SOLID WASTE MANAGEMENT IN PUERTO RICO:
AN ASSESSMENT OF ENVIRONMENTAL IMPACTS AND BENEFITS
A THESIS
SUBMITTED TO THE GRADUATE SCHOOL
IN PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE
MASTER OF SCIENCE
NATURAL RESOURCES AND ENVIRONMENTAL MANAGEMENT
BY
JOSÉ F. MARTÍNEZ-COLÓN
JAMES EFLIN, PH.D.
BALL STATE UNIVERSITY
MUNCIE, INDIANA
JULY 2011
In loving memory of my father:
Aníbal Martinez Rivera
May he rest in God’s divine glory.
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ACKNOWLEDGMENTS
I would like to express my gratitude to the professors in my thesis committee: Dr. James
Eflin, Dr. John Pichtel, and Dr. Petra Zimmermann. I would like to thank also the following
individuals for their time and contribution to this project: Ivette Nazario, Director of the GIS
Office at the Puerto Rico Highway and Transportation Authority, and Margarita Dijols and
Edwin Rosario, employees of the Solid Waste Authority of Puerto Rico. In addition, I would like
to acknowledge the support and friendship of all other faculty members and staff of the
Department of Natural Resources and Environmental Management at Ball State University.
Finally, I greatly appreciate the support of my family, especially my mother, Carmen Milagros
Colón, for her encouragement and support through this process.
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TABLE OF CONTENTS
ACKNOWLEDGEMENTS
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LIST OF FIGURES
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LIST OF TABLES
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LIST OF EQUATIONS
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ABSTRACT
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CHAPTER I: INTRODUCTION
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CHAPTER II: LITERATURE REVIEW
2.1 History of Solid Waste Management
2.2 Solid Waste Management Options
2.3 Overview of Climate Change and Greenhouse Gases (GHG)
2.3.1 GHGs and Solid Waste Management
2.3.1.1 Landfilling
2.3.1.2 Recycling
2.3.1.3 Composting
2.3.1.4 Source Reduction
2.3.1.5 Combustion/Waste-to-Energy
2.3.2 Modeling GHG Emissions in Solid Waste Management
2.3.2.1 Waste Reduction Model (WARM)
2.4 Geographic Information Systems and Solid Waste Management
2.5 Site of Study: Puerto Rico
2.5.1 General Features
2.5.2 Climate Change and Puerto Rico
2.5.3 Solid Waste Management in Puerto Rico
2.5.4 Waste Characterization for Puerto Rico
2.5.5 Energy Use and Production in Puerto Rico
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CHAPTER III: METHODS
3.1 WARM Inputs
3.1.1 WARM Alternative Scenario 1 (“Base Case”)
3.1.2 WARM Alternative Scenario 2 (“Backup Case”)
3.1.3 WARM Business-as-Usual Scenario (“No Action Case”)
3.2 Transportation of MSW
3.3 Study Assumptions and Limitations
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CHAPTER IV: RESULTS AND DISCUSSION
4.1 Transportation Analysis
4.1.1 Transportation in “Base Case”
4.1.2 Transportation in “Backup Case”
4.1.3 Transportation in “No Action Case”
4.1.4 Summary of Transportation Analysis
4.2 Greenhouse Gas Emissions Analysis
4.2.1 Emissions in “No Action Case”
4.2.2 Emissions in “Backup Case”
4.2.3 Emissions in “Base Case”
4.2.4 Summary of Greenhouse Gas Emissions Analysis
4.3 Energy Use Analysis
4.3.1 Energy Use in “No Action Case”
4.3.2 Energy Use in “Backup Case”
4.3.3 Energy Use in “Base Case”
4.3.4 Summary of Energy Use Analysis
4.4 Considerations about Proposed MSW Scenarios
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CHAPTER V: CONCLUSION
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REFERENCES
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APPENDICES
I. MSW Hauling Origins and Destination: “Base Case” 2010
II. MSW Hauling Origins and Destination: “Base Case” 2020
III. MSW Hauling Origins and Destination: “Base Case” 2030
IV. MSW Hauling Origins and Destination: “Backup Case” 2010
V. MSW Hauling Origins and Destination: “Backup Case” 2020
VI. MSW Hauling Origins and Destination: “Backup Case” 2030
VII. MSW Hauling Origins and Destination: “No Action Case” 2010
VIII. MSW Hauling Origins and Destination: “No Action Case” 2020
IX. MSW Hauling Origins and Destination: “No Action Case” 2030
X. WARM Greenhouse Gas Emission Factors (MTCO2E per short ton)
XI. WARM Greenhouse Gas Emission Factors (MTCE per short ton)
XII. WARM Energy Use Factors (million BTU per short ton)
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LIST OF FIGURES
1. Life Cycle of Products and Waste Management
2. Municipalities of Puerto Rico
3. Generalized Topography of Puerto Rico
4. Current MSW Management Infrastructure
5. Waste Characterization for Puerto Rico (% by weight)
6. MSW Management Infrastructure for "Base Case," 2010
7. MSW Management Infrastructure for "Base Case," 2020
8. MSW Management Infrastructure for "Base Case," 2030
9. MSW Management Infrastructure for "Backup Case," 2010
10. MSW Management Infrastructure for "Backup Case," 2020
11. MSW Management Infrastructure for "Backup Case," 2030
12. MSW Management Infrastructure for "No Action Case," 2010
13. MSW Management Infrastructure for "No Action Case," 2020
14. MSW Management Infrastructure for "No Action Case," 2030
15. Road Network of Puerto Rico (highways only)
16. MSW Hauling Distances: Municipalities – Landfills (“Base Case” 2010)
17. MSW Hauling Distances: Municipalities – Landfills (“Base Case” 2020)
18. MSW Hauling Distances: Municipalities – Landfills (“Base Case” 2030)
19. MSW Hauling Distances: Municipalities - Transfer Station (“Base Case”
2010, 2020, and 2030
20. MSW Hauling Distances: Transfer Stations – Landfills (“Base Case” 2010)
21. MSW Hauling Distances: Transfer Stations – Landfills (“Base Case” 2020)
22. MSW Hauling Distances: Transfer Stations – Landfills (“Base Case” 2030)
23. MSW Hauling Distances: Municipalities – MRF (“Base Case” 2010)
24. MSW Hauling Distances: Municipalities – MRF (“Base Case” 2020
and 2030)
25. MSW Hauling Distances: Municipalities – Composts (“Base Case” 2010)
26. MSW Hauling Distances: Municipalities – Composts (“Base Case” 2020
and 2030)
27. MSW Hauling Distances: Municipalities – WtE (“Base Case” 2020)
28. MSW Hauling Distances: Municipalities – WtE (“Base Case” 2030)
29. MSW Hauling Distances: Municipalities – Landfills (“Backup Case” 2010)
30. MSW Hauling Distances: Municipalities – Landfills (“Backup Case” 2020)
31. MSW Hauling Distances: Municipalities – Landfills (“Backup Case” 2030)
32. MSW Hauling Distances: Municipalities – Transfer Stations (“Backup Case”
2010, 2020, and 2030)
33. MSW Hauling Distances: Transfer Stations – Landfills (“Backup Case” 2010)
34. MSW Hauling Distances: Transfer Stations – Landfills (“Backup Case” 2020)
35. MSW Hauling Distances: Transfer Stations – Landfills (“Backup Case” 2030)
36. MSW Hauling Distances: Municipalities – MRF (“Backup Case” 2010)
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37. MSW Hauling Distances: Municipalities – MRF (“Backup Case” 2020
and 2030)
38. MSW Hauling Distances: Municipalities – Composts (“Backup Case” 2010)
39. MSW Hauling Distances: Municipalities – Composts (“Backup Case” 2020
and 2030)
40. MSW Hauling Distances: Municipalities – Landfills (“No Action Case” 2010)
41. MSW Hauling Distances: Municipalities – Landfills (“No Action Case” 2020)
42. MSW Hauling Distances: Municipalities – Landfills (“No Action Case” 2030)
43. MSW Hauling Distances: Municipalities – Transfer Stations (“No Action Case”
2010)
44. MSW Hauling Distances: Municipalities – Transfer Stations (“No Action Case”
2020 and 2030)
45. MSW Hauling Distances: Transfer Stations – Landfills (“No Action Case” 2010)
46. MSW Hauling Distances: Transfer Stations – Landfills (“No Action Case” 2020)
47. MSW Hauling Distances: Transfer Stations – Landfills (“No Action Case” 2030)
48. MSW Hauling Distances: Municipalities – MRF (“No Action Case”
2010, 2020, and 2030)
49. MSW Hauling Distances: Municipalities – Composts (“No Action Case”
2010, 2020, and 2030)
50. Greenhouse Gas Emissions for the "No Action Case" (Business-as-Usual)
51. Greenhouse Gas Emissions for the "Backup Case" (Alternative 2)
52. Greenhouse Gas Emissions for the "Base Case" (Alternative 1)
53. Net Greenhouse Gas Emissions for All Studied Cases and Years
54. Energy Consumption in the "No Action Case" (Business-as-Usual)
55. Energy Consumption in the "Backup Case" (Alternative 2)
56. Energy Consumption in the "Base Case" (Alternative 1)
57. Net Energy Consumption in All Studied Cases and Years
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LIST OF TABLES
1. Costs of Inaction against Climate Change for Puerto Rico
2. Population and MSW Generation in Puerto Rico for Studied Years
3. WARM MSW Inputs for “Base Case”, 2010
4. WARM MSW Inputs for “Base Case”, 2020
5. WARM MSW Inputs for “Base Case”, 2030
6. WARM MSW Inputs for “Backup Case”, 2010
7. WARM MSW Inputs for “Backup Case”, 2020
8. WARM MSW Inputs for “Backup Case”, 2030
9. WARM MSW Inputs for “No Action Case”, 2010
10. WARM MSW Inputs for “No Action Case”, 2020
11. WARM MSW Inputs for “No Action Case”, 2030
12. MSW Hauling Distances as Determined by ArcGIS Network Analyst
13. Comparison of MSW Management Scenarios
14. ADS Strategies and Goals for Achieving the 35% Diversion Rate
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LIST OF EQUATIONS
1. Example of WARM calculations
2. Calculation of Diversion Rate for Puerto Rico
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ABSTRACT
THESIS: Solid Waste Management in Puerto Rico: An Assessment of Environmental Impacts
and Benefits
STUDENT: José F. Martínez-Colón
DEGREE: Master of Science – Natural Resources and Environmental Management
COLLEGE: Science and Humanities
DATE: July, 2011
PAGES: 120
Municipal solid waste (MSW) management has been a challenging issue throughout
history. Waste management options have evolved, but they can present distinct environmental
impacts, such as the emission of greenhouse gases (GHG). This study quantified the
environmental benefits (i.e., greenhouse gas emission and energy use reductions) of various
MSW management plans proposed for Puerto Rico through the use of the Waste Reduction
Model (WARM). The waste management initiative known as the “Base Case” was found to
offer the most environmental benefits. Thus, higher benefits can be attained from the
implementation of an integrated solid waste management.
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CHAPTER I
INTRODUCTION
Throughout history, humans have inevitably been impacted by waste. As
populations settle and grow, waste management becomes a more acute issue (Wilson,
1976). Not only does waste management affect our quality of life, but it also impacts our
environment as such practices contribute to the emission of greenhouse gases (GHG), and
consequently climate change. From this standpoint, it is imperative that mitigation
actions be taken accordingly.
Municipal solid waste (MSW), commonly known as trash or garbage, is
composed of products used in everyday life and then disposed. MSW typically comes
from residential, commercial, and institutional locales, while industrial, hazardous, and
construction/demolition (C&D) wastes are not included under this definition (USEPA,
2008). Modern methods of waste management include landfilling, recycling, composting,
combustion, and source reduction (Tchobanoglous et al, 2002). Even though these
practices have evolved throughout history, this issue still constitutes a compelling
environmental, health, and economic challenge.
The environmental impacts from the management of solid waste can be measured
from a life-cycle perspective. Virgin materials must be extracted in order to create new
products. Once these have reached the end of their usefulness, they are typically
discarded in landfills. As these materials decompose, GHGs are released. However,
modern practices such as recycling, composting, and source reduction allow for the
diversion of garbage and organic material from sanitary landfills, thus lessening
environmental impacts. Another means of disposal, combustion (i.e., Waste-to-Energy –
WtE), not only has the potential to decrease the volume of discarded MSW, but can also
serve as a source of heat and power, thus displacing a percentage of fossil fuels destined
for this task (USEPA, 2002a). While there are options available for solid waste
management, countries may still struggle with the implementation and impacts of
proposed alternatives. The Caribbean island of Puerto Rico serves as an example of such
a nation.
Both MSW management and climate change are issues of concern for Puerto
Rico, primarily due to insufficient disposal space, inefficient waste management, and
increased vulnerability to extreme weather. Solutions must be developed with such
concerns in mind. In particular, waste management concerns have prompted the Solid
Waste Authority of Puerto Rico (or Autoridad de Desperdicios Sólidos - ADS in Spanish)
to develop a series of MSW management alternatives that could be employed through the
year 2030. The focus of this study is to quantify the environmental benefits (i.e.,
reductions in GHG and energy use) brought about by the diverse practices proposed by
ADS using the Waste Reduction Model (WARM), an MSW-based GHG calculation tool
developed by the United States Environmental Protection Agency (USEPA). These
practices include the implementation of improved recycling and composting initiatives,
as well as the introduction of WtE in order to reduce/divert the amount of solid waste
reaching landfills. This project provides an assessment and educational model for Puerto
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Rico, one that bridges gaps of information and demonstrates the environmental benefits
of alternative solid waste management options.
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CHAPTER II
LITERATURE REVIEW
2.1
History of Solid Waste Management
Solid waste disposal is a critical issue in the United States. Cities are confronted
with increasing volumes of solid waste generated by residential, commercial, and
industrial activities (USEPA, 2002b). However, this problem has its roots in even the
earliest civilizations.
Earliest humans are believed to have deposited their refuse outside their dwelling
entrances until its overwhelming size would prompt them to move out. However, once
the nomadic ways were abandoned, waste management was of increased concern. Early
dump sites (as early as 8000 – 9000 b.c.) were established in the outskirts of settlements.
In Egypt, waste collection was a privilege for the elite, but all the refuse ended up in the
Nile River. Another approach arose in Greece, where there were town dumps and
household-centered waste management. Furthermore, citizens used to toss their garbage
into the streets, which were later covered by layers of soil (Pichtel, 2005; Wilson, 1976).
Not only did these practices present a health problem (i.e., epidemics were first
associated with uncontrolled waste disposal), but it also compromised local defense, as
refuse piles accumulated near city walls could be scaled by invaders. In Rome, even
though waste was collected and transported to open pits in an organized fashion for the
first time in history, open street disposal or dumping into the Tiber River were common
practices. It is suggested that the waste management problem (especially with regard to
odors) may have driven aristocrats away, thus decentralizing power and perhaps leading
to Rome’s downfall. In Europe, the surge of population and urbanization also meant
greater impacts of waste. Besides street dumping, garbage was burned in household open
fires and wildlife often feasted upon the waste. Moreover, discarding refuse into surface
waters may have begun the plague outbreak (“The Black Death”) in medieval Europe,
and thus laws were promulgated to prohibit this practice (Pichtel, 2005).
Just before the Industrial Revolution, waste had some profitable use, but once this
period began, waste generation was intensified while environmental and health issues
were not as important as production. However, in the 19th century there was increased
awareness due to the linking of improper sanitation and the incidence of diseases (“Great
Sanitary Awakening”), thus more stringent regulations were established. In the United
States, the first forms of sanitation were promoted by Benjamin Franklin, in which
servants were charged with the removal of waste from the streets. Public-paid collection
began in 1856, and incinerators were first used during the winter time after the passing of
a bill in 1885. However, the rapid growth of urban areas and population (both American
and foreign) aggravated waste management, which by the middle-to late-1800s was
inefficient, and the common practice was to transport refuse miles away (or offshore).
More advanced practices were seen during the second half of the 19th century, when
industrialization and urbanism were intensified (Pichtel, 2005).
This period saw the contributions of Civil War veteran Col. George E. Waring, Jr.
in New York City, which included the establishment of a systematic waste classification
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scheme (Pichtel, 2005; Wilson, 1976). Furthermore, his reforms improved the efficiency
and costs of collection, as well as promoting further experimentation with incineration
and waste reduction. These advances were further developed with the coming of the 20th
century (Pichtel, 2005). Ocean dumping received criticism due to the pollution of the
East and West Coast Beaches, and was deemed illegal in 1934. Furthermore, there was a
shift from land disposal/dumping to the widespread use of sanitary landfills (Pichtel,
2005; O’Leary and Tchobanoglous, 2002).
In modern times, the traditional approach to deal with solid waste has been
through the disposal in sanitary landfills (O’Leary and Tchobanoglous, 2002; Rogoff,
1987). The landfill mindset has given rise to varied environmental problems such as
leaching of contaminants into soils and groundwater, and atmospheric emissions.
Therefore, landfills must operate with control features, and siting conditions (mainly soil
and geologic properties, and proximity to urbanized areas) must be adequate. These
issues are aggravated by citizen opposition and not-in-my-back-yard (NIMBY) attitudes
(Rogoff, 1987). However, the continued pursuit and development of alternatives greatly
improved waste management issues.
2.2
Solid Waste Management Options
As population and industrialization increase, so does the generation of solid
waste, and thus management problems become more challenging. A variety of solid
waste management options have been adopted by governments at all levels. While
landfilling is a less preferred option compared to other strategies, advances in technology
allowed this practice to thrive (O’Leary and Tchobanoglous, 2002). Furthermore,
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enhanced awareness of human health and environmental impacts prompted agencies to
incorporate practices such as source reduction, recycling, composting, and combustion to
deal with MSW. USEPA defines and combines these strategies into an Integrated Solid
Waste Management (ISWM) system (USEPA, 2002a; Tchobanoglous et al, 2002).
The first types of solid waste management are intended to divert refuse from
disposal (primarily landfilling). Source reduction, reduces waste at the beginning of its
life cycle by reducing the demand for new products. This entails acquiring reusable
products or redesigning products (i.e., new products that require fewer virgin materials or
last longer). Recycling practices convert used products into valuable resources instead of
being discarded. There are a variety of markets for recyclable materials. Governments
can build on these practices by providing support to organize and improve recycling
efforts. Moreover, the development of Materials Recovery Facilities (MRF), Transfer
Stations (TS), and certain forms of combustion can allow for more effective recycling
strategies. Organics such as food scraps or plant matter can also be diverted from the flow
of MSW and be decomposed in a controlled aerobic biological process known as
composting. Composts act as soil amendments, thus reducing the need for chemical
fertilizers and pesticides (USEPA, 2002a, Tchobanoglous et al, 2002).
The combustion process entails the controlled burning of waste in a specialized
facility. In this case, the benefits may be two-fold as it can reduce the volume of MSW by
90% and generate energy/electricity. In an ISWM, this technology is employed when
wastes cannot be recycled or composted, or where landfill space is limited. Landfills may
provide a safer alternative than simply discarding MSW uncontrollably (if properly
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designed, constructed, and managed). Modern modifications may include earthen or
synthetic liners that prevent leachates from reaching soils, and flaring systems that can
burn methane produced from waste decomposition. The latter can also be developed as an
energy recovery system (USEPA, 2002a; Tchobanoglous et al, 2002).
As USEPA (2002a) states, a proper ISWM makes an effective combined use of
the previously explained strategies. Taking human health and environmental well-being
as a foundation, authorities must develop plans that address the needs of communities,
while ensuring the effective management of solid waste and the adherence to regulations.
Furthermore, ISWM may provide opportunities to improve economic conditions by
providing new jobs and adequate funding management (Tchobanoglous et al, 2002).
However, judging from the various challenges posed by solid waste management, it is
expected that major environmental issues (i.e., climate change) arise, and strategies must
address these impacts accordingly.
2.3
Overview of Climate Change and Greenhouse Gases (GHG)
The Intergovernmental Panel on Climate Change (IPCC) defines the term
“climate change” as “any change in climate over time, whether due to natural variability
or as a result of human activity” (2007). Their reports and several observations
characterize this phenomenon as “unequivocal”, and projections are treated with a certain
degree of confidence based on prior knowledge, but with a recognized uncertainty (IPCC,
2007).
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One of the most important factors that originated and aggravated climate change
is the increase in GHG emissions, which are emitted from natural (e.g., volcanic activity)
and anthropogenic sources (e.g., industrial processes). The IPCC characterizes the latter
to be a “likely” player in exacerbating the changes in the climate system. Carbon dioxide
(CO2) is reported to have increased in the atmosphere since pre-industrial times (from
280 ppm in 1750 to 379 ppm in 2005). The continued dependence on fossil fuels,
changes in land use, and even agriculture substantially contributed to these increases, as
well as methane (CH4), and nitrous oxide (NOx) emissions (IPCC, 2007).
Popular mitigation strategies have been proposed to minimize climate change
impacts at global and individual levels. Some policies now argue for the change from
fossil fuel usage to alternative and renewable sources. Furthermore, what energy is
produced today has been directed to be used more efficiently; strategies include the
design of better buildings and systems. In terms of GHG capture, protection of existing
vegetative cover and reforestation contribute to the capturing of carbon, as well as more
technical strategies in geo-engineering such as carbon sequestration. Human behavior is,
and may forever be, a key factor in mitigation as humans are encouraged to make use of
public transportation and carefully monitor the electricity usage, among other solutions
(Biello, 2007).
2.3.1
GHGs and Solid Waste Management
Diverse MSW management practices have different impacts on the environment.
Certain options may yield greater greenhouse gas emissions than others, such as the
direct disposal of solid waste into landfills, or incinerating the refuse with no
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resource/energy recovery. Transportation of MSW from curbside to management
facilities also adds CO2 emissions. Additionally, more emissions will be generated from
the processing of raw materials into new products. As informed by USEPA (2002b), the
emissions and offsets of such can be observed through a life-cycle approach (Figure 1).
First, extraction and transportation of raw materials involves the use of fossil fuels, thus
resulting in CO2 emissions. Further emissions occur in the manufacturing of new
products, the next stage in the cycle. Once products are completely used, typically the
next stage would be disposal, composting, or combustion, in which case more emissions
from transportation of MSW will occur. In the case of disposal, degradation of materials
in landfills results in increased emissions, specifically methane. However, practices such
as recycling and source reduction help prevent/offset GHG emissions. Composting the
organic materials offsets emissions as some of the carbon is returned to the soils. Finally,
from the combustion of solid waste, even though it has been known to release CO2 and
N2O, emissions are offset due to the use of fewer fossil fuels to generate energy (USEPA,
2002b). The same can be expected in some landfills equipped with landfill gas-to-energy
systems (“General Information”, 2010). More detailed observations for each MSW
management option are presented next.
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Figure 1. Life Cycle of Products and Waste Management
(Source: USEPA)
2.3.1.1 Landfilling
The disposal of solid waste residues (i.e., un-recycled or otherwise processed
MSW) has been historically carried out in or on surface soils. Another practice was the
dumping of refuse in oceans. Nevertheless, sanitary landfills are an “economical and
environmentally accepted method” for disposing MSW (O’Leary and Tchobanoglous,
2002). These sites are analogous to biochemical reactors in the sense that MSW residues
are the inputs, while landfill gas and leachates are the outputs of this process. Throughout
its various phases, which are dominated by bacterial action in aerobic and anaerobic
mediums, MSW is degraded and GHGs such as CO2 and CH4 undergo an evolutionary
process and are ultimately released into the atmosphere (O’Leary and Tchobanoglous,
2002).
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The evolution of landfill gas is described by O’Leary and Tchobanoglous (2002)
as a five-stage process, in which duration per stage and volume of gases generated
depends on various conditions, such as the distribution of organic components,
availability of nutrients, moisture content and paths thereof within waste, and
compaction. Each step is summarized as follows:

“Initial Adjustment:” Once the refuse is placed in a landfill, bacteria begin to
decompose the biodegradable components in MSW under aerobic conditions.
The soil material that is used for landfill cover provides these organisms.

“Transition Phase:” At this stage the oxygen originally found in the first phase
is depleted and anaerobic bacteria develop. Electron receptors, specifically
NO3- and SO4- are reduced, thus N2 and H2S are formed. As the
oxidation/reduction potential decreases, organics-degrading microorganisms
begin to develop.

“Acid Phase:” Bacterial activity is accelerated with increasing production of
organic acids and decreasing N2. Within this phase, organic material
undergoes more degradation, allowing microorganisms to use the converted
compounds for energy and carbon, leaving CH3COOH and fulvic acids. Also,
CO2 and H2 are generated.

“Methane Fermentation:” In this phase, methanogenic bacteria become
dominant, and begin to convert the acids formed in the previous stage into
CH4 and CO2.
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“Maturation:” The biodegradable material is ultimately converted into CH4
and CO2. Due to moisture migration, more materials will be converted in the
same fashion as stated throughout this process. Nevertheless, landfill gas
generation rates decrease due to the removal of nutrients along with the
leachate formed in former stages, while the remaining substrates are slowly
degraded.
The two primary GHGs found in landfills are CO2 and CH4, accounting for
approximately 45% and 55% of the total respectively. CH4 is considered to have a global
warming potential (or heat retention potential - GWP) 21 times that of CO2 (Block,
2000). However, CO2 is not commonly considered an addition in GHG emissions due to
its biogenic nature. On the other hand, the contributions of methane can vary with
original concentration of its counterpart, as well as the MSW components containing
carbon. The type of landfill will also have a significant impact on GHG generation, with
rudimentary dumps accounting for greater emissions, while well-engineered landfills, or
sites with lower organic MSW fractions, will emit less (Manfredi et al, 2009).
Nitrous oxides are yet another GHG emitted by landfills, though the
concentrations are lower than CH4 and CO2. Rinne et al (2005) encountered N2O
emissions on the undisturbed landfill surface and compared them with measurements
taken within the landfill cover. They also found a connection between ages of landfilled
materials and soil cover: older materials having some vegetation cover indicated a higher
release of N2O due to the activity of CH4-oxidizing bacteria on the landfill surface (Rinne
et al, 2005). Emission rates for these gases are affected by a number of conditions. Park
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and Shin (2001) determined these conditions through measurements taken with an air
flux chamber and gas chromatography at a Korean landfill. They discovered that
emission rates were lower during the winter season, while the summer season gave higher
readings. They attributed these findings to changes in temperature and precipitation: low
temperatures in landfills exhibit more compaction, while the frequent precipitation during
the summer accelerated landfill gas production and subsequently, gases were released
under sunny conditions (Park and Shin, 2001). While landfills are a major source of
anthropogenic GHG emissions, mitigation strategies have been devised, as explained
next.
Typical methods for managing landfill gas include flaring and energy recovery. In
flare systems, CH4 and other trace gases undergo combustion, thus forming primarily
CO2, SO2, and NOx. This method is often subjected to meet stringent air pollution
controls. On the other hand, landfill gas can be converted into a useful form of energy
(e.g., electricity) through technologies such as combustion piston engines and turbines
(O’Leary and Tchobanoglous, 2002). Moreover, greater GHG reductions can be
achieved, depending on the end use of landfill gas. Han et al (2009) studied three
different scenarios: 1) no collection of gases, 2) thermal energy generation from gases for
fossil fuel replacement in boilers and air heaters, and 3) electricity generation from
landfill gas. The major findings were that the second scenario fared better against the
third in terms of gas utilization, but emission reductions were greater when the end use
was electricity generation due to gas collection efficiencies (Han et al, 2009).
Furthermore, if these emission reductions are accounted for along with any reductions
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from an electricity grid, landfill gas-to-energy projects may improve electricity prices
(Jaramillo and Matthews, 2005).
There are other landfill gas mitigation strategies that do not involve its usage and
still achieve GHG reductions. Purification of landfill gas can be achieved by separating
CO2 and CH4 through physical and chemical adsorption or membrane separation
(O’Leary and Tchobanoglous, 2002). The evolution of gases (as explained previously)
can also be controlled through in situ landfill aeration, thus achieving GHG savings as
determined by Ritzkowski and Stergmann (2010). “Biocovers” (i.e., composted yard
waste deposited on top of landfill soil cover) have also been found to be effective in
reducing CH4 emissions as well as other non-methane hydrocarbons due to increases in
methane oxidation (Bogner et al, 2010). Judging from these research findings, landfills
can still be an important part of an ISWM.
2.3.1.2 Recycling
Since the 1980s, recycling has been a widely accepted and environmentally
attractive method of solid waste management in the United States and elsewhere
(Leverenz et al, 2002). According to Leverenz et al (2002), its success may depend on
wise allocation of responsibilities and adequate costs, which means developing
achievable waste diversion goals. Recycling programs may be either voluntary or
mandatory, and some target specific types of wastes (e.g., cardboard boxes, glass, metals,
and plastics). Furthermore, recycling mechanisms may vary: recyclables can be separated
by the waste generator (e.g., consumer), the collector (at curbside), or processed in
15
specialized facilities (i.e., Materials Recovery Facilities – MRFs). They outline certain
implications from different recycling methods (Leverenz et al, 2002):

“Separation by generator:” segregation of recyclables by homeowner, often
with high collection costs, and low processing costs.

“Commingled collection” (MRF): most recyclables separated by generator
and collection/processing efficiency is increased.

“Mixed-waste collection:” no separation from generator, no increments in
collection costs, but high processing costs due to low recovery efficiency.
The general effects of recycling on GHG are well known and straightforward. For
instance, these are well-documented and researched through life-cycle analyses of the
diverse MSW management practices. Recycling can be seen as a “materials management
strategy” rather than be strictly referred to as a climate change mitigation effort (Boisson
and Georgis, 2009). Through recycling, there is less dependence on the acquisition of
virgin materials, thus reducing energy use and costs as well as GHG emissions. In terms
of achieving accurate GHG accounting it is important to consider that this practice can
influence several different industrial sectors as well as the commercial and residential
realms (Boisson and Georgis, 2009; USEPA, 2002a). On the other hand, recycling may
not represent significant GHG savings at the downstream of the life-cycle due to the
transportation of recycling materials. Despite this, recycling is still a much preferred
option over landfilling or combustion. Furthermore, the practice of industrial symbiosis
may be a key to reduce GHG emissions from transportation in this context, as
16
participating industrial processes are clustered within a short geographic proximity
(Chertow, 2009).
The benefits of recycling programs can be further strengthened by the
implementation of waste management incentives and regulations. An example is the PayAs-You-Throw (PAYT) program, in which residents are charged for trash collection
service based on the amount of MSW set out for disposal. In this case, residents are
encouraged to recycle in order for them to reduce or avoid these costs, thus improving
waste diversion rates (Skumatz, 2008).
2.3.1.3 Composting
Composting has become a widely used diversion method for MSW, specifically
paper, food scraps, yard waste, and other organic materials. This practice consists of an
aerobic process in which microorganism degrade the organic material. Common outputs
include water, minerals, and CO2. In addition, the composting process makes for
“biologically-stabilized” material, which can be used for horticulture and/or agriculture.
This practice can be carried out in specialized facilities and with a variety of
technologies. These include “windrows” (i.e., piles arranged in rows exposed to wind),
“aerated piles” (i.e., enclosed conditioning of compost), or “rotating drums” (i.e.,
compost processing within a reactor) (Andersen, 2010).
There are diverse processes occurring in composts at different levels. The
organisms’ role in this system is to contribute in the mineralization process, and it is
reported that different feeding levels occur. Zeman et al (2002) state that the
17
biochemistry of this system varies with temperature, moisture, particle size, carbon-tonitrogen proportions (C:N), phosphorus and sulfur content, and pH. It has been observed
that differences in temperature at varying stages of the decomposition process allow
certain microorganisms to thrive. These properties are further affected if the composting
process is done under active conditions (i.e., mechanical movement/rotation of compost
for aeration) instead of passive conditions (i.e., natural aeration) (Zeman et al, 2002).
Specifically when dealing with manure, its water content and the livestock’s diet can play
an important role in the properties and decomposition of the compost material. For this
particular kind of organic waste, windrows have been commonly used as the composting
method, thus reducing the liquid fraction (Larney, 2006). However, the previously
mentioned properties have another effect besides decomposition rates and nutrient
availability: the rates and types of greenhouse gas emissions.
In a compost system, the predominant GHGs emitted are CO2, CH4, and N2O. The
stages at which CO2 is considered an addition to climate change-related emissions
include the transportation of input materials to the compost facility and of finished
product off-site, energy used during the process (e.g., mechanical rotation), and end uses
of the compost products. CH4 and N2O do have an additional effect to GHG emissions.
Methane is produced as a by-product under anaerobic conditions. In its evolution, carbon
(C) remains as the only electron acceptor available after the exhaustion of oxygen,
nitrogen, iron, manganese, and sulfur. The nitrous oxides are formed via nitrification or
most commonly, denitrification (Brown et al, 2008). In terms of methane emissions, it is
reported that methane, even though it is produced deep within anaerobic zones of a
18
compost system, may very well be oxidized in aerobic pockets before leaving the pile
(Zeman and Rich, 2001). While GHG emissions may be lower in composts compared to
landfills, sound management is required in order to keep emissions low. For instance, a
compost pile that is well-aerated can reduce emissions, accelerate stabilization, and
reduce odors (Brown and Subler, 2007). However, the properties of composts can greatly
affect the amounts of GHGs released.
The properties governing GHG emissions in composts include the type of input,
moisture content, bulk density, C:N ratio, pH, and the presence of other compounds and
elements. Brown et al (2008) reported that yard wastes have a lower moisture content,
lower bulk density, and higher C:N ratio than manure or biosolids. Emissions have been
lower than wet inputs with a low C:N ratio. This higher moisture content also means that
anaerobic decomposition may be at work, giving off CH4 as explained before. Therefore,
this is of special concern when dealing with manure or biosolids composting practices
(Brown et al, 2008).
Methane emissions have also been found to decrease with low pH. Hao et al
(2005) conducted an experiment in which a phosphorus-based fertilizer, phosphogypsum
(PG), was added to active manure composts. In this case, CH4 emissions were decreased
in composts where PG was applied, a result attributed to the decrease in pH and the
enhanced sulfur content (Hao et al, 2005). Another study including PG involved the
examination of stored manure compost. CH4 emissions behaved in a similar fashion as in
the previous study, but were not affected by the amendment of PG (Hao, 2007).
19
Nitrous oxide is reported to behave differently from CH4. High emissions of N2O
have been associated with the increasing NH4+ during nitrification and increasing NO3during denitrification (under aerobic and anaerobic conditions, respectively).
Furthermore, N2O emissions have been found to increase significantly with decreasing
pH in active composting (Hao et al, 2005). However, N2O emissions are lower in
passive/stored composts. The same behavior toward pH was observed as well (Hao,
2007). Nevertheless, literature sustains that composts emit lower amounts of GHG when
compared to landfills. Moreover, the potential for emissions can be carried over to the
end use stage, thus affecting the soils ability to capture or emit gases.
The benefits of compost have been well researched, especially for soils. It has
been found that composted material can increase soils’ water retention capabilities, act as
an effective fertilizer and herbicide replacement (composts are treated with heat to
remove pathogens in some cases), and increase carbon sequestration. The organic matter
present can also increase aggregate stability, and decrease bulk density (Termorshuizen et
al, 2004). Composted materials can also serve as a substitute for peat in horticulture,
which would minimize carbon losses and thus GHG flux to the atmosphere. However, the
retention of carbon is only temporary and it is eventually released into the atmosphere
(Favoino and Hogg, 2008).
2.3.1.4 Source Reduction
Source reduction has been recognized by USEPA as one of the most important
approaches to deal with MSW. The goal of source reduction programs is to decrease or
prevent the amount and toxicity of materials at the source before waste is generated (i.e.,
20
at manufacturing). Furthermore, they have the potential to eliminate/facilitate waste
management problems. As such, one can expect that source reduction will have far better
effects on the environment. From a life-cycle and climate change perspective, this
practice can result in GHG emission reductions from the following (Leverenz, 2002):

Reduced need for extraction of natural resources

Less energy use and pollution from materials processing

Reduced disposal of MSW in landfills or combustion plants

Reduced need for transportation of materials and waste overall
Life-cycle analyses suggest that source reduction has the potential to achieve
GHG reductions greater than other waste management options. Bogner et al (2008) report
that at certain stages throughout a product’s life the materials’ efficiency can be improved
through better design and material substitution. They explain that this would, in turn,
mean greater energy savings as well as reductions (or avoidance) in emissions, especially
for energy-intensive products such as metals, glass, plastic, and paper. In this area,
measures that have been proposed to enforce source reduction are Extended Producer
Responsibility (EPR), thus including environmental costs of goods into their market
price. Through the implementation of such policies, there is an encouragement to
redesign new products using fewer materials or incorporating those that have higher
recycling potentials (Bogner et al, 2008; Leverenz, 2002). Analogous to recycling, PAYT
programs can also serve as incentives for source reduction, as citizens are encouraged to
reuse their products (Skumatz, 2008; Leverenz, 2002).
21
2.3.1.5 Combustion/Waste-to-Energy
Problems associated with solid waste landfilling have provided an opportunity to
explore new waste management practices such as recovery of energy from waste. WtE is
the conversion of solid waste into energy or a marketable fuel (Kreith, 2002). These
systems provide an alternative to the typical practice of landfilling waste, as they can
reduce the volume of refuse. Traditionally, the first major criterion for consideration of
WtE technology is whether or not a community is facing a waste disposal crisis, which
may include one or more of the following problems (APPA, 1986):

Diminishing landfill capacity

Lack of acceptable land for new landfills

Increased hauling distances

High landfill operating costs

Stringent environmental standards

Negative environmental impacts of landfills
WtE processes have typically produced electricity directly through combustion, or
through a combustible fuel commodity, such as methane, methanol, ethanol or synthetic
fuels (e.g., syngas) (Rogoff, 1987). Major examples of WtE technological options are the
traditional incineration/mass burn, refuse-derived fuel (RDF) processing, pyrolysis,
gasification, and other modern alternatives.
Incineration has been a prominent process for recovering energy from waste in the
United States. This process consists of destroying waste materials (un-sorted) by the
22
controlled application of heat and oxygen. Various types of incinerators have been
developed which are able to handle the different types and quantities of waste (Schwarz
and Brunner, 1983). Incineration has several advantages, such as immediate volume
reduction, on-site processing, production of sterile ash residues, and reduced operation
costs through energy offsets. However, incineration may be associated with high capital
costs, potential need of fuels for process maintenance, and the requirement of specialized
personnel, not to mention high costs in air pollution control systems (Kreith, 2002).
RDF systems convert solid waste into a fuel with low moisture content and
uniform size while yielding lower amounts of ash than other types of WtE. There have
been different kinds of RDF products, such as “fluff RDF” (MSW separation and
shredding), “densified RDF” (production of highly-densed pellets), “dust RDF”
(powdered fuel with high combustion properties), and “wet pulp RDF” (production of
slurry-like fuel). The product formed is aimed to be a substitute/supplement to fossil fuels
in industrial practices (Schwarz and Brunner, 1983). While these systems improve the
properties of MSW as they are separated into combustible fractions, RDF technologies
also require high costs regarding air pollution control (Kumar, 2000).
Contrary to common incineration, pyrolysis involves the “distilled destruction” of
solid MSW components through the application of heat in an anoxic environment. As
such, this process will yield endothermic reactions, and the gases that are produced
(mainly CO, CH4) are combusted. Even though this process does not entail the injection
of much air, minute concentrations of oxygen (less than that of optimal air/fuel ratio) are
added at startup (Schwarz and Brunner, 1983). Recyclable materials such as glass,
23
metals, and cardboard can be recovered prior to processing. When the process is
complete, the off-gas can be stored. The resulting byproduct is a solid termed “charcoal.”
Nevertheless, pyrolysis has not been a widely successful technology. Complications
include increasingly difficult gas clean-up and the formation of “slag” from recoverable
materials (if not removed at the beginning of the process), thus compromising the
system’s integrity and proper functions (Kreith, 2002).
Extracting heat from fuels depends on the efficiency of mixing them with air, as is
the case of the gasification WtE technology. Gaseous fuels provide a greater amount of
heat to be extracted. In this case, solid waste such as biomass can be converted into a
fuel. The material that is extracted after the solid waste is treated and sorted is fed into a
gasification chamber, which in turn produces power after cooling and cleaning through a
gas engine connected to an electric generator. The result is a high quality gas that is
easier to handle and has great thermal efficiency. While gasification offers the added
advantages of creating less air pollution, it may turn out to be a costly endeavor to
maintain the systems in optimum conditions (Kumar, 2000).
Other approaches have been reported. Plasma arc systems use a high temperature
heat source (“plasma arc flame”) created by passing a highly ionized gas through two
electrodes discharging a high voltage. The high temperatures (5,600 – 30,000 °F) break
molecules into individual atoms, followed by controlled cooling, thus creating a synthetic
fuel gas (Kumar, 2000). Another novel technology is termed “Thermoselect.” This
process produces a synthetic gas through gasification and melting of waste in a highly
controlled environment. The “syngas” allows for the generation of electricity at a thermal
24
efficiency higher than what a conventional WtE plant (using a steam turbine) can
achieve. The gas cleaning process may be quite complex, but this type of technology has
been reported to have much lower emissions (Psomopoulos et al, 2009).
The major GHGs emitted from WtE facilities are CO2 and N2O. The latter is
strictly associated with the combustion of MSW. However, the former is typically
derived from the combustion of solid waste, and the fuels required for starting and
maintaining the process. Moreover, CO2 emissions can also be emitted from equipment
commonly used in landfills where the ash has to be disposed. Nevertheless, the product
(either RDF or energy) can achieve GHG emission reductions in the sense that fossil
fuels (often coal) are potentially replaced (Papageourgiou et al, 2009a). In fact, coal-fired
power plants often emit greater amounts of SO2, NO2, and fossil CO2 (Kaplan et al,
2009). In this respect, the versatility of a WtE plays an important role in the amounts of
GHGs emitted. Papageorgiou et al (2009b) studied various scenarios using Life Cycle
Analysis (LCA), in which different products were generated from incineration. It was
concluded that recovering both electricity and heat (“combined heat and power”) meant
greater GHG emission savings, followed by electricity recovery only.
2.3.2
Modeling GHG Emissions in Solid Waste Management
As environmental awareness increase among public and private sectors, so do the
methods to minimize environmental impacts of both waste management practices and
products manufacturing. A prominent method used to understand these effects is the Life
Cycle Analysis (LCA) (USEPA, 2002a). This technique allows for the study of the lifespan of goods, in which inputs are commonly the raw materials and energy, while outputs
25
may be pollution (air or water emissions), by-products, and wastes. A main advantage of
LCA is that it allows for wise decision-making regarding which goods result in the least
impact to the environment. However, depending on the depth of the study, it can turn out
to be a resource- and time-intensive effort (SAIC, 2006). Many tools have been
developed under a LCA basis.
Using the knowledge and application of LCA, USEPA, its partners, and other
organizations have developed tools that allow users from a variety of backgrounds to
determine the environmental benefits associated with solid waste management. Some
programs may target the entire life-cycle of various practices or products, but there are
certain calculators that work specifically for a particular MSW management method.
Examples of these calculators are USEPA’s Waste Reduction Model (WARM), the
Northeast Recycling Council Environmental Benefits Calculator (NERC-EBC), the
Recycled Content Tool (ReCon), the National Recycling Council’s Environmental
Benefits Calculator (NRC-EBC), the Durable Goods Calculator (DGC), the Cities for
Climate Protection Greenhouse Gas Emissions software, and the Municipal Solid Waste
Decision Support Tool (MSW-DST) (USEPA, 2002c). WARM was the tool of choice for
the reported study. This model explores a wide variety of MSW components managed
through landfilling, composting, combustion, and source reduction, and serves as an
inexpensive and comprehensive planning tool for both public and private sectors in future
waste management intiatives.
26
2.3.2.1 Waste Reduction Model (WARM)
The USEPA tool WARM is designed to aid solid waste planners and
organizations so that they may voluntarily track and report GHG emission reductions
from their MSW management approaches. It calculates GHG emissions of a business-asusual scenario and an alternative practice in metric tons of carbon equivalent (MTCE),
metric tons of carbon dioxide equivalent (MTCO2E), and energy units consumed (million
BTU) from a range of material types commonly characterized in a solid waste generation
stream. The latest version of WARM, used in the current project, was released in August
2010 (USEPA, 2010).
The emission factors from the material types recognized in WARM represent the
GHG emissions associated with managing one short ton (2,000 lbs) of MSW by
landfilling, recycling, composting, combusting, or source reduction (Appendices X XII). The basic concept can be exemplified through the following formula (USEPA,
2010):
Material type: aluminum
(1 short ton × -13.61 MTCO2E/short ton) - (1 short ton × 0.04 MTCO2E/short ton) = -13.65 MTCO2E
↑
↑
Alternative: recycling
Business-as-Usual: landfilling
Equation 1. Example of WARM calculations
(Source: USEPA, 2010)
The foundations for WARM arise from various background reports and studies,
which have explored emission factors from specific materials. These extensive research
27
efforts were compiled by USEPA in its report on GHG emissions entitled Solid Waste
Management and Greenhouse Gas Assessment of Emissions and Sinks (2002b). The latest
documentation is structured around the materials’ life cycle and the associated impact of
waste management practices. WARM assumes that each management practice influences
net GHG emissions as follows (USEPA, 2002b):

Source reduction: Emissions throughout the life-cycle of materials are avoided

Recycling: Reduction of emissions due to the use of fewer virgin input
materials for the manufacture of new products

Composting: Composting of materials such as paper, yard waste, and food
scraps (or related organic material) results in carbon storage

Landfilling: Results in CH4 emissions and carbon storage. Technological
advances have allowed landfills to capture and flare gas. If used for energy
recovery, the flaring process would offset emissions from fossil fuel
combustion for energy generation.

Combustion: Results in offsets in GHG emissions as it is used to generate
electricity while displacing fossil fuel-derived energy.
WARM employs a life-cycle analysis. However, this approach is streamlined and
centered on waste generation rather than raw material extraction, as the point of this tool
is to compare choices in waste management. In terms of emissions from energy use it is
necessary to understand and input the current energy mix in order to establish a context
of emission reductions associated with energy recovery from landfill gas flaring systems
or combustion. Such information is determined by inputting the resource mix of the state
28
of interest as determined by data from the Emissions & Generation Resource Integrated
Database (eGRID) (Hartwell, 2011). Transportation of materials also plays a key role in
WARM. Average distances to management facilities (landfills, combustion plants,
recycling facilities, and composts) represent a source of GHG emissions from fossil fuels
consumed by MSW-hauling trucks (USEPA, 2002b). The mode of transportation
included in WARM is a diesel-fueled vehicle (Hartwell, 2010).
A distance component is required for the operation of WARM. Even though a
default distance can be selected (20 miles to each MSW management facility), a
geographic information system (GIS) can determine these distances along a road network
in order to model the emissions and energy use impacts of MSW transportation more
accurately.
2.4
Geographic Information Systems and Solid Waste Management
There are a myriad of uses for GIS: planning, monitoring, assessment, decision-
making processes, among others. In waste management, it has become increasingly
important to reduce costs of municipal solid waste collection, transportation, storage, and
disposal; GIS can be a cost-effective tool that can facilitate many waste-related processes,
as well as serve as an efficient analytic tool.
Traditional concerns have been the search for suitable locations to place waste
collection bins, as well as considering the estimates of waste generation and on-site
storage capacity. The improper siting of bins may result in increased hauling and
maintenance costs. Vijay et al (2008) addressed these concerns by implementing a “p-
29
median constraint model” on a GIS platform. This model identified centers to locate a bin
by minimizing total weighted distance from this center to the demand nodes. The
algorithm implemented allowed for proper site evaluation based on practical and
aesthetic considerations. The resulting sites allowed for easy access to these bins and
proximity between bins (Vijay et al, 2008).
Another use of GIS in waste management deals with routing and waste collection
schedules. Chang et al (1997) developed a multi-objective model for collection vehicle
routing and scheduling for solid waste management systems within a GIS environment.
Three goals were proposed in this analysis in order to ensure maximum consensus and
minimum disruption: 1) route consolidation, 2) preservation of existing collection points
where possible, and 3) management of resources among sub-districts (haulers and other
vehicles would operate under the same rules and conditions). The resulting model was
relatively successful in minimizing the total waste collection distance, costs, and time
(Chang et al, 1997).
In order to implement a successful recycling program, several physical and nonphysical considerations must be taken into account: land, number of depots, number of
trucks available for pick-up, pick-up frequency, size and number of bins, awareness, and
acceptance (Valeo et al, 1998). Valeo et al (1998) sought to implement a locationallocation model within a GIS environment with the objective of designing a recycling
depot scheme for 22,000 people. This model optimizes the locations of centers and
allocates consumers or demand to those centers. Two schemes were considered: location
of depots within walking distance and within driving distance. It is noteworthy that the
30
model can be adjusted to changes in demand, making this approach both effective and
efficient for planning and engineering purposes (Valeo et al, 1998).
As stated before, GIS can also be implemented as a monitoring tool in waste
management. Green (2009) employed GIS in order to monitor the properties of landfills
in United Kingdom. The studied properties included areas of landfill liners, location of
leachate piping systems, and records of filling and volume parameters, among others. It
was also observed that GIS can also be used to monitor landfills after their closure. This
is an important factor as excessive surface settlement of closed landfill sites can cause
ponding, among other environmental concerns (Green, 2009).
2.5
Site of Study: Puerto Rico
2.5.1
General Features
The island of Puerto Rico is located between latitudes 17°45’ and 18°30’N and
longitudes 65°45’ to 67°15’W (Daly et al, 2003). The main island has a total area of
approximately 4,421 m2, with two out of a total 78 municipalities as neighboring islands
(Figure 2). The island’s most characteristic topographic feature is a central chain of
mountains (“Cordillera Central”) crossing from east to west. Some of its mountains reach
elevations of over 4,000 feet (CSA Group, 2008). The highest peak is “Cerro Punta,”
reaching an altitude of approximately 4,389 feet above sea level (Carter and Elsner,
1997). These elevations descend towards the flatter areas of the coast; the majority of the
island has elevations of less than 1,000 feet (Figure 3). The various changes in elevation
from the coasts towards the Cordillera Central are an important factor in inducing
31
orographic precipitation. On average, annual precipitation is approximately 69 inches;
however this value varies by region, with the most in “Sierra de Luquillo” (“El Yunque”
Rainforest) and the least in the south and western parts of the island. Furthermore,
precipitation changes significantly throughout the year: an initial drought period occurs
between January and April, followed by a wet period from May until June. A second
drought period lasts until August, and finally there is an intense wet period for the rest of
the year. The latter corresponds to the storm season (CSA Group, 2008). Humidity is
generally high due to the surrounding warm ocean waters (Daly et al, 2003). Temperature
does not vary significantly throughout the year, with an average of 82 °F. There is,
typically, a difference of 5 – 6 °F in the northwestern coastal areas between the warmer
and cooler months. In contrast, there is greater temperature variability in the inner regions
due to the diverse elevations. Easterly trade winds are predominant throughout the year
(average wind speeds of 6 – 9 miles per hour) and may be accelerated by the
mountainous areas (CSA Group, 2008).
32
Figure 2. Municipalities of Puerto Rico
(Basemap source: ESRI)
Figure 3. Topography of Puerto Rico
(Adapted from: CSA Group, 2008)
33
2.5.2
Climate Change and Puerto Rico
The island of Puerto Rico, despite being a non-incorporated territory of the United
States (Commonwealth) and thus enjoying slightly higher advantages in the Caribbean
region compared to other islands, is vulnerable to climate change impacts (Hoey and
Diaz-Mendez, 2009). A report by the Global Development and Environment Institute at
Tufts University (Bueno et al, 2008) explores this premise from an economic perspective.
Bueno et al (2008) explain that concerns of higher local temperatures will
jeopardize the tourism industry eventually. Furthermore, Puerto Rico may be susceptible
to significant threats such as beach erosion from sea level rise and the development of
stronger hurricanes, ocean surges and heavy rains. A major portion of the island’s
population and economic activity are found in coastal areas, especially in the San Juan
metropolitan area, an important tourist attraction. In the inner parts of the island, where
there are pronounced elevations, vulnerability to landslide hazards could be aggravated
by heavy rainfall. As population density increases, there will be a greater need for
construction, which unfortunately, may be sited in areas with dangerous slopes.
Furthermore, energy consumption will increase, primarily from electricity generation and
transportation needs, thus contributing to greater dependence on fossil fuels, increased
emissions, and higher costs. It was determined by Bueno et al (2008) that the costs of not
rising to the climate change challenge may spell losses of billions of dollars over the
years, especially if the previous issues are considered (Table 1).
34
Table 1. Costs of Inaction against Climate Change for Puerto Rico
(Source: Bueno et al, 2008)
Total Cost of Inaction
Study Category
(US Billion Dollars)
2025
2050
2075
2100
Storms
0.2
0.4
0.7
1.1
Tourism
0.2
0.5
0.7
1
Infrastructure
0.8
1.6
2.4
3.2
Total
1.2
2.5
3.8
5.2
Percentage of GDP
1.4%
2.8%
4.4%
6%
(based on 2004 GDP)
Puerto Rico has fragile ecosystems, such as the karst regions in the south and
northern regions of the island (the latter being the most prominent). As stated by the
National Wildlife Federation (Hoey Diaz-Mendez, 2009), these areas are home to
approximately 1,300 species flora and fauna. Thirty are considered to be endangered, like
the Puerto Rican parrot (Amazona vittata). Changes in sea water temperatures and
nutrients could affect the lives of marine animals and plants, as well as increase coral
bleaching (which in turn endangers this important tourist attraction). Endangered marine
turtles are at risk as increasing sea levels flood nesting grounds on beaches. Populations
of endemic amphibians, such as the “coquí” (genus Eleutherodactylus), have declined, a
phenomenon that has been correlated with altered precipitation patterns (Hoey and DiazMendez, 2009).
2.5.3
Solid Waste Management in Puerto Rico
The Solid Waste Authority of Puerto Rico (or Autoridad de Desperdicios Sólidos,
ADS in Spanish) is the government agency in charge of developing waste management
programs. Puerto Rico has a solid waste generation factor of 5.56 lbs. per person per day
35
(3.91 lbs. per person per day excluding C&D). However, the diversion rate stands
currently at 15.3% (MP Engineers of PR, 2008). By contrast, United States’ MSW
generation factor as of 2008 was 4.50 lbs. per person per day (excluding C&D), of which
approximately 33% is diverted (USEPA, 2009).
Some waste management practices in Puerto Rico that have been available
traditionally include landfilling and recycling, although the former has been the dominant
course of action (Carim et al, 2007). By 1980 there were approximately 62 landfills
operating on the island, most of which posed serious environmental problems, primarily
leaching. ADS has taken the responsibility of developing safer waste management plans.
In particular, approximately 32 landfills were closed due to non-compliance with
environmental standards, and some of those currently operational are expected to reach
their capacity soon (Miranda and Hale, 2005).
ADS serves all 78 municipalities in Puerto Rico and implements a variety of
MSW management strategies. The measures currently available for waste management in
Puerto Rico include: source reduction and recycle programs, nine resource recovery
facilities, four composting facilities, 17 transfer stations, and 30 sanitary landfills (Figure
4). Some of these facilities are privately owned. Furthermore, municipalities can dispose
of their own waste (by hauling MSW to other municipalities or in their own landfills) or
contract a private company, ADS also implements and monitors recycling programs
among community groups, private commerce and industries, schools, and government
entities. Among these are collections of recyclables via “blue bags,” drop-off programs,
and other source separation programs (MP Engineers of PR, 2008). Improvements and
36
additions to current management practices have been proposed under the public policy
document Dynamic Itinerary of Infrastructure Projects (2008). In this document, ADS
explores the implementation of new MSW management initiatives through 2030.
Figure 4. Existing MSW Management Infrastructure (as of 2008)
(Source: MP Engineers, 2008)
2.5.4
Waste Characterization for Puerto Rico
Wehran Inc. (2003) classified the composition of MSW in Puerto Rico
through a study of twelve landfills and two transfer stations in 2003 (Figure 5). Their
study is used as one of the founding concepts for the Dynamic Itinerary for
Infrastructure Projects in order to draw projections of waste allocation and diversion
strategies. This type of project is typically carried out by collecting, sorting, and
weighing waste generated at different facilities and classifying the material into the
appropriate composition categories. The accuracy of such a study and its frequency
depend largely on costs (Dijols, 2010).
37
Figure 5. Waste Characterization for Puerto Rico (% by weight)
(Source: Wehran, Inc., 2003)
2.5.5
Energy Use and Production in Puerto Rico
Based on information from the Energy Information Administration (EIA) (2011)
for 2008, Puerto Rico consumes approximately 170 thousand barrels of petroleum
products per day, 26 billion cubic feet of natural gas per year, and 1,653 thousand short
tons of coal per year. The island consumes 0.389 quadrillion Btu (EIA, 2011). As a
primary input for electricity generation, approximately 90% are imports of oil from the
United States and Caribbean suppliers. Estimated electricity generation for 2002 was 19.2
billion kWh (Miranda and Hale, 2005). The most recent energy mix, however, as
estimated by the Puerto Rico Electric Power Authority (PREPA), is 68% oil-based, 15%
natural gas (LNG), 15% coal, and 2% hydro-power (PREPA, 2009).
38
CHAPTER III
METHODS
This study focuses on the quantification of GHG and energy savings of two
alternative solid waste management scenarios (“Base Case” and “Backup Case”)
compared to a business-as-usual (“No Action Case”) scenario for the years 2010, 2020,
and 2030. Table 2 shows the population projections, solid waste generation, and
projected MSW generation assumed for all scenarios (ADS calculations include C&D
debris). The scenarios explored were proposed by ADS in their public policy document
Dynamic Itinerary for Infrastructure Projects (2008).
Table 2. Population and MSW Generation in Puerto Rico, 2010 – 2030
(Source: MP Engineers of PR, 2008)
MSW Generation Factor Projected MSW
Year Population Projection
(lbs. per person per day) Generation (tons)
2010
4,030,152
5.56
4,089,395
2020
4,172,242
5.56
4,233,574
2030
4,256,441
5.56
4,319,011
3.1
WARM Inputs
This section outlines the information to be considered in WARM. ADS proposed
two major alternative scenarios for handling MSW through the year 2030. The scenarios
modeled in the Dynamic Itinerary assumed that the waste generation factor of 5.56 lbs.
per person per day remains constant throughout the planning period. This factor is
claimed to have been corroborated by comparing the waste generation factors of 4.5 lbs.
per person per day for the United States, which remained constant from the 1990s
through 2003 (MP Engineers of PR, 2008). The figures calculated by ADS show the
tonnage to be disposed (i.e., combustion and/or landfilling), and the amount to be
diverted (i.e., recycled and/or composted). The rates for the latter are determined using
the following formula (ADS, 2007):
(Recovered materials / Generated MSW) x 100 = % Diversion rate
Equation 2. Calculation of Diversion Rate for Puerto Rico
(Source: ADS, 2007)
The following strategies have been proposed to further integrate waste
management efforts, expand the current infrastructure, and attempt to re-allocate MSW in
Puerto Rico effectively. A brief description of each case as explained in the Dynamic
Itinerary is shown; Tables 3 – 11 provide the inputs for WARM calculations.
3.1.1
WARM Alternative Scenario 1 (“Base Case”)
The first alternative MSW management scenario is referred to as the “Base Case”
scenario. This includes the optimal MSW management strategies to be developed in
Puerto Rico. The projections from ADS indicate that there will be eight landfills in
operation with 17.8 years of useful life left at the end of the planning period (year 2030).
The following assumptions were considered by ADS (inputs on Tables 3 – 5; maps on
Figures 6 - 8) (MP Engineers, 2008):
40

Diversion rate reaches a 35% goal by 2016, and is assumed to remain constant
through 2030.

Two WtE facilities are constructed: the Northeastern plant processes
approximately 1,560 tons per day and is in service by 2013, while another,
constructed in the Northwestern region, processes 1,350 tons per day and is
online by 2012.

Once the landfills close, the MSW loads from various municipalities are
transferred to the new WtE facilities.

Existing landfills will use all of their remaining useful life before closing.

Remaining landfills are expanded.

Transfer of waste from closed to operating facilities is carried out through the
use of transfer stations (TS).

A new landfill is established in Peñuelas in 2010.
Figure 6. MSW Management Infrastructure for "Base Case," 2010
(Source: MP Engineers, 2008)
41
Figure 7. MSW Management Infrastructure for "Base Case," 2020
(Source: MP Engineers, 2008)
Figure 8. MSW Management Infrastructure for "Base Case," 2030
(Source: MP Engineers, 2008)
42
Table 3. WARM MSW Inputs for “Base Case”, 2010
Materials
Tons Generated Tons Landfilled Tons Recycled Tons Composted Tons Combusted
Polyethylene
44,983
34,637
10,346
0
0
HDPE
118,592
91,316
27,276
0
0
PVC, LDPE, PP, PS, Mixed
265,811
204,674
61,136
0
0
High Quality Paper
53,162
40,935
12,227
0
0
Low Quality Paper
355,777
273,949
81,829
0
0
Corrugated Carton
380,314
292,842
87,472
0
0
Ferrous Metals
384,403
295,990
88,413
0
0
Non-Ferrous Metals
44,983
34,637
10,346
0
0
Yard Waste
834,237
642,362
0
191,874
0
Organic Waste
527,532
406,200
0
121,332
0
Glass (all types)
98,145
75,572
22,573
0
0
Household hazardous waste
20,447
15,744
4,703
0
0
Not defined
257,632
198,377
59,255
0
0
Table 4. WARM MSW Inputs for “Base Case”, 2020
Materials
Tons Generated Tons Landfilled Tons Recycled Tons Composted Tons Combusted
Polyethylene
46,569
18,953
18,099
0
9,517
HDPE
122,774
49,968
47,716
0
25,090
PVC, LDPE, PP, PS, Mixed
275,182
111,997
106,949
0
56,236
High Quality Paper
55,036
22,399
21,390
0
11,247
Low Quality Paper
368,321
149,904
143,148
0
75,269
Corrugated Carton
393,722
160,242
153,020
0
80,460
Ferrous Metals
397,956
161,965
154,665
0
81,325
Non-Ferrous Metals
46,569
18,953
18,099
0
9,517
Yard Waste
863,649
351,500
0
335,656
176,493
Organic Waste
546,131
222,272
0
212,253
111,606
Glass (all types)
101,606
41,353
39,489
0
20,764
Household hazardous waste
21,168
8,615
8,227
0
4,326
Not defined
266,715
108,551
103,659
0
54,505
Table 5. WARM MSW Inputs for “Base Case”, 2030
Materials
Tons Generated Tons Landfilled Tons Recycled Tons Composted Tons Combusted
Polyethylene
47,509
19,228
18,483
0
9,798
HDPE
125,251
50,692
48,728
0
25,832
PVC, LDPE, PP, PS, Mixed
280,736
113,620
109,217
0
57,898
High Quality Paper
56,147
22,724
21,843
0
11,580
Low Quality Paper
375,754
152,076
146,183
0
77,495
Corrugated Carton
401,668
162,564
156,265
0
82,839
Ferrous Metals
405,987
164,312
157,945
0
83,730
Non-Ferrous Metals
47,509
19,228
18,483
0
9,798
Yard Waste
881,078
356,592
0
342,774
181,712
Organic Waste
557,152
225,492
0
216,754
114,906
Glass (all types)
103,656
41,952
40,326
0
21,378
Household hazardous waste
21,595
8,740
8,401
0
4,454
Not defined
272,098
110,124
105,857
0
56,117
43
3.1.2
WARM Alternative Scenario 2 (“Backup Case”)
This scenario is a substitute, in case the “Base Case” is not implemented.
Projections for the strategies of the “Backup Case” demonstrate that by 2030 there will be
eight landfills in operation with approximately 7.5 years of useful life left. Furthermore,
the development of WtE facilities is not pursued. The following assumptions are
considered in this scenario (see Tables 6 – 8 for inputs; maps on Figures 9 - 11):

MSW diversion rate in Puerto Rico reaches the 35% goal in 2026.

Existing landfills use all their remaining useful life before closing.

Expansion of landfills (similar to “Base Case”)

Transfer of waste from closed to operating landfills is facilitated through the
use of transfer stations.
Figure 9. MSW Management Infrastructure for "Backup Case," 2010
(Source: MP Engineers, 2008)
44
Figure 10. MSW Management Infrastructure for "Backup Case," 2020
(Source: MP Engineers, 2008)
Figure 11. MSW Management Infrastructure for "Backup Case," 2030
(Source: MP Engineers, 2008)
45
Table 6. WARM MSW Inputs for “Backup Case”, 2010
Materials
Tons Generated Tons Landfilled Tons Recycled Tons Composted Tons Combusted
Polyethylene
44,983
36,437
8,547
0
0
HDPE
118,592
96,060
22,533
0
0
PVC, LDPE, PP, PS, Mixed
265,811
215,307
50,504
0
0
High Quality Paper
53,162
43,061
10,101
0
0
Low Quality Paper
355,777
288,180
67,598
0
0
Corrugated Carton
380,314
308,054
72,260
0
0
Ferrous Metals
384,403
311,367
73,037
0
0
Non-Ferrous Metals
44,983
36,437
8,547
0
0
Yard Waste
834,237
675,732
0
158,505
0
Organic Waste
527,532
427,301
0
100,231
0
Glass (all types)
98,145
79,498
18,648
0
0
Household hazardous waste
20,447
16,562
3,885
0
0
Not defined
257,632
208,682
48,950
0
0
Table 7. WARM MSW Inputs for “Backup Case”, 2020
Materials
Tons Generated Tons Landfilled Tons Recycled Tons Composted Tons Combusted
Polyethylene
46,569
33,064
13,505
0
0
HDPE
122,774
87,169
35,604
0
0
PVC, LDPE, PP, PS, Mixed
275,182
195,379
79,803
0
0
High Quality Paper
55,036
39,076
15,961
0
0
Low Quality Paper
368,321
261,508
106,813
0
0
Corrugated Carton
393,722
279,543
114,179
0
0
Ferrous Metals
397,956
282,549
115,407
0
0
Non-Ferrous Metals
46,569
33,064
13,505
0
0
Yard Waste
863,649
613,191
0
250,458
0
Organic Waste
546,131
387,753
0
158,378
0
Glass (all types)
101,606
72,140
29,466
0
0
Household hazardous waste
21,168
15,029
6,139
0
0
Not defined
266,715
189,368
77,347
0
0
Table 8. WARM MSW Inputs for “Backup Case”, 2030
Materials
Tons Generated Tons Landfilled Tons Recycled Tons Composted Tons Combusted
Polyethylene
47,509
30,879
16,630
0
0
HDPE
125,251
81,408
43,844
0
0
PVC, LDPE, PP, PS, Mixed
280,736
182,465
98,271
0
0
High Quality Paper
56,147
36,493
19,654
0
0
Low Quality Paper
375,754
244,223
131,531
0
0
Corrugated Carton
401,668
261,066
140,602
0
0
Ferrous Metals
405,987
263,873
142,114
0
0
Non-Ferrous Metals
47,509
30,879
16,630
0
0
Yard Waste
881,078
572,660
0
308,418
0
Organic Waste
557,152
362,123
0
195,029
0
Glass (all types)
103,656
67,372
36,284
0
0
Household hazardous waste
21,595
14,036
7,559
0
0
Not defined
272,098
176,851
95,247
0
0
46
3.1.3
WARM Business-as-Usual Scenario (“No Action Case”)
The final waste management scenario is the “No Action Case”. This scenario
projects how quickly the currently-available disposal capacity will be depleted if no
future actions are taken and no growth in the current diversion rate occurs. While the
Dynamic Itinerary suggests that Puerto Rico will run out of landfill space by 2018, the
useful life of the current landfills is currently under revision (Rosario, 2011). The
following assumptions are considered (see Tables 9 – 11 for inputs; maps on Figures 12 14):

The current diversion rate of 15.3% remains constant through 2030.

No alternative technology processing facilities are implemented during the
period.

Existing landfills use all their remaining useful life before closing.

No landfill expansions are implemented.

Transfer of waste from closed to operating landfills is facilitated through the
use of transfer stations.

A new landfill is established at Peñuelas in 2010.
47
Figure 12. MSW Management Infrastructure for "No Action Case," 2010
(Sources: ADS; MP Engineers, 2008)
Figure 13. MSW Management Infrastructure for "No Action Case," 2020
(Sources: ADS; MP Engineers, 2008)
48
Figure 14. MSW Management Infrastructure for "No Action Case," 2030
(Sources: ADS; MP Engineers, 2008)
Table 9. WARM MSW Inputs for “No Action Case”, 2010
Materials
Tons Generated Tons Landfilled Tons Recycled Tons Composted Tons Combusted
Polyethylene
44,983
38,101
6,882
0
0
HDPE
118,592
100,448
18,145
0
0
PVC, LDPE, PP, PS, Mixed
265,811
225,142
40,669
0
0
High Quality Paper
53,162
45,028
8,134
0
0
Low Quality Paper
355,777
301,343
54,434
0
0
Corrugated Carton
380,314
322,126
58,188
0
0
Ferrous Metals
384,403
325,589
58,814
0
0
Non-Ferrous Metals
44,983
38,101
6,882
0
0
Yard Waste
834,237
706,598
0
127,638
0
Organic Waste
527,532
446,820
0
80,712
0
Glass (all types)
98,145
83,129
15,016
0
0
Household hazardous waste
20,447
17,319
3,128
0
0
Not defined
257,632
218,214
39,418
0
0
49
Table 10. WARM MSW Inputs for “No Action Case”, 2020
Materials
Tons Generated Tons Landfilled Tons Recycled Tons Composted Tons Combusted
Polyethylene
46,569
39,444
7,125
0
0
HDPE
122,774
103,989
18,784
0
0
PVC, LDPE, PP, PS, Mixed
275,182
233,079
42,103
0
0
High Quality Paper
55,036
46,616
8,421
0
0
Low Quality Paper
368,321
311,968
56,353
0
0
Corrugated Carton
393,722
333,483
60,240
0
0
Ferrous Metals
397,956
337,069
60,887
0
0
Non-Ferrous Metals
46,569
39,444
7,125
0
0
Yard Waste
863,649
731,511
0
132,138
0
Organic Waste
546,131
462,573
0
83,558
0
Glass (all types)
101,606
86,060
15,546
0
0
Household hazardous waste
21,168
17,929
3,239
0
0
Not defined
266,715
225,908
40,807
0
0
Table 11. WARM MSW Inputs for “No Action Case”, 2030
Materials
Tons Generated Tons Landfilled Tons Recycled Tons Composted Tons Combusted
Polyethylene
47,509
40,240
7,269
0
0
HDPE
125,251
106,088
19,163
0
0
PVC, LDPE, PP, PS, Mixed
280,736
237,783
42,953
0
0
High Quality Paper
56,147
47,557
8,591
0
0
Low Quality Paper
375,754
318,264
57,490
0
0
Corrugated Carton
401,668
340,213
61,455
0
0
Ferrous Metals
405,987
343,871
62,116
0
0
Non-Ferrous Metals
47,509
40,240
7,269
0
0
Yard Waste
881,078
746,273
0
134,805
0
Organic Waste
557,152
471,908
0
85,244
0
Glass (all types)
103,656
87,797
15,859
0
0
Household hazardous waste
21,595
18,291
3,304
0
0
Not defined
272,098
230,467
41,631
0
0
3.2
Transportation of MSW
WARM incorporates the impacts of transporting MSW to landfills, composting
facilities, recycling facilities, or WtE plants. The user may allow the default distances (20
miles towards any management facility) or define them according to particular needs or
plans. For the current project, distances were determined using ArcGIS (Environmental
Systems Research Institute – ESRI). This section explains the necessary steps taken in
50
order to complete this procedure. The GIS data (state roads and street level data) were
obtained from the Highway and Transportation Authority of Puerto Rico (Autoridad de
Carreteras y Transportación – ACT in Spanish). The road data was converted into a
network dataset, a required format for the ArcGIS extension Network Analyst (Figure
15).
The built-in extension Network Analyst offers the user a variety of analysis tools
to solve problems in the transportation arena. Researchers and analysts often use this
software to determine the least-cost road network paths between several origins and
destinations. An example is the Origin – Destination (OD) Cost Matrix analysis. When
configuring this type of analysis, the user can specify the number of destinations to
determine and a maximum distance to search over a road network. Even though its output
is represented by straight lines, the analysis is still carried out using the road data input
(ESRI, 2011).
Due to the complexity of the MSW transfer procedures over the years in question,
several OD Cost Matrices were created. “Centroids” (i.e., the geometric center of a
polygon) for each municipality were calculated in order to serve as locations. The origins
and destinations used in the analysis were (see Appendices I – IX for detailed tables):
Municipalities  Composting Facilities
Municipalities  MRF
Municipalities  Landfills
Municipalities  Transfer Stations
Transfer Stations  Landfills and/or WTE
51
Pre-processing consisted in creating the necessary files for analysis. The “roads”
shapefile obtained was first converted into a network dataset in ArcCatalog. The defaults
were selected in order to create the dataset. However, in the “Connectivity” menu, the
values were set for “Any Vertex,” thus allowing turns at any point in a road segment and
not just at the end vertex. Next, the dataset attributes were specified to be based on
“shape length,” which is the default value when no other attribute is specified. Directions
were of no concern in this study. Once the necessary parameters are set, ArcCatalog
builds the network dataset, resulting in the creation of two network feature classes: nodes
(representing the points of intersection between line segments), and edges (representing
the actual road geometry, and the basis of distance measurements).
The newly-created network dataset was added to a map document in ArcMap for
analysis. Once there, the Network Analyst toolbar was used. From the options offered for
analysis, only located “Origins” and “Destinations,” and “Lines” were used. In the
Network Analyst window, these were loaded by selecting “Load Locations,” taking the
“Centroids” shapefile as the layer of choice for both origins and destinations, based on
the information shown in the Dynamic Itinerary for each case. For example, in the case
of hauling waste from municipalities to compost sites, the chosen municipalities were set
as the origin while the centroids known to have these facilities were set as destinations.
This was carried out individually for every case, year of interest, and type of MSW
management facility (landfill, MRF, transfer station, compost facility, or WtE) in order to
obtain the distances required in WARM.
52
Before the analysis is run, certain parameters must be set in the OD Cost Matrix
layer properties. In this window, the “Analysis Settings” were set as defaults, except “UTurns” were specified to be allowed only at dead-ends and intersections. Second,
“Length” was selected as the accumulation attribute in the “Accumulation” tab. Finally, a
high search tolerance value was selected in order to ensure that all the locations were
found by Network Analyst within the road network. Once this procedure is completed,
the analysis was run by selecting “Solve.” The OD Cost Matrix layer now included
values in the “Lines” feature class. Since the search tolerance was set to be high, the
analysis connected every origin with all found destinations. Therefore, the resulting
feature class was reviewed, and only the paths for the researched origins and destinations
were selected, thus tying each participating municipality with the one MSW management
option, depending on the case studied. This process was carried out for every OD Cost
Matrix layer developed in this project. The coordinate system of the road network utilizes
meters as distance units; therefore, these were converted to miles in order to be used in
WARM.
The street level distances for every municipality were extracted using the tool
“Intersect” and then averages were determined with the “Summary Statistics” analysis
tool. The measurements were then added to the distances computed in the OD Cost
matrices, thus including curbside collection in the analysis. Finally, the average distances
towards any facility were calculated and entered in WARM.
53
Figure 15. Road Network of Puerto Rico (highways only)
(Source: ACT, 2010)
3.3
Study Assumptions and Limitations
 The study took into account the assumptions by ADS for each scenario.
However, under the “No Action” scenario it is assumed that the landfills
proposed to be closed during the years 2007 – 2010 are still in operation
(applicable to the WARM analysis for 2010).
 MSW composition is the same for all scenarios and studied years (MP
Engineers, 2008).
 The main recovery strategy for all inorganic materials is considered to be
recycling while composting is the main strategy for organic waste.
 LFG combustion is considered to be negligible, as there are only two landfills
out of 32 with such capability; the gas is not converted to energy (MP
Engineers, 2008).
54
 The vehicle type considered by WARM is a diesel-fueled truck (Hartwell,
2011).
 Puerto Rico’s resource mix is not included in the eGRID database. Therefore,
the “National Average” option was selected as the energy analysis input in
WARM.
 The facilities shown on maps and the distances from municipalities towards
any facility are based mainly on research and interpretation from the Dynamic
Itinerary of Infrastructure Projects, the Strategic Plan for the Management of
Solid Residues (PEMRS, 2003), and interviews with ADS personnel from the
Planning and Engineering Division. However, the position of facilities on the
maps are meant for study purposes only and do not represent their actual
locations in Puerto Rico.
 The researched documents do not show which municipalities participate in
composting; therefore, municipalities adjacent to composting facilities were
selected for this study in order to show the impacts of hauling organic waste.
 ADS has determined that a certain percentage of C&D debris will be
combusted. However, WARM does not include this option in detail.
Furthermore, USEPA does not include C&D a component in MSW (USEPA,
2009). Thus, these materials were not included in this study.
55
CHAPTER IV
RESULTS AND DISCUSSION
The results from this study are presented in three sections. First, results and
analysis from MSW transportation through the Puerto Rican road network are disclosed.
As stated in Chapter III, the determination of distances to solid waste management
facilities is a necessary component in WARM. Secondly, the GHG emission estimates
from WARM are discussed, both as total and per ton of each MSW components managed
(per ton basis). Finally, WARM estimates for energy usage per case are presented (total
and per ton basis). Furthermore, certain issues about the development and
implementation of the studied scenarios are discussed.
4.1
Transportation Analysis
Average distances covering the stages from curbside collection to any MSW
management option were calculated using ArcGIS Network Analyst (Table 12). These
values represent the mileage that the collective MSW generated in a given case would be
hauled to other municipalities housing the corresponding waste management facility. The
closure of landfills over the years (especially in the northern part of the island) would
mean greater distances would be travelled in order to dispose of waste in the remaining
landfills. However, recycling and composting of waste may be more accessible to several
municipalities as more facilities are constructed, even though the decisions to send the
recyclable material to any processing facility would most likely be determined by the
monetary value that could be gained (Rosario, 2011). Despite the premise that only
average distances in any given year are used in WARM, each waste management
scenario has distinct characteristics regarding hauling distances. Maps are shown for each
case and year studied (Figures 16 – 49). In each map, the lines represent the trips from
municipalities to waste management facilities (symbolized by icons).
Table 12. MSW Hauling Distances as Determined by ArcGIS Network Analyst
MSW Management Facility
Case
Average Distances to Facilities (miles)
2010
2020
2030
Base
38
38
45
Backup
43
54
56
Landfills
NoAction
29
54
61
Average
37
49
54
Base
19
17
17
Backup
19
18
18
MRF
NoAction
19
19
19
Average
19
18
18
Base
9
9
9
Backup
9
9
9
Compost
NoAction
9
9
9
Average
9
9
9
Base
0
30
30
WTE
Backup
0
0
0
NoAction
0
0
0
4.1.1
Transportation in “Base Case”
The “Base Case” (WARM Alternative 1) scenario is characterized by the goal of
reaching a 35% recycling rate, decreasing reliance on landfills, and the introduction of
WtE as a disposal method. As landfills are set for closure through 2030 (Figures 16 - 22)
and approximately 20 - 25% of MSW is processed by combustion, the average hauling
57
distances to landfills within this scenario are lower compared with those in the other two
cases. In terms of distances towards recycling facilities, the implementation of more
MRFs would allow for more municipalities to have their recyclable materials processed
within shorter distances, instead of sending them to facilities located farther from
participating municipalities (Figures 23 and 24). The same would apply to new
composting facilities (Figures 25 and 26). Distances to WtE facilities would increase as
more distant municipalities transport their waste (Figures 27 and 28). Another factor that
influences the distances toward the disposal facilities (either landfill or WtE) is the use of
transfer stations, in which case the waste from municipalities would be temporarily
deposited and then hauled to the corresponding facilities in trips as frequent as 4-5 times
each day (Rosario, 2011).
Figure 16. MSW Hauling Distances: Municipalities – Landfills
“Base Case” 2010
58
Figure 17. MSW Hauling Distances: Municipalities – Landfills
“Base Case” 2020
Figure 18. MSW Hauling Distances: Municipalities – Landfills
“Base Case” 2030
59
Figure 19. MSW Hauling Distances: Municipalities - Transfer Stations
“Base Case” 2010, 2020, and 2030
Figure 20. MSW Hauling Distances: Transfer Stations – Landfills
“Base Case” 2010
60
Figure 21. MSW Hauling Distances: Transfer Stations – Landfills
“Base Case” 2020
Figure 22. MSW Hauling Distances: Transfer Stations – Landfills
“Base Case” 2030
61
Figure 23. MSW Hauling Distances: Municipalities – MRF
“Base Case” 2010
Figure 24. MSW Hauling Distances: Municipalities – MRF
“Base Case” 2020 and 2030
62
Figure 25. MSW Hauling Distances: Municipalities – Compost Facilities
“Base Case” 2010
Figure 26. MSW Hauling Distances: Municipalities – Compost Facilities
“Base Case” 2020 and 2030
63
Figure 27. MSW Hauling Distances: Municipalities – WtE
“Base Case” 2020
Figure 28. MSW Hauling Distances: Municipalities – WtE
“Base Case” 2030
64
4.1.2
Transportation in “Backup Case”
The “Backup Case” (WARM Alternative 2) scenario is characterized by reaching
the 35% diversion rate much later than in the “Base Case.” Moreover, no WTE projects
would be implemented. Since the landfills would receive more MSW than in the previous
scenario, their capacities will be reached sooner, and so will their corresponding closure
dates (Figures 29 - 35). MSW may also need to be hauled more frequently. However, the
distances travelled to recycling and composting facilities would be similar to the “Base
Case” as the same facilities have been proposed for this scenario as well (Figures 36 39).
Figure 29. MSW Hauling Distances: Municipalities – Landfills
“Backup Case” 2010
65
Figure 30. MSW Hauling Distances: Municipalities – Landfills
“Backup Case” 2020
Figure 31. MSW Hauling Distances: Municipalities – Landfills
“Backup Case” 2030
66
Figure 32. MSW Hauling Distances: Municipalities – Transfer Stations
“Backup Case” 2010, 2020, and 2030
Figure 33. MSW Hauling Distances: Transfer Stations – Landfills
“Backup Case,” 2010
67
Figure 34. MSW Hauling Distances: Transfer Stations – Landfills
“Backup Case” 2020
Figure 35. MSW Hauling Distances: Transfer Stations – Landfills
“Backup Case” 2030
68
Figure 36. MSW Hauling Distances: Municipalities – MRF
“Backup Case” 2010
Figure 37. MSW Hauling Distances: Municipalities – MRF
“Backup Case” 2020 and 2030
69
Figure 38. MSW Hauling Distances: Municipalities – Compost Facilities
“Backup Case” 2010
Figure 39. MSW Hauling Distances: Municipalities – Compost Facilities
“Backup Case” 2020 and 2030
70
4.1.3
Transportation in “No Action Case”
Even though the “No Action” (WARM Business-as-Usual) scenario was not
explored in the Dynamic Itinerary, it was still necessary to develop distance models for
comparison. It has been suggested that Puerto Rico will run out of landfill space by 2018
if there are no changes in disposal and diversion rates (MP Engineers of PR, 2008).
However, the closure dates for landfills need to be revised extensively, as they may be
able to withstand more years than estimated in the aforementioned document (Rosario,
2011). Based on this premise, the modeled distances share some similarity to the
“Backup Case”, except that landfill space would be depleted more quickly. This scenario
also assumes that certain landfills that would have ceased operations in 2010 in the
previous cases are still open in said year, thus showing shorter distances from
municipalities to landfills (Figures 40 – 47). However, as the years progress, the MSW
would be more difficult to transport due to the lack of new transfer stations. As for
recycling and composting, the reduced number of facilities would mean longer distance
for the transportation of recyclables (Figures 48 and 49).
71
Figure 40. MSW Hauling Distances: Municipalities – Landfills
“No Action Case” 2010
Figure 41: MSW Hauling Distances: Municipalities – Landfills
“No Action Case” 2020
72
Figure 42. MSW Hauling Distances: Municipalities – Landfills
“No Action Case” 2030
Figure 43. MSW Hauling Distances: Municipalities – Transfer Stations
“No Action Case” 2010
73
Figure 44. MSW Hauling Distances: Municipalities – Transfer Stations
“No Action Case” 2020 and 2030
Figure 45. MSW Hauling Distances: Transfer Stations – Landfills
“No Action Case” 2010
74
Figure 46. MSW Hauling Distances: Transfer Stations – Landfills
“No Action Case” 2020
Figure 47. MSW Hauling Distances: Transfer Stations – Landfills
“No Action Case” 2030
75
Figure 48. MSW Hauling Distances: Municipalities – MRF
“No Action Case” 2010, 2020, and 2030
Figure 49. MSW Hauling Distances: Municipalities – Compost Facilities
“No Action Case” 2010, 2020, and 2030
76
4.1.4
Summary of Transportation Analysis
GHG emissions from transportation of waste varies at certain points of the life
cycle, mostly due to the distances travelled, transport efficiencies, and type of transport
vehicle. Eisted et al (2009) concluded that there are fewer emissions when larger vehicles
(including marine transports) are employed to transport waste. This type of vehicle is also
used for longer hauling distances, and newer equipment often offers better fuel
efficiencies (Eisted et al, 2009). This represents an important opportunity for Puerto
Rico, in the sense that the proposed transfer stations will play an important role in the
mitigation of GHG emissions. As the northern municipalities transfer their waste to the
south or to WtE plants, further emission savings can be achieved. The municipalities of
Vieques and Culebra, however, will have to rely on barges to transport their MSW to the
main island.
Regarding recyclable materials, changes in transport-based emissions are seen in
the upstream parts of the life cycle (i.e., materials extraction). By reaching higher
diversion rates, there will be less mileage travelled in order to transport virgin materials
for manufacturing of new products (USEPA, 2002b). While Puerto Rico has several
drop-off points for recycling materials, it is important to continue to encourage the
citizens towards this practice. Furthermore, materials exchange programs can contribute
to source reduction of waste.
4.2
Greenhouse Gas Emissions Analysis
Both alternative scenarios were analyzed in WARM and compared to the “No
Action Case,” thus estimating GHG emission reductions. The GHG emissions from both
77
the total within a specific scenario and the emissions from each of the waste components
selected (per ton basis) are shown in MTCO2E (Figures 50 – 53).
On a per ton basis, the output of emissions from the materials included in WARM
are a net result of their life cycle. The considerations drawn from the model’s background
documentation are summarized below (USEPA, 2002b):

Metals: emissions are positive from transportation and sorting/processing of
MSW. Virtually no emissions are determined from their disposal in landfills
or WtE. Recycling and source reduction of metals result in emission savings.

Glass and Plastics: positive emissions are observed in transportation and
sorting/processing of MSW. Offsets from source reduction and landfilling are
slightly higher than landfilling or combustion emissions (specially for glass)

Paper-based MSW (carton and paper): positive emissions result from
transportation, processing, and combustion. WARM emission values,
however, are slightly positive for the landfilling of corrugated carton and high
quality paper (e.g., from offices and textbooks). Net combustion values are
negative for all paper-based products due to the potential avoidance of fossil
fuel-based utility emissions. Source reduction and recycling result in emission
reductions. Composting of these products is not modeled in WARM.
4.2.1
Emissions in “No Action Case”
The “No Action” scenario showed the least GHG emission reductions compared
to the other two alternative cases for all years. In the “No Action Case,” there is an overreliance on landfills, while keeping the MSW diversion rates capped at 15.3% for all
78
studied years (MP Engineers, 2008). On a per ton basis, fewer reductions in GHG arise
from the management of paper, cardboard, mixed organic material, and mixed
recyclables represent increases in emissions (Figure 50). As more carbon-based solid
waste is sent to landfills, there will be more methane emitted as a result of
biodegradation, in addition to the emissions from first stages of the products’ life cycle
and transportation (USEPA, 2002b). Furthermore, the landfills do not possess LFG
flaring or energy recovery capabilities, in which case WARM assumed increased
emissions mainly due to fugitive emissions.
Figure 50. Greenhouse Gas Emissions for the "No Action Case" (Business-as-Usual)
4.2.2
Emissions in “Backup Case”
The “Backup” scenario shows higher GHG reductions than the “No Action Case”
(Figure 51). In this case, the diversion rates expected for 2010, 2020, and 2030 are 19%,
29%, and 35% respectively. Since there would be increased materials recycling, GHG
79
reductions are achieved for the studied years (25% for 2010, 93% for 2020, 134% for
2030) when compared to the “No Action” Case). From an LCA perspective, this means
that there would be fewer raw materials extraction and less energy use for the
manufacturing of new products.
Figure 51. Greenhouse Gas Emissions for the "Backup Case" (Alternative 2)
4.2.3
Emissions in “Base Case”
In contrast to the two previous scenarios, the “Base Case” considers the
introduction of combustion as a new waste management option (Figure 52). Furthermore,
higher diversion rates are reached sooner (23% in 2010 and 35% in 2020 and 2030) (MP
Engineers, 2008). For the year 2010, the “Base Case” also follows a similar trend as the
previous scenarios in terms of landfilling (i.e., low emissions for glass, metals, and
plastics, and higher for carbon-bearing materials), but the emissions are lower for carbon-
80
based waste due to the higher diversion rates. The greater differences in GHG emissions,
however, are observed after 2020. Once WtE plants go online as proposed, the reductions
in GHG seem to be higher than in the other scenarios (53% in 2010, 215% in 2020, and
216% in 2030 when compared against the “No Action” scenario).
Figure 52. Greenhouse Gas Emissions for the "Base Case" (Alternative 1)
4.2.4
Summary of Greenhouse Gas Emissions Analysis
Overall, net GHG emissions would increase gradually if no action is taken toward
implementing and enforcing better MSW management initiatives (Figure 53). From the
results derived from WARM, a balanced plan including combustion and higher diversion
rates (i.e., “Base Case”) would mean greater savings in GHG emissions (i.e., increased
environmental benefits). Recyling and composting more waste (as presented in the two
alternative scenarios), will decrease the amounts to be disposed in landfills, and in turn,
81
avoid GHG emissions from the uncontrolled decomposition of waste. However, the main
factor that accentuates the environmental benefits of the “Base Case” is the
implementation of WtE. As explained in Chapter II, these technologies do emit GHGs,
but these values are well below the regulated emissions. Moreover, WtE has a potential
for materials recovery and displacement of fossil fuels for electricity generation (USEPA,
2002b). Further considerations regarding implementation are presented in Section 4.4.
Figure 53. Net Greenhouse Gas Emissions for All Studied Cases and Years
4.3
Energy Use Analysis
WARM calculated results for energy consumption per waste management
scenario in million BTUs. As with the previous analysis, both alternative scenarios were
compared against the “No Action” case.
82
WARM draws most of its energy values from the upstream stages of the life cycle
(i.e., raw materials acquisition, processing, and manufacturing), but it also includes
energy values from transportation of virgin material, products, and waste. These values
vary depending on waste management practice and type of material. Considerations
included in the model are summarized as follows (USEPA, 2002b):

Source reduction: higher energy savings are observed due to the higher
potential of virgin materials displacement and diminishing need to transport
raw inputs.

Recycling: energy values follow a similar trend to those from source
reduction. However, certain materials, such as dimensional lumber and
fiberboard, require some energy in processing and transportation throughout
their life cycle.

Combustion: energy savings are observed for all materials except metals and
glass, primarily due to the use of fossil fuels for processing. Even though
these materials require more energy for their successful combustion, metals
and glass can be recovered, resulting in some energy savings in this respect.

Landfilling: energy is consumed mostly in transportation of MSW to landfills.
Their disposal, however, means that little energy is used in their processing, as
wastes are allowed to decompose. Furthermore, if landfills are equipped with
landfill gas-to-energy systems, an energy savings will result.
83
4.3.1
Energy Use in “No Action Case”
The “No Action” scenario showed the lowest reductions of energy consumed (net
and per ton basis) (Figure 54). This is due to the simplistic management scheme
employed for all years, which involves increased landfilling and a low diversion rate (MP
Engineers, 2008). The organic materials would require additional energy for management
practices in landfills and compost facilities, especially for equipment and hauling vehicles
(USEPA, 2002b). For other materials, the energy factors used in WARM for recycling
outweigh the factors for landfilling. Therefore, with the diversion rate of 15.3%, the
reductions in energy use per recycled ton of select MSW may be less.
Figure 54. Energy Consumption in the "No Action Case" (Business-as-Usual)
84
4.3.2
Energy Use in “Backup Case”
The “Backup” (Alternative 2) scenario shows even greater reductions in energy
usage for all materials (Figure 55). As with the GHG emissions analysis, it is observed
that higher diversion rates result in more energy savings per ton of managed MSW.
However, the energy use reductions show gradual changes, mainly due to the employing
recycling and composting as the only diversion strategies.
Figure 55. Energy Consumption in the "Backup Case" (Alternative 2)
4.3.3 Energy Use in “Base Case”
In contrast to the two previous MSW management scenarios, energy consumption
in the “Base Case” changes once combustion is introduced. The combination of both WtE
and improved recycling results in greater savings in energy use for some MSW
components (Figure 56). It is important to consider that recycling factors in WARM are
85
higher than those for combustion on a per ton basis (USEPA, 2002b). This is especially
true for metals, glass, and paper, but the diversion rates are higher than the rates for
combustion. On the other hand, the implementation of WtE can potentially serve as a
replacement for fossil fuels used for electricity generation.
Figure 56. Energy Consumption in the "Base Case" (Alternative 1)
4.3.4
Summary of Energy Consumption Analysis
In general, energy benefits can be derived in all scenarios. However, the “Base
Case” would offer the greatest overall reductions. (Figure 57). In LCA terms, energy use
savings are derived from transportation, materials extraction, manufacturing, and energy
production (USEPA, 2002b). As recycling rates increase, there is a reduced need for the
extraction, transportation, and usage of virgin materials for the manufacturing of new
86
products. This would also be applied to the displacement of fossil fuels for energy
generation achieved by implementing combustion.
Figure 57. Net Energy Consumption in All Studied Cases and Years
4.4
Considerations regarding Proposed MSW Scenarios
In addition to the reductions both in GHG and energy usage, the previous results
also represent the importance of achieving higher diversion rates of MSW from landfills
(Table 13). The information shown in the Dynamic Itinerary describes certain initiatives
such as collecting recyclables at curbside, the development of more MRFs and compost
sites, implementation of community programs, and increased participation rates, in
addition to promoting mandatory recycling programs.
87
Table 13. Comparison of MSW Management Scenarios as Calculated in WARM
ADS Scenario
"Base Case"
"Backup Case"
"No Action Case"
GHG Emissions (MTCO2E)
Years
2010
2020
2030
558,795 -1,409,860 -1,461,456
883,854
77,828
-434,633
1,184,519 1,231,236 1,258,209
Energy Use (million BTU)
Years
2010
2020
2030
-11,970,162 -26,619,000 -27,210,447
-9,558,595 -16,081,152 -20,211,814
-7,328,120
-7,519,179
-7,642,085
* Negative values represent benefits or savings
In terms of increased recovery, capture, and participation rates for recyclable
materials, the Wehran Inc. Study recommendations (included in the Dynamic Itinerary)
determined that the required rates to achieve the 35% diversion rate are as shown in
Table 14 (MP Engineers of PR, 2008).
Table 14: ADS Strategies and Goals for Achieving the 35% Diversion Rate
(Source: MP Engineers of PR, 2008)
Material Capture Rate (%) Participation Rate (%) Recovery Rate (%)
Plastics
50 - 60
40 - 60
25 - 50
Paper
70 - 90
50 - 70
20 - 50
Carton
90
80
70
Metals
80 - 90
60 - 80
50 - 70
Yard waste
90
70
60
Glass
60 - 70
50 - 60
30 - 40
ADS has recognized that implementing recycling and source reduction programs
would be challenging, particularly if programs such as PAYT are implemented. In such
cases, the costs would most likely concern citizens and may give way to littering and
clandestine disposal (MP Engineers of PR, 2008). Another alternative for increasing the
diversion rate would be implementing programs similar to the WasteWise program
sponsored by USEPA. This is a free and voluntary program through which organizations
minimize both the costs of MSW management and environmental degradation. Through
the promotion of commercial and industrial partnerships, there is the potential to improve
88
materials exchange (USEPA, 2011). Currently, ADS and USEPA sponsor an initiative
known as “Puerto Rico Materials Exchange”, in which companies that generate
recyclable waste can register and communicate with other companies that may need such
materials as inputs (ADS, 2011).
WtE has been proposed in the past for Puerto Rico, but it has encountered heavy
opposition from the general public as well as certain scientific organizations. A major
WtE project that was defeated mainly due to public opposition was the development of a
plant in Caguas (Gigante, 2000). The most recent controversy is over the development of
a WtE project in the municipality of Arecibo by the company Energy Answers, and there
are claims that such a project would be detrimental to the surrounding communities as
emissions are thought to compromise human health (Colón, 2011). Even though this
method of MSW management has been used for years in the U.S., it may still run into
obstacles before it is implemented successfully in Puerto Rico. While it is important to
investigate this technology thoroughly, it is equally imperative to determine a solution in
response to the increasing loads of MSW that will be generated in the future and the lack
of space to dispose of such in the island.
The “Base Case” offers more benefits other than GHG emission and energy
consumption savings. This scenario represents an opportunity to strengthen industrial
ecology and symbiosis practices. The principles of such practices involve the exchange of
wastes, by-products, and energy among industrial facilities located in geographic
proximity (Ehrenfeld and Gertler, 1997). Moreover, by exchanging resources there is a
reduced need for virgin materials and their associated costs (Chertow, 2007). An example
89
of materials recovery and recycling was reported by Eckelman and Chertow (2009) in
Hawaii. This state reuses approximately 210,000 tons of inorganic minerals as landfill
caps, structural fill, and road base material (Eckelman and Chertow, 2009). Energy
recovery could also serve as a materials recovery practice. For instance, metals can be
extracted easily, while ash residues can be used as inputs in the cement industry (Pichtel,
2005). Such opportunities have been observed by Hashimoto et al (2010), in which there
was a reduction in GHGs from this practice. In Puerto Rico, the WtE project to be
implemented by Energy Answers is claimed to include a materials recovery function, as
well as energy recovery (Energy Answers, 2008). As such, it can be concluded that it
may be possible to develop stronger materials exchange networks in solid waste
management. Examples to follow in this regard are the pharmaceutical companies
stationed in Puerto Rico, which share wastewater processing (Chertow, 2007).
Nevertheless, in order to fully integrate an industrial ecology framework, the
participating processes must be located closely.
90
CHAPTER V
CONCLUSION
GHG emissions and energy consumption analyses for all MSW management
scenarios proposed by ADS in Puerto Rico were assessed. It was concluded that the
“Base Case” includes the best strategies that would result in increased environmental
benefits (i.e., GHG reductions) while decreasing energy usage. The “Backup Case” may
offer fewer GHG reductions, but it is another alternative to pursue if the “Base Case” is
not fully implemented. While WARM may not be as accurate for the island as it would
be for other US states, mainly due to the absence of energy-related data in the model’s
programming, this tool represents an opportunity for Puerto Rico to track emissions from
waste management efforts, either private or public. Moreover, the results can be used to
better understand the benefits derived from wise management decisions.
Judging from the analysis by the USEPA greenhouse gas accounting tool WARM,
it is possible for Puerto Rico to enjoy enhanced environmental benefits by improving
waste management strategies. In order to increase these benefits it is evident that wise
integrated solid waste management plans are required. It is also highly encouraged for
Puerto Rico to consider more specific accounting tools and to remain updated on
management strategies in order to solve this problem and mitigate its climate change
footprint.
REFERENCES
ACT. Puerto Rico Road Network. Apr. 2010. GIS data. Autoridad De Carreteras Y
Transportacion, San Juan, PR.
ADS. "News and Info." Puerto Rico Materials Exchange. Autoridad De Desperdicios
Sólidos. http://www.prmatex.org/ (accessed March 27, 2011).
ADS. Tasa De Reciclaje Y Tasa De Desvio: Informe Final. Rep. San Juan, PR: Autoridad
De Desperdicios Sólidos, 2007.
American Public Power Association. Waste-to-Energy: A Primer for Utility Decisionmakers. Falls Church,VA: Meridian Corporation, 1986.
Andersen, Jacob K. Composting of Organic Waste: Quantification and Assessment of
Greenhouse Gas Emissions. Thesis. Technical University of Denmark, 2010.
Virum: Vester Kopi, 2010.
Biello, David. "10 Solutions for Climate Change." Scientific American. Nature America
Inc., 26 Nov. 2007. http://www.scientificamerican.com/article.cfm?id=10
solutions-for-climate-change (accessed December 20, 2010).
Block, Dave. "Reducing Greenhouse Gases at Landfills." BioCycle Apr. 2000: 40-46.
Bogner, Jean E., Jeffrey P. Chanton, Donald Blake, Tarek Abichou, and David Powelson.
"Effectiveness of a Florida Landfill Biocover for Reduction of CH4 and NMHC
Emissions." Environmental Science & Technology 44 (2010): 1197-203.
Bogner, Jean, Ritta Pipatti, Seiji Hashimoto, Cristobal Diaz, Katarina Mareckova, Luis
Diaz, Peter Kjeldsen, Suvi Monni, Andre Faaij, Qingxian Gao, Tianzhu Zhang,
Mohammed A. Ahmed, R.T. M. Sutamihardja, and Robert Gregory. "Mitigation
of Global Greenhouse Gas Emissions from Waste: Conclusions and Strategies
from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment
Report. Working Group III (Mitigation)." Waste Management & Research 26
(2008): 11-32.
Boisson, Ed, and Tony Georgis. "Recycling and Climate Change: A Primer." Resource
Recycling 28.8 (2009): 16-22.
Brown, Sally, and Scott Subler. "Composting and Greenhouse Gas Emissions: A
Producer's Perspective." BioCycle March (2007): 37-41.
Brown, Sally, Chad Kruger, and Scott Subler. "Greenhouse Gas Balance for Composting
Operations." Journal of Environmental Quality 37 (2008): 1396-410.
Bueno, Ramon, Cornelia Herzfeld, Elizabeth A. Stanton, and Frank Ackerman. The
Caribbean and Climate Change: The Costs of Inaction. Rep. Tufts University,
2008.
Carim, Michael, Whitney Blake, Alex Amerman, Billy Gridley, Monica Kurpiewski,
Sung Ah Lee, Safet Marke, Nina Kishore, Adam Raphaely, and Allison D. Reilly.
Waste to Energy: A Possibility for Puerto Rico. Rep. New York, NY: Columbia
University, 2007.
Carter, M. M., and J. B. Elsner. "A Statistical Method for Forecasting Rainfall over
Puerto Rico." American Meteorological Society 12. September (1997): 515-25.
Chang, Ni-Bin, H. Y. Lu, and Y. L. Wei. "GIS Technology for Vehicle Routing and
Scheduling in Solid Waste Collection Systems." Journal of Environmental
Engineering 123.9 (1997): 901-10.
Chertow, Marian. "The Ecology of Recycling." UN Chronicle 3-4 (2009): 56-60.
Chertow, Marian R. "Uncovering Industrial Symbiosis." Journal of Industrial Ecology
11.1 (2007): 11-30.
Colón, Raúl. "House to Probe Arecibo Incinerator." Puerto Rico Daily Sun. Cooperative
Prensa Unida, 25 Feb. 2011. http://www.prdailysun.com/?page=news.article&id=
1298656160 (accessed March 27, 2011).
CSA Group. Declaracion De Impacto Ambiental Estrategica Para El Itinerario
Dinamico Para Proyectos De Infraestructura: Documento De Politica Publica.
Rep. no. CEE-SA-08-997. San Juan, PR: Comision Estatal De Elecciones, 2008.
Daly, Christopher, E. H. Helmer, and Maya Quinones. "Mapping the Climate of Puerto
Rico, Vieques, and Culebra." International Journal of Climatology 23 (2003):
1359-381.
De Cuba, Kevin, Francisco Burgos, Ruben Contreras-Lisperguer, and Renortha Penny.
“Limits and Potential of Waste-to-Energy Systems in the Caribbean.” Department
of Sustainable Development: Organization of American States, 2008.
93
Dijols, Margarita. "Dynamic Itinerary." Telephone interview. 21 Dec. 2010.
Eckelman, Matthew J., and Marian R. Chertow. "Using Material Flow Analysis to
Illuminate Long-Term Waste Management Solutions in Oahu, Hawaii." Journal
of Industrial Ecology 13.5 (2009): 758-74.
Ehrenfeld, John, and Nicholas Gertler. "Industrial Ecology in Practice." Journal of
Industrial Ecology 1.1 (1997): 67-79.
EIA. "Puerto Rico." US Energy Information Administration. US Department of Energy,
14 June 2010. http://www.eia.gov/countries/country-data.cfm?fips=RQ#data
(accessed October 10, 2010).
Eisted, Rasmus, Anna W. Larsen, and Thomas H. Christensen. "Collection, Transfer, and
Transport of Waste: Accounting of Greenhouse Gases and Global Warming
Contribution." Waste Management & Research 27 (2009): 738-45.
Energy Answers. "Puerto Rico Resource Recovery and Renewable Energy Project."
Energy Answers International. 2008. http://www.energyanswers.com/
development/current_projects/arecibo_resource_recovery_facility/ (accessed
April 4, 2011).
ESRI. "OD Cost Matrix Analysis." ArcGIS Resource Center. Environmental Systems
Research Institute, 2010. http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.
html#//00470000004r000000.htm (accessed January 20, 2011).
Favoino, Enzo, and Dominic Hogg. "The Potential Role of Compost in Reducing
Greenhouse Gases." Waste Management & Research 26 (2008): 61-69.
"General Information on the Link Between Solid Waste Management and Greenhouse
Gas Emissions." Climate Change. US Environmental Protection Agency, 17 Dec.
2010. http://www.epa.gov/climatechange/wycd/waste/generalinfo.html (accessed
December 20, 2010).
Gigante, Lucienne. "Wiping Out Waste: Gov. Pedro Rossello Signs Bill To Allow
Construction Of Plant In Caguas To Process 30% Of Puerto Rico’s Garbage,
Including San Juan." Puerto Rico Herald. Casiano Communications, 10 Aug.
2000. http://www.puertorico-herald.org/issues/vol4n32/CBWaste-en.html
(accessed October 10, 2010).
Han, Haibin, Guangren Qian, Jisheng Long, and Shude Li. "Comparison of Two
Different Ways of Landfill Gas Utilization through Greenhouse Gas Emission
Reductions Analysis and Financial Analysis." Waste Management & Research 27
(2009): 922-27.
94
Hao, Xiying, Francis J. Larney, Chi Chang, Greg R. Travis, Connie K. Nichol, and Eric
Bremer. "The Effect of Phosphogypsum on Greenhouse Gas Emissions during
Cattle Manure Composting." Journal of Environmental Quality 34.May-June
(2005): 774-81.
Hao, Xiying. "Nitrate Accumulation and Greenhouse Gas Emissions during Compost
Storage." Nutrient Cycling in Agrosystems 78.2 (2007): 189-95.
Hartwell, Sara. "WARM Energy Parameters." Telephone interview. 10 Mar. 2011.
Hartwell, Sara. "WARM Tool Question for Master's Thesis Project." Message to the
author. 13 Dec. 2010. E-mail.
Hashimoto, Shizuka, Tsuyoshi Fujita, Yong Geng, and Emiri Nagasawa. "Realizing CO2
Emission Reductions through Industrial Symbiosis: A Cement Production Case
Study for Kawasaki." Resources, Conservation, and Recycling 54 (2010): 704-10.
Hoey, Geralyn, and Sheylda N. Diaz-Mendez. Global Warming and Puerto Rico.
National Wildlife Federation, 2009.
IPCC, 2007: Summary for Policymakers. In: Climate Change 2007: The Physical Science
Basis. Contribution of Working Group I to the Fourth Assessment Report of the
Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning,
Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)]. Cambridge
University Press, Cambridge, United Kingdom and New York, NY, USA.
Jaramillo, Paulina, and H. S. Matthews. "Landfill-Gas-to-Energy Projects: Analysis of
Net Private and Social Benefits." Environmental Science & Technology 39.19
(2005): 7365-373.
Kreith, Frank. "Waste-to-Energy Combustion." Handbook of Solid Waste Management.
2nd ed. New York, NY: McGraw-Hill, 2002. 13.1-13.175.
Kumar, Sudhir. "Technology options for municipal solid waste-to-energy project." TERI
Information Monitor on Environmental Science 5 (2000): 1-11.
Larney, Francis J., Dan M. Sullivan, Katherine E. Buckley, and Bahman Eghball. "The
Role of Composting in Recycling Manure Nutrients." Canadian Journal of
Science 86.4 (2006): 597-611.
Leverenz, Harold, George Tchobanoglous, and David B. Spencer. "Recycling."
Handbook of Solid Waste Management. 2nd ed. New York, NY: McGraw-Hill,
2002. 8.1-8.77.
95
Leverenz, Harold. "Source Reduction." Handbook of Solid Waste Management. 2nd ed.
New York, NY: McGraw-Hill, 2002. 6.1-6.41.
Manfredi, Simone, Davide Tonini, Thomas H. Christensen, and Heijo Scharff.
"Landfilling of Waste: Accounting of Greenhouse Gases and Global Warming
Contributions." Waste Management & Research 27 (2009): 825-36.
Miranda, Marie L., and Brack Hale. "Paradise Recovered: Energy Production and Waste
Management in Island Environments." Energy Policy 33 (2005): 1691-702.
MP Engineers of Puerto Rico, P.S.C. Dynamic Itinerary for Infrastructure Projects;
Public Policy Document. Rep. San Juan, PR: Autoridad De Desperdicios Sólidos,
2008.
O'Leary, Philip R., and George Tchobanoglous. "Landfilling." Handbook of Solid Waste
Management. 2nd ed. New York, NY: McGraw-Hill, 2002. 14.1-14.93.
Papageourgiou, A., J. R. Barton, and A. Karagiannidis. "Assessment of the Greenhouse
Effect Impact of Technologies Used for Energy Recovery from Municipal Waste:
A Case of England." Journal of Environmental Management 90 (2009a): 29993012.
Papageourgiou, Asterios, Avraam Karagiannidis, John R. Barton, and Efstratios
Kalogirou. "Municipal Solid Waste Management Scenarios for Attica and Their
Greenhouse Gas Emission Impact." Waste Management & Research 27 (2009b):
928-37.
Park, Jin-Won, and Ho-Chul Shin. "Surface Emission of Landfill Gas from Solid Waste
Landfill." Atmospheric Environment 35 (2001): 3445-451.
Pichtel, John. Waste Management Practices: Municipal, Hazardous, and Industrial. Boca
Raton: Taylor & Francis, 2005.
"PREPA Is..." PREPA. Autoridad De Energia Electrica, 2009. http://www.prepa.com/
AEEES2_ENG.ASP (accessed March 1, 2011).
Psomopoulos, C. S., A. Bourka, and N. J. Themelis. "Waste-to-Energy: A Review of the
Status and Benefits in USA." Waste Management 29.5 (2009): 1718-724.
Rinne, Janne, Mari Pihlatie, Annalea Lohila, Tea Thum, Mika Aurela, Juha-Pekka
Tuovinen, Tuomas Laurila, and Timo Vesala. "Nitrous Oxide Emissions from a
Municipal Landfill." Environmental Science & Technology 39.20 (2005): 7790793.
96
Ritzkowski, M., and R. Stegmann. "Generating CO2-Credits through Landfill in Situ
Aeration." Waste Management 30 (2010): 702-06.
Rogoff, Marc J. How to Implement Waste-to-Energy Projects. Park Ridge, NJ: Noyes
Publications, 1987.
Rosario, Edwin. "ADS Waste Management." Telephone interview. 8 Mar. 2011.
Schwarz, Stephen C., and Calvin R. Brunner. Energy and Resource Recovery from
Waste. Park Ridge, NJ: Noyes Data Corporation, 1983.
Scientific Applications International Corporation. Life Cycle Assessment: Principles and
Practice. Rep. no. EPA/600/R-06/060. Cincinnati: US Environmental Protection
Agency, 2006.
Skumatz, Lisa. "Recycling and Climate Change." Resource Recycling 27.10 (2008): 1417.
Termorshuizen, A. J., S. W. Moolenaar, A.H. M. Veeken, and W. J. Blok. "The Value of
Compost." Reviews in Environmental Science & Bio/Technology 3 (2004): 34347.
Tchobanoglous, George, Frank Kreith, and Marcia, E. Williams. "Introduction."
Handbook of Solid Waste Management. 2nd ed. New York, NY: McGraw-Hill,
2002. 1.1-1.27.
USEPA. "Conserving Resources, Conserving Waste." Waste-Partnerships-Waste
Programs (USEPA). US Environmental Protection Agency, 14 Mar. 2011.
http://www.epa.gov/ wastes/partnerships/wastewise/index.htm (accessed March
26, 2011).
USEPA. Fact Sheet: Cutting-edge Software to Cut Emissions. Rep. no. EPA-530-F-02024. Washinton, DC: U.S. Environmental Protection Agency. 2002c.
USEPA. Municipal Solid Waste Generation, Recycling, and Disposal in the United
States: Facts and Figures for 2008. Rep. no. EPA-530-F-009-021. Washinton,
DC: U.S. Environmental Protection Agency, 2009.
USEPA. Solid Waste Generation: A Local Challenge with Global Impacts. Rep. no.
EPA-530-F-02-026. Washinton, DC: U.S. Environmental Protection Agency,
2002a.
USEPA. Solid Waste Management and Greenhouse Gases: A Life-Cycle Assessment of
Emissions and Sinks. Rep. no. EPA530-R-02-006. Washinton, DC: U.S.
Environmental Protection Agency, 2002b.
97
USEPA. "Waste Reduction Model - WARM." Climate Change – Waste (USEPA). U.S.
Environmental Protection Agency, 5 Nov. 2010. http://www.epa.gov/
climatechange/wycd/waste/calculators/Warm_home.html (accessed November
10, 2010).
Valeo, Caterina, Brian W. Baetz, and Ioannis K. Tsanis. "Location of Recycling Depots
with GIS." Journal of Urban Planning and Development 124.2 (1998): 93-99.
Vijay, Ritesh, Ajay Gautam, Ajay Kalamdhad, Apurba Gupta, and Sukumar Devotta.
"GIS-based Locational Analysis of Collection Bins in Municipal Solid Waste
Management Systems." Journal of Environmental Engineering and Science 7.1
(2008): 39-43.
Wehran, Inc. Waste Characterization Study. Rep. Autoridad de Desperdicios Sólidos De
Puerto Rico, 2003.
Wilson, D. G. "A Brief History of Solid Waste Management." International Journal of
Environmental Studies 9.2 (1976): 123-29.
Zeman, Catherine, Diane Depken, and Michaela Rich. "Research on How the
Composting Process Impacts Greenhouse Gas Emissions and Global Warming."
Compost Science & Utilization 10.1 (2002): 72-86.
Zeman, Chatherine L., and Michaela Rich. "Composting in a Hot World - The Cool
Facts." BioCycle December (2001): 68-76.
98
APPENDICES
I.
MSW Hauling Origins and Destinations: “Base Case” 2010
Landfill
Destination
MRF
Adjuntas
Ponce
Hatillo
Aguada
Moca
Municipalities
Transfer Station
Aguadilla
Aguadilla
Cabo Rojo
Aguas Buenas
Cidra
Ponce
Aibonito
Salinas
Añasco
Añasco
Arecibo
Arecibo
Compost
WTE
n/a
n/a
Hatillo
n/a
n/a
Aibonito
n/a
Hatillo
Mayaguez
n/a
Guaynabo/Arecibo
Arecibo
n/a
Arroyo
Salinas
Barceloneta
Arecibo
Arecibo
n/a
Aibonito
n/a
Barranquitas
Barranquitas
Ponce
Bayamón
Toa Baja
Humacao
n/a
Bayamon/San Juan
n/a
Cabo Rojo
Hatillo
n/a
Humacao
Caguas/Humacao/San
Juan
n/a
Camuy
Arecibo
Hatillo
n/a
Canóvanas
Juncos
Humacao
n/a
Carolina
Carolina
Carolina
n/a
Cabo Rojo
Caguas
Cataño
Caguas
Cataño
Ponce
Cayey
Cayey
Ceiba
Fajardo
Ciales
Arecibo
Cidra
Cidra
Coamo
n/a
Aibonito
n/a
n/a
Hatillo
n/a
Ponce
n/a
Juana Diaz
n/a
Comerío
Comerío
Ponce
Guaynabo
n/a
Corozal
Toa Baja
Humacao
Guaynabo
n/a
Fajardo
Humacao
n/a
Culebra
Dorado
Toa Baja
Humacao
n/a
Fajardo
Fajardo
Humacao
Florida
Arecibo
Hatillo
Guánica
Yauco
n/a
Guayama
Guayama
n/a
Guayanilla
Yauco
Hatillo/Guayanilla
n/a
Humacao
Guaynabo
n/a
Humacao
Guaynabo
n/a
Guaynabo
Gurabo
Guaynabo
n/a
Arecibo
n/a
Hatillo
Arecibo
Hatillo
Arecibo
n/a
Hormigueros
Hormigueros
Hatillo/Hormigueros
Mayaguez
n/a
Humacao
Humacao
Humacao
n/a
Isabela
Isabela
Hatillo
n/a
Jayuya
Jayuya
Hatillo
n/a
100
Juana Díaz
Juana Diaz
n/a
Juncos
Juncos
n/a
Lajas
Lajas
n/a
Lares
Lares
Las Marías
Las Marías
Arecibo
Hatillo
n/a
Moca
Hatillo
n/a
Las Piedras
Humacao
Humacao
n/a
Loíza
Fajardo
Humacao
n/a
Luquillo
Fajardo
Humacao
n/a
Manatí
Arecibo
Hatillo
n/a
Maricao
Maricao
Mayaguez
Maunabo
Maunabo
Humacao
Mayagüez
Moca
Morovis
Morovis
Naguabo
Mayaguez
n/a
n/a
Mayaguez
Hatillo
Mayaguez
n/a
Moca
Hatillo
n/a
Arecibo
Hatillo
n/a
Fajardo
Humacao
n/a
Naranjito
Toa Baja
Humacao
Orocovis
Barranquitas
Ponce
n/a
Hatillo
n/a
Patillas
Salinas
n/a
Peñuelas
Yauco
n/a
Ponce
Ponce
Guayanilla
n/a
Quebradillas
Moca
Hatillo
n/a
Rincón
Quebradillas
Moca
Hatillo
n/a
Río Grande
Fajardo
Humacao
n/a
Sabana Grande
Yauco
Salinas
Salinas
San Germán
San Germán
Yauco
San Juan
San Juan
Humacao
San Lorenzo
San Sebastián
n/a
Aibonito
n/a
San Juan/Guaynabo
Humacao
San Sebastián
Santa Isabel
Moca
n/a
n/a
n/a
Hatillo
n/a
Ponce
n/a
Toa Alta
Toa Baja
Humacao
n/a
Toa Baja
Toa Baja
Humacao
n/a
Trujillo Alto
Juncos
Guaynabo/San Juan
n/a
Utuado
Arecibo
Hatillo
n/a
Vega Alta
Arecibo
Hatillo
n/a
Vega Baja
Arecibo
Hatillo
n/a
Vieques
Vieques
n/a
Juana Diaz
n/a
Yabucoa
Humacao
n/a
Yauco
Yauco
n/a
Villalba
Villalba
101
II. MSW Hauling Origins and Destinations: “Base Case” 2020
Municipalities
Middlepoint (TS)
Adjuntas
Aguada
Aguadilla
Aguadilla
Aguadilla
Aguas Buenas
Cidra
Aibonito
Landfill
Destination
MRF
Compost
Ponce
Hatillo
Ponce
WTE
NW
Hatillo
NW
Ponce
Salinas
Aibonito
Añasco
Mayaguez
Hatillo
Mayaguez
NW
Arecibo
Arecibo
Guaynabo/Arecibo
Arecibo
NW
Arecibo
NW
Arroyo
Salinas
Barceloneta
Arecibo
Barranquitas
Barranquitas
Ponce
Aibonito
Bayamón
Toa Baja
Cabo Rojo
Lajas
Penuelas New
Hatillo
Caguas
Caguas
Humacao
Caguas/Humacao/San
Juan
Camuy
Arecibo
Canóvanas
Bayamon/San Juan
Hatillo
Juncos
Carolina
Carolina
Cataño
Cataño
Cayey
Cayey
Ceiba
Ciales
Arecibo
Cidra
Cidra
Coamo
Toa Baja
NE
NW
Humacao
Carolina
NE
NE
Ponce
Aibonito
Fajardo
Ceiba
Hatillo
NW
Ponce/Salinas
Juana Diaz
Comerío
Comerío
Guaynabo
NE
Corozal
Toa Baja
Guaynabo
NE
Culebra
Culebra
Dorado
Toa Baja
Fajardo
Florida
Fajardo
Toa Baja
Fajardo
Arecibo
Guánica
Yauco
Guayama
Salinas
Guayanilla
Yauco
Guaynabo
Guaynabo
Gurabo
Arecibo
Hormigueros
Mayaguez
Humacao
Ceiba
Hatillo
Arecibo
NW
NE
Guaynabo
Hatillo
Arecibo
NW
Hatillo/Hormigueros
Mayaguez
NW
Humacao
Humacao
Humacao
Isabela
Isabela
Hatillo
Jayuya
Jayuya
Hatillo
102
NE
Hatillo/Guayanilla
Guaynabo
Humacao
Hatillo
Culebra
Juana Díaz
Juana Diaz
Juncos
Juncos
Lajas
Lajas
Ponce
Penuelas New
Lares
Lares
Hatillo
NW
Las Marías
Las Marías
Hatillo
NW
Las Piedras
Humacao
Humacao
Loíza
Fajardo
Humacao
Luquillo
Fajardo
Humacao
Manatí
Arecibo
Maricao
Maricao
Penuelas New
Maunabo
Maunabo
Humacao
Mayagüez
Mayagüez
Hatillo
Moca
Aguadilla
Hatillo
NW
Morovis
Morovis
Hatillo
NW
Naguabo
Hatillo
Fajardo
Naranjito
Toa Baja
Orocovis
Barranquitas
Mayaguez
Humacao
Mayaguez
NW
Ceiba
NE
Ponce
Patillas
Salinas
Peñuelas
Penuelas New
Ponce
NW
Ponce
Hatillo
Ponce
Ponce/Guayanilla
Ponce
Quebradillas
Quebradillas
Hatillo
NW
Rincón
Aguadilla
Hatillo
NW
Río Grande
Fajardo
Sabana Grande
Yauco
Salinas
Salinas
San Germán
Lajas
Penuelas New
San Juan
San Juan
Humacao
San Lorenzo
San Sebastián
Humacao
Aibonito
San Juan/Guaynabo
Humacao
San Sebastián
Santa Isabel
Hatillo
NW
Ponce
Toa Alta
Toa Baja
Toa Baja
Toa Baja
NE
Toa Baja
Toa Baja
Toa Baja
Toa Baja
NE
Arecibo/Ponce
NW
Trujillo Alto
Juncos
Guaynabo /San Juan
Utuado
Arecibo
Hatillo
Vega Alta
Arecibo
Hatillo
NE
Vega Baja
Arecibo
Hatillo
NE
Vieques
Villalba
Vieques
Villalba
Juana Diaz
Yabucoa
Humacao
Yauco
Yauco
103
Vieques
III. MSW Hauling Origins and Destinations: “Base Case” 2030
Municipalities
Transfer Stations
Adjuntas
Aguada
Aguadilla
Aguadilla
Aguadilla
Aguas Buenas
Cidra
Aibonito
Landfill
Destination
MRF
Compost
Ponce
Hatillo
Ponce
WTE
NW
Hatillo
NW
Ponce
Salinas
Aibonito
Añasco
Mayaguez
Hatillo
Mayaguez
NW
Arecibo
Arecibo
Guaynabo/Arecibo
Arecibo
NW
Arecibo
NW
Arroyo
Salinas
Barceloneta
Arecibo
Barranquitas
Barranquitas
Ponce
Aibonito
Bayamón
Toa Baja
Cabo Rojo
Lajas
Caguas
Caguas
Caguas/Humacao/San
Juan
NE
Camuy
Arecibo
Hatillo
NW
Canóvanas
Bayamon/San Juan
Penuelas New
Juncos
Carolina
Carolina
Cataño
Cataño
Cayey
Cayey
Ceiba
Ciales
Arecibo
Cidra
Cidra
Coamo
Toa Baja
NE
Hatillo
Humacao
Carolina
NE
NE
Ponce
Aibonito
Fajardo
Ceiba
Hatillo
NW
Ponce
Yauco
Comerío
Comerío
Guaynabo
NE
Corozal
Toa Baja
Guaynabo
NE
Culebra
Culebra
Dorado
Toa Baja
Fajardo
Florida
Fajardo
Toa Baja
Fajardo
Arecibo
Guánica
Yauco
Guayama
Salinas
Guayanilla
Yauco
Guaynabo
Guayanabo
Gurabo
Arecibo
Hormigueros
Mayaguez
Humacao
Ceiba
Hatillo
Arecibo
NW
NE
Guaynabo
Hatillo
Arecibo
NW
Hatillo/Hormigueros
Mayaguez
NW
Humacao
Humacao
Humacao
Isabela
Isabela
Hatillo
Jayuya
Penuelas New
Hatillo
104
NE
Hatillo/Guayanilla
Guaynabo
Humacao
Hatillo
Culebra
Juana Díaz
Juana Diaz
Juncos
Lajas
Yauco
Ponce
Juncos
Lajas
Penuelas New
Lares
Lares
Hatillo
NW
Las Marías
Las Marías
Hatillo
NW
Las Piedras
Humacao
Humacao
Loíza
Fajardo
Humacao
Luquillo
Fajardo
Humacao
Manatí
Arecibo
Maricao
Maricao
Maunabo
Maunabo
Mayagüez
Mayagüez
Hatillo
Moca
Aguadilla
Hatillo
NW
Morovis
Morovis
Hatillo
NW
Naguabo
Hatillo
Toa Baja
Orocovis
Barranquitas
NW
Mayaguez
NW
Humacao
Ceiba
NE
Ponce
Patillas
Salinas
Peñuelas
Penuelas New
Ponce
Mayaguez
Humacao
Fajardo
Naranjito
NW
Ponce
Hatillo
Ponce
Ponce/Guayanilla
Ponce
Quebradillas
Quebradillas
Hatillo
NW
Rincón
Aguadilla
Hatillo
NW
Río Grande
Fajardo
Sabana Grande
Yauco
Salinas
Salinas
San Germán
Lajas
Penuelas New
San Juan
San Juan
Humacao
San Lorenzo
San Sebastián
Humacao
Aibonito
San Juan/Guaynabo
Humacao
San Sebastián
Santa Isabel
Hatillo
NW
Ponce
Toa Alta
Toa Baja
Toa Baja
Toa Baja
NE
Toa Baja
Toa Baja
Toa Baja
Toa Baja
NE
Arecibo/Ponce
NW
Trujillo Alto
Juncos
Guaynabo /San Juan
Utuado
Arecibo
Hatillo
Vega Alta
Arecibo
Hatillo
NW
Hatillo
NW
Vega Baja
Arecibo
Vieques
Vieques
Fajardo
Villalba
Villalba
Yauco
Yabucoa
Humacao
Yauco
Yauco
105
Vieques
IV. MSW Hauling Origins and Destinations: “Backup Case” 2010
Landfill
Destination
MRF
Adjuntas
Ponce
Hatillo
Aguada
Moca
Municipalities
Transfer Stations
Aguadilla
Aguadilla
Cabo Rojo
Aguas Buenas
Cidra
Ponce
Compost
WTE
n/a
n/a
Hatillo
n/a
n/a
Aibonito
Ponce
Añasco
Añasco
Arecibo
Arecibo
Arroyo
Ponce
Barceloneta
Arecibo
Arecibo
n/a
Ponce
Aibonito
n/a
Barranquitas
Barranquitas
Bayamón
Toa Baja
Aibonito
n/a
Hatillo
Mayaguez
n/a
Guaynabo/Arecibo
Arecibo
n/a
n/a
Penuelas
Bayamon
n/a
Cabo Rojo
Hatillo
n/a
Humacao
Caguas/Humacao/San
Juan
n/a
Camuy
Arecibo
Hatillo
n/a
Canóvanas
Juncos
Humacao
n/a
Carolina
Carolina
Carolina
n/a
Cabo Rojo
Caguas
Cataño
Caguas
Cataño
Penuelas
Cayey
Cayey
Ceiba
Fajardo
Ciales
Arecibo
Cidra
Cidra
Coamo
n/a
Aibonito
n/a
n/a
Hatillo
n/a
Ponce
n/a
Juana Diaz
n/a
Comerío
Comerio
Ponce
Guaynabo
n/a
Corozal
Toa Baja
Arecibo
Guaynabo
n/a
Fajardo
Humacao
n/a
Culebra
Dorado
Toa Baja
Penuelas
n/a
Fajardo
Fajardo
Humacao
Florida
Arecibo
Hatillo
Guánica
Yauco
n/a
Guayama
Guayama
n/a
Guayanilla
Yauco
Hatillo/Guayanilla
n/a
Humacao
Guaynabo
n/a
Gurabo
Humacao
Guaynabo
n/a
Hatillo
Arecibo
Hatillo
Arecibo
n/a
Hormigueros
Hormigueros
Hatillo/Hormigueros
Mayaguez
n/a
Humacao
Humacao
Humacao
n/a
Isabela
Isabela
Hatillo
n/a
Jayuya
Jayuya
Hatillo
n/a
Guaynabo
Guayanabo
106
n/a
Arecibo
n/a
Juana Díaz
Juana Diaz
n/a
Juncos
Juncos
n/a
Lajas
Lajas
n/a
Lares
Lares
Arecibo
Hatillo
n/a
Las Marías
Las Marias
Moca
Hatillo
n/a
Las Piedras
Humacao
Humacao
n/a
Loíza
Fajardo
Humacao
n/a
Luquillo
Fajardo
Humacao
n/a
Manatí
Arecibo
Hatillo
n/a
Maricao
Maricao
Mayaguez
Maunabo
Maunabo
Humacao
Mayaguez
n/a
n/a
Mayagüez
Mayaguez
Hatillo
Moca
Moca
Hatillo
n/a
Penuelas
Hatillo
n/a
Fajardo
Humacao
n/a
Morovis
Morovis
Naguabo
Naranjito
Toa Baja
Arecibo
Orocovis
Barranquitas
Ponce
Mayaguez
n/a
n/a
Hatillo
n/a
Patillas
Ponce
n/a
Peñuelas
Yauco
n/a
Ponce
Ponce
Guayanilla
n/a
Moca
Hatillo
n/a
Rincón
Moca
Hatillo
n/a
Río Grande
Fajardo
Humacao
n/a
Sabana Grande
Yauco
Salinas
Ponce
Quebradillas
Quebradillas
San Germán
San Germán
Yauco
San Juan
San Juan
Humacao
San Lorenzo
San Sebastián
n/a
Aibonito
n/a
Guaynabo/San Juan
Humacao
San Sebastián
Santa Isabel
Moca
n/a
n/a
n/a
Hatillo
n/a
Ponce
n/a
Toa Alta
Toa Baja
Arecibo
n/a
Toa Baja
Toa Baja
Penuelas
n/a
Trujillo Alto
Juncos
Guaynabo/San Juan
n/a
Utuado
Arecibo
Hatillo
n/a
Vega Alta
Arecibo
Hatillo
n/a
Vega Baja
Arecibo
Hatillo
n/a
Vieques
Vieques
n/a
Juana Diaz
n/a
Yabucoa
Humacao
n/a
Yauco
Yauco
n/a
Villalba
Villalba
107
V. MSW Hauling Origins and Destinations: “Backup Case” 2020
Municipalities
Transfer Stations
Adjuntas
Landfill
Destination
MRF
Compost
WTE
Ponce
Hatillo
Ponce
n/a
Aguada
Mayaguez
Penuelas New
Aguadilla
Aguadilla
Cabo Rojo
Aguas Buenas
Cidra
Ponce
Aibonito
n/a
Hatillo
n/a
n/a
Ponce
Aibonito
n/a
Añasco
Mayaguez
Penuelas New
Hatillo
Mayaguez
n/a
Arecibo
Arecibo
Penuelas New
Guaynabo/Arecibo
Arecibo
n/a
Arroyo
Ponce
n/a
Barceloneta
Arecibo
Penuelas New
Arecibo
n/a
Barranquitas
Barranquitas
Ponce
Aibonito
n/a
Bayamón
Toa Baja
Penuelas New
Bayamon/San Juan
Toa Baja
n/a
Cabo Rojo
Hatillo
n/a
Cabo Rojo
Caguas
Caguas
Humacao
Caguas/Humacao/San
Juan
n/a
Camuy
Arecibo
Penuelas New
Hatillo
n/a
Canóvanas
Juncos
Humacao
n/a
Carolina
Fajardo
Carolina
n/a
Cataño
Cataño
Cayey
Cayey
Ceiba
Penuelas New
n/a
Ponce
Aibonito
n/a
Fajardo
Ceiba
n/a
Ciales
Arecibo
Penuelas New
Cidra
Cidra
Ponce
n/a
Juana Diaz
n/a
Coamo
Hatillo
n/a
Comerío
Comerio
Ponce
Guaynabo
n/a
Corozal
Toa Baja
Penuelas New
Guaynabo
n/a
Culebra
Culebra
Fajardo
Humacao
n/a
Dorado
Toa Baja
Penuelas New
Fajardo
Arecibo
Penuelas New
Fajardo
Florida
Toa Baja
n/a
Humacao
Ceiba
n/a
Hatillo
Arecibo
n/a
Guánica
Yauco
n/a
Guayama
Ponce
n/a
Guayanilla
Yauco
Hatillo/Guayanilla
n/a
Humacao
Guaynabo
n/a
Humacao
Guaynabo
n/a
Guaynabo
Guaynabo
Gurabo
Hatillo
Arecibo
Penuelas New
Hatillo
Arecibo
n/a
Hormigueros
Mayaguez
Mayaguez
n/a
Penuelas New
Hatillo/Hormigueros
Humacao
Humacao
Humacao
n/a
Isabela
Isabela
Hatillo
n/a
Jayuya
Jayuya
Hatillo
n/a
108
Juana Díaz
Juana Diaz
Ponce
n/a
Juncos
Juncos
n/a
Lajas
Penuelas New
n/a
Lares
Lares
Penuelas New
Hatillo
n/a
Las Marías
Las Marias
Penuelas New
Hatillo
n/a
Las Piedras
Humacao
Humacao
n/a
Loíza
Fajardo
Humacao
n/a
Luquillo
Fajardo
Humacao
n/a
Hatillo
n/a
Manatí
Arecibo
Penuelas New
Maricao
Maricao
Penuelas New
Maunabo
Maunabo
Humacao
Mayagüez
Mayagüez
Penuelas New
Hatillo
Moca
Aguadilla
Penuelas New
Hatillo
n/a
Morovis
Morovis
Penuelas New
Hatillo
n/a
Fajardo
Humacao
Naguabo
Naranjito
Toa Baja
Penuelas New
Orocovis
Barranquitas
Ponce
Patillas
Ponce
Peñuelas
Penuelas New
Ponce
Mayaguez
n/a
n/a
Mayaguez
Ceiba
n/a
n/a
n/a
Hatillo
n/a
n/a
Ponce
n/a
Ponce
n/a
Ponce
Ponce/Guayanilla
Quebradillas
Quebradillas
Penuelas New
Hatillo
n/a
Rincón
Aguadilla
Penuelas New
Hatillo
n/a
Río Grande
Fajardo
Humacao
n/a
Sabana Grande
Yauco
Salinas
Ponce
San Germán
San Germán
Yauco
San Juan
San Juan
Humacao
San Sebastián
Penuelas New
San Lorenzo
San Sebastián
n/a
Aibonito
n/a
San Juan/Guaynabo
n/a
Humacao
Santa Isabel
n/a
n/a
Hatillo
n/a
Ponce
n/a
Toa Alta
Toa Baja
Penuelas New
Toa Baja
Toa Baja
n/a
Toa Baja
Toa Baja
Penuelas New
Toa Baja
Toa Baja
n/a
Juncos
Guaynabo /San Juan
Trujillo Alto
n/a
Utuado
Arecibo
Penuelas New
Hatillo
Vega Alta
Arecibo
Penuelas New
Hatillo
n/a
Vega Baja
Arecibo
Penuelas New
Hatillo
n/a
Vieques
Arecibo/Ponce
n/a
Vieques
n/a
Juana Diaz
n/a
Yabucoa
Humacao
n/a
Yauco
Yauco
n/a
Villalba
Villalba
109
VI. MSW Hauling Origins and Destinations: “Backup Case” 2030
Municipalities
Transfer Stations
Adjuntas
Landfill
Destination
MRF
Compost
WTE
Ponce
Hatillo
Ponce
n/a
Aguada
Mayaguez
Penuelas New
Aguadilla
Aguadilla
Cabo Rojo
Aguas Buenas
Cidra
Ponce
Aibonito
n/a
Hatillo
n/a
n/a
Ponce
Aibonito
n/a
Añasco
Mayaguez
Penuelas New
Hatillo
Mayaguez
n/a
Arecibo
Arecibo
Penuelas New
Guaynabo/Arecibo
Arecibo
n/a
Arroyo
Ponce
n/a
Barceloneta
Arecibo
Penuelas New
Arecibo
n/a
Barranquitas
Barranquitas
Ponce
Aibonito
n/a
Bayamón
Toa Baja
Penuelas New
Bayamon/San Juan
Toa Baja
n/a
Cabo Rojo
Hatillo
n/a
Cabo Rojo
Caguas
Caguas
Humacao
Caguas/Humacao/San
Juan
n/a
Camuy
Arecibo
Penuelas New
Hatillo
n/a
Canóvanas
Juncos
Humacao
n/a
Carolina
Fajardo
Carolina
n/a
Cataño
Cataño
Cayey
Cayey
Ceiba
Penuelas New
n/a
Ponce
Aibonito
n/a
Fajardo
Ceiba
n/a
Ciales
Arecibo
Penuelas New
Cidra
Cidra
Ponce
n/a
Coamo
Juana Diaz
Yauco
n/a
Comerío
Comerio
Ponce
Guaynabo
n/a
Corozal
Toa Baja
Penuelas New
Guaynabo
n/a
Culebra
Culebra
Fajardo
Humacao
n/a
Dorado
Toa Baja
Penuelas New
Fajardo
Arecibo
Penuelas New
Fajardo
Florida
Hatillo
n/a
Toa Baja
n/a
Humacao
Ceiba
n/a
Hatillo
Arecibo
n/a
Guánica
Yauco
n/a
Guayama
Ponce
n/a
Guayanilla
Yauco
Hatillo/Guayanilla
n/a
Humacao
Guaynabo
n/a
Humacao
Guaynabo
n/a
Guaynabo
Guaynabo
Gurabo
Hatillo
Arecibo
Penuelas New
Hatillo
Arecibo
n/a
Hormigueros
Mayaguez
Mayaguez
n/a
Penuelas New
Hatillo/Hormigueros
Humacao
Humacao
Humacao
n/a
Isabela
Isabela
Hatillo
n/a
Jayuya
Penuelas New
Hatillo
n/a
110
Juana Díaz
Juana Diaz
Yauco
Ponce
n/a
Juncos
Juncos
n/a
Lajas
Penuelas New
n/a
Lares
Lares
Penuelas New
Hatillo
n/a
Las Marías
Las Marias
Penuelas New
Hatillo
n/a
Las Piedras
Humacao
Humacao
n/a
Loíza
Fajardo
Humacao
n/a
Luquillo
Fajardo
Humacao
n/a
Hatillo
n/a
Manatí
Arecibo
Penuelas New
Maricao
Maricao
Penuelas New
Maunabo
Maunabo
Humacao
Mayagüez
Mayagüez
Penuelas New
Hatillo
Moca
Aguadilla
Penuelas New
Hatillo
n/a
Morovis
Morovis
Penuelas New
Hatillo
n/a
Fajardo
Humacao
Naguabo
Naranjito
Toa Baja
Penuelas New
Orocovis
Barranquitas
Ponce
Patillas
Ponce
Peñuelas
Penuelas New
Ponce
Mayaguez
n/a
n/a
Mayaguez
Ceiba
n/a
n/a
n/a
Hatillo
n/a
n/a
Ponce
n/a
Ponce
n/a
Ponce
Ponce/Guayanilla
Quebradillas
Quebradillas
Yauco
Hatillo
n/a
Rincón
Aguadilla
Penuelas New
Hatillo
n/a
Río Grande
Fajardo
Humacao
n/a
Sabana Grande
Yauco
Salinas
Ponce
San Germán
San German
Yauco
San Juan
San Juan
Humacao
San Sebastian
Penuelas New
San Lorenzo
San Sebastián
n/a
Aibonito
n/a
San Juan/Guaynabo
n/a
Humacao
Santa Isabel
n/a
n/a
Hatillo
n/a
Ponce
n/a
Toa Alta
Toa Baja
Penuelas New
Toa Baja
Toa Baja
n/a
Toa Baja
Toa Baja
Penuelas New
Toa Baja
Toa Baja
n/a
Juncos
Guaynabo /San Juan
Trujillo Alto
n/a
Utuado
Arecibo
Penuelas New
Hatillo
Vega Alta
Arecibo
Penuelas New
Hatillo
n/a
Vega Baja
Arecibo
Penuelas New
Hatillo
n/a
Vieques
Vieques
Fajardo
n/a
Villalba
Villalba
Yauco
n/a
Yabucoa
Humacao
n/a
Yauco
Yauco
n/a
111
Arecibo/Ponce
n/a
VII. MSW Hauling Origins and Destinations: “No Action Case” 2010
Landfill
Destination
MRF
Adjuntas
Ponce
Hatillo
Aguada
Moca
Municipalities
Transfer Stations
Aguadilla
Aguas Buenas
Cabo Rojo
Cidra
Compost
WTE
n/a
n/a
Hatillo
n/a
Ponce
n/a
Aibonito
Salinas
Aibonito
n/a
Añasco
Añasco
Hatillo
Mayaguez
n/a
Arecibo
Arecibo
Guaynabo/Arecibo
Arecibo
n/a
Arroyo
Arroyo
Barceloneta
Arecibo
Arecibo
n/a
Barranquitas
Barranquitas
Aibonito
n/a
n/a
Bayamón
Toa Baja
Bayamon
n/a
Cabo Rojo
Cabo Rojo
Hatillo
n/a
Humacao
Caguas/Humacao/San
Juan
n/a
Camuy
Arecibo
Hatillo
n/a
Canóvanas
Juncos
Humacao
n/a
Carolina
Carolina
Carolina
n/a
Caguas
Cataño
Caguas
Cataño
Ponce
Cayey
Cayey
Ceiba
Fajardo
Ciales
Vega Baja
Cidra
Cidra
Coamo
Comerío
Comerio
n/a
Aibonito
n/a
n/a
Hatillo
n/a
Salinas
n/a
Juana Diaz
n/a
Toa Alta
Guaynabo
n/a
Corozal
Toa Alta
Guaynabo
n/a
Culebra
Culebra
Humacao
n/a
Dorado
Toa Baja
Fajardo
Fajardo
Humacao
Florida
Florida
Hatillo
Guánica
Yauco
n/a
Guayama
Guayama
n/a
Guayanilla
Yauco
Hatillo/Guayanilla
n/a
Guaynabo
Humacao
Guaynabo
n/a
Gurabo
Humacao
Guaynabo
n/a
Hatillo
Arecibo
Hatillo
Arecibo
n/a
Hormigueros
Hormigueros
Hatillo/Hormigueros
Mayaguez
n/a
Humacao
Humacao
Humacao
n/a
Isabela
Isabela
Hatillo
n/a
Jayuya
Jayuya
Hatillo
n/a
112
n/a
n/a
Arecibo
n/a
Juana Díaz
Juana Diaz
n/a
Juncos
Juncos
n/a
Lajas
Lajas
n/a
Lares
Lares
Arecibo
Hatillo
n/a
Las Marías
Las Marias
Moca
Hatillo
n/a
Las Piedras
Humacao
Humacao
n/a
Loíza
Fajardo
Humacao
n/a
Luquillo
Fajardo
Humacao
n/a
Manatí
Arecibo
Hatillo
n/a
Maricao
Maricao
Mayaguez
Maunabo
Maunabo
Arroyo
Mayaguez
n/a
n/a
Mayagüez
Mayaguez
Hatillo
Moca
Moca
Hatillo
n/a
Arecibo
Hatillo
n/a
Naguabo
Fajardo
Humacao
n/a
Naranjito
Toa Alta
Orocovis
Barranquitas
Patillas
Arroyo
n/a
Peñuelas
Yauco
n/a
Morovis
Morovis
Ponce
Mayaguez
n/a
n/a
Hatillo
n/a
Ponce
Guayanilla
n/a
Moca
Hatillo
n/a
Rincón
Moca
Hatillo
n/a
Río Grande
Fajardo
Humacao
n/a
Sabana Grande
Yauco
Salinas
Salinas
Quebradillas
Quebradillas
San Germán
San German
Yauco
San Juan
San Juan
Humacao
San Lorenzo
San Sebastián
n/a
Aibonito
n/a
Guaynabo/San Juan
Humacao
San Sebastian
Moca
n/a
n/a
n/a
Hatillo
n/a
Santa Isabel
Santa Isabel
n/a
Toa Alta
Toa Alta
n/a
Toa Baja
Toa Baja
n/a
Trujillo Alto
Juncos
Guaynabo/San Juan
n/a
Utuado
Arecibo
Hatillo
n/a
Vega Alta
Vega Baja
Hatillo
n/a
Vega Baja
Vega Baja
Hatillo
n/a
Vieques
Vieques
n/a
Juana Diaz
n/a
Yabucoa
Yabucoa
n/a
Yauco
Yauco
n/a
Villalba
Villalba
113
VIII. MSW Hauling Origins and Destinations: “No Action Case” 2020
Municipalities
Transfer Stations
Adjuntas
Aguada
San Sebastian
Aguadilla
Landfill
Destination
MRF
Ponce
Hatillo
Compost
n/a
Penuelas New
Cabo Rojo
WTE
n/a
Hatillo
n/a
Aguas Buenas
Cidra
Ponce
Aibonito
Cidra
Ponce
Añasco
Las Marias
Penuelas New
Arecibo
Penuelas New
Arroyo
Ponce
Barceloneta
Florida
Arecibo
n/a
Ponce
Aibonito
n/a
Barranquitas
Comerio
n/a
Aibonito
n/a
Hatillo
Mayaguez
n/a
Guaynabo/Arecibo
Arecibo
n/a
n/a
Bayamón
Penuelas New
Bayamon
n/a
Cabo Rojo
Cabo Rojo
Hatillo
n/a
Humacao
Caguas/Humacao/San
Juan
n/a
Camuy
Penuelas New
Hatillo
n/a
Canóvanas
Juncos
Humacao
n/a
Carolina
Fajardo
Carolina
n/a
Caguas
Caguas
Cataño
Cataño
Cayey
Cidra
Ceiba
Ponce
n/a
Ponce
Aibonito
Fajardo
n/a
n/a
Ciales
Morovis
Penuelas New
Cidra
Cidra
Ponce
n/a
Juana Diaz
n/a
Coamo
Hatillo
n/a
Comerío
Comerio
Ponce
Guaynabo
n/a
Corozal
Morovis
Penuelas New
Guaynabo
n/a
Fajardo
Humacao
n/a
Culebra
Dorado
Dorado
Penuelas New
n/a
Fajardo
Fajardo
Humacao
Florida
Florida
Hatillo
n/a
Guánica
Yauco
n/a
Guayama
Ponce
n/a
Guayanilla
Yauco
Hatillo/Guayanilla
n/a
Arecibo
n/a
Guaynabo
San Juan
Humacao
Guaynabo
n/a
Gurabo
Caguas
Humacao
Guaynabo
n/a
Hatillo
Lares
Penuelas New
Hatillo
Arecibo
n/a
Hormigueros
Penuelas New
Hatillo/Hormigueros
Mayaguez
n/a
Humacao
Humacao
Humacao
n/a
Isabela
Isabela
Hatillo
n/a
Jayuya
Jayuya
Hatillo
n/a
114
Juana Díaz
Juana Diaz
n/a
Juncos
Juncos
n/a
Lajas
Penuelas New
n/a
Lares
Lares
Penuelas New
Hatillo
n/a
Las Marías
Las Marias
Penuelas New
Hatillo
n/a
Las Piedras
Caguas
Humacao
Humacao
n/a
Loíza
Fajardo
Humacao
n/a
Luquillo
Fajardo
Humacao
n/a
Hatillo
n/a
Manatí
Morovis
Penuelas New
Maricao
Maricao
Penuelas New
Maunabo
Maunabo
Humacao
Mayagüez
Las Marias
Penuelas New
Hatillo
Moca
San Sebastian
Penuelas New
Hatillo
n/a
Morovis
Morovis
Penuelas New
Hatillo
n/a
Fajardo
Humacao
n/a
Naguabo
Naranjito
Morovis
Orocovis
Patillas
Peñuelas
Ponce
n/a
n/a
Mayaguez
Penuelas New
Ponce
Maunabo
Mayaguez
n/a
n/a
Hatillo
n/a
Ponce
n/a
Penuelas New
n/a
Ponce
Guayanilla
n/a
Quebradillas
Quebradillas
Penuelas New
Hatillo
n/a
Rincón
San Sebastian
Penuelas New
Hatillo
n/a
Fajardo
Humacao
n/a
Río Grande
Sabana Grande
San German
Salinas
Yauco
n/a
Ponce
San Germán
San German
Yauco
San Juan
San Juan
Humacao
San Lorenzo
Caguas
Humacao
San Sebastián
San Sebastian
Penuelas New
Santa Isabel
Aibonito
n/a
n/a
Guaynabo/San Juan
n/a
n/a
Hatillo
n/a
Ponce
n/a
Toa Alta
Morovis
Penuelas New
n/a
Toa Baja
Morovis
Penuelas New
n/a
Trujillo Alto
Juncos
Guaynabo/San Juan
n/a
Utuado
Penuelas New
Hatillo
n/a
Vega Alta
Morovis
Penuelas New
Hatillo
n/a
Vega Baja
Morovis
Penuelas New
Hatillo
n/a
Vieques
Vieques
n/a
Juana Diaz
n/a
Yabucoa
Humacao
n/a
Yauco
Yauco
n/a
Villalba
Villalba
115
IX. MSW Hauling Origins and Destinations: “No Action Case” 2030
Municipalities
Transfer Stations
Adjuntas
Aguada
San Sebastian
Aguadilla
Landfill
Destination
MRF
Ponce
Hatillo
Compost
n/a
Penuelas New
Cabo Rojo
WTE
n/a
Hatillo
n/a
Aguas Buenas
Cidra
Ponce
Aibonito
Cidra
Ponce
Añasco
Las Marias
Penuelas New
Arecibo
Penuelas New
Arroyo
Ponce
Barceloneta
Florida
Arecibo
n/a
Ponce
Aibonito
n/a
Barranquitas
Comerio
n/a
Aibonito
n/a
Hatillo
Mayaguez
n/a
Guaynabo/Arecibo
Arecibo
n/a
n/a
Bayamón
Penuelas New
Bayamon
n/a
Cabo Rojo
Cabo Rojo
Hatillo
n/a
Humacao
Caguas/Humacao/San
Juan
n/a
Camuy
Penuelas New
Hatillo
n/a
Canóvanas
Juncos
Humacao
n/a
Carolina
Fajardo
Carolina
n/a
Caguas
Caguas
Cataño
Cataño
Cayey
Cidra
Ceiba
Penuelas New
n/a
Ponce
Aibonito
Fajardo
n/a
n/a
Ciales
Morovis
Penuelas New
Cidra
Cidra
Ponce
n/a
Yauco
n/a
Coamo
Hatillo
n/a
Comerío
Comerio
Ponce
Guaynabo
n/a
Corozal
Morovis
Penuelas New
Guaynabo
n/a
Fajardo
Humacao
n/a
Culebra
Dorado
Dorado
Penuelas New
n/a
Fajardo
Fajardo
Humacao
Florida
Florida
Hatillo
n/a
Guánica
Yauco
n/a
Guayama
Ponce
n/a
Guayanilla
Yauco
Hatillo/Guayanilla
n/a
Arecibo
n/a
Guaynabo
San Juan
Humacao
Guaynabo
n/a
Gurabo
Caguas
Humacao
Guaynabo
n/a
Hatillo
Lares
Penuelas New
Hatillo
Arecibo
n/a
Hormigueros
Penuelas New
Hatillo/Hormigueros
Mayaguez
n/a
Humacao
Humacao
Humacao
n/a
Isabela
Isabela
Hatillo
n/a
Jayuya
Penuelas New
Hatillo
n/a
116
Juana Díaz
Yauco
n/a
Juncos
Juncos
n/a
Lajas
Penuelas New
n/a
Lares
Lares
Penuelas New
Hatillo
n/a
Las Marías
Las Marias
Penuelas New
Hatillo
n/a
Las Piedras
Caguas
Humacao
Humacao
n/a
Loíza
Fajardo
Humacao
n/a
Luquillo
Fajardo
Humacao
n/a
Hatillo
n/a
Manatí
Morovis
Penuelas New
Maricao
Maricao
Penuelas New
Maunabo
Maunabo
Humacao
Mayagüez
Las Marias
Penuelas New
Hatillo
Moca
San Sebastian
Penuelas New
Hatillo
n/a
Morovis
Morovis
Penuelas New
Hatillo
n/a
Fajardo
Humacao
n/a
Naguabo
Naranjito
Morovis
Orocovis
Patillas
Peñuelas
Ponce
n/a
n/a
Mayaguez
Penuelas New
Ponce
Maunabo
Mayaguez
n/a
n/a
Hatillo
n/a
Ponce
n/a
Penuelas New
n/a
Ponce
Guayanilla
n/a
Quebradillas
Quebradillas
Penuelas New
Hatillo
n/a
Rincón
San Sebastian
Penuelas New
Hatillo
n/a
Fajardo
Humacao
n/a
Río Grande
Sabana Grande
San German
Salinas
Yauco
n/a
Ponce
San Germán
San German
Yauco
San Juan
San Juan
Humacao
San Lorenzo
Caguas
Humacao
San Sebastián
San Sebastian
Penuelas New
Santa Isabel
Aibonito
n/a
n/a
Guaynabo/San Juan
n/a
n/a
Hatillo
n/a
Ponce
n/a
Toa Alta
Morovis
Penuelas New
n/a
Toa Baja
Morovis
Penuelas New
n/a
Trujillo Alto
Juncos
Guaynabo/San Juan
n/a
Utuado
Penuelas New
Hatillo
n/a
Vega Alta
Morovis
Penuelas New
Hatillo
n/a
Vega Baja
Morovis
Penuelas New
Hatillo
n/a
Vieques
Fajardo
n/a
Yauco
n/a
Yabucoa
Humacao
n/a
Yauco
Yauco
n/a
Villalba
Villalba
117
X. WARM Greenhouse Gas Emission Factors (MTCO2E per short ton)
Material
Source
Recycling
Reduction
Landfilling, Landfilling,
Landfilling,
Landfilling,
National
No
Energy Combustion Composting
Flaring
Average Recovery
Recovery
0.04
0.04
0.04
0.04
0.05
N/A
0.04
0.04
0.04
0.04
-1.54
N/A
0.04
0.04
0.04
0.04
0.05
N/A
0.04
0.04
0.04
0.04
0.05
N/A
0.04
0.04
0.04
0.04
1.31
N/A
0.04
0.04
0.04
0.04
1.31
N/A
0.04
0.04
0.04
0.04
1.28
N/A
0.08
1.49
-0.54
-0.8
-0.51
N/A
Aluminum Cans
Steel Cans
Copper Wire
Glass
HDPE
LDPE
PET
Corrugated Containers
Magazines / Third-class
mail
Newspaper
Office Paper
Phonebooks
Textbooks
Dimensional Lumber
-8.26
-3.19
-7.38
-0.53
-1.77
-2.25
-2.07
-5.6
-13.61
-1.8
-4.97
-0.28
-1.38
-1.67
-1.52
-3.1
-8.65
-3.07
-0.42
0.14
-0.66
-0.76
-0.36
N/A
-4.89
-8
-6.29
-9.13
-2.02
-2.8
-2.85
-2.65
-3.11
-2.46
-0.97
1.38
-0.97
1.38
-0.66
-0.48
3.71
-0.48
3.71
0.07
-1.18
0.36
-1.18
0.36
-0.98
-1.27
-0.07
-1.27
-0.07
-1.12
-0.58
-0.49
-0.58
-0.49
-0.61
N/A
N/A
N/A
N/A
N/A
Medium-density Fiberboard
-2.23
-2.47
-0.66
0.07
-0.98
-1.12
-0.61
N/A
Food Scraps
Yard Trimmings
Grass
Leaves
Branches
Mixed Paper (general)
Mixed Paper (primarily
residential)
Mixed Paper (primarily
from offices)
Mixed Metals
Mixed Plastics
Mixed Recyclables
Mixed Organics
Mixed MSW
Carpet
Personal Computers
Clay Bricks
Concrete
Fly Ash
Tires
Asphalt Concrete
Asphalt Shingles
Drywall
Fiberglass Insulation
Vinyl Flooring
Wood Flooring
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
-3.51
0.75
-0.11
0.28
-0.54
-0.66
0.05
1.43
0.2
0.51
-0.3
0.07
1.35
0.46
-0.24
0.17
-0.65
-0.98
-0.49
0.33
-0.3
0.13
-0.69
-1.12
-0.72
-0.13
-0.16
-0.16
-0.16
-0.16
-0.51
-0.2
-0.2
-0.2
-0.2
-0.2
N/A
N/A
-3.51
-0.03
1.21
-0.53
-0.75
-0.51
N/A
N/A
-3.6
0.17
1.43
-0.23
-0.44
-0.46
N/A
N/A
N/A
N/A
N/A
N/A
-4.02
-55.78
-0.29
N/A
N/A
-4.34
-0.11
-0.2
-0.22
-0.39
-0.63
-4.08
-5.4
-1.5
-2.87
N/A
N/A
-7.22
-2.26
N/A
-0.01
-0.87
-0.39
-0.08
-0.09
0.03
N/A
N/A
N/A
0.04
0.04
-0.05
0.31
1.15
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.13
0.04
0.04
0.07
0.04
0.04
0.96
0.77
3.1
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.13
0.04
0.04
0.07
0.04
0.04
-0.47
0.11
0.31
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.13
0.04
0.04
0.07
0.04
0.04
-0.66
0.02
-0.05
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.13
0.04
0.04
0.07
-1.05
1.29
-0.44
-0.15
-0.06
0.66
-0.17
N/A
N/A
N/A
0.51
N/A
-0.34
N/A
N/A
-0.33
-0.8
N/A
N/A
N/A
-0.2
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
118
XI. WARM Greenhouse Gas Emission Factors (MTCE per short ton)
Material
Source
Recycling
Reduction
Landfilling, Landfilling,
Landfilling,
Landfilling,
National
No
Energy Combustion Composting
Flaring
Average Recovery
Recovery
0.01
0.01
0.01
0.01
0.01
N/A
0.01
0.01
0.01
0.01
-0.42
N/A
0.01
0.01
0.01
0.01
0.01
N/A
0.01
0.01
0.01
0.01
0.01
N/A
0.01
0.01
0.01
0.01
0.36
N/A
0.01
0.01
0.01
0.01
0.36
N/A
0.01
0.01
0.01
0.01
0.35
N/A
0.02
0.41
-0.15
-0.22
-0.14
N/A
Aluminum Cans
Steel Cans
Copper Wire
Glass
HDPE
LDPE
PET
Corrugated Containers
Magazines / Third-class
mail
Newspaper
Office Paper
Phonebooks
Textbooks
Dimensional Lumber
-2.25
-0.87
-2.01
-0.14
-0.48
-0.61
-0.57
-1.53
-3.71
-0.49
-1.36
-0.08
-0.38
-0.46
-0.41
-0.85
-2.36
-0.84
-0.11
0.04
-0.18
-0.21
-0.1
N/A
-1.33
-2.18
-1.72
-2.49
-0.55
-0.76
-0.78
-0.72
-0.85
-0.67
-0.26
0.38
-0.26
0.38
-0.18
-0.13
1.01
-0.13
1.01
0.02
-0.32
0.1
-0.32
0.1
-0.27
-0.35
-0.02
-0.35
-0.02
-0.3
-0.16
-0.13
-0.16
-0.13
-0.17
N/A
N/A
N/A
N/A
N/A
Medium-density Fiberboard
-0.61
-0.67
-0.18
0.02
-0.27
-0.3
-0.17
N/A
Food Scraps
Yard Trimmings
Grass
Leaves
Branches
Mixed Paper (general)
Mixed Paper (primarily
residential)
Mixed Paper (primarily
from offices)
Mixed Metals
Mixed Plastics
Mixed Recyclables
Mixed Organics
Mixed MSW
Carpet
Personal Computers
Clay Bricks
Concrete
Fly Ash
Tires
Asphalt Concrete
Asphalt Shingles
Drywall
Fiberglass Insulation
Vinyl Flooring
Wood Flooring
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
-0.96
0.2
-0.03
0.08
-0.15
-0.18
0.01
0.39
0.05
0.14
-0.08
0.02
0.37
0.12
-0.07
0.05
-0.18
-0.27
-0.13
0.09
-0.08
0.04
-0.19
-0.3
-0.2
-0.03
-0.04
-0.04
-0.04
-0.04
-0.14
-0.05
-0.05
-0.05
-0.05
-0.05
N/A
N/A
-0.96
-0.01
0.33
-0.14
-0.21
-0.14
N/A
N/A
-0.98
0.05
0.39
-0.06
-0.12
-0.13
N/A
N/A
N/A
N/A
N/A
N/A
-1.1
-15.21
-0.08
N/A
N/A
-1.18
-0.03
-0.06
-0.06
-0.11
-0.17
-1.11
-1.47
-0.41
-0.78
N/A
N/A
-1.97
-0.62
N/A
0
-0.24
-0.11
-0.02
-0.03
0.01
N/A
N/A
N/A
0.01
0.01
-0.01
0.09
0.31
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.03
0.01
0.01
0.02
0.01
0.01
0.26
0.21
0.84
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.03
0.01
0.01
0.02
0.01
0.01
-0.13
0.03
0.08
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.03
0.01
0.01
0.02
0.01
0.01
-0.18
0
-0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.03
0.01
0.01
0.02
-0.29
0.35
-0.12
-0.04
-0.02
0.18
-0.05
N/A
N/A
N/A
0.14
N/A
-0.09
N/A
N/A
-0.09
-0.22
N/A
N/A
N/A
-0.05
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
119
XII. WARM Energy Use Factors (million BTU per short ton)
Material
Source
Recycling
Reduction
Landfilling, Landfilling,
Landfilling,
Landfilling,
National
No
Energy Combustion Composting
Flaring
Average Recovery
Recovery
0.53
0.53
0.53
0.53
0.64
N/A
0.53
0.53
0.53
0.53
-17.1
N/A
0.53
0.53
0.53
0.53
0.57
N/A
0.53
0.53
0.53
0.53
0.53
N/A
0.53
0.53
0.53
0.53
-18.65
N/A
0.53
0.53
0.53
0.53
-18.65
N/A
0.53
0.53
0.53
0.53
-9.54
N/A
0.15
0.53
0.53
-0.7
-6.84
N/A
Aluminum Cans
Steel Cans
Copper Wire
Glass
HDPE
LDPE
PET
Corrugated Containers
Magazines / Third-class
mail
Newspaper
Office Paper
Phonebooks
Textbooks
Dimensional Lumber
-126.22
-30.82
-122.34
-6.93
-63.76
-74
-70.75
-22.01
-206.42
-19.97
-82.59
-2.13
-50.9
-56.01
-52.83
-15.05
-33.22
-0.69
0.38
0.53
0.53
0.04
-5.03
N/A
-36.45
-36.59
-40.19
-35.59
-3.53
-16.49
-10.08
-11.93
-1.03
0.59
0.4
-0.1
0.4
-0.1
0.33
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.1
-1.5
0.1
-1.5
-0.11
-7.76
-6.6
-7.76
-6.6
-8.12
N/A
N/A
N/A
N/A
N/A
Medium-density Fiberboard
-11.61
0.86
0.33
0.53
0.53
-0.11
-8.12
N/A
Food Scraps
Yard Trimmings
Grass
Leaves
Branches
Mixed Paper (general)
Mixed Paper (primarily
residential)
Mixed Paper (primarily
from offices)
Mixed Metals
Mixed Plastics
Mixed Recyclables
Mixed Organics
Mixed MSW
Carpet
Personal Computers
Clay Bricks
Concrete
Fly Ash
Tires
Asphalt Concrete
Asphalt Shingles
Drywall
Fiberglass Insulation
Vinyl Flooring
Wood Flooring
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
-20.36
0.35
0.44
0.46
0.46
0.33
0.18
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
-0.06
0.26
0.24
0.32
-0.11
-0.59
-2.11
-2.54
-2.54
-2.54
-2.54
7.46
0.58
0.58
0.58
0.58
0.58
N/A
N/A
-20.36
0.2
0.53
0.53
-0.53
7.43
N/A
N/A
-20.85
0.19
0.53
0.53
-0.48
6.88
N/A
N/A
N/A
N/A
N/A
N/A
-91.06
-956.74
-5.13
N/A
N/A
-71.63
-1.68
-3.18
-3.59
-4.77
-10.72
-14.48
-76.89
-52.76
-16.57
N/A
N/A
-96.29
-30.48
N/A
-0.11
-4.77
-56.68
-1.22
-2.46
-2.65
N/A
N/A
N/A
0.53
0.53
0.25
0.4
0.01
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
-0.37
0.1
-1.16
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
0.53
-11.68
-14.68
-6.9
-2.33
-4.77
-13.29
-6.29
N/A
N/A
N/A
-28.49
N/A
-8.5
N/A
N/A
-7.69
-10.71
N/A
N/A
N/A
0.58
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
* The energy factors presented in this table reflect national average landfill gas recovery practices and
transportation distances.
120