
Chromated copper arsenate (CCA) was previously the most extensively used chemical to treat lumber and
other wood products; CCA use began in the 1940s. Three types of CCA-treated wood were available. Type
C CCA was the most common wood preservative when it was in widespread use (prior to phase-out)
(Jambeck 2004). Other treatment chemicals, such as the copper-based alkaline copper quaternary (ACQ),
copper azole (CBA), and disodium octaborate tetrahydrate (DOT) are being used in greater volume due to
phase-out of CCA. Jambeck et al. (2007) estimated that the peak quantity of CCA wood in the waste stream
would occur in 2008, when approximately 9.7 million m3 would be disposed of. The presence of wood
treatment chemicals and other chemicals in paints (which may contain lead), stains, etc. has a significant
impact on the quality of liquid emissions (Lebow et al. 2004, Townsend et al. 2004) and complicates and
often impedes the EOL management via disposal or reuse/recycling.
Lebow et al. (2004) conducted an extensive review of the published leaching data from treated wood and
reported that several factors such as particle size, wood species, leaching water characteristics, and surface
finishes (e.g., paint) have significant impact on preservative leaching from pressure-treated wood. For
example, Lebow et al. (2004) reported that red oak leached approximately 15% of the total As, while yellow
poplar leached only approximately 1% of As for the same treatment type (Type C CCA). Townsend et al.
(2004) reported that for the same treated wood, a 100-g block leached at levels approximately a quarter of
the arsenic leached by sawdust particles.
Similar to other CDD materials, wood is typically disposed of with other CDD materials. The actual
measurement of long-term wood-specific liquids emissions from full-scale landfills are not available and
not expected to be available in the future. The laboratory-scale leachate quality data published by various
sources (Townsend et al. 1999, Jang 2000, Lebow et al. 2002, Lebow et al. 2004, Jambeck 2004, Dubey
2005, Jambeck et al. 2006, Dubey et al. 2007, Mitsuhashi et al. 2007, Dubey et al. 2010, Hasan et al. 2010,
Clausen etal. 2010, Tao et al. 2013, Tao 2014) were reviewed to estimate liquids emission from the disposal
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of untreated and treated wood in landfills. The following criteria were used to select data for estimating
liquids emission from wood products disposal in landfills:
1. Sample size. Wood products are not expected to undergo a significant size reduction during waste
placement and compaction in a landfill. The data from leaching tests conducted on larger particle
sizes (e.g., wood blocks) were preferred over data from tests on aggressively size-reduced wood
samples (e.g., sawdust) (e.g. Townsend et al. 2004, and Townsend et al. 2005) for liquids emission
estimates.
2. L:S ratio. The cumulative amount of chemicals leached from treated wood has been reported to be
a function of the amount of liquid wood is exposed to (Jambeck 2004, Tao et al. 2013). Many
studies assessed leaching from sample columns exposed to natural or synthetic precipitation (Jang
2000, Jambeck 2004, Tao et al. 2013, and Tao 2014) for a limited timeframe. None of these studies
reported 100% leaching of the preservatives. The L:S ratio for these studies was either not reported
or significantly lower than L:S ratio of the standardized leaching tests such as SPLP and TCLP.
The data from tests with greater L:S ratio were preferred over those from lower L:S ratio tests.
3. Leaching fluid. As leaching in landfill environment is expected to occur under slightly acidic
conditions, leaching data associated with neutral or basic fluids such as deionized water (e.g.,
Jambeck 2004, Jambeck et al. 2006, Dubey et al. 2007) were not used for estimating liquids
emission associated with disposal of untreated/treated wood in landfills. Data from tests using
SPLP and TCLP extraction fluids were used for estimating liquids emission from an unlined inert
debris landfill and MSW landfill, respectively.
Based on these criteria, results from SPLP batch leaching test (L:S=20) data reported by Jang (2000) were
used for estimating liquids emission (for COD, chloride, potassium, calcium, arsenic, chromium, copper,
and manganese) from untreated wood and CCA wood disposal in an unlined inert debris (CDD materials)
landfill. Jang (2000) conducted batch leaching tests using SPLP extraction fluid on individual CDD
materials, including untreated and CCA-treated wood. The column leaching data from Townsend et al.
(1999) were used for parameters that were measured below the detection limit by Jang (2000). Townsend
et al. (1999) conducted column leaching tests on individual CDD materials, including wood (untreated,
new, southern pine lumber) with SPLP extraction fluid. The overall L:S ratio for the column experiment
was approximately 5.
Table 6-3Table 6-3 presents a proposed LCI for untreated wood disposal in unlined CDD materials landfill.
The bulk density of wood waste presented in CCG (2006) was used to estimate cover soil requirements for
placement of untreated wood waste at a CDD landfill. Additional details on the diesel and electricity
requirements included in the "CDD landfill operations" flow and details on the cover soil estimate are
provided in Chapter 2. A 20 km average nationwide distance between the wood removal site and CDD
landfills was assumed.
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Table 6-3. Proposed LCI Dataset: Untreated Wood Waste, at Unlined CDD Landfill
Input Flow
Untreated wood waste, from
EOL removal
Truck transport, class 8, heavy
heavy-duty (HHD), diesel,
short-haul, load factor 0.75
CDD landfill operations
Cover soil, from offsite source
Output Flow
Untreated wood waste, at
unlined CDD landfill
Methane
Carbon dioxide
Chloride
Calcium
COD
Potassium
Manganese
Magnesium
Carbonate
Sodium
Source
Assumed
See Chapter 2
See Chapter 2
Source
US EPA (20 12)
US EPA (20 12)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Townsendetal. (1999)
Townsend et al. (1999)
Townsendetal. (1999)
Category
Construction and
Demolition Debris
Management
Construction and
Demolition Debris
Management
Construction and
Demolition Debris
Management
Category
Construction and
Demolition Debris
Management
Air/Unspecified
Air/Unspecified
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Units
kg
t*km
kg
kg
Units
kg
kg
kg
mg
mg
mg
mg
mg
mg
mg
mg
Amount
1
0.001*20
1
0.176
Amount
;
0.064
0.21
74.0
24.0
2,400
42.0
2.20
29.0
6.1
7.5
Leaching of chemicals from wood treated with CCA and other chemicals have been investigated by several
authors (e.g., Jang 2000, Townsend et al. 2004, Jambeck 2004, Dubey et al. 2010, Hasan et al. 2010). Based
on the criteria discussed above, data presented by Jang (2000) were selected to estimate liquid emissions
associated with CCA-wood (Type C, chemical retention rate of 4.0 kg/m3) disposal in unlined CDD
materials landfill. Data from SPLP tests conducted by Dubey et al. (2010) on sawdust of CCA-treated wood
(Type C, retention rate of 6.4 kg/m3) were used for the parameters not measured by Jang (2000). Table 6-4
presents proposed LCI for CCA wood disposal in unlined CDD materials landfill. As can be seen from
Table 6-4 COD, chloride, calcium, manganese, and potassium emission from CCA-treated wood are at
similar levels to those from untreated wood.
6-11
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Multimedia Environmental Assessment
Section 6 - Wood
Table 6-4. Proposed LCI Dataset: CCA-Treated Wood Products, at Unlined CDD Landfill
Input Flow
CCA-treated wood, from EOL
removal
Truck transport, class 8, heavy
heavy-duty (HHD), diesel, short-
haul, load factor 0.75
CDD landfill operations
Cover soil, from offsite source
Output Flow
CCA-treated wood products, at
unlined CDD landfill
Methane
Carbon dioxide
Arsenic
Boron
Chromium
Copper
COD
Chloride
Calcium
Potassium
Manganese
Source
Assumed
See Chapter 2
See Chapter 2
Source
US EPA (20 12)
US EPA (20 12)
Jang (2000)
Dubey et al.
(2010)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Category
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Category
Construction and Demolition
Debris Management
Air/Unspecified
Air/Unspecified
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Units
kg
t*km
kg
kg
Units
kg
kg
kg
mg
mg
mg
mg
mg
mg
mg
mg
mg
Amount
1
0.001*20
1
0.176
Amount
;
0.064
0.21
47.6
9.0
19.4
10.4
2,600
72.0
50.0
82.0
2.8
Table 6-5, 6-6, and 6-7 present proposed LCI for disposal of ACQ-, CBA-, and DOT-treated wood in
unlined CDD landfills. The liquids emissions for these treated wood types were estimated based on SPLP
data presented by Dubey et al. (2010). Dubey et al. (2010) conducted tests on sawdust from various treated
wood using a variety of extraction fluids, including SPLP, TCLP, and leachates from MSW landfills. The
same quantity of cover soil, diesel and electricity consumption for landfill operations, and transport distance
between the site of wood removal and the CDD landfill were assumed as was assumed for the CDD landfill
disposal of untreated wood.
Table 6-5. Proposed LCI Dataset: ACQ-Treated Wood Products, at Unlined CDD Landfill
Input Flow
ACQ-treated wood, from EOL
removal
Truck transport, class 8, heavy
heavy-duty (HHD), diesel,
short-haul, load factor 0.75
CDD landfill operations
Cover soil, from offsite source
Output Flow
ACQ-treated wood products,
at unlined CDD landfill
Methane
Source
Assumed
See Chapter 2
See Chapter 2
Source
US EPA (20 12)
Category
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Category
Construction and Demolition
Debris Management
Air/Unspecified
Unit
kg
t*km
kg
kg
Unit
kg
kg
Amount
1
0.001*20
1
0.176
Amount
;
0.064
6-12
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Multimedia Environmental Assessment
Section 6 - Wood
Carbon dioxide
Arsenic
Boron
Copper
Chromium
US EPA (20 12)
Dubeyetal. (2010)
Dubeyetal. (2010)
Dubeyetal. (2010
Dubeyetal. (2010)
Air/Unspecified
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
kg
mg
mg
mg
mg
0.21
0.55
168
391
1.05
Table 6-6. Proposed LCI Dataset: CBA-Treated Wood Products, at Unlined CDD Landfill
Input Flow
CBA-treated wood, from EOL
removal
Truck transport, class 8, heavy
heavy-duty (HHD), diesel,
short-haul, load factor 0.75
CDD landfill operations
Cover soil, from offsite source
Output Flow
CBA-treated wood products,
at unlined CDD landfill
Methane
Carbon dioxide
Arsenic
Boron
Copper
Chromium
Source
Assumed
See Chapter 2
See Chapter 2
Source
US EPA (20 12)
US EPA (20 12)
Dubeyetal. (2010)
Dubeyetal. (2010)
Dubeyetal. (2010
Dubeyetal. (2010)
Category
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Category
Construction and Demolition
Debris Management
Air/Unspecified
Air/Unspecified
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Unit
kg
t*km
kg
kg
Unit
kg
kg
kg
mg
mg
mg
mg
Amount
1
0.001*20
1
0.176
Amount
;
0.064
0.21
0.1
341
619
0.3
Table 6-7. Proposed LCI Dataset: DOT-Treated Wood Products, at Unlined CDD Landfill
Input Flow
DOT-treated wood, from
EOL removal
Truck transport, class 8,
heavy heavy-duty (HHD),
diesel, short-haul, load factor
0.75
CDD landfill operations
Cover soil, from offsite
source
Output Flow
DOT-treated wood products,
at unlined CDD landfill
Methane
Carbon dioxide
Arsenic
Boron
Copper
Chromium
Source
Assumed
See Chapter 2
See Chapter 2
Source
US EPA (20 12)
US EPA (20 12)
Dubeyetal. (2010)
Dubeyetal. (2010)
Dubeyetal. (2010
Dubeyetal. (2010)
Category
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Category
Construction and Demolition
Debris Management
Air/Unspecified
Air/Unspecified
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Unit
kg
t*km
kg
kg
Unit
kg
kg
kg
mg
mg
mg
mg
Amount
1
0.001*20
1
0.176
Amount
;
0.064
0.21
2.28
1,450
1.32
0.115
6-13
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Multimedia Environmental Assessment
Section 6 - Wood
Leachate related emissions from wood products in an MSW landfill environment were estimated based on
TCLP data reported in literature. Table 6-8 through Table 6-11 present the proposed LCI for four types of
treated wood based on the TCLP test data reported by Dubey et al. (2010). The cover soil requirements and
material and energy flows included for MSW landfill construction, operation and closure and post-closure
care are detailed in Chapter 2 of the report. The bulk density of wood products presented in CCG (2006)
was used to estimate cover soil requirements. The distance between the wood removal site and MSW
landfills was assumed to be 20 km in the absence of average nationwide data.
Table 6-8. Proposed LCI Dataset: CCA-Treated Wood Products, at MSW Landfill
Input Flow
CCA-treated wood, from
EOL removal
Truck transport, class 8,
heavy heavy-duty (HHD),
diesel, short-haul, load factor
0.75
MSW landfill construction,
for CDD materials
MSW landfill operations
MSW landfill closure and
post-closure, for CDD
materials
Cover soil, from MSW
landfill stockpile
Output Flow
CCA-treated wood products,
at an MSW landfill
Methane
Carbon Dioxide
Arsenic
Boron
Chromium
Copper
Source
Assumed
See Chapter 2
See Chapter 2
See Chapter 2
See Chapter 2
Source
US EPA (20 12)
US EPA (20 12)
Dubey etal. (2010)
Dubey etal. (2010)
Dubey etal. (2010)
Dubey etal. (2010)
Category
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Category
Construction and Demolition
Debris Management
Air/Unspecified
Air/Unspecified
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Units
kg
t*km
kg
kg
kg
kg
Units
kg
kg
kg
mg
mg
mg
mg
Amount
1
0.001*20
1
1
1
1.24
Amount
;
0.022
0.33
226
12.6
74.7
217
Table 6-9. Proposed LCI Dataset: ACQ-Treated Wood Products, at MSW Landfill
Input Flow
ACQ-treated wood products,
from EOL removal
Truck transport, class 8,
heavy heavy-duty (HHD),
diesel, short-haul, load factor
0.75
MSW landfill construction,
for CDD materials
MSW landfill operations
MSW landfill closure and
post-closure, for CDD
materials
Cover soil, from MSW
landfill stockpile
Source
Assumed
See Chapter 2
See Chapter 2
See Chapter 2
See Chapter 2
Category
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Units
kg
t*km
kg
kg
kg
kg
Amount
1
0.001*20
1
1
1
1.24
6-14
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Multimedia Environmental Assessment
Section 6 - Wood
Output Flow
ACQ-treated wood products,
at an MSW landfill
Methane
Carbon Dioxide
Arsenic
Boron
Copper
Chromium
Source
US EPA (20 12)
US EPA (20 12)
Dubeyetal. (2010)
Dubeyetal. (2010)
Dubeyetal. (2010)
Dubeyetal. (2010)
Category
Construction and Demolition
Debris Management
Air/Unspecified
Air/Unspecified
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Units
kg
kg
kg
mg
mg
mg
mg
Amount
;
0.022
0.33
1.34
181
940
1.0
Table 6-10. Proposed LCI Dataset: CBA-Treated Wood Products, at MSW Landfill
Input Flow
CBA-treated wood products,
from EOL removal
Truck transport, class 8,
heavy heavy-duty (HHD),
diesel, short-haul, load factor
0.75
MSW landfill construction,
for CDD materials
MSW landfill operations
MSW landfill closure and
post-closure, for CDD
materials
Cover soil, from MSW
landfill stockpile
Output Flow
CBA-treated wood products,
at an MSW landfill
Methane
Carbon Dioxide
Arsenic
Boron
Copper
Chromium
Source
Assumed
See Chapter 2
See Chapter 2
See Chapter 2
See Chapter 2
Source
US EPA (20 12)
US EPA (20 12)
Dubeyetal. (2010)
Dubeyetal. (2010)
Dubeyetal. (2010)
Dubeyetal. (2010)
Category
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Category
Construction and Demolition
Debris Management
Air/Unspecified
Air/Unspecified
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Units
kg
t*km
kg
kg
kg
kg
Units
kg
kg
kg
mg
mg
mg
mg
Amount
1
0.001*20
1
1
1
1.24
Amount
;
0.022
0.33
0.133
393
721
0.313
6-15
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Multimedia Environmental Assessment
Section 6 - Wood
Table 6-11. Proposed LCI Dataset: DOT-Treated Wood Products, at MSW Landfill
Input Flow
DOT-treated wood products,
from EOL removal
Truck transport, class 8,
heavy heavy-duty (HHD),
diesel, short-haul, load factor
0.75
MSW landfill construction,
for CDD materials
MSW landfill operations
MSW landfill closure and
post-closure, for CDD
materials
Cover soil, from MSW
landfill stockpile
Output Flow
DOT-treated wood products,
at an MSW landfill
Methane
Carbon Dioxide
Arsenic
Boron
Copper
Chromium
Source
Assumed
See Chapter 2
See Chapter 2
See Chapter 2
See Chapter 2
Source
US EPA (20 12)
US EPA (20 12)
Dubeyetal. (2010)
Dubeyetal. (2010)
Dubeyetal. (2010)
Dubeyetal. (2010)
Category
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Category
Construction and Demolition
Debris Management
Air/Unspecified
Air/Unspecified
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Units
kg
t*km
kg
kg
kg
kg
Units
kg
kg
kg
mg
mg
mg
mg
Amount
1
0.001*20
1
1
1
1.24
Amount
;
0.022
0.33
2.84
1,300
3.35
0.280
Several factors should be considered when using the proposed liquids emissions for MSW landfills. First,
the emissions presented in Table 6-8 through Table 6-11 should be considered as partial as these are based
on batch leaching tests with an L:S ratio of 20. In reality, wood placed in a landfill would be subjected to
leaching a much greater L:S ratio (assuming that the landfilled waste will never be reclaimed) associated
with untreated leachate. Second, leachate from an MSW landfill is typically collected and treated before
the effluent is discharged into the environment during active disposal, closure, and post-closure care. The
wastewater treatment process partitions contaminants from the liquid phase into the treated effluent and
solid residues (sludge, biosolids). The contaminant amounts released into the environment with effluent
discharge depends on the treatment plant's contaminant-removal efficiency, which in turn depends on the
contaminant type (NCSU and ERG 2011). A treatment efficiency of 85% for heavy metals is used by
MSW-DST. The sludge from a wastewater treatment plant is commonly managed by either land-application
or disposal at MSW landfills. Based on a nationwide survey NEBRA (2007) estimated that approximately
49% of the WWTP sludge generated in the US is land applied. The inorganic contaminants contained in
sludge would potentially leach and be released into the environment (groundwater, surface water).
The additional pathways, apart from effluent discharge, by which leachate emits contaminants into the
environment are fugitive leachate emissions through the bottom liner imperfections (e.g., geomembrane pin
holes that occur during construction), leaching of chemicals from land-applied sludge, and the cyclic
process of contaminant release from wastewater treatment plant sludge deposited in landfills, leachate
treatment, and sludge disposal at landfills. Moreover, 100% of the leachate would discharge into the
environment at the conclusion of the post-closure care period. For example, MSW-DST and EASETECH
account for leachate collection and treatment for a default period of 100 years. EASETECH and MSW-
DST documentations do not appear to consider contaminants emission from sludge disposal or sludge land
application.
6-16
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Multimedia Environmental Assessment Section 6 - Wood
6,6 LCI Related to Recycling
Mulch and biomass fuel production are the two primary recycling options for CDD wood (Wiltsee 1998,
Townsend et al. 2003). As discussed earlier, approximately 30% of wood (equivalent to more than 8 MMT)
is recycled as mulch or biomass fuel (Wiltsee 1998, US EPA 2014). A lack of demand for end-products
(mulch, biomass), coupled with competition from wood product manufacturing industries, are potential
challenges for CDD wood recovery and recycling. The US mulch demand in 2005 of approximately 3 MMT
(estimated by Cochran 2006) was small compared to the amount of residue produced by wood product
manufacturing (177 MMT in 2002 as reported by McKeever (2004). Moreover, CDD wood is often
considered to be a less-desirable feedstock for mulch production due to aesthetics (Townsend et al. 2003).
Information on CDD wood composting is lacking, likely owing to the limited nature of this practice. All
potential recycling options (including closed-loop recycling for wood product manufacturing and
composting) entail wood processing (i.e., grinding/chipping) as the first step. As closed-loop recycling of
discarded wood is not prevalent, processing and reuse of discarded wood for wood product manufacturing
is not discussed further.
Energy inputs and emissions associated with CDD wood waste processing to produce mulch include those
related to manufacturing and the use of sorting, grinding, and screening equipment (Cochran 2006). Based
on the data reported by Morbark (2006), Diamond Z (2006), and Bandi (2006) (as reported by Cochran
2006) for a horizontal grinder and manufacturer equipment specifications (for an excavator and loader), the
diesel equipment energy requirements is 29.5 MJ per MT of wood waste processed in a mixed CDD MRF.
This is equivalent to a fuel consumption of approximately 0.755 L of diesel per MT of wood. As a point
of comparison, Levis (2008) estimated yard-waste shredding fuel consumption to be approximately 1.18 L
and 3.0 L per MT; the estimate was based on a regression analysis of production rate, horsepower, and fuel
consumption data from manufacturers for several models of horizontal grinders and tub grinders,
respectively. This wide range of data suggests a need for measuring energy and material inputs from actual
facility operations so that more reliable LCI can be developed. Until such data are available, the use of the
fuel consumption data reported by Cochran (2006) is proposed.
The non-energy-related emissions from wood grinding include particulate matter emission and liquid
emission from wood/wood chip stockpiles. AP-42 presents air emission factors for log chipping as part of
MDF manufacturing. These data can be used as a proxy for CDD wood grinding until measurements from
operating facilities become available. However, it appears that unlike CDD wood processing facilities,
engineering controls such as cyclone and/or fabric filter collection are implemented to control particulate
matter emission from chipping operations at MDF manufacturing facilities. Using log chipping air emission
as a proxy would, therefore, result in underestimating particulate matter emission from CDD wood
processing facilities. As the wood decomposition in this scenario would occur under aerobic conditions,
gas emissions from the land application of mulch were estimated by assuming that 100% of carbon content
will decompose to produce carbon dioxide. Using the biogenic carbon content of branches (published by
Barlaz 1998) as a proxy for wood products, approximately 1.63 kg of carbon dioxide (biogenic) would be
produced from aerobic decomposition of 1 kg of wood products; this estimate is based on 0.494 g of carbon
content as C per dry kg of wood product and 0.9 kg of dry wood per kg of wet wood product.
The liquids emissions from land application of mulch are expected to be the same as those from wood
disposal in CDD materials landfills as leaching is primarily influenced by natural precipitation. It was
assumed that the CDD wood would be transported 20 km from the job site to the processing facility and
the mulch would be transported 20 km to the mulch end user. Table 6-12 presents proposed LCI for CDD
wood grinding to produce mulch and land application of mulch.
6-17
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Multimedia Environmental Assessment
Section 6 - Wood
Table 6-12. Proposed LCI Dataset: Mulch Production and Land Application
Input Flow
Wood waste
Truck transport, class 8, heavy
heavy-duty (HHD), diesel, short-
haul, load factor 0.75
Diesel, combusted in industrial
equipment
Output Flow
Land-applied mulch
Carbon Dioxide (biogenic)
Chloride
Calcium
COD
Potassium
Manganese
Magnesium
Carbonate
Sodium
Source
Assumed
Cochran (2006)
Source
US EPA (20 12)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Townsend et al. (1999)
Townsendetal. (1999)
Townsend et al. (1999)
Category
Construction and Demolition
Debris Management
Flows
Category
Construction and Demolition
Debris Management
Air/Unspecified
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Units
kg
t*km
L
Units
kg
kg
mg
mg
mg
mg
mg
mg
mg
mg
Amount
1
0.001*40
0.000755
Amount
;
1.63
74.0
24.0
2,400
42.0
2.20
29.0
6.1
7.5
6.7 LCI Related to Combustion
As described earlier, one of the predominant markets for mixed wood recovered at CDD processing
facilities is use as a boiler fuel. Cochran et al. (2006) estimates that approximately 5 MMT of waste wood
products could be combusted for electricity production without expanding the US capacity for wood
combustion. Recovered wood is typically size reduced at these facilities and transported for combustion in
incinerators or boilers (McKeever 2002). At these combustion facilities, the CDD debris is often mixed
with other sources of woody debris, such as yard trash, LCD, pulp and paper mill residues, and
agriculture/silviculture waste. Wood wastes may also be dried to concurrently reduce their moisture content
and raise their heating value. However, for use as a boiler fuel, this drying step appears to not be necessary
for the relatively low moisture contents (e.g., 10 - 20%) commonly encountered in CDD wood products
(Koch 1980, US EPA 1995b). Drying is more of a concern for treating green wood (i.e., freshly cut) residue
feedstock from the timber industry; Curkeet (2011) estimates that green wood may have a moisture content
greater than 75%.
The environmental emissions produced from combustion will depend on the boiler configuration in
combination with in-place environmental controls. Different types of boiler configurations may be used,
such as spreader stoker, Dutch oven, and suspension-fired, each of which may release a different set of
emissions (e.g., fluidized bed combustion reduces the emissions associated with incomplete combustion
byproducts) (US EPA 1995b). US-specific LCI data related to wood waste combustion as part of an MSW
mass burn scenario is included in the US EPA WARM model, where the focus is on MSW mass burn
because of the relatively low number of MSW RDF fuel facilities in the US. The biogenic carbon dioxide
released as a result of wood combustion is not accounted for in WARM; however, a nitrous oxide emission
factor is assigned to the wood waste material categories (i.e., dimensional lumber, wood flooring, MDF).
6-18
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Multimedia Environmental Assessment Section 6 - Wood
The nitrous oxide emission factor is not wood specific - it is evenly allocated to all possible nitrogen-
containing waste materials based on the results of mixed MSW combustor emissions reported by the
Intergovernmental Panel on Climate Change (IPCC) (US EPA 2012).
The US LCI (2012) database contains emissions data for two wood-combustion processes (i.e., combustion
of wet and dry wood residue) based on US EPA (1995b) AP-42 emissions included in the database's "Other
Electric Power Generation" subfolder of the "Utilities" folder. An additional process located in the same
place represent electricity generation at a biomass plant. However, the process system boundaries include
biomass production, and thus emissions from biomass growth/management and combustion cannot be
distinguished. Additional wood combustion LCI datasets can be found in the "Steam and Air-Conditioning
Supply" subfolder of the "Utilities" folder, which include another 14 process datasets that simulate the
combustion of different wood fuels combusted in industrial boilers. These processes are subcategorized by
whether they handle softwood or hardwood, the region of the US the wood originated from, and the specific
type of facility which produced the wood material.
Since emissions for the combustion of dry wood residue have already been compiled from AP-42 into an
LCI process dataset, the use of this dataset to model air emissions released from the combustion of
processed CDD wood is proposed. However, to build a product system that incorporates this existing
process, the process would need to be modified to have a processed wood input flow and would need to
have an output flow of combusted wood ash. Currently, the emissions from the "Combustion, wet wood
residue, AP-42" process are quantified per energy (MJ) recovered from the combustion process. AP-42
(US EPA 1995b) and US EPA (2012) together support a moisture content of CDD wood (e.g. dimensional
lumber, furniture) of 10% (wet basis) and Jenkins et al. (1998) presents the ash content of demolition wood
as 13% of initial dry mass; together, these statistics could be used to update this process so that it could be
included with a CDD wood combustion product system.
6.7.1 Wood Ash
Wood ash is generated at a rate of approximately 2.7 MMT annually in the US (Risse 2010). In the US,
ash is managed by two major pathways: landfilling (approx. 65%) and land application (9%), while 25%
goes towards "other" undefined uses (Spokas 2010). When used as a soil amendment, wood ash is capable
of providing valuable nutrients (e.g., potassium, phosphorus, magnesium) as well as acting as a liming
agent, raising the pH and thus assisting in the retention of nutrients (Kahl et al. 1996, NEWMOA 2001,
ASTSWMO 2007, ODEQ 2011). Land application is practiced more frequently in the northeastern US (at
a rate of approximately 80% generation); in contrast, the Southeastern US practices land application at only
about 10% and the Midwest at about 33% (Vance 1996, Risse 2010). Although practiced on a more limited
scale, wood ash may also be composted with sewage sludge, practiced at a rate of about 5% in the
northeastern US (Spokas 2010). Additional uses for this material include as an ingredient in concrete
manufacture (due to potential pozzolanic properties) and as alternative daily or intermediate cover in
landfills (Naik 2001, ODEQ 2011).
The presence of CCA-treated wood has been recognized as a major issue with CDD wood waste combustion
(Cochran 2006). Incinerated CCA-treated wood can produce ash with heavy metal concentrations that
exceed toxicity characteristic hazardous waste limits (Solo-Gabriele et al. 2002). In batch leaching tests
(TCLP, SPLP) performed by Solo-Gabriele et al. (2002), wood ash produced from mixed wood waste with
only 5% CCA-treated wood (by mass) caused consistent exceedance of toxicity limits for arsenic and
intermittent exceedances for chromium. For ash resulting from the combustion of CCA-treated wood
retaining high levels of preservative, heavy metals represented up to 36% (by weight) of the resulting ash.
Regulations related to beneficial use of wood ash reflect concerns over the presence of treated wood
combustion ash. For example, Florida allows the land application of wood ash provided it was not produced
from combustion of treated or painted wood (FDEP 2002).
6-19
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Multimedia Environmental Assessment Section 6 - Wood
Wood ash composition and characteristics (e.g., leaching behavior, reactivity) can vary significantly,
depending on the temperature of the system and the characteristics and degree of contaminants in the fuel
wood (Jenkins et al. 1998). Several studies have examined the chemical characteristics and the wood ash
effects on plant growth as well as total metals extractable under variably acidic conditions (Zhan et al. 1994,
Demeyer et al. 2001, Norstrom et al. 2012). Other researchers in the US have examined ash leaching using
deionized water, ammonium citrate, and humic and fulvic acids as extraction fluids (Erich 1991, Clapham
and Zibilske 1992, Chirenje et al. 2002). Except for the limited testing performed by Solo-Gabriele et al.
(2002), leaching data from wood ash in conditions simulating precipitation exposure or a landfill
environment were not found in the literature.
Table 6-13 through Table 6-17 present the proposed LCI datasets for untreated or treated wood (provided
at different treatment levels) ash in both CDD and MSW landfill environments based on the data reported
by Solo-Gabriele et al. (2002); the SPLP results (used to simulate wood ash placed in a CDD landfill) and
TCLP results (used to simulate wood ash placed in an MSW landfill) were derived from leaching tests
performed on seven ash samples. It was assumed that treated-wood-derived ash would be disposed of in a
lined cell (MSW landfill) and not in an unlined landfill (CDD landfill). These samples included ash from
untreated wood (southern yellow pine) (one sample), ash from pre-consumer CCA-treated wood (three
samples, each with a different treatment level), and ash produced from recycled wood recovered from CDD
processing facilities (three samples, each recovered from a different facility). The SPLP and TCLP leaching
results from the ash samples produced from the combustion of the recycled wood recovered from the three
CDD processing facilities were each averaged to respectively provide the leaching LCI data presented in
Table 6-15 through Table 6-17. Only copper, chromium, and arsenic leaching results were provided in this
study. The expected leachable concentrations of non-metal organics and inorganics are unknown; however,
the total and leachable ash concentrations of these parameters as published in other studies (as listed above)
suggest that detectable concentrations of numerous other parameters (e.g. calcium, manganese, iron) may
be encountered if analyzed. Wood ash derived from untreated CDD wood did not show detectable leached
concentrations of any of the three metals. The only environmental burdens included in the proposed LCI
which represents the placement of untreated wood at a CDD or MSW landfill would be those associated
with landfill construction, operations, and closure/post-closure care. The liquids emissions presented for
MSW landfill disposal represent the emissions with untreated leachate. Leachate from lined landfills is
typically collected and treated during active landfill operation, closure, and post-closure care prior to
discharge into the environment.
The proposed datasets for placing ash in a CDD landfill may be used to simulate the land application of
wood ash if the flows associated with landfilling and cover soil are removed. Except for untreated wood
ash, all contaminants measurements below the detection limit were analyzed at the detection limit for
dataset development purposes. The nationwide average distance between wood combustion and
CDD/MSW landfills was not found; a distance of 20 km was assumed. For estimating the amount of landfill
cover soil required, a bulk wood ash density of 702 kg/m3 was assumed (Huang et al. 1992).
6-20
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Multimedia Environmental Assessment
Section 6 - Wood
Table 6-13. Proposed LCI Dataset: Untreated Waste Wood Ash, at Unlined CDD Landfill
Input Flow
Wood ash, from combustion
Cover soil, from offsite source
CDD landfill operations
Truck transport, class 8, heavy
heavy-duty (HHD), diesel,
short-haul, load factor 0.75
Output Flow
Untreated waste wood ash, at
unlined CDD landfill
Source
See Chapter 2
See Chapter 2
Assumed
Source
Category
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Category
Construction and Demolition
Debris Management
Unit
kg
kg
kg
t*km
Unit
kg
Amount
1
0.0271
1
0.001*20
Amount
;
Table 6-14. Proposed LCI Dataset: Untreated Waste Wood Ash, at MSW Landfill
Input Flow
Wood ash, from combustion
Cover soil, at MSW landfill
stockpile
MSW landfill construction, for
CDD materials
MSW landfill operations
MSW landfill closure and
post-closure, for CDD
materials
Truck transport, class 8, heavy
heavy-duty (HHD), diesel,
short-haul, load factor 0.75
Output Flow
Untreated waste wood ash, at
MSW landfill
Source
See Chapter 2
See Chapter 2
See Chapter 2
See Chapter 2
Assumed
Source
Category
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Category
Construction and Demolition
Debris Management
Unit
kg
kg
kg
kg
kg
t*km
Unit
kg
Amount
1
0.190
1
1
1
0.001*20
Amount
;
Table 6-15. Proposed LCI Dataset: CCA-Treated Wood Ash, 4 kg/m3 CCA Retention Level, at
MSW Landfill
Input Flow
Wood ash, from combustion
Cover soil, at MSW landfill
stockpile
MSW landfill construction, for
CDD materials
MSW landfill operations
Source
See Chapter 2
See Chapter 2
See Chapter 2
Category
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Unit
kg
kg
kg
kg
Amount
1
0.190
1
1
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Multimedia Environmental Assessment
Section 6 - Wood
MSW landfill closure and
post-closure, for CDD
materials
Truck transport, class 8, heavy
heavy-duty (HHD), diesel,
short-haul, load factor 0.75
Output Flow
Arsenic
Chromium
Copper
Wood ash, CCA 4 kg/m3, at
MSW landfill
See Chapter 2
Assumed
Source
Solo-Gabriele et al.
(2002)
Solo-Gabriele et al.
(2002)
Solo-Gabriele et al.
(2002)
Construction and Demolition
Debris Management
Category
water/groundwater
water/groundwater
water/groundwater
Construction and Demolition
Debris Management
kg
t*km
Unit
mg
mg
mg
kg
1
0.001*20
Amount
1010
120
11
;
Table 6-16. Proposed LCI Dataset: CCA-Treated Wood Ash, 9.6 kg/m3 CCA Retention Level, at
MSW Landfill
Input Flow
Wood ash, from combustion
Cover soil, at MSW landfill
stockpile
MSW landfill construction,
for CDD materials
MSW landfill operations
MSW landfill closure and
post-closure, for CDD
materials
Truck transport, class 8, heavy
heavy-duty (HHD), diesel,
short-haul, load factor 0.75
Output Flow
Arsenic
Chromium
Copper
Wood ash, CCA 9. 6 kg/m3, at
MSW landfill
Source
See Chapter 2
See Chapter 2
See Chapter 2
See Chapter 2
Assumed
Source
Solo-Gabriele et al.
(2002)
Solo-Gabriele et al.
(2002)
Solo-Gabriele et al.
(2002)
Category
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Category
water/groundwater
water/groundwater
water/groundwater
Construction and Demolition
Debris Management
Unit
kg
kg
kg
kg
kg
t*km
Unit
mg
mg
mg
kg
Amount
1
0.190
1
1
1
0.001*20
Amount
2660
2
296
;
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Multimedia Environmental Assessment
Section 6 - Wood
Table 6-17. Proposed LCI Dataset: CCA-Treated Wood Ash, 40 kg/m3 CCA Retention Level, at
MSW Landfill
Input Flow
Wood ash, from combustion
Cover soil, at MSW landfill
stockpile
MSW landfill construction, for
CDD materials
MSW landfill operations
MSW landfill closure and
post-closure, for CDD
materials
Truck transport, class 8, heavy
heavy-duty (HHD), diesel,
short-haul, load factor 0.75
Output Flow
Arsenic
Chromium
Copper
Wood ash, CCA 40 kg/m3, at
MSW landfill
Source
See Chapter 2
See Chapter 2
See Chapter 2
See Chapter 2
Assumed
Source
Solo-Gabriele et al.
(2002)
Solo-Gabriele et al.
(2002)
Solo-Gabriele et al.
(2002)
Category
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Category
water/groundwater
water/groundwater
water/groundwater
Construction and Demolition
Debris Management
Unit
kg
kg
kg
kg
kg
t*km
Unit
mg
mg
mg
kg
Amount
1
0.190
1
1
1
0.001*20
Amount
10200
37.6
236
;
S.8 Data Gap analysis and Opportunities for Additional LCI Data
Table 6-18 summarizes the type of data presented by various sources reviewed for compilation of wood
products EOL management LCI. Several LCA models (e.g., WARM, MSW-DST) and LCI databases (US
LCI, US EPA LCI) provide data with respect to US-based processes. Some sources used data from the other
sources. For example, the US EPA (2012) used data from the NREL database and Cochran (2006). As
shown in the table, many sources present only part of the data/information needed for LCI compilation.
For example, WARM presents only GHG emissions and uses emissions only associated fuel consumption
in equipment to estimate landfill emission factor. Similarly, Ecoinvent only has partial landfill leachate
emissions data because leachate from inert materials landfills are not considered.
A majority of LCI information available on wood products pertains to the manufacturing aspects of the life
cycle. Only limited EOL-specific LCI are available. Based on a review of the available information, the
following data gaps were identified that, if collected, would allow for a more comprehensive LCI dataset
for wood products EOL management:
1. Data pertaining to CDD wood EOL management practices. Only a few studies that attempted
to assess CDD wood EOL management practices were identified; these studies estimated wood
management practices based on either verbal survey or material flow analysis. As these data are
of interest to multiple governmental agencies (e.g., US EPA, USDA, state environmental agencies),
an opportunity for collaborative research exists to quantify current practices of wood management
in the EOL phase.
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Multimedia Environmental Assessment Section 6 - Wood
2. Long-term leachable emissions from wood products placed in a landfill. As described earlier,
the liquid emissions presented in this study are based on SPLP and TCLP tests, which simulate
leaching from synthetic rainwater or an aggressive MSW landfill environment, respectively.
Moreover, the batch leaching data used for estimating liquid emissions correspond to an L:S ratio
of 20 and, therefore, do not represent complete liquid emission. In addition, leaching data of only
certain chemical constituents are reported in literature. For example, studies evaluating leaching
from CCA wood primarily reported copper, chromium, and arsenic data. Furthermore, the
standardized leaching tests simulate leaching associated with physical and chemical mechanisms
and do not simulate leaching associated with biological decomposition of wood due to the short
duration of these tests (18 hours). As wood products are typically disposed of with other discarded
materials and not disposed of in a monofill, field-scale leachate quality data specific to wood
products disposal in landfill are rare and probably would not be available in the future. The liquids
emissions from wood products placement in landfills would therefore need to be based on
laboratory-scale studies. Future research should consider assessment of leaching of a larger suite
of chemicals over a greater L:S ratio and those associated with biological decomposition.
3. Long-term gaseous emissions from wood biodegradation in landfill. The data reported for
branches were used as a proxy for estimating gaseous emission from anaerobic biodegradation of
wood production disposed of in landfills due to lack of CDD wood-specific data. Moreover, the
emission of two compounds (methane and carbon dioxide) are included in the proposed LCI for
landfill disposal of wood products. Future research should consider quantification of a larger suite
of gaseous emission from dimensional as well as different engineered wood products to assess the
impact of resins on gaseous emissions.
4. Materials and energy input and emission from discarded wood products processing. The
wood products processing LCI presented in this report are based on the energy requirements
reported by one data source (Cochran 2006). Cochran (2006) identified the energy requirement of
CDD wood processing based on a survey of a few equipment manufacturers. Some of the data (e.g.,
consumables, fuel and electricity usage, water consumption, material throughput) tracked by the
facility owner from a financial accounting perspective can be readily used for developing more
comprehensive LCI for wood processing. The process non-energy emission (e.g., particulate
matter emission into the atmosphere and liquids emission from short-term wood stockpile to water)
are not included in the proposed LCI due to the lack of these data. Future research should consider
collecting and compiling these data.
5. Wood combustion ash. Numerous studies characterized wood residue ash to assess its benefits as
a soil amendment (e.g., as lime substitute). Leaching data (SPLP, TCLP), however, are lacking to
assess liquids emission for untreated wood ash land-application or disposal scenarios. Only limited
leaching data are available for CCA-treated wood ash. Future research should consider quantifying
leaching emission of a wider suite of chemicals and for greater L:S ratio from wood ash (untreated
as well as treated) for land application and various disposal scenarios.
6. Environmental Impact of emerging wood preservation chemicals. Although the phase out of
certain treatment chemicals (CCA) has occurred, future research efforts should consider assessing
the impacts of emerging treatment preservatives such as nano-zinc oxide (Clausen et al. 2010).
6-24
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Multimedia Environmental Assessment
Section 6 - Wood
Table 6-18. Overview of Wood Product Specific LCI Data Available
Process
Dimensional Lumber
manufacturing
WPM- Engineered Wood
Production
WPM- Ancillary Materials
(e.g., CCA)
EOL Product Removal
Landfill Construction &
Operation
Landfill Leachate Emissions
Landfill Gas Emissions
Wood Processing
Mulch-Liquids Emission from
Land Application
Untreated Wood Combustion-
Air Emission
Treated Wood Combustion-
Air Emission
Untreated Wood Combustion
Ash-Liquids Emissions
Treated Wood Combustion
Ash- Liquids Emission
AP
-42
X
X
Cochran
(2006)
X
X
US
EPA
WAR
M
P
P
MSW-
DST
X
X
us
EPA/
NREL
X
X
P
Jang
(2000)
X
X
Dubey
etal.
(2010)
X
Solo-
Gabriele
etal.
(2001)
X
6.9 References
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Cochran, K., Townsend, T., Reinhart, D., Heck, H. (2007). Estimation of Regional Building-Related C&D
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De La Cruz, F.B., Barlaz, M.A. (2010). Estimation of Waste Component-Specific Landfill Decay Rates
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Denhart, H. (2010). Deconstructing Disaster: Economic and Environmental Impacts of Deconstruction in
Post-Katrina New Orleans. Resources, Conservation, and Recycling, 54, 194-204.
Doka, G. (2009). Life Cycle Inventories for Waste Treatment Services, Part V: Building Material Disposal.
Ecoinvent Report No. 13, Swiss Centre for Life Cycle Inventories, Dubendorf. December 2009.
Dubey, B.K. (2005). Comparison of Environmental Impacts of Wood Treated with Chromated Copper
Arsenate (CCA) and Three Diffeent Arsenic-Free Preservatives. Ph.D. Dissertation, University of
Florida, Gainesville, FL, USA.
Dubey, B., Townsend, T., Solo-Gabriele, H., Bitton, G. (2007). Impact of Surface Water Conditions on
Preservative Leaching and Aquatic Toxicity from Treated Wood Products. Environmental Science
& Technology, 41, 3781-3786.
Dubey, B., Townsend, T., Solo-Gabriele, H. (2010). Metal Loss from Treated Wood Products in Contact
with Municipal Solid Waste Landfill Leachate. Journal of Hazardous Materials, 175, 558-568.
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of Arsenic, Chromium, and Copper from Weathered Treated Wood. Environmental Pollution, 158,
1479-1486.
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Building Deconstruction- A Case Study for Southeast Germany. Resources, Conservation and
Recycling, 78, 81-91.
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Disposed in Landfills and Life-Cycle Trade-Offs with Waste-to-Energy and MSW Landfill
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Jang, Y. (2000). A Study of Construction and Demolition Waste Leachate From Laboratory Landfill
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Lebow, S., Brooks, K., Simonsen, J. (2002). Environmental Impact of Treated Wood in Service.
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Multimedia Environmental Assessment Section 6 - Wood
McKeever, D. (2004). Woody Residues and Solid Waste Wood Available for Recovery in the United States,
2002. USDA Forest Service, Forest Products Laboratory.
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Mitsuhashi, J., Love, C.S., Freitag, C., Morrell, J.J. (2007). Migration of Boron from Douglas-Fir Lumber
Subjected to Simulated Rainfall. Forest Products Journal, 57 (12), 52-57.
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Multimedia Environmental Assessment Section 6 - Wood
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Multimedia Environmental Assessment
Section 7 - Land Clearing Debris
7 Land Clearing Debris
7,1 Introduction
LCD is comprised of tree tops, branches, and stumps and can also include materials such as soil, rocks, and
shrubs resulting from vegetation removal for building/infrastructure construction and land development
(US EPA 2011). According to a study conducted in Canada, approximately 97% of non-merchantable LCD
is comprised of non-foliage woody material (PGEC 1997). The moisture content of LCD is typically greater
than that of other wood sources (e.g., dimensional lumber, plywood) in CDD, estimated at approximately
50% (wet basis) (Maker 1994, US EPA 2003, Tumuluru et al. 2011).
Estimates of LCD production are difficult because this category of materials is often excluded from
regulation as a solid waste. US EPA (2014) found that states representing approximately 65% of the U.S.
population either did not include LCD in the definition of CDD or exempted LCD from solid waste
regulations altogether. Wiltsee (1998) indicated difficulty with estimating LCD quantities because the
major management approaches for LCD (which includes chipping on-site and burning without energy
recovery) often do not involve any mass or volume estimates.
Figure 7-1 identifies the flow of materials and processes that should be considered for conducting an LCA
of LCD EOL management. LCD is most commonly disposed of onsite (at the site of generation) through
burning, but also may be disposed of offsite at a landfill (Wiltsee 1998). LCD is typically processed (e.g.
chipped, ground-up, screened) prior to use in a recycling applications such as mulch production, compost,
or combustion with energy recovery. Although wood in LCD can be used for wood product manufacturing,
this is not a common practice. This EOL management option of LCD is, therefore, not discussed further in
this report.
Land Clearing
Debris (LCD)
Landfilling
LCD Processing
On-site Burning
Mulch Use
Composting
Combustion with
Energy Recovery
High Value
Wood Products
Ash Agricultural
Use/Soil
Amendment
Ash Landfilling
Figure 7-1. Material Flows for LCD and EOL Phase Management
7.2 EOL Management
Based on a survey of LCD contractors, Wiltsee (1998) found that the most common method of LCD EOL
management is on-site burning of LCD materials. Air emissions and liquids emission from combustion ash
are the primary environmental concerns with burning LCD. LCD, depending on state regulations, may be
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Section 7 - Land Clearing Debris
disposed of in a designated LCD, inert waste, CDD, and MSW landfills that accept LCD. LCD can be used
for mulch production, compost production, and biomass fuel. These management options typically require
size reducing the debris with a chipper or grinder. Based on a survey of 180 wood collection and processing
facilities in 14 counties in Michigan, Nzokou et al. (2011) reported that LCD constituted 61% of the total
amount processed by these facilities, and mulch, wood chips, firewood, and industrial fuel were the top four
types of recycling products produced at the processing facilities; these materials made up approximately
94% of the recycled products with mulch and chips comprising 42% and 38.6% of all the recycled products,
respectively. A nationwide estimate of the quantities of LCD managed with these EOL options is not
available.
The emissions associated with composting include gaseous and liquids emissions associated with biological
decomposition of LCD. The beneficial uses of compost as a soil amendment include rebuilding the structure
of organically-depleted soils, enhancing moisture retention of existent soils, supplanting chemical fertilizer
use by supplying depleted nutrients, mitigating pathogens and weed seeds, and remediating/treating
contaminated soils (US EPA 1989, Haug 1993).
Chipped LCD can also be used in a boiler for energy recovery. The US EPA (2003) provides a range of
heating values for different wood residues (including hogged wood, bark, and chips) on a "wet, as-fired"
basis and a dry wood basis as, respectively, 4,500 Btu/lb and 8,000 Btu/lb, with the moisture content of as-
fired wood being typically 50% and ranging from 5% to 75% depending on the type of residue and storage
techniques.
Table 7-1 lists the processes that should be considered for an LCA of EOL management of LCD. The
emissions associated with both energy and materials requirements and process non-energy emissions (e.g.,
fugitive dust, liquid emissions associated with disposal in a landfill) should be considered for LCA.
Table 7-1. LCD EOL Management Process Descriptions and Considerations for LCA
Process
On-site burning
Landfill Disposal
LCD Use as Mulch
LCD Use as Compost
LCD Combustion for
Energy Recovery
Description and LCA Considerations
Open burning and air curtain incinerators (ACI) are two approaches
associated with burning LCD at its site of generation. The emissions
related to the preparation of LCD for combustion, air emissions from
combustion and the long-term liquids emission from combustion ash.
Emissions with the materials (e.g., equipment, soil, water) and energy
(fuel, electricity) inputs for placement and compaction of LCD in a
landfill along with process non-energy emissions (e.g., dust emissions
from equipment operation and liquids emission associated with
biogeochemical degradation of LCD in a landfill).
Emissions associated with grinding and land application, as well as
those from leaching due to exposure to precipitation.
Process energy and non-energy emissions associated with LCD and
compost processing and handling as well as long-term liquids emission
from land-applied compost.
Air emission from LCD processing and combustion as well as those
associated with management of combustion ash.
7.3 LCI Sources
Peer-reviewed literature, government and private industry publications, and various LCA modeling tools
were reviewed to identify available LCI datasets pertaining to LCD EOL management processes. Table 7-
2 presents a list of data sources reviewed to develop the LCI presented in this chapter. If LCI data were not
available, process metadata and documentation (e.g., included emission categories, background data used
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Section 7 - Land Clearing Debris
to compile the dataset, geographic location, and time period of the data) were reviewed to evaluate the
completeness of the dataset. If available, the primary sources of information used to develop the LCI
datasets and information were reviewed.
Table 7-2. List of Sources Reviewed for LCI Data
LCI Source
US LCI (20 12)
Cochran (2006)
Springsteen et
al. (2011)
WARM
AP-42 (US
EPA 1996,
2002, 2003)
MSW-DST
Ecoinvent
WRATE
EASETECH
Komilis and
Ham (2004)
Lutes and
Kariher(1997)
Description
NREL published an LCI database that includes datasets for a wide variety of
services and material, component and assembly production processes within the
United States.
Cochran (2006) presented diesel energy requirements for C&D wood grinding
equipment based on a survey of equipment manufacturers.
Springsteen et al. (201 1) compiled air emissions for open pile burning, wood
grinding to produce biomass, biomass transport and combustion in boilers along
with energy requirement for biomass production. These data were used to
quantify air emission reduction achieved with use of LCD as biomass fuel over
open burning for a demonstration project.
WARM presents data on GHG emissions associated with transport, landfilling
(i.e., collection and placement), combustion, and composting of organics.
Provides air emissions data for trench air curtain burning, wood chipping, and
combusting wood residue in boilers.
Provides details on composting LCI on processing of yard waste at a composting
facility and emissions from land-applying compost.
Ecoinvent is an LCI database developed by the Swiss Centre for Life Cycle
Inventories which includes specific processes related to the EOL management of
numerous individual materials. It includes inventories related to the windrow
composting of biogenic waste.
Presents LCI data specific to the UK for wood chipping C&D wood materials
and composting of yard waste.
Simulates the emissions associated with enclosed windrow composting based on
US -specific input data (Komilis and Ham 2004).
Komilis and Ham (2004) present US LCI data for solid waste composting and
provide compost equipment fuel consumption data.
The authors present VOC, SVOC, PAH, and criteria air pollutant emission data
from burning LCD with and without an air blower.
7,4 LCI Related to On-site Burning
An estimate of the amount of LCD disposed of in the US is not available, but it has been reported that most
LCD wood is disposed of at the site of generation. Open burning is one method of LCD disposal; the debris
is typically heaped in piles or placed in pits and burned in the absence of emission control devices. As open
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Multimedia Environmental Assessment Section 7 - Land Clearing Debris
burning is typically regulated at the state or local level in the US, the emission control requirements and,
therefore, emission would depend on location (ERGI2001).
Combusting LCD using an air curtain incinerator (ACI) is another management approach of LCD at the
point of generation. In this case an air blower blows air into the burning debris to enhance combustion,
speeding up the combustion process and ideally reducing emissions by achieving more complete
combustion. There are two general types of ACIs; a trench ACI is comprised of a mobile air blowing
system that is placed along a constructed trench that contains debris and blows air into the trench; another
ACI option is a self-contained firebox ACI unit. For the above-ground firebox units, the debris is placed
in the firebox, ignited, and the air blower circulates air into the container.
The emissions from burning LCD at its site of generation include those associated with materials and energy
input as well as process non-energy emissions released during the preparation of the LCD for combustion
and the combustion of LCD. LCI were developed for the on-site burning of LCD through open burning and
the use of a firebox ACI. In open burning and ACI scenarios, equipment is needed to arrange the LCD into
piles in preparation for burning in the case of open burning or to load the ACI firebox. Cochran (2006)
discusses energy consumption for the use of a loader and excavator used to move CDD wood and load a
grinder, 11.6 and 0.9 MJ/Mg respectively, at a CDD recycling facility. The fuel consumption for the loader
from Cochran (2006) was used as a proxy for moving LCD into piles for open burning (as shown in Table
7-3).
The excavator loading data from Springsteen et al. (2011) were used as a proxy for the fuel consumption
for loading LCD into the ACI firebox for combustion (as shown in Table 7-4). Springsteen et al. (2011)
documented the average fuel consumption for loading woody biomass into a grinder as 0.79 L of diesel fuel
per MT of green material. Operating the blower system of an ACI firebox will also require energy usage.
Air Burners's model S-327 ACI specifications were used to approximate the average fuel consumption for
a firebox ACI, and was calculated as 1.83 L of diesel fuel per MT of material to be burned (Air Burners
2012). The total diesel consumption for loading and combustion in an ACI was, therefore, estimated to be
2.62 L per MT of LCD.
Springsteen et al. (2011) presented emission factors for nitrogen oxides, particulate matter, non-methane
organic compounds (NMOC), carbon monoxide, and methane based on numerous references, including US
EPA's AP-42 sections on open burning and wildfires and prescribed burning, laboratory studies, pilot, and
full-scale studies on conifer (cone bearing trees) biomass. In the absence of emissions for carbon dioxide
and methane for burning LCD in an ACI, the open burning emissions were used as a proxy. Emissions for
SVOCs, VOCs, PAHs, and criteria pollutants were collected by Lutes and Kariher (1997) in pilot-scale
tests on LCD from two states in the US (Florida and Tennessee). The results from the burning tests (for
which greater than half of the data were above the level of detection) were averaged and incorporated into
the LCI tables for open burning and ACI air emissions. For data readings below the level of detection, the
detection limit was used for the average estimation. US EPA (1996) AP-42 provided estimates of burning
wood in a trench ACI. Therefore, sulfur dioxide and nitrogen oxides in the ACI scenario from the US EPA
(1996) were used. Table 7-3 and Table 7-4 present the proposed LCI datasets for the open burning and air
curtain incineration of LCD, respectively. Because LCD incineration frequently occurs at the site of
generation and in the absence of additional information, no LCD transportation is included in the LCI
datasets presented.
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Table 7-3. Proposed LCI Dataset: Land Clearing Debris, Open Burning
Input Flow
Land clearing debris
Diesel, combusted in
industrial equipment
Output Flow
Land clearing debris,
at open burning
Carbon dioxide
(biogenic)
Carbon monoxide
Methane
Nitrogen oxides
Particulates, > 2.5 um
and < 10 |rni
Particulates, < 2.5 |jm
Chloromethane
1,3 -butadiene
Acetone
Methylene chloride
Cis-1,2-
dichloroethene
2-butanone
Ethyl acetate
Benzene
Octane
Toluene
Ethyl benzene
m,p-Xylene
o-Xylene
Styrene
Pinene
4-ethyltoluene
1,3,5-
trimethylbenzene
1,2,4-
trimethylbenzene
Limonene
Undecane
Naphthalene
Source
Cochran (2006)
Source
Springsteen et al. (201 1)
Springsteen et al. (201 1)
Springsteen et al. (201 1)
Springsteen et al. (201 1)
Springsteen et al. (2011)
Springsteen et al. (201 1)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Category
Construction and
Demolition Debris
Management
Category
Construction and
Demolition Debris
Management
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Units
kg
L
Units
kg
g
g
g
g
g
g
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
Amount
1
0.0003
Amount
;
917
31.50
1.50
1.50
2.25
7.62
50
102
179
3.00
20.5
33.5
33.5
265
5.50
150
24
55.8
15.0
50.8
48.8
17.3
3.50
11.8
46.8
3.50
53.5
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Section 7 - Land Clearing Debris
Table 7-4. Land Clearing Debris, at Air Curtain Incineration
Input Flow
Land clearing debris
Diesel, combusted in
industrial equipment
Output Flow
Land clearing debris, at
air curtain incineration
Carbon dioxide
Carbon monoxide
Methane
Nitrogen oxides
Particulates, > 2.5 um and
Particulates, < 2.5 |im
Sulfur dioxide
Chloromethane
1,3 -butadiene
Acetone
Cis- 1 ,2 -dichloroethene
2-butanone
Ethyl acetate
Benzene
Octane
Toluene
Ethyl benzene
M,p-xylene
O-xylene
Styrene
Pinene
4-ethyltoluene
1,3,5 -trimethylbenzene
1 ,2,4-trimethylbenzene
Limonene
Benzyl chloride
Undecane
Dodecane
Naphthalene
Source
Springsteen et al. (2011)
and Air Burners (2012)
Source
Springsteen et al. (201 1)
Lutes and Kariner (1997)
Springsteen et al. (201 1)
US EPA (1996)
Springsteen et al. (201 1)
Springsteen et al. (201 1)
US EPA (1996)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Lutes and Kariner (1997)
Category
Construction and
Demolition Debris
Management
Category
Construction and
Demolition Debris
Management
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Air
Units
kg
L
Units
kg
g
mg
g
g
g
g
g
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
mg
Amount
1
0.00262
Amount
(wet basis)
;
917
12.00
1.5
2.00
0.330
10.2
0.05
4.50
138
152
20.5
24.5
24.5
272
3.00
189
31.0
119
18.0
72.5
102
39.0
4.50
20.0
71.5
2.50
4.00
3.00
47.5
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7.5 LCI Related to Landfill Disposal
Emissions associated with LCD disposal in a landfill include air emissions from equipment used for placing
LCD in the landfill, emissions associated with landfill construction and operation, and liquids and gaseous
emissions from material decomposition in the landfill. The potential for leachate and landfill gas release to
the environment depends on the biogeochemical environment of the landfill and the environmental controls,
as discussed in Chapter 2. There are various sources that provide landfilling emission factors related to
equipment usage and landfill construction and operation; however, none are specific to LCD landfilling.
Generalized landfill construction and operations LCI data are also presented in Chapter 2.
The primary constituent in LCD is wood, and as discussed in Chapter 6, due to its organic nature, the decay
of wood wastes in an anaerobic (i.e., oxygen poor) environment produces methane, which may be collected
by a GCCS and converted to biogenic carbon dioxide via flaring or energy conversion technology, if the
landfill has a GCCS present. LCD exposure to precipitation or other liquids (e.g., landfill leachate) is also
expected to result in chemical leaching and the emissions are expected to depend on biogeochemical
environment (e.g., MSW landfill, CDD landfill). Details on the gaseous emissions produced from
decomposition and leachable emissions of untreated wood are presented in Chapter 6.
The emissions from wood decomposition and leaching, energy consumption data from landfill operations,
estimated cover soil demand, and an assumed transport distance were used to develop an LCI process
dataset for the disposal of LCD at an unlined CDD or inert debris landfill, as presented in Table 7-5. The
gaseous and liquid emissions were developed based on the untreated wood waste LCI developed in Chapter
6, but were adjusted for the greater moisture content of LCD. Moisture content of wood used by Jang
(2000), Townsend et al. (1999) was assumed to be 10% and amoisture content of 50% was used for LCD;
the methane and carbon dioxide emission for wood products disposal in landfills (presented in Chapter 6)
are based on a moisture content of 10%. Additional information on how methane and carbon dioxide
emissions were estimated for the landfill disposal of LCD can be found in Section 2.5.10.8. The energy
use and the associated emissions from landfill operation (e.g., waste placement, compaction) include diesel
use in heavy equipment and electricity use in landfill buildings (e.g., administrative buildings, workshop);
calculations detailing these emissions and the method of estimating the quantity of cover soil use are also
included in Chapter 2 of this report. Diesel consumption from landfill operations and electricity
consumption from landfill administrative offices and workshop areas were estimated from Ecobalance
(1999) and IWCS (2014b), respectively. In the absence of nation-wide average transport data, it was
assumed that LCD would be transported 20 km for landfill disposal. For the purpose of estimating cover
soil requirements for the disposal of LCD at an unlined CDD landfill, the density of LCD was estimated
from the bulk density of unprocessed forest product fuel wood, as provided Angus-Hankin et al. (1995). It
should be noted that inert debris or LCD landfills may not have a cover soil requirement.
Table 7-5. Proposed LCI Dataset: Land Clearing Debris, at Unlined CDD Landfill
Input Flow
Land clearing debris
Truck transport, class 8,
heavy heavy-duty
(HHD), diesel, short-
haul, load factor 0.75
CDD landfill operations
Cover soil, from offsite
source
Source
Assumed
Category
Construction and Demolition Debris
Management
Construction and Demolition Debris
Management
Construction and Demolition Debris
Management
Units
kg
t*km
kg
kg
Amount
1
0.001*20
1
0.141
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Section 7 - Land Clearing Debris
Output Flow
Land clearing debris, at
unlined CDD landfill
Methane
Carbon Dioxide
Chloride
Calcium
COD
Potassium
Manganese
Magnesium
Carbonate
Sodium
Source
US EPA (20 12)
US EPA (20 12)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Townsend et al.
(1999)
Townsend et al.
(1999)
Townsend et al.
(1999)
Category
Construction and Demolition Debris
Management
Air/Unspecified
Air/Unspecified
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Units
kg
kg
kg
mg
mg
mg
mg
mg
mg
mg
mg
Amount (wet
basis)
;
0.036
0.12
41.1
13.3
1330
23.3
1.22
16.1
3.39
4.17
7.6 LCI Related to Recycling
7.6.1 LCD Used as Mulch
LCD recycling generally involves processing (i.e., chipping/grinding) prior to use as boiler fuel, mulch, or
other end uses and can occur at the site of LCD generation, mobile equipment, or LCD can be transported
to a larger processing facility. The LCI information provided in this section incorporates the transportation
of LCD to a large processing facility to produce mulch. Processing of LCD in preparation for mulch
production typically involves loading and operating a grinder. Horizontal grinders or tub grinders can be
used for grinding vegetative debris. Horizontal grinders are better equipped to handle debris such as tall
trees that may be pre-organized prior to being fed into the grinder. Tub grinders, although they can process
materials wider in diameter such as tree stumps, root balls, and brushy debris, require long trees to be cut
to fit into the tub of the grinder (ESEI 2014). Land clearing applications often involve removing and
processing large trees; therefore, a horizontal grinder was the grinding equipment used in the LCD
processing LCI presented in Table 7-6.
The emissions from processing LCD include those associated with materials and energy (e.g., transportation
and equipment fuel) input as well as process non-energy emission released during grinding/chipping and
storing the processed materials. Springsteen et al. (2011) documented the average fuel consumption for
grinding woody biomass. The biomass was generated from a prescribed tree thinning in California and
included only non-merchantable forest debris. The consumption estimates provided by Springsteen et al.
(2011) for loading debris into the grinding with an excavator and grinding the material with a horizontal
grinder were 0.79 and 2.92 L of diesel fuel per MT of green material; other studies have reported similar
grinder fuel usage (Jones et al. 2010 and Pan et al. 2008).
The process non-energy-related emissions from LCD grinding include particulate matter emission and
liquid emission from wood/wood chip stockpiles. AP-42 presents air emission factors for a log chipping
operation as a part of an MDF manufacturing operation. These data can be used as a proxy for an LCD
wood grinding operation until measurements from operating facilities become available. However, it
appears that unlike LCD/CDD processing facilities, engineering controls such as a cyclone and/or fabric
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Section 7 - Land Clearing Debris
filter collection are implemented to control participate matter emission from chipping operations at MDF
manufacturing facilities. The use of log chipping air emission as a proxy would, therefore, underestimate
particulate matter emission from an LCD wood processing facility.
As the wood decomposition in this scenario would occur under aerobic conditions, gas emission from land
application of mulch were estimated by assuming that 100% of carbon content will decompose to produce
carbon dioxide. Using biogenic carbon content of branches (published by Barlaz 1998) as a proxy for wood
products, approximately 1.63 kg of carbon dioxide (biogenic) would be produced from aerobic
decomposition of 1 kg of wood products; the estimate is based on 0.494 g of carbon content as C per dry
kg of wood product and 0.9 kg of dry wood per kg of wet wood product. The liquids emissions from the
land application of mulch are expected to be the same as those from wood disposal in CDD materials landfill
as leaching is primarily influenced by precipitation. Moisture content of wood used by Jang (2000),
Townsend et al. (1999) was assumed to be 10% and a moisture content of 50% was used for LCD; the
methane and carbon dioxide emission for wood products disposal in landfills (presented in Chapter 6) are
based on a moisture content of 10%.
It was assumed that the LCD wood would be transported 20 km from the job site to the processing facility
and the mulch would be transported 20 km; NREL (2013) provides general transport process LCI and are
further discussed in Chapter 2. Table 7-6 presents proposed LCI for LCD wood grinding to produce mulch
and land application of mulch.
Table 7-6. Proposed LCI Dataset: Ground LCD, Processed and Applied as Mulch
Input Flow
Land clearing debris
Truck transport, class 8,
heavy heavy-duty (HHD),
diesel, short-haul, load
factor 0.75
Diesel, combusted in
industrial equipment
Output Flow
Ground LCD, processed
and applied as mulch
THC as carbon
VOC as propane
Methanol
Carbon Dioxide
Chloride
Calcium
COD
Potassium
Manganese
Magnesium
Carbonate
Sodium
Source
Assumed
Springsteen et al.
(2011)
Source
US EPA (2002)
US EPA (2002)
US EPA (2002)
US EPA (20 12)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Townsend et al.
(1999)
Townsend et al.
(1999)
Townsend et al.
(1999)
Category
Construction and
Demolition Debris
Management
Flows
Category
Construction and
Demolition Debris
Management
Air/Unspecified
Air/Unspecified
Air/Unspecified
Air/Unspecified
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Water/groundwater
Unit
kg
t*km
L
Unit
kg
kg
kg
kg
kg
mg
mg
mg
mg
mg
mg
mg
mg
Amount
1
0.001*20
0.00371
Amount (wet basis)
;
1.03E-06
1.25E-06
2.50E-07
0.906
41.1
13.3
1330
23.3
1.22
16.1
3.39
4.17
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7.6.2 LCD Used as Compost
Since windrows are the most common method by which composting occurs in the US, windrow composting
was the composting scenario evaluated for LCD. The emissions resulting from composting LCD are those
emitted to air from processing the LCD, the gases released during the decomposition of the organic fraction
of LCD, and emissions from leaching of chemicals during land application. LCD emissions during
processing will include those energy consumption and non-fuel emissions from grinding (as was previously
discussed within the mulch production section), those from actively managing the compost, and from post-
composting screening. Since windrow composting is the method evaluated in this report, windrow turners
or other comparable equipment (e.g., front-end loader) are assumed to be used to turn the windrows on a
regular basis during the active composting phase. Once the compost has undergone a period of curing
following active composting, the final compost product is screened to remove any large pieces which can
undergo a second round of grinding and decomposition, or the screening overs can be disposed of. Other
than grinding, it was found there were no processing emissions specific to the composting of LCD; this was
expected due to the known scarcity of LCD tracking.
Although the LCI data presented in Komilis and Ham (2004) is not specific to an LCD composting scenario,
the fuel consumption of composting MSW and yard waste used in the study are used as a proxy for LCD.
The data for estimated diesel consumption for a front-end loader and a windrow turner, both of which could
be used to turn windrows, were estimated to be respectively 0.40 and 0.90 L/MT of MSW [US EPA (1991)
as cited by Komilis and Ham 2004)]. The electrical requirement for a trommel screen, based on the original
data from Diaz et al. (1982) (as cited in Komilis and Ham 2004), to screen out post-composted material
was estimated to be 0.8 kWh/MT feedstock material. A summary of optional compost processing fuel
consumption data is provided in Table 7-7 in units of per kg "LCD."
Table 7-7. Composting Equipment Energy Consumption per Kilogram of LCD
Equipment
Diesel, LCD loading and grinding
Diesel, windrow turner
Diesel, windrow turning with front-
end loader
Electricity, trommel screen
Source
Springsteen
etal. (2011)
US EPA
(1991)
US EPA
(1991)
Diaz et al.
(1982)
Unit
L
L
L
kWh
Amount
0.00371
0.0009
0.0004
0.0008
A lack of available material-specific emissions data for LCD composting was observed for gaseous and
liquid emissions. LCI data for composting LCD in the absence of other more nitrogen-rich waste organic
materials (e.g., yard waste and food waste) were not identified. Wood wastes, such as those in LCD
[estimated to be comprised of approximately 97% non-foliage woody material (PGEC 1997)], are high in
carbon and thus desirable and commonly used for combination with high nitrogen wastes (e.g., food scraps)
as a bulking agent and to create a more nutrient-balanced compost. Since LCD is comprised mostly of
wood, it is expected that the air and liquid emissions released from the composting LCD will be
proportionally similar to those from the composting of wood. There are multiple data resources that provide
gaseous emission estimates for composting; however, these resources are not specific to wood alone, and
there is no way to disaggregate the contribution of wood/LCD to the gaseous emissions data from other
organic materials (Boldrin et al. 2009, CAR 2010, and Komilis and Ham 2004). Therefore, LCI gas
emissions were assumed to be the same as those released from land applying mulch (Table 7-6).
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Multimedia Environmental Assessment Section 7 - Land Clearing Debris
Since compost is generally land applied, similarly to mulching LCD, similar concerns with leaching from
the wood from rainfall are implied. In contrast to CDD wood, LCD is not expected to contain potentially
harmful wood preservation chemicals. Therefore, liquids emissions from land-applying wood mulch are
recommended to be used as a proxy for liquids emissions from LCD compost (Table 7-6).
No LCA modeling tools were identified that included an LCD composting dataset or module. Other organic
materials such as yard waste or food waste were generally designated waste materials that can be assessed
for use in composting in the following LCA modeling tools and sources: WARM, MSW-DST, Ecoinvent,
EASETECH, and WRATE.
7.6.3 LCD Combusted as Boiler Fuel
The two major emissions resulting from the combustion of LCD are those emitted to air and those emitted
as a result of leaching of the ash that remains following combustion. Similar to waste wood, LCD may be
beneficially used as a boiler fuel for energy recovery, where US EPA (2003) estimates an energy content
of approximately 18.6 MJ per kilogram dry wood material. LCD is mainly comprised of woody material;
PGEC (1997) reports that approximately 97% of LCD (by mass) is comprised of non-foliage woody
material; therefore, it is expected that the air emissions released from the combustion of LCD will be
proportionally similar to those from the combustion of dimensional wood. However, emissions from the
combustion of LCD will need to be adjusted for moisture content, which is estimated at 50% (wet basis) as
presented in several sources for woody biomass and "wet" wood materials used as feedstock for boilers
(Maker 1994, US EPA 2003, Tumuluru et al. 2011).
An additional difference associated with the combustion of LCD is the ash fraction of the feedstock
material. The ash content of woody biomass waste as delivered to a power generation facility in California
was found as 2% (dry basis) (Springsteen et al. 2011), which appears to be consistent with the ash content
of tree species presented in Jenkins et al. (1998). A review of government and peer-reviewed literature did
not provide information on leaching emissions from the landfilling or land application of ash from LCD
combustion; however, there have been leaching studies performed on wood ash [e.g., Tolaymat (2003)
performed leaching tests on ash from combusted wood and tires]. In the absence of specific data for LCD,
it is proposed that the untreated wood ash leaching dataset provided in the wood product chapter be used to
simulate emissions associated with disposal of LCD ash in landfills.
The NREL/US EPA LCI database includes a "Combustion, wet wood residue, AP-42" process developed
from US EPA (2003) AP-42 emission factors which simulates wet wood residue combustion in a boiler. It
is recommended that this process dataset be used to model the emissions and energy recovery associated
with the combustion of LCD. However, it is recommended that the process dataset be updated to include
the mass flow input of processed LCD as described elsewhere in this chapter and to include the output mass
flow of ash resulting from the combustion process. This modification would allow the inclusion of this
combustion process dataset in a product system that models the overall emissions associated with this EOL
management of LCD from clearing operations to final deposition of ash.
Additionally, the "Combustion, wet wood residue, AP-42" process does not include processing of the wood
prior to combustion. Woody biomass must first be processed (by chipping or grinding) prior to being
combusted in a boiler, therefore dataset Table 7-8 (adapted from Table 7-6, LCD mulching) is proposed for
estimating the emissions from transporting and grinding LCD prior to combustion.
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Section 7 - Land Clearing Debris
Table 7-8. Proposed LCI Dataset: Ground LCD, at Processing Facility
Input Flow
Land clearing debris
Transport, single unit
truck, short-haul, diesel
powered - US
Diesel, combusted in
industrial equipment
Output Flow
Ground LCD, at
processing
THC as carbon
VOC as propane
Methanol
Source
Assumed
Springsteen et al. (201 1)
Source
US EPA (2002)
US EPA (2002)
US EPA (2002)
Category
Construction and
Demolition Debris
Management
Flows
Category
Construction and
Demolition Debris
Management
Air/Unspecified
Air/Unspecified
Air/Unspecified
Unit
kg
t*km
L
Unit
kg
kg
kg
kg
Amount
1
0.001*20
0.00371
Amount (wet basis)
;
1.03E-06
1.25E-06
2.50E-07
7.7 Data Gap analysis and Opportunities for Additional LCI Data
Table 7-9 summarizes the type of US-based LCI identified from reviewed compilations of LCD EOL
management sources. Most of the data identified are recognized as being partial as these provide only
energy consumption data or emissions from one aspect (e.g., air, water, materials) of EOL management for
LCD. Overall, limited EOL-specific LCI are available for LCD, which is likely a result of limited material
management tracking of LCD. Based on a review of the available information, the following data gaps
were identified for compilation of a more comprehensive LCI dataset for LCD EOL management:
1. Data pertaining to LCD generation and disposal estimates and EOL management practices.
Scarce information is available on the quantities of LCD that are managed in the US, which is likely
due to variable or absent tracking systems at the state and local level; for example, some states
consider LCD as CDD whereas other do not. Thus, evaluating LCD management in the EOL phase
is difficult due to a lack of quantitative data available for LCD. As these data are of interest to
multiple governmental agencies (e.g., US EPA, USDA, state environmental agencies), an
opportunity for collaborative research exist to quantify current practices of LCD management in
the EOL phase.
2. Long-term leachable emissions from LCD products placed in a landfill. As described earlier,
the liquid emission presented in this study are based on SPLP and TCLP tests on untreated wood,
which simulates leaching from disposal in inert debris landfill (or land-application), and MSW
landfill, respectively. The leaching test data of untreated dimensional lumber was used as a proxy
for liquids emission estimate for LCD due to lack of data. Although woody material is the primary
constituent of LCD, other LCD constituents such as leaves, roots, stems, bark may impact liquid
emissions. Moreover, the batch leaching data used for estimating liquid emissions correspond to
L:S ratio of 20 and are, therefore, not representative of complete liquid emission. Furthermore, the
standardized leaching tests simulate leaching associated with physical and chemical mechanisms
and do not simulate leaching associated with biological decomposition of wood due to the short
duration of these tests (18 hours). Future research should consider assessment of leaching over a
greater L: S ratio and those associated with biological decomposition, leaching should also consider
observing for the presence of pesticides or herbicides that may have historically been used to
control insects and vegetation where LCD is generated.
3. Long-term gaseous emission from LCD biodegradation in landfill. The data reported for
branches were used as a proxy for estimating gaseous emission from anaerobic biodegradation of
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Section 7 - Land Clearing Debris
LCD disposed of in landfills due to lack of LCD-specific data. Moreover, the emissions of only
two compounds (methane and carbon dioxide) are included in the proposed LCI for landfill disposal
of wood/LCI products. Future research should consider quantifying a larger suite of gaseous
emission from LCD to assess the impact of large amounts of LCD disposed of in landfills collecting
primarily just LCD materials.
4. Materials and energy input and emission from LCD processing. Emissions from logs chipping
operation for medium density fiberboard (MDF) were used as a proxy for emissions from LCD
grinding. Particulate matter emission, from log grinding for MDF manufacturing, however, were
not detected likely due to air pollution control practices for MDF manufacturing operations. The
proposed LCI for LCD processing does not include particulate matter emission and liquids emission
from short-term LCD stockpile to water due to the lack of these data. Future research should
consider collecting and compiling these data. Some of the data for processing (e.g., consumables,
fuel and electricity usage, water consumption, material throughput) tracked by LCD processing
facility owners from a financial accounting perspective can be readily used for developing more
comprehensive LCI for LCD processing.
5. LCD composting. There is a large body of literature available for composting organics (e.g., yard
waste, food waste). The data pertaining to LCD composting, however, are lacking; yard waste data
were not used as proxy as yard waste composition is significantly different from LCD. Future
research should consider quantifying air and liquid emissions from LCD composting operations.
6. LCD combustion (including onsite LCD burning) ash. Numerous studies characterized wood
residue ash to assess its benefits as soil amendment (e.g., as lime substitute). Leaching data (SPLP),
however, are inadequate to assess nutrients released from land-application of LCD. Future research
should consider quantifying leaching emission from onsite burning and combustion for energy
projects for land application and various disposal scenarios.
7. ACI emissions data for onsite burning of LCD. Research has been conducted on open burning
of LCD and related materials; there have been some studies conducted with ACIs burning woody
materials and one instance of burning LCD (Lutes and Kariher 2004) from which data were
collected which could be developed into emission factors. Although it has been debated that ACIs
likely improve emissions compared to emissions from open burning, little data with respect to LCD,
confirming the effectiveness of ACIs burning LCD. Future research should consider collection and
compilation of these data since burning LCD at the site of LCD generation is still presumed to be
the most commonly used EOL management strategy.
Table 7-9. Overview of LCD Data Available
Process
Onsite Disposal by
Burning
Transport
Landfill Leachate
Landfill Gas Emissions
Mulch Processing and Use
Compost Processing and
Use
Combustion of LCD for
Energy
Ash landfilling
AP-
42
P
P
P
US EPA/
NREL
X
X
Springsteen
et al. (2011)
P
P
Cochran
(2006)
P
Ko mills
and Ham
(2004)
P
Lutes and
Kariher
(1997)
P
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7.8 References
Air Burners (2012). Fire Box Specification S-327. Palm City, Florida, USA.
Angus-Hankin, C., Stokes, B., and Twaddle, A. (1995). The Transportation of Fuelwood from Forest to
Facility. Biomass and Bioenergy, 9(1-5): 191-203.
Barlaz, M.A. (1998). Carbon Storage during Biodegradation of Municipal Solid Waste Components in
Laboratory-scale Landfills. Global Biogeochemical Cycles 12 (2), 373-380.
Boldrin, A., J.K. Andersen, J. Moller, E. Favoino, and T.H. Christensen (2009). Composting and Compost
Utilization: Accounting of Greenhouse Gases and Global Warming Potentials. Waste Management
& Research: 27: 800-812.
CAR (2010). Climate Action Reserve, http://www.climateactionreserve.org/resources/. Accessed 25 July
2014.
Cochran, K.M. (2006). Construction and Demolition Debris Recycling: Methods, Markets, and Policy.
Ph.D. Dissertation, University of Florida, Gainesville, FL, USA.
Ecobalance (1999). Life Cycle Inventory of a Modern Municipal Solid Waste Landfill. A Report Prepared
by Ecobalance, Inc. for the Environmental Research and Education Foundation, June 1999.
ERGI (2001). Open Burning Volume III: Chapter 16. Prepared by Eastern Research Group, Inc. for the
Area Sources Committee Emission Inventory Improvement Program, January 2001.
ESEI (2014). Tub Grinder vs. Horizontal Grinder. http://earthsaverequipment.com/Equipment-Guide/tub-
grinder-vs-horizontal-grinder. Accessed 14 July 2014.
Haug, R.T. (1993). The Practical Handbook of Compost Engineering. Ann Arbor, MI: Lewis Publishers.
IWCS (2014b). Personal Communication between Pradeep Jain, P.E., Innovative Waste Consulting
Services, LLC with a Confidential Client.
Jang, Y. (2000). A Study of Construction and Demolition Waste Leachate From Laboratory Landfill
Simulators. Ph.D. Dissertation, University of Florida, Gainesville, FL, USA.
Jenkins, B. M., Baxter, L. L., Miles Jr., T. R., and Miles, T. R. (1998). Combustion Properties of
Biomass. Fuel Processing Technology 54: 17-46.
Jones, G., Loeffler, D., Calkin, D., and Chung, W. (2010). Forest Treatment Residues for Thermal Energy
Compared with Disposal by Onsite Burning: Emissions and Energy Return. Biomass and
Bioenergy, 34: 737-746.
Komilis, D. P. and Ham, R. K. (2004). Life-Cycle Inventory of Municipal Solid Waste and Yard Waste
Windrow Composting in the United States. Journal of Environmental Engineering, 130: 1390-
1400.
Lutes, C. C. and Kariher, P. H. (1997). Evaluation of Emissions from the Open Burning of Land-
Clearing Debris. A Report Prepared by National Risk Management Research Laboratory for the
United State Environmental Protection Agency, EPA/600/SR-96/128, Cincinnati, Ohio, USA.
Maker, T. M. (1994). Wood-chip Heating Systems: A Guide for Institutional and Commercial Biomass
Installations. http://www.biomasscenter.org/pdfs/Wood-Chip-Heating-Guide.pdf
Nzokou, P., Simons, J., and Weatherspoon, A. (2011). Wood Residue Processing and Utilization in
Southeastern Michigan, U.S. Arboriculture and Urban Forestry, 37(1): 13-18.
Pan, F., Han, H. S., Johnson, L. R., and Elliot, W. J. (2008). Net Energy Output from Harvesting Small-
Diameter Trees Using a Mechanized System. Forest Products Journal, 58: 25-30.
PGEC (1997) Report - Beneficial Reuse of Landclearing Debris. Prepared by Pottinger Gaherty
Environmental Consultants Ltd. for Environment Canada, Contract #KM759-7-4601, October
1997.
Springsteen , B. ,Christofk, T., Eubanks, S., Mason , T., Clavin, C. and Storey, B. (2011). Emission
Reductions from Woody Biomass Waste for Energy as an Alternative to Open Burning, Journal
of the Air and Waste Management Association, 61(1): 63-68.
Tolaymat, T. M. (2003). Leaching Tests for Assessing Management Options for Industrial Solid Waste: A
Case Study Using Ash from the Combustion of Wood and Tires. Ph.D. Dissertation, University
of Florida, Gainesville, FL, USA.
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Multimedia Environmental Assessment Section 7 - Land Clearing Debris
Townsend, T.G., Jang, Y-C., Thurn, L.G. (1999). Simulation of Construction and Demolition Waste
Leachate. Journal of Environmental Engineering, ASCE, 125 (11), 1071-1081.
Tumuluru, J. S., Sokhansanj, S., Wright, C. T., Boardman, R. D., and Yancey, N. A. (2011). A Review
on Biomass Classification and Composition, Co-Firing Issues and Pretreatment Methods. 2011
AS ABE Annual International Meeting.
US EPA (1989). Yard Waste Composting - A Study of Eight Programs. EPA530-SW-89-038, published
April 1989.
US EPA (1991). Nonroad Engine and Vehicle Emission Study - Report. Office of Air and Radiation
EPA-21A-2001, November 1991.
US EPA (1996). AP-42, Fifth Edition, Volume I, Chapter 2, Section 2.1: Refuse Combustion.
http: //www .epa. gov/ttn/chief/ap42/ch02/index.html
US EPA (2002). AP-42, Fifth Edition, Volume I, Chapter 10, Section 6.3: Medium Density Fiberboard
Manufacturing. http://www.epa.gov/ttnchiel/ap42/chlO/
US EPA (2003). AP-42, Fifth Edition, Volume I, Chapter 2, Section 1.6: Wood Residue Combustion in
Boilers, http://www.epa.gov/ttn/chief/ap42/ch01/index.html
US EPA (2011). Materials Characterization Paper In Support of the Final Rulemaking: Identification of
Nonhazardous Secondary Materials that are Solid Waste Construction and Demolition Materials
- Land Clearing Debris. February 2011.
http: //www. epa. gov/waste/nonhaz/define/rulemaking .htm
US EPA (2012). EPA Waste Resources Model, Landfilling, WARM Version 12. United States
Environmental Protection Agency.
US EPA (2014). Methodology to Estimate the Quantity, Composition, and Management of Construction
and Demolition Debris in the United States. A Report Prepared by Innovative Waste Consulting
Services, LLC and Pegasus Technical Services, Inc. for the United States Environmental
Protection Agency, June 2014, Unpublished report.
US LCI (2012). U.S. Life Cycle Inventory Database, http://www.nrel.gov/lci/. Accessed 20 February
2014.
Wiltsee, G. (1998). Urban Wood Waste Resource Assessment. A Report Prepared by National Renewable
Energy Laboratory Managed by Midwest Research Institute for U.S. Department of Energy.
November 1998.
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Section 8 - Portland Cement Concrete
8 Portland Cement Concrete
8. 1 Introduction
PCC is a composite material formed from fine aggregates (i.e., sand), coarse aggregates (e.g., gravel,
crushed stone), binder (Portland cement), water, and stabilizers. By volume, aggregates, cement, and water
represent 60-70%, 10-15%, and 15-20% of the concrete mix, respectively (PCA 2014a). The remaining
volume of concrete is entrained air and any additional stabilizers or other amendments added to enhance
desired properties of the concrete. Concrete is widely used in the construction industry due to its versatility,
strength, and cost - (assuming a density of 150 pounds per cubic foot) nearly 480 MMT of ready-mixed
concrete is used annually in the US (PCA 2014b). Ready-mix concrete is the most commonly used concrete
type and accounts for about three-fourths of all concrete used annually (PCA 2014b).
Pavements, bridges, and various components of airports and buildings that have been constructed from
concrete may be rehabilitated or demolished and reconstructed due to wearing or damage that has occurred
over time. Concrete may be removed by different techniques (e.g., blasting, crushing, cutting, impacting,
milling, and presplitting), which are determined based on factors such as cost, project duration, the quality
of the concrete, the potential for recycling, transport distances, and accessibility (Lee et al. 2002, Lechemi
et al. 2007 and Woodson 2009).
Once removed, reclaimed PCC may be recycled or disposed of in a landfill. The concrete is typically
processed (e.g. crushing, sorting, metal removal) prior to use in a recycling application. Figure 8-1 identifies
the flow of materials and processes that should be considered for conducting an LCA of concrete EOL
management. Most commonly, recovered concrete is recycled as aggregates (referred to here as recycled
concrete aggregate [RCA]) in road base, for new concrete mix, or for asphalt pavement mix production.
Closed-loop recycling of concrete, where RCA replaces both primary aggregate and cement, is not a
common practice at present; the US EPA (2012) indicated lack of data for developing emission factors for
closed-loop recycling of concrete.
Concrete Ready-
Mix Production
Retail/
Wholesale
v. j
In Service
End-of-Life 1
Product Removal |
Crushing, Sorting
and Metal
Removal
Landfilling
RCA
Replacement of
Primary
Aggregae
Demolished
Concrete
Replacement of
Natural Soil
Scrap Metals
Aggregate
Production
Natural Soil
Production
Figure 8-1. Materials Flow for Concrete EOL Phase Management
8.2 EOL Management
As presented in Figure 8-1, there are three primary EOL management pathways for concrete: use as RCA,
use as general fill, and landfill disposal. CDRA (2014) reports that approximately 127 MMT of concrete
are recycled annually; however, the basis of this estimate of recycled concrete is not well documented.
Concrete (with and without rebar, painted and unpainted concrete) represents approximately 10.8 to 15.2%
(by mass) of CDD materials received at CDD landfills (CCG 2006, COM 2009, and RWB et al. 2010).
Based on US EPA's estimate of total CDD landfilled (as presented in Chapter 2 of this report),
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Section 8 - Portland Cement Concrete
approximately 9.5 to 13 MMT of concrete was disposed of in landfills in 2011. However, based on
information from CDRA (2014), Turley (2002) and Wilburn and Goonan (1998), it appears that the total
amount of concrete recovered for EOL management in the US on an annual basis may range between 212
to 254 MMT, though the primary sources of data used to develop the estimates provided in these documents
are not clearly provided.
An earlier dated estimate, as derived from various USGS and industry sources, presented by Wilburn and
Goonan (1998) reported that approximately 50% of cement concrete debris generated in the US is landfilled
and the rest is recycled. Of the recycled amount, 86% is used as road base, 8% is used in asphaltic concrete
(i.e., atotal of 94% is used as RCA), and 6% is used as general fill (Wilburn and Goonan 1998). However,
these end-use projections are based on the USGS estimate of a total of 14.5 MMT generated in the US,
which is likely a substantial underestimation of the actual amount of concrete debris generated in the US.
Deal (1997) (as cited in Kelly 1998 and USGS 2000) also presented recycled concrete uses; a copy of Deal
(1997) was not available for more details of the projections presented. Figure 8-2 presents the distribution
of concrete debris used in different applications in the US based on US EPA's estimate of concrete
landfilled, CDRA's estimate of concrete recycled, and the distribution of concrete uses reported by Deal
(1997). The use as aggregate for road base is the most common management option for RCA (FHWA
2004, CTCA 2012). Use of RCA in asphalt mixes is another desirable option as it can improve the stability
and surface friction of the pavement apart from offsetting production of primary aggregate (Snyder and
Rodden n.d.). However, the use of RCA in asphalt mixes can increase the need for greater asphalt content
in the paving mix due to RCA's absorptive properties (Snyder and Rodden n.d.).
Road Base
62%
Landfilled
9%
Drainage.
Aggregates
6%
Riprap Hot Mix Asphalt
3% 8%
New Concrete
Mix
6%
Figure 8-2. Distribution of Recycled Concrete Uses in the US (Deal 1997)
Decreased workability as a result of its angular structure, reduced durability due to potential alkali-silica
reaction, and reduced compressive strength when substituted for fine aggregates or substituted for more
than 30% of coarse aggregates are some of the challenges of recycling RCA into new concrete mixes
(Hansen 1986, Li and Gress 2006, Mclntyre et al. 2009 and Hiller et al. 2011). In a survey of state concrete
recycling practices, 10 out of 30 responding states allowed the use of crushed concrete for road surface
course (CTCA 2012). However, only two Alabama and Texas reported this use as a common practice.
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Section 8 - Portland Cement Concrete
Recycled concrete can also be used as riprap. FHWA (2004) reported that most states allow processed
recycled concrete to be used as riprap for erosion control, as long as steel reinforcement has been removed
prior to use. Demolished concrete can also be used in fill applications (e.g., embankments) as a substitute
for natural soil. The "drainage aggregates" includes uses such as drainage fields and pipe bedding. The
"Other" category includes use as railroad ballast and landscaping rock.
Table 8-1 lists the processes that should be considered for an LCA of EOL management of concrete. The
emissions associated with energy and materials requirements and process non-energy emissions (e.g.,
fugitive dust, liquid emissions associated with disposal of concrete in a landfill) were taken into account in
compiling the different LCI datasets.
Table 8-1. Concrete EOL Management Process Descriptions
Process
Concrete
Removal/Demolition
Transport
Landfill Disposal
Concrete Processing
RCA Replacement of
Primary Aggregates
Concrete Replacement of
Natural Soil
Description
Concrete may be removed by a variety of processes at the end of
serviceable life and the mechanism of removal will depend on project
needs and constraints and intended end-use of recovered concrete.
The emissions associated with the transport of demolished concrete to a
recycling facility or a landfill, primary aggregate and RCA to end users
should be considered for LCA.
The materials (e.g., equipment, soil, water) and energy (fuel, electricity)
inputs for placing and compacting discarded concrete in a CDD landfill
along with process non-energy emissions (e.g., dust emissions from
equipment operation and liquids emission associated with physiochemical
degradation of concrete in a landfill) should be included in LCA.
Concrete processing includes crushing, sorting, and removing metal. The
extent of concrete processing depends on the end use of the processed
material. Concrete can be processed on-site or off-site using mobile or
stationary equipment.
RCA may be used as primary aggregate substitute in a variety of
applications, including road base construction, asphalt or concrete mix
production, or as riprap. This use of RCA precludes the production of an
equivalent amount of primary aggregate.
Concrete may be used as a soil substitute in fill applications. When used
as a fill material, the concrete will likely not need the processing and
sorting requirements necessary for using concrete as aggregate. This use of
demolished concrete precludes the production of natural soil.
8.3 LCI Sources
Peer-reviewed literature, government and private industry publications, and various LCA modeling tools
were reviewed to identify available LCI datasets pertaining to concrete EOL management processes. Table
8-2 lists sources reviewed to develop the LCI presented in this chapter. If LCI data were not available,
process metadata and documentation (e.g., included emission categories, background data used to compile
the dataset, geographic location and time period of the data) were reviewed to evaluate the completeness of
the dataset. If available, the primary sources of information used to develop the LCI datasets and
information were reviewed. The USLCI, EPA, and GaBi database also present LCI for various processes
primarily related to cement and aggregate production.
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Section 8 - Portland Cement Concrete
Table 8-2. List of Sources Reviewed for LCI Data
LCI Source
Description
Wilburn and
Goonan(1998)
The authors provide energy requirements associated with crushing/sorting
stone, sand and gravel, and concrete. These data were taken from the Portland
Cement Association and an energy audit of a recycling facility in Denver,
Colorado.
Stripple (2001)
H. Stripple, on behalf of the IVL Swedish Environmental Research Institute,
presents a LCA of Road for the Swedish National Road Administration. The
document provides LCI for a wide variety of road construction, pavement
production, maintenance, and demolition activities (e.g., land clearing
activities for road placement, installation of signs). Emissions are based on
information gathered from 1990-1994 for numerous road manufacturing and
upkeep processes taken from a variety of industry and heavy equipment
manufacturer sources.
US EPA (2012)
EPA's Waste Reduction Model presents data on GHG emissions associated
with transporting, recycling, and landfilling (i.e., collection and placement)
concrete.
Ecoinvent(2014)
Ecoinvent is an LCI database developed by the Swiss Centre for Life Cycle
Inventories, which includes specific processes related to the EOL management
(demolition, processing, and disposal) of numerous individual materials,
including waste concrete.
Cochran (2006)
Cochran (2006) presented diesel energy requirements for concrete processing
equipment based on a survey of equipment manufacturers.
Jang (2000)
Jang (2000) presents batch and column leaching tests data for various CDD
materials, including concrete.
Mclntyre et al.
(2009)
Mclntyre et al. (2009) presents energy and GHG emissions savings estimates
for RCA production and substitution for primary aggregates in nonstructural
applications.
NIST (2007)
BEES
The National Institute of Standards and Technology Building for
Environmental and Economic Sustainability model allows an economic and
environmental impact comparison among various building materials, including
concrete.
8.4 LCI Related to Removal/Demolition
Concrete demolition generally includes breaking the concrete into manageable chunks for ease of handling
and transportation. In-place concrete characteristics may be analyzed to assess properties and suitability for
use in targeted applications prior to demolition (Hiller et al. 2011). Contaminants such as joint sealant and
large portions of asphalt overlay or patch are recommended to be removed prior to concrete demolition,
but, depending on the RCA application, small amounts of asphalt contamination are not detrimental (CDRA
2014). The project location and nature (e.g., need to protect the surrounding infrastructure) dictate the
concrete removal method and equipment used (Lechemi et al. 2007 and Woodson 2009). Dykins and Epps
(1987) and NHI (1998) [as cited in Hiller et al. (2011)] describe two general types of equipment that can
8-4
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Multimedia Environmental Assessment Section 8 - Portland Cement Concrete
be used for breaking up concrete in highway applications to render concrete into sizes acceptable for
crushing: impact breakers and resonant breakers. Impact breakers use individual weighted drops to break
the concrete and this equipment has greater production rates than resonant breakers (900 to 1,100 m2/hr
compared to 670 m2/hr), which use a high-frequency, low-amplitude pulse to fracture the concrete.
Resonant breakers have the advantage of producing more uniform slabs and causing fewer disturbances to
underlying infrastructure (e.g., sewers, utilities).
After the concrete has been fractured and separated from reinforcement, larger pieces of concrete (<24")
chunks of concrete can be removed using a backhoe while a front end loader can be used to remove the
remaining pieces. The demolished concrete may be processed onsite or transported to an offsite
recycling/processing facility to produce RCA or may be transported to a landfill for disposal.
The emissions for demolishing concrete include those associated with demolition equipment manufacture
and EOL management, operation and maintenance consumables (e.g., lubricants, air filters, belts), energy
(fuel) inputs, and particulate matter releases during demolition. The US Advisory Council on Historic
Preservation (1981) [as cited in Cole and Kernan (1996)] provided the energy needed for demolishing a
concrete building on a MJ/m2 basis. However, the energy uses (e.g., transportation, equipment fuel usage)
and the calculation methodology of this estimate were not clearly defined. Weiland and Muench (2010)
used the US EPA NONROAD 2005 model to estimate air emissions from fuel consumption in equipment
used for breaking and loading PCC as part of an LCA for concrete pavement. As NONROAD does not
include a pavement breaker, a combination of off-road truck and a crushing/processing equipment was used
to estimate emission from a pavement breaker. Although fuel usage (BTU/hr) for this equipment was
reported, the concrete demolition rate (MT/hour) was not reported to estimate energy used for demolishing
a unit mass of in-place concrete.
Various European and other non-US literature sources have published energy consumption and emissions
information associated with demolishing or dismantling concrete structures. The Ecoinvent database
includes estimates of diesel fuel consumption for dismantling reinforced (0.0612 MJ/kg) and non-reinforced
concrete (0.0437 MJ/kg) based on dismantling practice in Switzerland (with hydraulic diggers) (Doka
2003). Ecoinvent inventories particulate matter (PM) emissions from building construction, demolition,
renovation, and highway reconstruction; however, it does not distinguish between PM related to concrete
handling and the handling of other mineral construction materials (e.g., bricks, cement, gypsum, plaster).
MGE (1997) presented demolition energy estimates for three structural materials (wood, steel, and
concrete) for Canada based on factors such as typical equipment used, fuel used, and energy consumption
rates. The estimated energy for demolishing a concrete structure (including cutting reinforcing steel) was
0.0681 MJ/kg concrete. Stripple (2001) published energy consumption from milling a concrete road in
units of liters of diesel per area of concrete milled and mega joules per area of milled concrete in Sweden.
LCI projecting the environmental burdens from concrete structure demolition could not be compiled due to
lack of data.
8.5 LCI Related to Disposal
As discussed earlier, based on published literature and US EPA's compilation of state data, it is estimated
that approximately 9% of the concrete generated in the US is disposed of in landfills. Emissions associated
with concrete disposal in a landfill include air emissions from equipment used for placing concrete in the
landfill, emissions associated with landfill construction and operation, and liquid emissions from material
decomposition in the landfill. There are various sources which provide landfilling emission factors related
to equipment use and landfill construction and operation; however, none are specific to concrete landfilling.
Generalized landfill construction and operations LCI data are presented in Chapter 2.
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Concrete exposure to precipitation or other liquids (e.g., landfill leachate) is expected to result in
contaminants leaching and the emissions are expected to depend on biogeochemical environment (e.g.,
MSW landfill, CDD landfill). Leachable emissions were estimated using batch leaching tests (SPLP) and
leaching column data reported by Jang (2000). Jang (2000) conducted leaching tests on several individual
CDD materials, including concrete (size reduced to 1") collected from a concrete recycling facility in
Florida to assess leaching of conventional water parameters [e.g., pH, conductance, TDS, and COD], ions
and heavy metals. The L:S ratio of the batch tests in Jang (2000) were much greater than the L:S ratio in
the column tests (20:1 versus 1.3:1); batch data were used for parameters (calcium, chloride, potassium and
sodium) that were measured above the detection limits (because of the greater propensity to leach
pollutants). Batch test concentrations were multiplied by the total solution volume and divided by the
sample mass to estimate leachability on a per-kilogram-concrete basis.
For parameters that were either below the detection limit in the batch testing experiment or were not
measured during the batch test, column test data were used to develop leaching LCI. Leachability of COD
and magnesium were calculated from column test data by summing the total mass of pollutant leached and
dividing this mass by the mass of the concrete material in the column. Non-purgeable organic compound
emission was not estimated as this compound is not included as a flow in US LCI (2012) datasets. Nitrate
and sulfate emission data reported by the study were not used for developing the LCI dataset since SPLP
extraction fluid contains these anions. TDS data reported by the study were also not included to avoid
double-counting emissions, as some of the contaminants listed in Table 8-3 are included in TDS
measurement.
Concrete leaching data, energy consumption data from landfill operations, estimated cover soil demand,
and an assumed transport distance were used to develop an LCI process dataset for disposing of concrete
at an unlined CDD or inert debris landfill, as presented in Table 8-3. The energy use and the associated
emissions from landfill operations (e.g., waste placement, compaction) include diesel use in heavy
equipment and electricity use in landfill buildings (e.g., administrative buildings, workshop); calculations
detailing these input flows are included in Chapter 2 of this report. The bulk density of loose concrete used
to estimate cover soil requirements was provided by CCG (2006); additional details on the cover soil
estimate are provided in Chapter 2. In the absence of nationwide average transport data, it was assumed
that concrete would be transported 20 km for landfill disposal. US LCI (2012) provides general transport
process LCI, which are further discussed in Chapter 2. Emissions are provided per kilogram "Concrete, at
unlined CDD landfill" flow.
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Table 8-3. Proposed LCI Dataset: Concrete, at Unlined CDD Landfill
Input Flow
Concrete, from demolition
Truck transport, class 8, heavy
heavy-duty (HHD), diesel, short-
haul, load factor 0.75
CDD landfill operations
Cover soil, from offsite source
Output Flow
Concrete, at unlined CDD landfill
Calcium
Chloride
COD, Chemical Oxygen Demand
Magnesium
Potassium
Sodium
Source
Assumed
See Chapter 2
See Chapter 2
Source
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Category
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Construction and Demolition
Debris Management
Category
Construction and Demolition
Debris Management
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Unit
kg
t*km
kg
kg
Unit
kg
mg
mg
mg
mg
mg
mg
Amount
1
0.001*20
1
0.0372
Amount
;
2860
74.0
49.4
1.44
240
52.0
8.6 LCI Related to Recycling
8.6.1 Concrete Processing
The recycling end-use and corresponding specifications and project and end-use locations dictate the
processing degree and location. For example, no processing may be needed if concrete is used to replace
natural soil fill in a non-load-bearing fill application. RCA production, on the other hand, requires extensive
processing. Concrete may be processed on-site using mobile equipment if the processed concrete is intended
to be used at the site. It may be transported for off-site processing for future end uses. Concrete commingled
with other CDD materials would need to be segregated prior to processing. Additional details on CDD
processing facilities are provided in Chapter 2 of this report.
Off-site processing facilities may have a multi-phase crushing operation in which the concrete passes from
a primary crusher to a secondary crusher. Several types of crushers can be used in concrete processing: jaw
crushers are typically primary crushers, cone crushers are secondary crushers, and impact crushers can be
both primary and secondary crushers. While impact crushers have the advantage of removing a greater
amount of mortar from concrete aggregates (yielding a better quality aggregate), removing more mortar
results in a larger amount of (typically landfilled) fine material (Hiller et al. 2011). Hiller et al. (2011)
reported that the overall grading of RCA is difficult to control in a concrete crushing operation and the
crushed concrete, typically, is gap-graded (i.e., mostly consists of large and fine aggregate, but generally
only has a small amount of mid-size aggregate). The crushed concrete may need to be screened to achieve
a desired gradation (e.g., a scalping screen may be used to remove excess dirt and foreign particles or a fine
harp deck screen may be used to remove fine material from coarse aggregate). The RCA recovery rate
(amount of RCA produced per unit mass of concrete processed) depends on the targeted maximum
aggregate size (Hiller et al. 2011). The recovery rate is greater for crushing operations with greater
maximum particle size of RCA. For example, a recovery rate of 80% is reported from a crusher set to
produce RCA with a maximum particle size of 38 mm, whereas the recovery rate is less than 60% for
crushing operations producing RCA with a maximum particle size of 19 mm (Hiller et al. 2011).
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Magnetic separators may also be incorporated between crushing processes to remove steel (e.g., mesh,
rebar, dowels) from demolished concrete. The fraction of steel recovered from concrete recycling depends
on how easily the steel can be separated from the concrete. For example, wire mesh (generally used for
reinforced pipes) usually retains a large quantity of concrete and is not recovered [ACPA (1993) (as cited
in FWHA 2004)]. NIST 2007 reported 135 Ib of steel per cubic yard of concrete as the industry average
steel content of concrete. However, no data regarding distribution of reinforced and non-reinforced
concrete and steel recovery rates from concrete crushing operations were found.
Facilities may store and process concrete by material source to maintain a homogeneous RCA quality (TRB
2013). The processing facilities may need to temporarily stockpile the incoming concrete debris and RCA
depending on demand for the end product as a result of this practice. Liquids emission associated with
exposure to natural precipitation has been reported to be an issues associated with concrete/RCA stockpiles.
Various departments of transportation and research groups have identified the potential for runoff (i.e.,
leachate) from unbound RCA to be highly alkaline (reaching up to a pH of around 12) (Snyder 1995, Steffes
1999, Jang 2000, Hiller et al. 2011 and Chen et al. 2012). Water used for controlling particulate matter
emission from crushing operation is another source of liquid emission. The emissions from stockpiling
should, therefore, be considered for an LCA on recycled concrete. No literature reporting water
consumption for dust control was found. Another issue with RCA stockpiling is that the material is
susceptible to cementing since RCA may contain some amount of unhydrated cement; therefore, the
material should be protected from moisture to prevent agglomeration (Hiller et al. 2011).
The emissions from processing waste concrete include those associated with materials and energy input as
well as non-energy emissions released during crushing, screening, and storing the processed materials.
MGE (1997) estimated on-site concrete debris processing energy requirement of 5 MJ/MT; processing
included stockpiling, preparing the concrete for crushing (size reducing from 380 mm to 200 mm), loading
the crusher, and crushing the concrete to 63-mm aggregate. Cochran (2006) used equipment manufacture
energy consumption and approximate production rates to estimate the energy required to operate a concrete
crushing operation, which includes use of an impact crusher, excavator, and loader. Cochran (2006)
estimated that approximately 7 MJ/Mg (total) of energy would be consumed by the equipment; however,
this estimate does not include additional energy consumption from ancillary buildings, equipment, or
processes. Wilburn and Goonan (1998) reported an energy requirement of 34 MJ for crushing/sorting 1
MT of PCC based on data from the Portland Cement Association and data from a recycling facility in
Colorado; these data do not explain what sources are consuming the energy (e.g., buildings, equipment).
Wilburn and Goonan (1998) also provide transport energy requirements recycled concrete in terms of joules
per kg-km. Wilburn and Goonan (1998) is commonly cited (e.g., within Mclntyre et al. 2009, WARM
model, Cochran 2006) as a source for concrete processing data.
The energy estimates provided by Wilburn and Goonan (1998) are used to create a generalized energy
estimate for the concrete processing LCI presented in Table 8-4. In the absence of additional data,
electricity and diesel consumption were each assumed to constitute 50% the total energy requirements. A
similar approach was used by the US EPA (2012) in estimating GHG emission factors for demolished
concrete processing for WARM; US EPA (2012) also used the energy consumption data reported by
Wilburn and Goonan (1998) to estimate the emission factors for WARM.
Concrete crushing and sorting particulate emissions were not identified from US Sources. As discussed in
Chapter 2, US EPA AP-42 (1995) does not provide PM emissions for primary and secondary stone crushing
operations (the most similar industrial process to concrete crushing that has quantified emissions). Estevez
et al. (2008) documents 0.14 g dust per MT of recycled concrete and other air emissions from mobile
concrete crushing operations in Spain. Due to lack of data (quantity and quality of liquid emission from
concrete/RCA stockpile) leachate/runoff emissions to groundwater/surface water from RCA stockpiling
were not included in the concrete processing dataset.
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Section 8 - Portland Cement Concrete
Table 8-4 presents the proposed LCI dataset for concrete processing that occurs at a concrete waste
generation site with mobile equipment or at an offsite processing facility. Similar to aggregate crushing and
sorting during production, it is expected that particulates would be a source of emissions released from
concrete crushing and sorting operations. However, as explained previously, due to a lack of data, fugitive
dust emissions released during the crushing process and emissions from the manufacturing, maintenance,
and disposal/dismantling of the crushing equipment are not included in Table 8-4. This dataset should not
be used if recovered concrete is not processed prior to end use (e.g., application to replace a soil
embankment fill). In the absence of national average data on the distance from the demolition site to offsite
concrete processing, a distance of 20 km was assumed, US LCI (2012) provides general transport process
LCI, which are further discussed in Chapter 2. It should be noted that on-site concrete processing operations
would likely result in fewer emissions associated with transport because transport emissions will typically
include only those associated with equipment mobilization.
Table 8-4. Proposed LCI Dataset: Crushed Concrete, at Processing Plant
Input Flow
Concrete, from demolition
Diesel, combusted in
industrial equipment
electricity, at industrial user
Truck transport, class 8,
heavy heavy-duty (HHD),
diesel, short-haul, load factor
0.75
Output Flow
Crushed concrete, at
processing plant
Source
Wilburn and Goonan
(1998)
Wilburn and Goonan
(1998)
Source
Category
Construction and Demolition
Debris Management
Flows
Flows
Category
Construction and Demolition
Debris Management
Unit
kg
L
kWh
t*km
Unit
kg
Amount
1
0.00044
0.00472
0.001*20
Amount
;
8.6.2 RCA Use as Aggregate
Recycled concrete is most commonly used to replace primary aggregate in the following applications: road
base, subbase, asphalt and cement concrete, and riprap. RCA produced from demolition activities will
likely need to be crushed, processed to remove contaminants such as steel, and sorted prior to use in these
applications to meet gradation specifications. The primary emissions resulting from the use of RCA as an
aggregate material (after the concrete has been processed) include leaching to groundwater/surface water.
Granular base (unbound) applications of RCA have been shown to leach calcium carbonate precipitate that
can clog drainage pipes (particularly if there is a large amount of fine material in the RCA) and may restrict
use in various drainage applications (Gupta 1993, Snyder 1995, Steffes 1999). Although there have been
no reported problems with this precipitate for embankment applications, there is the possibility for highly
alkaline precipitates to occur (FHWA 2012). The liquid emissions from unbound RCA are expected to be
similar to those from an inert landfill. While it would take longer for bound RCA (e.g., use in asphalt
pavement, use in new concrete mixes) to leach contaminants, it is expected that over an infinite time
horizon, these emissions would ultimately be the same.
The use of RCA in an aggregate-required fill application avoids the need for the production of primary
aggregates; emissions associated with primary aggregate production and transport are presented in Chapter
2. The US EPA (2003) background documentation for the WARM model used a distance of 15 miles for
the transport distance of recycled aggregate material; however, the justification for this distance was not
provided. Again, because the transport distance from the processing facility to the aggregate fill site is
unknown, this distance was assumed to be 20 kilometers. Table 8-5 presents the proposed LCI dataset for
RCA used to replace primary aggregate.
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8.6.3 Demolished Concrete Use as Soil Fill Replacement
The use of demolished concrete to replace natural soil fill (e.g. lake fill, embankment fill) would avoid the
emissions resulting from the production and transport of natural soils. Table 8-6 presents the proposed LCI
dataset for demolished concrete used to replace natural soil. While leachable emissions are assumed to
ultimately be the same whether demolished concrete is used as a substitute for bound aggregate, unbound
aggregate, or natural soil, this dataset assumes that the concrete debris used as a fill material does not need
to be size reduced or screened. It was assumed that concrete debris will be transported 20 km from the
demolition site to the fill site.
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Section 8 - Portland Cement Concrete
Table 8-5. Proposed LCI Dataset: Recycled Concrete Aggregate, Use as Aggregate
Input Flow
Processed concrete, at processing plant
Truck transport, class 8, heavy heavy-duty
(HHD), diesel, short-haul, load factor 0.75
Output Flow
Recycled concrete aggregate, use as
aggregate
Calcium
Chloride
COD, Chemical Oxygen Demand
Magnesium
Potassium
Sodium
Source
Source
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Category
Construction and Demolition Debris Management
Category
Construction and Demolition Debris Management
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Unit
kg
t*km
Unit
kg
mg
mg
mg
mg
mg
mg
Amount
1
0.001*20
Amount
;
2860
74.0
49.3
1.44
240
52.0
Table 8-6. Proposed LCI Dataset: Concrete debris, Use as Soil Fill Substitute
Input Flow
Demolished concrete, at demolition
Truck transport, class 8, heavy heavy-duty
(HHD), diesel, short-haul, load factor 0.75
Output Flow
Recycled concrete aggregate, use as soil fill
substitute
Calcium
Chloride
COD, Chemical Oxygen Demand
Magnesium
Potassium
Sodium
Source
Source
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Jang (2000)
Category
Construction and Demolition Debris Management
Category
Construction and Demolition Debris Management
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Water/Groundwater
Unit
kg
t*km
Unit
kg
mg
mg
mg
mg
mg
mg
Amount
1
0.001*20
Amount
;
2860
74.0
49.3
1.44
240
52.0
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8.7 Data Gap Analysis and Opportunities for Additional LCI Data
Table 8-7 summarizes the type of US-based LCI identified from reviewed concrete EOL management
sources, including Wilburn and Goonan (1998), Jang (2000), and Cochran (2006). Wilburn and Goonan
(1998) and Cochran (2006) only provide partial data only present energy-consumption information for
concrete processing. Data sources that are not the primary source of LCI data have not been included in
Table 8-7 [e.g., the WARM model is not included because it uses data from Wilburn and Goonan (1998)
and is not the original source of data for the energy consumed in processing recycled concrete]. Overall,
limited EOL-specific LCI are available for concrete. Based on a review of the available information, the
following data gaps were identified for compiling a more comprehensive LCI dataset for concrete EOL
management:
1. Leachable emissions from the landfill disposal or use of RCA as aggregate or in the
replacement of natural soils are lacking. Although an estimate of liquid emissions from concrete
disposal in unlined CDD landfills and for use as aggregate and natural soil is included in the
proposed LCI datasets and was developed based on batch and column concrete leaching test data
reported by one study (Jang 2000), these liquids emissions are associated with a maximum L:S of
20 and do not represent the complete liquid emission perspective. Future research should consider
estimating the long-term leaching of RCA (at an L:S ratio that would represent complete
contaminants leaching).
2. The long-term impact of using recycled concrete in pavement applications and effect on
quality and service life of the pavement should be assessed. Numerous studies of the properties
of RCA and how it affects concrete and pavements constructed with it are available. Evaluating
long-term US-studies comparing RCA pavement durability and service life over an extended period
of time would be a valuable contribution to better understanding environmental burdens over the
entire life cycle of recycled concrete in pavement applications.
3. Limited data available for quantifying concrete carbonation. Studies have shown that the
cement portion of concrete can over time absorb carbon dioxide in a process called
carbonation. There have been several recent studies (e.g., Fade and Guimaraes 2007, Dodoo et al.
2009, Collins 2010, and Garcia-Segura et al. 2014) describing and comparing observations of
carbon dioxide uptake in different stages of the life cycle of concrete (e.g., calcination of cement,
concrete usage phase, demolition of concrete, use of crushed concrete as an aggregate). Most of
these studies estimate carbon dioxide uptake in concrete by using predictive modeling based on
Pick's law of diffusion and a carbon uptake equation developed by Lagerblad (2005). This
modeling approach incorporates the following parameters into the estimation of carbon dioxide
update: the amount of carbonation that has already occurred in the concrete, the amount of Portland
cement in the concrete, the amount of calcium oxide in cement, the molar weight of oxide (carbon
dioxide/calcium oxide), the service life of the concrete, the exposed concrete surface area, and a
carbonation rate coefficient based on the strength and environmental exposure conditions of the
concrete. The EOL management of concrete has been identified as an important component in
calculating carbon dioxide emissions in the life cycle of concrete (Collins 2010). Concrete EOL
management may enhance carbonation, particularly in recycling applications because concrete is
commonly size reduced when it is recycled; this creates a greater surface area that exposes fresh
uncarbonated carbon for carbonation. Due to lack of data, a carbonation factor was not included
in the proposed LCI.
4. Differences in transportation emissions between mobile concrete processing operations and
stationary concrete processing facilities. Recycling of concrete can occur at the site of demolition
(e.g., a concrete pavement being demolished and then crushed for use as subbase onsite) and a
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Section 8 - Portland Cement Concrete
mobile processing unit, usually smaller than a concrete processing facility, can be brought to the
construction site. The differences in using materials at the site of demolition will likely be realized
in emissions savings in transportation when comparing the emissions from the transportation
necessary to mobilize the processing equipment to the site and back and loading up and trucking
large amounts of material to a stationary facility. Details on the distances mobile operations are
transported, how they are transported, and average distances and the methods of transporting (e.g.,
barge, trucks, train) concrete to a recycling facility would be valuable in improving transportation
emissions estimates to compare each processing option.
5. LCI for mobile and stationary concrete processing facilities. Mobile processing units are
usually smaller and likely less efficient than a stationary concrete processing facility. Two sources
were identified that estimated the amount of energy necessary to process concrete [Wilburn and
Goonan (1998) and Cochran (2006)]. Cochran's (2006) energy consumption estimate was based
on a survey of equipment manufacturers and only includes fuel consumption in equipment. Wilburn
and Goonan (1998) did not provide sufficient detail for activities and operations included in the
reported energy requirement estimate. Neither of these sources provided a breakdown of fuel types
(e.g. electricity, diesel). An estimate of the average fuel mix used for concrete processing is
necessary for developing a more accurate LCI dataset for concrete processing. Also, data for
particulate matter emissions released from concrete processing as well as water usage for
controlling particulate matter emissions are lacking. No data pertaining to the environmental
burdens associated with the manufacture or decommissioning of concrete processing equipment
were identified.
6. No data were found to assess the difference in the energy requirement for processing
reinforced and non-reinforced concrete. Amounts of waste produced from processing concrete
were not identified. Although a majority of non-reinforced concrete may result in very little waste
to be disposed of, the recovery rate of concrete from reinforced concrete is likely to be less because
concrete can remain stuck to steel mesh or rebar. Amounts of recovered rebar per unit mass of
processed reinforced concrete were also not identified.
Table 8-7. Overview of LCI Data Available for Concrete
Process
Concrete Removal/Demolition
Transport
Landfill Leachate
Demolished Concrete Processing
RCA Replacement of Primary Aggregate
Concrete Debris Replacement of Natural Soil
Wilburn and Goonan
(1998)
P
P
Jang (2000)
X
Cochran (2006)
P
8.8 References
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for Selected Industry Groups. A Report Prepared by Cascadia Consulting Group for the California
Integrated Waste Management Board, June 2006.
COM (2009). Illinois Commodity/Waste Generation and Characterization Study. A Report Prepared by
COM Smith Commissioned by Illinois Department of Commerce & Economic Opportunity and
Contracted by the Illinois Recycling Association, 22 May 2009.
CDRA (2014). Good Economic Sense. http://bit.lv/lo07BGV
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Chen, J., Brown, B., Edil, T.B., Tinjum, J. (2012). Leaching Characteristics of Recycled Aggregate used as
Road Base. University of Wisconsin System Solid Waste Research Program: Student Project
Report, May 2012.
Cochran, K. M. (2006). Construction and Demolition Debris Recycling: Methods, Markets and Policy.
Ph.D. Dissertation, University of Florida, Gainesville, FL, USA.
Cole, R.J., Kernan, P.C. (1996). Life-Cycle Energy Use in Office Buildings. Building and Environment, 31
(4), 307-317.
Collins, F. (2010). Inclusion of Carbonation During the Life Cycle of Built and Recycled Concrete:
Influence on Their Carbon Footprint. International Journal of Life Cycle Assessment 15, 549-
556.
CTCA (2012). Concrete Recycling: Reuse of Returned Plastic Concrete and Crushed Concrete as
Aggregate. A Report Prepared by CTC & Associates LLC, Preliminary Investigation Caltrans
Division of Research and Innovation for Rock Products Committee: Materials and QA Sub Task
Group of the Concrete Products Task Group. Revised 7 September 2012.
Dodoo, A., Gustavsson, L., Sathre, R. (2009). Carbon Implications of End-of-Life Management of Building
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Ecoinvent (2014). Swiss Center for Life Cycle Inventories: Ecoinvent Centre. Dataset Information (UPR):
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Administration State of the Practice National Review, September 2004.
Garcia-Segura, T., Yepes, V., Alcala, J. (2014). Life Cycle Greenhouse Gas Emissions of Blended Cement
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Gupta, J. D., Kneller, W. A. (1993). Precipitate Potential of Highway Subbase Aggregates, Report No.
FHWA/OH-94/004 Prepared for the Ohio Department of Transportation, November 1993.
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Hansen, T. C. (1986). Recycled Aggregates and Recycled Aggregate Concrete: Second State-of the-Art
Report: Developments 1945-1985. Material Structures, 19 (111), 201-246.
Killer, J. E., Deshpande, Y. S., Qin, Y., Shorkey, C. J. (2011). Efficient Use of Recycled Concrete in
Transportation Infrastructure. A Report Prepared by Michigan Technological University,
Houghton, Michigan for Michigan Department of Transportation, January 2011.
Jang, Y.C. (2000). A Study of Construction and Demolition Waste Leachate from Laboratory Landfill
Simulators. Ph.D. Dissertation, University of Florida, Gainesville, FL, USA.
Kelly, T. (1998). Crushed Cement Concrete Substitution for Construction Aggregates - A Materials Flow
Analysis. U.S. Geological Survey Circular 1177.
Lagerblad, B. (2005). Carbon Dioxide Uptake During Concrete Life Cycle - State of the Art. Swedish
Cement and Concrete Research Institute, Stockholm, Sweden, Nordic Innovation Centre Project,
NI-project03018.
Lechemi, M., Hossain, K.M.A., Ramcharitar, M., Shehata, M. (2007). Bridge Deck Rehabilitation Practices
in North America. J. Infrastruct. Syst. 13, 225-234.
Lee, E. B., Roesler, J., Harvey, J. T., Ibbs, C. W. (2002). Case Study of Urban Concrete Pavement
Reconstruction on Interstate 10. J. Constr. Eng. Manage. 128, 49-56.
Li, X., Gress, D.L. (2006). Mitigating Alkali-Silica Reaction in Concrete Containing Recycled Concrete
Aggregate. Transportation Research Record: Journal of the Transportation Research Board, No.
1979, Transportation Research Board of the National Academies, Washington, D.C., 2006, 30-35.
Mclntyre, J., Spatari, S., MacLean, H.L. (2009). Energy and Greenhouse Gas Emissions Trade-Offs of
Recycled Concrete Aggregate Use in Nonstructural Concrete: A North American Case Study.
Journal of Infrastructure Systems, 15, 361-370.
MGE (1997). Demolition Energy Analysis of Office Building Structural Systems. A Report Prepared by
M. Gordon Engineering for the Athena Sustainable Materials Institute, March 1997.
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NIST (2007). Building for Environmental and Economic Sustainability Technical Manual and User Guide.
http://l.usa.gov/lswUFgL. Accessed 3 April 2014.
Fade, C., Guimaraes, M. (2007). The CO2 Uptake of Concrete in a 100 Year Perspective. Cement and
Concrete Research, 37, 1348-1356.
PCA (2014a). PCA America's Cement Manufacturers: How Concrete is Made.
http://www.cement.org/cement-concrete-basics/how-concrete-is-made. Accessed 8 July 2014.
PCA (2014b). PCA America's Cement Manufacturers: Products, http://www.cement.org/cement-
concrete-basics/products. Accessed 8 July 2014
RWB, CCG and IWCS (2010). Statewide Construction and Demolition Debris Characterization Study. A
Report Prepared by R.W.Beck, Inc., Cascadia Consulting Group, Innovative Waste Consulting
Services, lie. for Georgia Department of Natural Resources, Sustainability Division. June 2010.
Steffes, R. (1999). Laboratory Study of the Leachate from Crushed Portland Cement Concrete Base
Material. Final Report for MLR-96-4, Iowa Department of Transportation, September 1999.
Stripple, H. (2001). Life Cycle Assessment of Road - A Pilot Study for Inventory Analysis, 2nd Revised
Edition. A Report Prepared by the FVL Swedish Environmental Research Institute for the Swedish
National Road Administration, March 2001. http://bit.ly/lk623dN. Accessed 20 February 2014.
Snyder, M.B. (1995). Use of Crushed Concrete Products in Minnesota Pavement Foundations. A Report
Prepared by Mark B. Snyder, Ph.D., P.E. Published by the Minnesota Department of
Transportation, March 1995.
Synder, M.B., Rodden, R. (n.d.). Concrete Pavement Recycling Practices in the U.S.
TRB (2013). Recycled Materials and Byproducts in Highway Applications. Volume 8: Manufacturing and
Construction Byproducts. NCHRP Synthesis 435, National Cooperative Highway Research
Program, Transportation Research Board of the National Academies, Washington, D.C., USA.
Turley, W. (2002). Personal Communication between William Turley, Construction Materials Recycling
Association and Philip Groth of ICF Consulting, 2002. As cited in http://l .usa.gov/luDQzrG.
US EPA (1995). AP 42, Fifth Edition, Volume I, Chapter 11: Mineral Products Industry, Section 11.2 -
Asphalt Roofing. U.S. Environmental Protection Agency. http://l.usa.gov/lr8s2WR. Accessed 8
July 2014.
US EPA (2003). Background Document for Life-Cycle Greenhouse Gas Emission Factors for Clay Brick
Reuse and Concrete Recycling. EPA530-R-03-017, U.S. Environmental Protection Agency, 7
November 2003.
US EPA (2012). EPA Waste Resources Model, Landfilling, WARM Version 12. United States
Environmental Protection Agency.
US LCI (2012). U.S. Life Cycle Inventory Database. National Renewable Energy Laboratory.
http://www.nrel.gov/lci/. Accessed 20 February 2014.
USGS (2000). Recycled Aggregates - Profitable Resource Conservation. USGS Fact Sheet FS-181-99,
February 2000.
Wilburn, D.R., Goonan, T.G. (1998). Aggregates from Natural and Recycled Sources: Economic
Assessments for Construction Applications - A Materials Flow Analysis. U.S. Geological Survey
Circular 1176, U.S. Geological Survey and U.S. Department of the Interior.
Woodson, R. D. (2009). Concrete Structures: Protection, Repair and Rehabilitation. Chapter 5: Concrete
Removal and Preparation for Repair, Butterworth-Heinemann, 200
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Section 9 - Recovered Screened Materials
9 Recovered Screened Material
9.1 Introduction
RSM, sometimes referred to as CDD fines, is a by-product of CDD material recovery (i.e. processing)
operations. RSM includes soil, sand, and small aggregates from land clearing and demolition, as well as
small particles of larger CDD materials that break off during material handling and sorting (e.g., gypsum
drywall). The actual gradation of the RSM material will depend on the screen size(s) used during CDD
processing, where common screen sizes include openings from 0.6 to 5 cm (Jang and Townsend 200la).
RSM EOL management options may include landfill disposal or recycling options, including use as landfill
alternative daily cover (ADC) or application as a general fill. Both recycling management options would
replace the primary production and use of natural soil resources. Figure 9-1 shows a flow diagram depicting
EOL management processes for RSM.
RSM Production from
C&D Processing
(Screening)
Landfill Disposal
Use as Landfill
Cover
Use as General
Fill
Natural Soil
Production
Figure 9-1. Material Flows for RSM Production and EOL Management
Figure 9-2 presents the composition of RSM reported by Townsend et al. (1998), who characterized RSM
samples collected from 13 CDD processing facilities in Florida. While the majority of RSM resembled a
soil-like material (less than 0.64 cm in size), RSM fraction retained on 0.64-cm screen (referred to herein
as an identifiable fraction) was further segregated into individual components. The identifiable fraction
represented approximately 27% of RSM. As is evidenced in the figure below, the major CDD material
categories in identifiable RSM include small pieces of aggregate (e.g., rock, concrete), wood, ceramics,
paper, and drywall; these materials combined account for over 75% of the identifiable fraction. Of particular
interest is the drywall component of RSM. As discussed in the drywall chapter, the placement of drywall
in anaerobic conditions contributes to the production and release of hydrogen sulfide gas.
Currently, there is no known estimate of the nationwide production of RSM. A summary of recycled CDD
materials as provided by four states (Massachusetts, Florida, Washington, and Nevada) in 2011/2012
suggests that the fines content of recycled CDD materials is approximately 8% (US EPA 2014). However,
other sources suggest that fines represent nearly 25% of the mass of material handled at CDD processing
facilities (Calhoun 2012, Jang and Townsend 2001a, 2001b). Therefore, total nationwide RSM production
is estimated to range from 3.7 to 11.9 MMT of material.
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Wood
2%
Other
27%
Rock/concrete
15%
Unidentifiable
73%
Plastic
0%
Metals
(non-~ (Ferrous)
ferrous) 0%
0%
Figure 9-2. Composition of RSM (Townsend et al. 1998)
9.2 EOL Management
RSM is produced as a result of the EOL management of other CDD materials. As it is a byproduct of CDD
processing, RSM carries no upstream emission burdens. Once recovered from CDD materials processing,
RSM is either disposed of at a landfill, used as ADC at a landfill, or potentially applied in a general fill
application. There is currently no known nationwide estimate of the quantity of material that is handled
through each management option. Table 9-1 lists the processes that should be considered in developing an
LCA for the EOL management of RSM.
Table 9-1. RSM EOL Management Process Descriptions
Process
Landfill Disposal
RSM use as ADC
/
RSM use as General Fill
Transport
Description
Depending on state and local regulations, RSM may be disposed of in
either a CDD or a MSW landfill.
RSM may be used in place of soil cover material at a landfill site. The
use of RSM in this application would preclude the emissions resulting
from the excavation and transport of natural soil on/to the landfill site.
RSM may be used in place of soil in a general fill application. The use
of RSM in this application would avoid the emissions resulting from the
production and transport of natural soil to the general fill site.
While transport LCI are generally presented in units of mass-distance
(kg-km), regional average distances between processes is necessary for
developing a regional-level LCA. It should be noted that cover soil
production may occur at the landfill site where the soil will be applied.
9.3 LCI Sources
Government publications, peer-reviewed literature, and LCA models were searched for LCI datasets
pertaining to RSM management. None of the LCA models reviewed contained emissions inventory data on
RSM (or CDD fines). While Doka (2009) discusses the EOL management of fines resulting from the
operation of building waste sorting facilities, no information/datasets were found in the report or from
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Ecoinvent database search queries that provide emissions data. Table 9-2 lists the sources identified to
contain information or data which could be used for development LCI for RSM management processes
within an LCA framework.
Table 9-2. List of Sources Reviewed for LCI Data
LCI Source
Description
Townsend
etal. (1998)
The total and (SPLP) leachable concentrations of heavy metals, VOCs, and semi-
VOCs are reported from RSM samples collected from 13 CDD processing facilities
over 1996-1997. Additional sources that use the same raw data to perform
supplementary studies include Jang and Townsend (200la, 200Ib) (organic
compound leaching and sulfate leaching, respectively) and Townsend et al. (2004)
(heavy metals).
Anderson et
al. (2010)
Hydrogen sulfide data from six MSW landfill sites were used to estimate site-
specific gas generation potential (volume of hydrogen sulfide produced per ton
sulfur) and first-order decay rates. Eighty-nine samples of CDD fines were collected
from CDD processing facilities and landfill sites to estimate the total sulfur content
of CDD fines.
Tolaymat et
al. (2013)
Estimated laboratory hydrogen sulfide decay-rate constants for paperless drywall,
three sizes of crushed drywall (with paper), and estimated a theoretical hydrogen
sulfide generation potential per mass of drywall.
US EPA
(2012)
WARM has compiled estimates of LFG emissions (i.e. methane and carbon dioxide)
for numerous CDD waste materials (e.g., paper, wood, drywall) using numerous
sources. These estimates are used in conjunction with identified material fractions in
RSM to develop a weighted estimate of total RSM LFG emissions.
Ecoinvent
Doka (2009) (background documentation for the Ecoinvent LCI database) discusses
the management of various building materials, including CDD fines.
9.4 LCI Related to Production
As mentioned previously, RSM is a byproduct (i.e. residual) of CDD processing and is a composite of
various CDD materials that readily fragment into smaller pieces during the CDD material handling at
materials recovery facility. As RSM recovery is not the primary objective of the CDD materials processing,
the emissions associated with CDD processing should not be allocated to the RSM. In other words,
emissions associated with the construction, operation, and decommissioning of the CDD processing facility
should be allocated to the individual CDD materials targeted for recovery.
9.5 LCI Related to Disposal
RSM may be disposed of in either a CDD or an MSW landfill, where both leachate and gas emissions will
result. While it would be possible to take individual leaching data for each of the individual materials and
use the mass-fraction information as presented in Figure 9-2 to develop an estimate of the composite
leachability of RSM, this approach could potentially introduce emission inaccuracies as a result of the
following:
• No estimate of the composition of the unidentifiable fraction of RSM is available. Approximately
a quarter of RSM was identified as specific CDD materials. While the identified fractions of RSM
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could be applied to the unidentified and "miscellaneous" portion of the material on an equal mass-
fraction basis, the majority of the identified material likely consists of soil and small aggregate
material which may have substantially different leaching properties.
• There may be synergistic or antagonistic leaching effects between individual components for RSM.
For example, alkaline materials (e.g. gypsum drywall) may have an immobilizing effect on the
leaching of some heavy metals.
• There is very limited information on the long-term leachability of specific CDD materials.
Ecoinvent considers disposal of fines from CDD recovery facilities in landfills (Doka 2009). Placement in
a sanitary landfill is the typical practice due to challenges for recyclers resulting from the presence of
chlorides, sulfates, and fibers in the material. The fines can be disposed of in an inert or residual material
landfill depending on its properties, including the amount of materials that can dissolve when mixed with
distilled water. However, the solubility of the gypsum portion of the fine material alone is typically
sufficient to require placement in a sanitary landfill.
9.5.1 Leachable Emissions from RSM
Townsend et al. (1998) conducted a characterization of chemical and engineering properties (e.g., grain
size distribution, friction angle) of RSM using 99 samples collected from 13 CDD processing facilities in
Florida from 1996 to 1997. The total and leachable concentration of VOCs, semi-VOCs, and heavy metals
in RSM were analyzed; leaching data were based on SPLP tests. Townsend et al. (2004) provides the mean
concentration for each metal (not including BDL readings) and the number of detected and non-detected
measurements. The mean metal concentration measurement was adjusted for non-detects by including the
respective detection limit as the concentration for measurements below detection limit readings. An average
measured concentration was only developed for the metals that were detected in more than half of all the
samples analyzed, i.e., aluminum, arsenic, and zinc.
Average leachable amounts of VOC and semi-VOC concentrations were estimated using the raw data
presented by Townsend et al. (1998). Average parameter measurements were only developed for those
parameters which were detected in over half of all the samples analyzed. For these parameters, non-detect
measurements were included as the minimum quantification limit. Results from the SPLP tests were
converted from volume-based concentrations (i.e., leached parameter mass per solution volume) to mass-
based concentrations to (i.e., leached parameter mass per RSM mass) concentrations by multiply the
volume-based concentration by the SPLP L:S and adjusting for the moisture content of the sample.
Because leachable emissions from RSM were estimated using the SPLP testing procedure, the estimates
only simulate the leaching for applications such as disposal in inert debris landfills or general fill where
contaminants leach due to exposure to precipitation. TCLP simulates the contaminants leaching in the
biogeochemical environment of an MSW landfill.
9.5.2 Landfill Gas Emissions for RSM
The organic fraction of RSM (e.g., wood, paper) will contribute to the release of carbon dioxide, methane,
and other VOCs in an anaerobic environment. US EPA (2012) summarizes information provided by Barlaz
et al. (1989), Eleazer et al. (1997), and Barlaz (1998) to estimate methane and carbon dioxide emission
factors for the landfill disposal of individual RSM materials, including wood, paper and drywall. Additional
data on the development of these emission factors for MSW and CDD materials landfill disposal is included
in Chapter 2. The individual emission factors for each material were multiplied by the RSM material mass
fractions (presented in Figure 9-2) and summed to develop a composite emissions factor for each gas due
to the absence of emission factors for methane and carbon dioxide for RSM in literature. It was assumed
that the "unidentifiable fraction" and the "miscellaneous" portion of the "identifiable" fraction of RSM will
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Section 9 - Recovered Screened Materials
not contribute to LFG production, as a significant portion of these fractions likely represent sand, soil, small
aggregate, and other non- or poorly-degradable materials. While RSM is produced from CDD processing
facilities, landfill placement of RSM may occur at either CDD landfills or at MSW landfills. Because of
cardboard's prevalence in building material packaging, it is assumed that gas emissions data for cardboard
is representative of that from the degradation of the paper fraction encountered in RSM (as presented in
Figure 9-2).
Table 9-3 presents carbon dioxide and methane emission factors associated with disposal of wood (i.e.
dimensional lumber), cardboard and drywall and provides the mass fraction of these materials in RSM to
estimate the resulting methane and carbon dioxide emissions from RSM disposal in CDD and MSW
landfills. As discussed in Chapter 2, Section 2.5.10.8, these emission factors include 10% oxidation of
uncollected methane into carbon dioxide.
Table 9-3. Methane and Carbon Dioxide Emission Factors for CDD and MSW Landfill Disposal of
Different RSM Components (developed from US EPA (2012))
Material
Wood
Cardboard
Drywall
RSM
Fraction
of RSM
(w/w)
(Jang and
Townsend
2001b)
2.19%
1.59%
1.21%
-
Emissions from CDD
Landfills
Methane
Emissions (kg/kg
wet material)
0.064
0.12
0.010
0.003
Carbon
Dioxide
emissions
(kg/kg
wet
material)
0.21
0.40
0.034
0.011
Emissions from MSW
Landfills
Methane
Emissions (kg/kg
wet material)
0.022
0.042
0.0038
0.0012
Carbon
Dioxide
emissions
(kg/kg
wet
material)
0.33
0.60
0.052
0.017
In addition to the release of methane and carbon dioxide (from the decomposition of drywall paper facings),
the drywall component of RSM will contribute to the production of hydrogen sulfide gas if placed in an
anaerobic environment (Jang and Townsend 2001b, Lee et al. 2006). Anderson et al. (2010) used LFG
hydrogen sulfide concentration data, waste tonnage records, and LFG flow rates from six MSW landfill
sites to estimate the site-specific hydrogen sulfide gas generation potential (cubic feet hydrogen sulfide /ton
sulfur) and first-order decay rates of RSM drywall. Anderson et al. (2010) also collected 89 samples of
CDD fines from CDD processing facilities and landfill sites to estimate a total average CDD fines sulfate
content of 4.3% or a sulfur content of 1.4% (by weight). Therefore, approximately 14 grams of sulfur
would be disposed with every kilogram of RSM. The average hydrogen sulfide generation potential from
four landfill sites that did not monofill CDD fines (i.e., separately place CDD fines in a different location
than incoming MSW) was presented as 5,360 ft3 of hydrogen sulfide per ton of landfilled sulfur. Using a
density of 1.42 grams per liter of hydrogen sulfide at 20° C and 1 atmosphere pressure, this approximately
equates to 3.4 grams of hydrogen sulfide generation per kilogram of RSM disposed. The actual generation
of hydrogen sulfide at a specific site depends on a host of factors (e.g. precipitation, waste composition,
presence of organic matter, cover soil application, and compaction practices). The hydrogen sulfide
generation potential across the four sites described above ranged from 3,186 to 7,634 ft3 of hydrogen sulfide
per ton of landfilled sulfur.
Plaza et al. (2007) performed a laboratory-scale study using drywall degradation in columns to evaluate the
hydrogen sulfide attenuation efficiency of a 15-cm-thick layer of five landfill cover materials, including
fine crushed concrete, coarse crushed concrete, soil amended with lime, sandy soil, and clayey soil. The
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Section 9 - Recovered Screened Materials
sandy and clayey soils were natural soils taken in the vicinity of the lab and were respectively found to have
hydrogen sulfide removal efficiencies of 29.7% and 65.3% compared to control columns where no cover
material was used. An average of these removal efficiencies (47.5%) was used to simulate hydrogen sulfide
attenuation for RSM disposal at an average landfill site. As is evident by the range of hydrogen sulfide
removal efficiencies from naturally-occurring cover soils, actual removal efficiencies are strongly
dependent on the type of soil used. It should also be noted that a 15-cm-thick layer of cover soil is more
representative of the type of cover soil which would be used daily at an MSW landfill and often weekly (or
more or less frequently) at a CDD landfill. Final and intermediate landfill covers will be thicker and would
likely increase hydrogen sulfide attenuation. However, a majority of the hydrogen sulfide emissions would
have occurred prior to final cover placement due to high hydrogen sulfide generation rates. Anderson et al.
(2010) estimated a relatively high hydrogen sulfide generation rate constant, ranging from approximately
0.5 to 0.9 year1. Using the average decay rate constant of 0.702 year1 (calculated from landfills that did not
monofill CDD fines) approximately 75% and 97% of the total hydrogen sulfide emission would occur
within 2 and 5 years, respectively. The final cover, therefore, would only have a limited role in attenuating
hydrogen sulfide emission and the vast majority of hydrogen sulfide gas would likely be mitigated through
daily/weekly covers only.
The GCCS is also estimated to have a limited role in hydrogen sulfide emission attenuation. According to
federal regulations, the gas collection deadline for MSW landfill disposal areas is 2 years for areas that have
reached final grade and 5 years for those areas that have not reached final grade. Therefore, LFG collection
is expected to have a negligible impact on hydrogen sulfide emission from the disposal of RSM at MSW
landfills. The same emissions factor for hydrogen sulfide is assumed for both CDD and MSW landfill sites
in the absence of additional data. Therefore, including the effects of cover soil attenuation, it is estimated
that 0.0018 kg of hydrogen sulfide will be released for every kg of RSM disposed of in a landfill.
Table 9-4 and Table 9-5 present the emission and material burdens associated with CDD and MSW landfill
disposal of RSM, respectively. As described previously, leachable emissions from RSM disposed of in an
MSW landfill are not provided due to the lack of TCLP leaching data. Details describing the calculations
for estimating the quantity of cover soil used and diesel and electricity consumed for operating CDD and
MSW landfills, and the materials and energy requirements for the construction and closure and post-closure
care of MSW landfills are provided in Chapter 2 of this report. The bulk density of RSM as provided by
Jang and Townsend (200Ib) was used to estimate landfill cover soil requirements. In the absence of an
average nationwide transport distance between CDD processing facilities and CDD and MSW landfills, a
distance of 20 km was assumed.
Table 9-4. Proposed LCI Dataset: Recovered Screened Material, at Unlined CDD Landfill
Input Flow
Recovered screen material, from
CDD processing
Cover soil, from offsite source
Truck transport, class 8, heavy
heavy-duty (HHD), diesel, short-
haul, load factor 0.75
CDD landfill operations
Output Flow
Aluminum
Source
See Chapter 2
Assumed
See Chapter 2
Source
Townsend et al.
(2004)
Category
Construction and Demolition Debris
Management
Construction and Demolition Debris
Management
Construction and Demolition Debris
Management
Category
water/groundwater
Unit
kg
kg
t*km
kg
Unit
mg
Amount
1
0.0140
0.001*20
1
Amount
929
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Section 9 - Recovered Screened Materials
Arsenic
Benzene, ethyl
Calcium
Carbon Dioxide
Hydrogen Sulfide
Methane
Phthalate, bis(2-Ethylhexyl)
Phthalate, di-n-Butyl
Recovered screened material, at
unlined CDD landfill
Sulfate
Toluene
Toluene, 4-Isopropyl
Trichlorofluro methane
Trimethylbenzene, 1,2,4-
Xylene, m/p-
Xylene, o-
Zinc
Townsend et al.
(2004)
Townsend et al.
(1998)
Jang and Townsend
(200 Ib)
US EPA (20 12)
Anderson et al.
(2010)
US EPA (20 12)
Townsend et al.
(1998)
Townsend et al.
(1998)
Jang and Townsend
(200 Ib)
Townsend et al.
(1998)
Townsend et al.
(1998)
Townsend et al.
(1998)
Townsend et al.
(1998)
Townsend et al.
(1998)
Townsend et al.
(1998)
Townsend et al.
(2004)
water/groundwater
water/groundwater
water/groundwater
air/unspecified
air/unspecified
air/unspecified
Construction and Demolition Debris
Management/groundwater
Construction and Demolition Debris
Management/groundwater
Construction and Demolition Debris
Management
water/groundwater
water/groundwater
Construction and Demolition Debris
Management/groundwater
Construction and Demolition Debris
Management/groundwater
Construction and Demolition Debris
Management/groundwater
Construction and Demolition Debris
Management/groundwater
water/groundwater
water/groundwater
mg
ug
g
kg
kg
kg
mg
mg
kg
g
ug
ug
ug
ug
ug
ug
mg
176
56
12
0.011
0.0018
0.0034
0.072
0.062
;
30
403
34
289
38
256
122
1330
Table 9-5. Proposed LCI Dataset: Recovered Screened Material, at MSW Landfill
Input Flow
Recovered screen material, from
CDD processing
Cover soil, from MSW landfill
stockpile
Truck transport, class 8, heavy
heavy-duty (HHD), diesel, short-
haul, load factor 0.75
MSW landfill construction, for
CDD materials
MSW landfill operations
MSW landfill closure and post-
closure, for CDD materials
Output Flow
Carbon Dioxide
Source
See Chapter 2
Assumed
See Chapter 2
See Chapter 2
See Chapter 2
Source
US EPA (20 12)
Category
Construction and Demolition Debris
Management
Construction and Demolition Debris
Management
Construction and Demolition Debris
Management
Construction and Demolition Debris
Management
Construction and Demolition Debris
Management
Category
air/unspecified
Unit
kg
kg
t*km
kg
kg
kg
Unit
kg
Amount
1
0.098
0.001*20
1
1
1
Amount
0.017
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Section 9 - Recovered Screened Materials
Hydrogen Sulfide
Methane
Recovered screened material, at
MSW landfill
Anderson et al.
(2010)
US EPA (20 12)
air/unspecified
air/unspecified
Construction and Demolition Debris
Management
kg
kg
kg
0.0018
0.0012
;
9.6 LCI Related to Recycling
The primary beneficial uses of RSM include use as an ADC and use in a general fill application. Both
beneficial uses result in avoidance of the production of natural soil. Soil for use at general fill sites is
typically excavated, transported, and immediately used by the end user. The soil for landfill cover use is
often excavated and temporarily stockpiled onsite before use. The details of LCI proposed for natural soil
excavation, on-site transport, and stockpile (for landfill cover) are presented in Chapter 2.
While RSM has properties that could make it favorable for use in place of traditional soil material (e.g.,
potentially improved drainage and traction during rain), use as an ADC in an anaerobic environment
presents the same hydrogen sulfide production challenges as landfill disposal (Carlton et al. 2005, Musson
et al. 2008). Except for cover soil and landfill operation requirements (i.e., electricity and diesel
consumption for site operation is completely allocated to disposed materials, not cover materials), the use
of RSM as ADC is expected to have the same leachate and gas emissions as RSM placed in a landfill for
disposal. Both disposal sites are assumed to be located 20 kilometers from RSM production.
RSM may be beneficially used in place of natural soil for a general fill. Clark et al. (2010) presents a case
study examining the use of RSM in Florida for grading 60 residential sites located in low-lying areas. RSM
was mixed with onsite soil and placed at these residences to help alleviate historic flooding problems.
Following placement of the material, several of the property owners expressed concern regarding the
potential leaching of RSM contaminants. A follow-up investigation suggested that while the arsenic and
Total Recoverable Petroleum Hydrocarbon (TRPH) concentrations were elevated above Florida soil
cleanup target levels, the concentrations were either in the range of or below area background soil
concentrations and were not at levels which presented a public health threat.
The proposed LCI dataset for the use of RSM as a general fill is presented as Table 9-6. This table includes
the same set of leachable emissions as was estimated for disposal of RSM in a CDD landfill. However, it
is assumed that anaerobic conditions would not develop in the RSM-based general fill, so gas emissions
are not included. The burdens associated with RSM placement and surface grading for an "average" fill
application are unknown and not included in the dataset. The general fill site is assumed to be located 20
km from RSM production.
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Section 9 - Recovered Screened Materials
Table 9-6. Proposed LCI Dataset: Recovered Screened Material, Use in Environment
Input Flow
Recovered screen
material, from CDD
processing
Truck transport, class
8, heavy heavy-duty
(HHD), diesel, short-
haul, load factor 0.75
Output Flow
Aluminum
Arsenic
Benzene, ethyl
Calcium
o-Xylene
Phthalate, bis(2-
Ethylhexyl)
Phthalate, di-n-Butyl
Recovered screen
material, use in
environment
Sulfate
Toluene
Toluene, 4-Isopropyl
Trichlorofluromethane
Trimethylbenzene,
1,2,4-
Xylene, m/p-
Zinc
Source
Source
Townsend et al. (2004)
Townsend et al. (2004)
Townsend etal. (1998)
Jang and Townsend
(200 Ib)
Townsend etal. (1998)
Townsend etal. (1998)
Townsend etal. (1998)
Jang and Townsend
(200 Ib)
Townsend etal. (1998)
Townsend etal. (1998)
Townsend etal. (1998)
Townsend etal. (1998)
Townsend etal. (1998)
Townsend et al. (2004)
Category
Construction and Demolition Debris
Management
Category
water/groundwater
water/groundwater
water/groundwater
water/groundwater
water/groundwater
Construction and Demolition Debris
Management/groundwater
Construction and Demolition Debris
Management/groundwater
Construction and Demolition Debris
Management
water/groundwater
water/groundwater
Construction and Demolition Debris
Management/groundwater
Construction and Demolition Debris
Management/groundwater
Construction and Demolition Debris
Management/groundwater
Construction and Demolition Debris
Management/groundwater
water/groundwater
Unit
kg
t*km
Unit
mg
mg
ug
g
ug
mg
mg
kg
g
ug
ug
ug
ug
ug
mg
Amount
1
0.001*20
Amount
929
176
56
12
122
0.072
0.062
;
30
403
34
289
38
256
1,330
9.7 Data Gap Analysis and Opportunities for Additional LCI Data
Table 9-7 summarizes the extent of the LCI information found for developing the processes discussed in
this chapter. All the data sources found provided information specific to the US. As shown in Table 9-7,
all LCI information found for the management of RSM are partial. WARM LFG emissions are partial
because US EPA (2012) only focuses on major greenhouse gas (GHG) emissions from different
components of RSM - emission estimates for non- and minor GHGs and other LFG emissions are not
included (e.g. hydrogen sulfide, VOCs) . Townsend et al. (1998) and related sources only provide partial
data because non-metal inorganics were not included in the analysis, and only batch SPLP data are
available. Anderson et al. (2010) and Tolaymat et al. (2013) specifically focus on hydrogen sulfide
generation and do not provide emission estimates for other gaseous constituents related to RSM. Based on
a review of currently available LCI data on RSM management, the following data gaps were identified for
RSM process datasets:
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Multimedia Environmental Assessment
Section 9 - Recovered Screened Materials
1. Long-term leachable emissions from RSM placed in a CDD or an MSW landfill. While
Townsend et al. (1998) and related investigations (see Table 9-2) conducted an extensive
characterization of RSM from numerous CDD processing facilities from across the state, including
leaching of heavy metals, VOCs, and semi-VOCs emissions, sample leachability was assessed over
for a L:S ratio of 20. The leaching emission estimates represent only partial leaching amounts.
Jang and Townsend (200 Ib) provide very limited information on SPLP concentrations of non-metal
inorganics (e.g. sulfate, calcium). Moreover, SPLP data simulate contaminant leaching in inert
debris landfills (e.g., CDD landfill) or land application scenarios and cannot be extended to estimate
leaching in biogeochemical environment of an MSW landfill.
2. Gaseous emissions from the anaerobic decay of RSM. No gaseous emission measurements
associated with decomposition of RSM in anaerobic environments are reported in the literature.
Methane and carbon dioxide emissions estimates presented above are based on the mass fraction
of specific organic constituents in RSM. Reported hydrogen sulfide measurements have either
been measured from the decay of composite MSW (which may have other materials contributing
to the release of hydrogen sulfide) or from the individual decay of drywall. Gaseous emission
measurements from the actual material would provide a better estimate than measurements of
individual components of the material.
3. Average nationwide transport distances between CDD processing facilities and
disposal/beneficial use sites. These distances are of particular importance for the development of
comparative LCA to analyze the potential benefit or burden of beneficially using RSM as a
substitute for natural soil.
Table 9-7. Overview of LCI Data Available
Process
Landfill Gas
Emissions
Landfill Leachate
Emissions
General Fill
Leachate Emissions
WARM
P
Townsend et al.
(1998) and
related
P
P
Anderson et al.
(2010)
P
Tolaymat et al.
(2013)
P
9.8 References
Anderson, R., Janbeck, J.R., McCarron, G.P. (2010) Modeling of Hydrogen Sulfide Generation from
Landfills Beneficially Utilizing Processed Construction and Demolition Materials. A Report
Prepared for the Environmental Research and Education Foundation
Alexandria, VA. February 2010.
Barlaz, M.A. (1998). Carbon Storage During Biodegradation of Municipal Solid Waste Components in
Laboratory-Scale Landfills. Global Biogeochemical Cycles, 12 (2), 373-380.
Barlaz, M.A., Ham, R.K., Schaefer, D.M. (1989). Mass Balance Analysis of Decomposed Refuse in
Laboratory Scale Lysimeters. Journal of Environmental Engineering, ASCE, 115 (6), 1088-1102.
Calhoun, A.B., (2012). Impact of Construction and Demolition Debris Recovery Facilities on Job Creation
and the Environment in Florida. MS. Thesis. University of Florida, Gainesville, FL, USA.
Carlton, J.G., Zelley, R.L., McCarron, G.P. (2005). Case Study: The Impact of Construction and Demolition
Debris Screenings on Landfill Gas Quality
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Multimedia Environmental Assessment Section 9 - Recovered Screened Materials
Clark, B.S., Clewner, M., Medico, P.T., Bermudez, F.J., Wilkins, R.G., Coleman, R.M., Teaf, C.M. (2010).
Beneficial use of C&D Recovered Screen Material in Residential Applications: a Case Study.
Proceedings of the Annual International Conference on Soils, Sediments, Water and Energy, 11,
Article 25.
Doka, G. (2009). Life Cycle Inventories for Waste Treatment Services, Part V: Building Material Disposal.
Ecoinvent Report No. 13,Swiss Centre for Life Cycle Inventories, Dubendorf. December 2009.
Jang, Y.-C., Townsend, T.G. (200la). Occurrence of Organic Pollutants in Recovered Soil Fines from
Construction and Demolition Waste. Waste Management, 21, 703-715.
Jang, Y.-C., Townsend, T.G (2001b). Sulfate Leaching from Recovered Construction and Demolition
Debris Fines. Advances in Environmental Research, 5, 203-217.
Lee, S., Xu, Q., Booth, M., Townsend, T.G., Chadik, P., Bitton, G. (2006). Reduced Sulfur Compounds in
Gas from Construction and Demolition Debris Landfills. Waste Management, 26, 526-533.
Marvin, E. (2000). Gypsum Wallboard Recycling and Reuse Opportunities in the State of Vermont. Waste
Management Division, Vermont Agency of Natural Resources. August 2000.
Musson, S.E., Xu, Q., Timothy, T.G. (2008). Measuring the Gypsum Content of C&D Debris Fines. Waste
Management, 28, 2091-2096.
Plaza, C.P., Xu, Q., Townsend, T., Bitton, G., Booth, M. (2007). Evaluation of Alternative Landfill Cover
Soils for Attenuating Hydrogen Sulfide from Construction and Demolition (C&D) Debris
Landfills. Journal of Environmental Management, 84, 314-322.
Tolaymat, T.M., El Badawy, A.M., Carson, D.A. (2013). Estimate of the Decay Rate Constant of Hydrogen
Sulfide from Drywall in a Simulated Bench-Scale Study. Journal of Environmental Engineering,
ASCE 139, 538-544.
Townsend, T., Tolaymat, T., Leo, K., Jambeck, J. (2004). Heavy Metals in Recovered Fines from
Construction and Demolition Debris Recycling Facilities in Florida. Science of the Total
Environment, 332, 1-11.
Townsend, T.G., Jang, Y.-C., Lee, S., Leo, K., Messick, B., Tolaymat, T., Weber, W., (1998).
Characterization of Recovered Screened Material from C&D Recycling Facilities in Florida. The
Florida Center for Solid and Hazardous Waste Management investigation report 98-13, University
of Florida, Gainesville, FL, USA.
US EPA (2012). EPA Waste Resources Model, Landfilling, WARM Version 12. United States
Environmental Protection Agency.
US EPA (2014). Methodology to Estimate the Quantity, Composition, and Management of Construction
and Demolition Debris in the United States. A Report Prepared by Innovative Waste Consulting
Services, LLC and Pegasus Technical Services, Inc. for the United States Environmental Protection
Agency, June 2014, Unpublished report.
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Multimedia Environmental Assessment
Section 10 - Clay Bricks
10 Clay Bricks
10.1 Introduction
Clay bricks represent a relatively small fraction of the total CDD material stream and are commonly
generated from the demolition of buildings, structures, and pavements. The quantity of clay bricks
produced from demolition will vary depending on the building composition. Most clay bricks are produced
from common clay and shale, a material obtained from mining and excavation which must go through an
extensive drying and extrusion process prior to kiln firing. Clay bricks are primarily manufactured for
structural construction purposes, which require the use of common face brick, with over 3.3 billion clay
bricks being produced in 2008 in the US; this quantity accounts for 60% of the nationwide total annual
production of all brick types (USCB 2011). According to USGS, close to 15.9 MMT of common clay was
mined and nearly 57% of this was used for clay brick production (USGS 2008). Figure 10-1 shows the
typical flow of clay bricks from the primary extraction and processing through the EOL management of
clay bricks. The processes from the EOL removal of clay brick to their ultimate beneficial reuse or landfill
disposal should all be considered for conducting an LCA for EOL management.
Landfilling
Raw Material
Processing of
Clay & Shale
Clay Brick
Production (Kiln)
Retail/
Wholesale
In Service
End-of-Life
Removal
Crushing
Landscape
Material
Use as
Aggregate
Figure 10-1. Material Flows for Production through EOL Management of Clay Bricks
The clay extraction and brick manufacturing processes are not presented in detail in this chapter as clay
bricks are not recycled in closed loop (US EPA 2012a). The emissions associated with processing clay
bricks to produce recycled aggregate should be considered for EOL LCA.
10.2 EOL Management
US EPA (2012b) estimates that 1 to 5% of CDD is comprised of bricks. Approximately 136 MMT of CDD
were generated in 2011 (US EPA 2014), suggesting that approximately 1.4 to 6.8 MMT of bricks were
discarded in 2011. Disposal appears to be the dominant EOL management option for clay bricks. Only
limited amounts of discarded clay bricks are recycled. Due to concerns about structural strength, reuse of
salvaged bricks in load-bearing applications is not recommended (Webster 2002); salvaged clay bricks are
sometime reused in non-structural application such as brick fireplaces, hearths, patios, and other uses (US
EPA 2012a). Reza (2013) and Cavelline (2012) reported that typical brick recycling practices include reuse
as a replacement for aggregate in structural fills or pavements. Recovered clay bricks should be processed
prior to use as aggregate.
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Multimedia Environmental Assessment
Section 10 - Clay Bricks
Table 10-1 lists the processes that should be considered for conducting an LCA of EOL management
options for clay bricks. Primary aggregate production and general material transport LCI datasets are
relevant for multiple CDD materials in this report and are presented and discussed in detail in Chapter 2.
Table 10-1. Clay Brick EOL Management Process Descriptions
Process
Building Demolition
Landfill Disposal
Clay Brick Processing
Crushed Clay Brick Use
as Aggregate
Description
The material and energy inputs as well as process non-energy emissions
(e.g., particulate matter emission) associated with building demolition
should be considered.
Landfilling entails the placement and compaction of bricks and their long-
term physiochemical decomposition in a landfill environment.
Discarded clay brick processing may include sorting, crushing, and
fractionation (i.e., sorting into different size categories).
Recycled aggregate produced from clay bricks may be used as a primary
aggregate substitute in a fill application. Primary aggregate production
and transport emissions would be avoided with the use of clay bricks as an
aggregate material.
10.3 LCI Sources
Peer-reviewed literature and government and private industry publications were reviewed to identify
available LCI datasets pertaining to clay brick EOL management. WARM documentation was the only
source of US-based data found for EOL management-related data for bricks. Table 10-2 lists data sources
reviewed to compile LCI presented in this chapter. If LCI data were not available, process metadata and
documentation were reviewed to evaluate the completeness of applicable datasets (e.g., which emissions
categories were included, background data used to compile the dataset, geographic location, and time period
of the data). The primary sources of information used to develop the LCI datasets and information
identified, if available, were reviewed. It should be noted that the sources presenting clay brick production
LCI are not listed in the table as clay bricks recycling in closed loop is not prevalent.
Table 10-2. List of Sources Reviewed
LCI Source
Karius and Hamer
(2001)
USEPA(2012a)
Ecoinvent
Description
This German study compares total concentration and leaching data from bricks
made with 50% dredged harbor sediment to leaching data from manufactured
bricks pulled from other European brick companies.
The WARM Model presents data on GHG emissions associated with the source
reduction, transport, and landfilling (i.e., collection and placement) of clay
bricks. While clay brick recycling was mentioned, no LCI data were presented.
Ecoinvent is an LCI database developed by the Swiss Centre for Life Cycle
Inventories, which includes specific processes related to the EOL management
of numerous individual materials.
10.4 LCI Related to Disposal
The primary EOL management method for bricks in the US is landfill disposal. While the Ecoinvent (2014)
database includes processes for handling waste bricks, the model assumes the placement of bricks in an
inert debris landfill for which leachate emissions are not included (Doka 2009). Similar to all the other
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Multimedia Environmental Assessment Section 10 - Clay Bricks
materials modeled in WARM, US EPA (2012a) estimates GHG emissions released from fossil fuel
combustion resulting from the transport to and placement of demolished clay bricks at a landfill. Since clay
bricks are an inert material, they do not undergo biological decomposition.
A literature review only yielded international leaching test results for clay bricks. Karius and Hamer (2001)
conducted a series of leaching tests (pH static tests with a L:S-ratio of 10) on bricks made from clay and
dredging sediments from local water body to assess the impact of the sediments on leaching of 20
contaminants, including metals and sulfur. The tests were conducted on crushed bricks (grain size ranged
from 50 to 30,000 (im) made with and without sediment. In general, the heavy metals from the sediment
bricks leached at the upper end of the concentration ranges for the bricks made without sediments.
While the transportation, diesel, and electricity requirements for the landfill disposal of clay bricks would
be the same on a mass-fraction basis regardless of the type of material, due to lack of data the liquids
emissions from brick disposal in a landfill are unknown and an LCI dataset was not developed.
10.5 LCI Related to Recycling
10.5.1 Clay Brick Demolition
Doka (2009) presented building materials demolition-, recycling-, and disposal-related LCI as part of the
Ecoinvent database based on management practices in Switzerland. Energy consumption and air emission
estimates from the study were derived from other studies that were done in the European Union. Equipment
demolition efficiencies (i.e., the time spent per volume of waste demolished) and fuel consumption rates
were compiled from literature to estimate the energy required to demolish brick wall, gypsum board, and
cement-fiber slab as 0.0359 MJ/kg. Particulate matter is a major non-fuel air emission associated with
demolition activities. Doka (2009) included an air emissions factor of 80 mg PMio/kg of demolition waste
for all building construction, demolition, and renovations activities. AP-42 provides air emission factor
calculation methods for various heavy construction operations, which include dust generation activities
from the demolition of buildings and removal of debris as a function of various factors such as site-specific
conditions and equipment used (US EPA 1995).
10.5.2 Clay Brick Sorting
Prior to recycling, discarded clay bricks in the mixed CDD waste stream would undergo sorting operations
in which bricks are separated from other materials. While Doka (2009) reported energy requirements of
CDD materials sorting and size reduction specific to European practices, US-specific data regarding brick
processing are lacking. Please see Chapter 2 for more details regarding the development of an LCI dataset
for modeling and allocating the environmental burdens of a mixed CDD processing facility.
10.5.3 Clay Brick Use as Aggregate
While clay brick recycling does not appear to be heavily practiced in the US, limited beneficial applications
of recovered clay brick as aggregate have been documented (Cavalline 2012, Reza 2013). The Minnesota
Department of Transportation conducted a study in 2013 to test the feasibility of reusing bricks in aggregate
for road base; the study showed the material met department specifications (Reza 2013). Cavalline (2012)
explored the potential use of clay brick rubble as a possible replacement for aggregate in building and
pavement concrete mixtures with a focus on the mechanical and engineering properties of brick aggregate.
Cavalline (2012) reported that recycled brick may provide acceptable performance when used in pavement
and shows promise for use in structural applications. The recovered bricks would need to be size reduced
for use as aggregate. US-specific energy requirement and emission data specific to clay bricks processing
are lacking.
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Multimedia Environmental Assessment Section 10 - Clay Bricks
Similar to other CDD materials that may be processed and beneficially reused as aggregate, the use of
demolished clay brick aggregate would offset the production and transport of primary aggregate materials.
LCI datasets for primary aggregate production are presented and detailed in Chapter 2 of this report. Due
to the lack of gaseous and liquid emission and energy requirement data, LCI for processing and use of clay
bricks as recycled aggregates were not developed.
10.6 Data Gap Analysis and Opportunities for Additional LCI Data
Most LCI information on the EOL management of clay bricks is not specific to practices in the US; the US
EPA (2012a) was the only source of information that provided US-specific data, but these data only
included GHG emissions factors for source reduction and landfill of clay bricks. Based on a review of
government publications, peer-reviewed literature, and industry data, the following US-specific LCI data
gaps were identified with respect to bricks EOL management:
1. Energy requirements for sorting/processing clay bricks at a CDD processing facility. Clay
bricks that are part of a mixed CDD stream would be recovered at a CDD processing facility;
recovery may include separating, grinding, and fractioning operations (depending on the end-use
market). Although diesel consumption data for typical CDD materials sorting operation are
available (presented in Chapter 2), size-reduction processing energy requirements and associated
emissions specific to brick are lacking.
2. Long-term leachable emissions from bricks placed as aggregate (e.g., in a fill) or in a landfill.
No US-specific leaching data from clay brick are available to estimate liquids emission from brick
placement in a landfill or from beneficial use application as aggregate or fill material.
10.7 References
Cavalline, T.L. (2012) Recycled Brick Masonry Aggregate Concrete: Use of Recycled Aggregates from
demolished Brick Masonry Construction in Structural and Pavement Grade Portland Cement
Concrete. Ph.D. Dissertation. University of North Carolina, Charlotte, NC, USA.
Doka, G. (2009). Life Cycle Inventories of Waste Treatment Services, Part V: Inventory of Building
Material Disposal. Ecoinvent Report No. 13, Swiss Centre for Life Cycle Inventories, Dubendorf,
April 2009.
Ecoinvent (2014). Swiss Center for Life Cycle Inventories: Ecoinvent Centre. Dataset Information (UPR):
Treatment of Waste Asphalt, Sanitary Landfill, CH, (Author: Roland Hischier inactive).
http://bit.lv/ltRWFED. Accessed 16 July 2014.
Karius, V., Hamer, K. (2001). pH and Grain-Size Variation in Leaching Tests with Bricks Made of Harbour
Sediments Compared to Commercial Bricks. The Science of the Total Environment, 278 (1-3^ 73-
85.
Reza, F. (2013). Use of Recycled Bricks in Aggregates. A Report Prepared by Farhad Reza, Published by
the Minnesota Department of Transportation. Mankato, MN, USA. August 2013.
US EPA (1995). AP 42, Fifth Edition, Volume I, Chapter 13: Miscellaneous Sources, Section 13.2.3: Heavy
Construction Operations.
US EPA (2012a). Clay Bricks. Documentation Prepared by U.S. Environmental Protection Agency for the
Waste Reduction Model, Version 12, February 2012.
US EPA (2012b). Basic Information. http://l.usa.gov/lmW4C77. Accessed 17 July 2014.
US EPA (2014). Methodology to Estimate the Quantity, Composition, and Management of Construction
and Demolition Debris in the United States. A Report Prepared by Innovative Waste Consulting
Services, LLC and Pegasus Technical Services, Inc. for the U.S. Environmental Protection Agency,
June 2014, Unpublished report.
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USCB (2011). Clay Construction Products - Summary 2010. MQ327D(10)-5. U.S. Census Bureau,
Washington, D.C., USA. May 2011. http://l .usa.gov/WmLqW4. Accessed 20 March 2014.
USGS (2008). Clays Statistics and Information. Mineral Commodity Studies. http://on.doi.gov/lpj6Pri.
Accessed 16 July 2014.
Webster, M. (2002). The Use of Salvaged Structural Materials in New Construction. Presentation Posted
on the U.S. Green Building Council Website, November. As cited in http://l.usa.gov/lAuuNax.
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Multimedia Environmental Assessment
Section 11 - Summary and Future Research Needs
11 Summary and Future Research Needs
11.1 Summary
The objective of the work presented in this report was to assess the body of knowledge regarding CDD life-
cycle data and to compile US-specific LCI for distinct CDD material categories from publicly available
sources. In the previous chapters, available LCI data for processes common to all CDD (Chapter 2) as well
as LCI data for eight specific CDD materials (Chapters 3-10) were presented. While the eight materials
examined (asphalt pavement, asphalt shingles, gypsum drywall, wood products, LCD, PCC, RSM, and clay
bricks) do not represent every component of CDD, they do comprise more than 95% of the total CDD
materials generated annually in the US.
As described in the introduction to this report, CDD has not received the degree of attention with respect
to environmental emissions or other life-cycle considerations that other waste streams have. Thus, for many
LCI categories, US-specific data were not available from publicly available sources. In addition, some of
the available data that were used to develop an LCI category were not complete or were approximated by
using LCI data from similar materials. Each chapter thus ends with a description of LCI data gaps.
In this final chapter, the data gaps highlighted in the individual chapters are summarized. Table 11-1
presents a summary of processes; associated energy and materials inputs; as well as the gaseous, liquid and
solid emissions included in the LCI datasets developed. An "X" denotes that data are included in the
developed LCI category, though it does not indicate that all flows were included and/or quantified, only
information that was found for that category. Product manufacturing process LCI were evaluated only for
those CDD materials that are currently recycled in a closed loop. Construction materials manufacturing and
production LCI that were found to be appropriate for CDD LCI but that are contained in existing US NREL
or US EPA LCI datasets were not reproduced in this report.
Table 11-1. Summary of CDD Material LCI Process Datasets and Flows Included in the Report
Material
Granite: Crushed and
Broken
Construction Sand and
Gravel
Limestone: Crushed
and Broken
Other Stone: Crushed
and Broken
Natural Soil from
Borrow Pit
Asphalt Pavement
Process
Production and Transport
Production and Transport
Production and Transport
Production and Transport
Excavation
HMA production
Reclaimed asphalt
pavement processing
Energy
Input
X
X
X
X
X
X
X
Material
Input
Emissions
Air
X
X
X
X
X
Water
Land
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Multimedia Environmental Assessment
Section 11 - Summary and Future Research Needs
Material
Asphalt Shingles
Gypsum Drywall
Wood Products
LCD
Process
Use for HMA production2
Use as aggregate
Disposal in CDD landfill
Disposal in MSW landfill
Use for HMA production1
Reclaimed asphalt shingle
processing
Use as aggregate
Use as general fill
Disposal in CDD landfill
Disposal in MSW landfill
Facing and backing paper
production
Virgin gypsum production
1/2" Regular and 5/8" Type
X drywall manufacturing
Drywall processing-size
reduction and screening
Use in agricultural
application
Disposal in CDD landfill
Disposal in an MSW
landfill
Mulch production and land
application
Combustion with energy
recovery3
Disposal in CDD landfill
(untreated/treated)
Disposal in MSW landfill
(untreated/treated)
Ash disposal in CDD
landfill
Ash disposal in MSW
landfill (untreated/treated)
Ash land application
Size reduction
Mulch production and land
Energy
Input
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Material
Input
X
X
X
X
X
X
X
X
X
Emissions
Air
X
X
X
X
X
X
X
X
Water
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Land
X
X
X
X
2 These processes only represent the use of recycled materials to substitute primary materials - specific emissions for
these processes were not quantified.
3 An LCI dataset for this process is already provided in the US EPA LCI database - however, proposed modifications
were made for this process to account for moisture content and ash production
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Section 11 - Summary and Future Research Needs
Material
PCC
RSM
Clay Bricks
Mixed CDD
Process
application
Compost production and
land application
Disposal in CDD landfill
Disposal in MSW landfill
Open burning
Air curtain incineration
Combustion with energy
recovery2
Ash disposal CDD landfill
Ash disposal in MSW
landfill
Ash land application
Use as aggregate
Size reduction
Use as general fill
Disposal in CDD landfill
Disposal in MSW landfill
Use as general fill
Disposal/Use as cover in
CDD landfill
Disposal/Use as cover in
MSW landfill
Use as aggregate
Use as general fill
Disposal in CDD landfill
Disposal in MSW landfill
CDD recovery at
processing facility
Energy
Input
X
X
X
X
X
X
X
X
X
X
X4
Material
Input
X
X
X
X
X
X
Emissions
Air
X
X
X
X
X
X
Water
X
X
X
X
X
X
X
Land
X
X
11.2 Data Gaps and Future Research Opportunity
Based on the data gaps highlighted earlier in the report and that can be inferred from the table above, future
data-gathering and research opportunities have been identified. The following sections highlight major LCI
data categories pertaining to CDD materials and summarize their associated data gaps and identified
research needs.
EOL management practices of CDD materials
Of all the CDD materials reviewed during this study, only the EOL management practices of asphalt
pavement were found to be substantially well-documented and quantified; NAPA has been conducting a
1 Only diesel consumption information was found - process electricity use still needs to be assessed.
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U.S.-wide annual survey of paving mix producers since 2009 to track uses of asphalt pavement reclaimed
from road construction and maintenance projects. Although the USGS also compiles and reports the
amounts of RAP- and PCC-derived recycled aggregates in the US based on a survey of aggregate producers
and C&D contractors, the data are incomplete because of survey limitations. For other materials, data on
the amount of materials managed via different EOL management options (e.g., recycled versus disposed)
are very limited.
Many state environmental agencies track the statewide amount of CDD materials landfilled annually, but
only four states (Florida, Massachusetts, Nevada, and Washington) appear to closely track the amount of
materials recycled. Due to this lack of EOL management recycling data and because of the interest of
multiple government agencies (e.g., USGS, U.S. DOE, U.S. EPA, FFiWA, state environmental and
highway) and industry organizations (e.g., NAPA, CDRA) in analyzing this information, there is an
opportunity for collaborative research on the quantification of CDD materials EOL management practices.
CDD Material Processing LCI
CDD materials require some degree of processing prior to use in open- or closed-loop recycling
applications. CDD materials processing facilities require energy (e.g., electricity, diesel) and material (steel
used for building and equipment used for processing) inputs and release process energy and non-energy
emissions. Only a few of sources were identified to have reported CDD materials processing energy
requirements (Wilburn and Goonan 1998; Cochran 2006). Moreover, the available estimates are based on
limited data.
It is expected that most CDD material processors track basic energy demands (e.g., daily, weekly, or
monthly fuel and electricity usage) and material input data. If compiled, these data could provide valuable
input for more reliable estimates of CDD material processing energy requirements. The CDRA and the
University of Florida are currently conducting a nationwide survey of CDD materials recyclers to
characterize CDD recycling facilities in terms of material throughput, jobs, and energy use (among others).
Several federal agencies (e.g., the U.S. EIA and the U.S. Census Bureau) routinely survey U.S. industries
to collect various economic and labor data - addition of material and energy usage could potentially
supplement these existing surveys, and the results could be used to develop LCI. Although a NAICS code
exists for "material recovery facilities (56292), this corresponds to establishments that handle MSW.
Establishment of a new NAICS code for CDD materials recyclers would facilitate collection and
aggregation of key materials and energy input data on a routine basis. NAICS was developed to be a
dynamic industry classification and the classification is reviewed every 5 years to identify new or emerging
industries. There is a proposal solicitation currently underway for new and merging industries for inclusion
in the 2017 list, which presents an opportunity to include CDD recyclers with a unique NAICS code.
CDD Materials Transport
For the LCI presented in this report, a uniform transport distance of 20 km was assumed between the point
of generation and the next step of management (e.g., processing facility, landfill). Different transport
distances would impact the results of an LCA, but such detailed data are not currently available. This data
gap could be addressed in several ways. First, the U.S. Census Bureau's commodity flow survey, which
provides estimates of the distances various commodities are transported via different modes, represents an
opportunity to include waste haulers, recyclers, and material processors in the future surveys to estimate
the transport distances of CDD materials. The current commodity flow survey includes "waste and scrap,"
but details regarding the materials included and the universe of entities surveyed for the analysis are not
available. A second option would be to conduct direct research of facilities by compiling average or typical
transport distances for a variety of CDD management facility sizes (i.e., material quantity accepted) in
different geographic areas (e.g., each of the 10 U.S. EPA regions).
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Multimedia Environmental Assessment Section 11 - Summary and Future Research Needs
Long-Term Liquid Emissions from Materials Deposited in Landfills
None of the U.S.-specific LCA models (WARM, MSW-DST) include liquid emissions from the disposal
of materials at a CDD landfill. As discussed in the report, some MSW waste categories can be used as
proxies for estimating liquid emissions from a few of CDD materials, and some European databases (e.g.,
Ecoinvent) include liquid emissions from CDD material disposal in a sanitary landfill. Although liquid
emissions based on laboratory leaching data (SPLP and TCLP) for specific CDD components were
presented in this analysis, this approach has limitations and additional research must be conducted to
provide a more comprehensive and realistic view of liquids emissions at operating facilities. Example
research areas include:
• Identifying realistic L:S ratios for establishing a leaching test framework to assess liquids
emissions from a LCA perspective
• Including a larger listing of leached chemicals
• Including biological processes that result in leaching in addition to physico-chemical processes
• Including aggregated CDD materials rather than specific components, as the leaching behavior
of a specific CDD component may differ in the presence of another CDD component (or, in like
fashion, MSW components)
• The impact of the management of sludge from wastewater treatment plant used for treating
leachate on the overall release of metals into the environment.
Long-Term Gaseous Emissions from Materials Deposited in Landfills
Gaseous emission estimates presented in this report only included methane, carbon dioxide, and (to a lesser
extent) hydrogen sulfide and these estimates have several notable limitations. Methane generation potential
(based on research conducted at North Carolina State University) for branches and OCC were used as a
proxy to estimate the methane and biogenic carbon dioxide emissions for wood/LCD and gypsum drywall
(paper fronting and backing), respectively. The researchers at North Carolina State University estimated
methane generation potential of various MSW constituents based on bioassays conducted in 2-L reactors.
These data have been widely used by various LCA models (e.g., WARM, MSW-DST). Although multiple
studies investigated hydrogen sulfide emissions from drywall disposal in landfills, the hydrogen sulfide
generation potential specifically as a result of drywall and RSM disposal in CDD landfills has not been
reported. Hydrogen sulfide generation estimates have been the result of either laboratory testing or from
the bulk disposal of MSW (which may contain other sulfur-containing materials). Measurements specific
to CDD materials from larger-scale studies should be considered for future research to provide a better
estimate of the emissions of major (i.e., carbon dioxide, methane) and minor (hydrogen sulfide, non-
methane organic compounds) LFG constituents.
Several studies have documented how the cement in concrete can absorb atmospheric carbon dioxide over
time in a process called carbonation. This mechanism of carbon dioxide uptake was not included in the
LCI presented for concrete. Future studies should consider measurements of carbon dioxide uptake by
concrete disposed of in landfills or used in other recycling applications.
Long-Term Performance of Recycled Material-Derived Products and Services
Although the use of recycled materials to replace primary resource extraction would generally reduce the
overall impact on the environment, additional factors may reduce the anticipated benefits of recycling. For
example, pavement made from recycled concrete aggregate and/or RAP may have a shorter service life
compared to pavements manufactured entirely from primary materials. Additional research should attempt
to quantify the serviceable life of materials manufactured from recycled materials on a per-mass-recycled
basis and account for this lifespan difference in developing and updating LCI process datasets.
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Multimedia Environmental Assessment Section 11 - Summary and Future Research Needs
Capital Equipment and Land Development Burdens
Most LCI/LCA disregard emissions associated with the manufacturing of equipment and materials (e.g.,
steel, concrete used for facility construction) used for processing CDD materials. A common justification
provided for this exclusion is that the environmental burdens associated with the manufacturing and
production of products/equipment is generally inconsequential when compared to the impacts of the
operations phase. Future research should consider assessing the impact of the exclusion of capital
equipment burdens from LCA.
Furthermore, the process of greenfield development may disrupt naturally-occurring environmental
services. While some LCA programs (e.g., Ecoinvent) and LCI datasets (e.g., Stripple 2001) attempt to
quantify the environmental impact of land transformation and land-clearing activities (e.g., loss of carbon
sequestration associated with biomass loss), there are other services that natural ecosystems provide that
are more challenging to quantify (e.g., wetland treatment of stormwater runoff or process waters discharged
from adjacent industry, the effect of noise cancellation provided by vegetation on undeveloped land
between highways and neighborhoods). Without a consistent methodology to place a value on the
environmental services provided by undeveloped land, realistic environmental burdens associated with land
development are difficult to allocate. Additional research efforts should attempt to analyze and quantify the
average environmental services provided by undeveloped land in the U.S.
Decommissioning and Disposal Burdens
Similar to capital equipment burdens, a majority of LCI do not quantify the impacts of facility/equipment
decommissioning/disposal for the same reason described above. However, the manner in which a process-
dedicated piece of equipment is managed at the EOL may have a significant impact on the overall emissions
associated with that process. For example, if all the steel recovered from landfill operations equipment
(e.g. compactors, excavators, dozers) was recycled for the production of new landfill operations equipment,
the capital equipment burdens associated with virgin iron ore extraction and smelting would be avoided.
Operation and Maintenance Consumable Burdens
While it is likely that the bulk of emissions resulting from the operation of a particular process would occur
as a result of energy use, almost all equipment requires the replacement of various fluids, filters, and worn
mechanical components over the course of its service life. The environmental burdens resulting from the
production of these consumable materials should be accounted for during the future development of LCI;
until these emissions are quantified, it is not possible to estimate their impact on the overall emissions
associated with that particular process.
11.3 References
Wilburn, D.R., Goonan, T.G. (1998). Aggregates from Natural and Recycled Sources: Economic
Assessments for Construction Applications - A Materials Flow Analysis. US Geological Survey
Circular 1176, US Geological Survey and US Department of the Interior.
Cochran, K. M. (2006). Construction and Demolition Debris Recycling: Methods, Markets and Policy.
Ph.D. Dissertation, University of Florida, Gainesville, FL, USA.
Stripple, H. (2001). Life Cycle Assessment of Road - A Pilot Study for Inventory Analysis, 2nd Revised
Edition. A Report Prepared by the IVL Swedish Environmental Research Institute for the Swedish
National Road Administration, March 2001. http://bit.lv/lk623dN. Accessed 20 February 2014.
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