System Dynamics of the C ompetition of Municipal Solid Waste to
Landfill, Electricity, and Liquid Fuel in California
Westbrook, J.A.', Malczynski, L.A.?, Manley, D.K.!
1. Sandia National Laboratories, PO Box 969, Livermore, CA 94551
2. Sandia National Laboratories, PO Box 5800, Albuquerque, NM 87185
1. Telephone: (925) 294-4725, Fax: (925) 294-3870
2. Telephone: (505) 844-7219, Fax: (505) 844-8558
jwestbr@ sandia.gov, lamalcz@ sandia.gov, dmanley@ sandia.gov
Abstract
Increasing concern regarding the cost, security, and environmental impact of fossil fuel energy
use is driving research and investment towards developing the most strategic methods of
converting biomass resources into energy. Analyses to date have examined theoretical
limitations of biomass-to-energy through resource availability assessments, but have not
thoroughly challenged competing tradeoffs of biomass conversion into liquid fuel versus
electricity. Existing studies have focused on energy crops and cellulosic residues for biomass-to-
energy inputs, however the conversion of these biomass resources is often less energetically
efficient compared to fossil energy sources. Waste streams are beginning to be recognized as
valuable biomass to energy resources. Municipal solid waste (MSW) is a low-cost waste
biomass resource with a well-defined supply infrastructure and does not compete for land area
or food supply, making it a potentially attractive renewable feedstock for energy conversion.
The Waste Biomass to Energy Pathway model (WBEM) described here demonstrates a system
dynamics approach to analyze the impact of converting MSW biomass to either bioelectricity or
liquid fuel. The WBEM incorporates macro-scale feedback from supply chain costs, energy
sector impacts, and greenhouse gas (GHG) production within the competing pathways of MSW
to 1) landfill, 2) electricity, and 3) liquid fuel within California.
Introduction
Many biomass-to-energy studies and assessments focus on liquid fuel and electricity
energy conversion pathways separately, rather than their direct competition (Farrell et al., 2006;
Kaplan, et al., 2009; Lin & Tanaka, 2006; Morris, 2010). Regional diversities in energy
supplies, costs, and biomass resources suggest considering these pathways in competition.
MSW-to-energy is quickly becoming a topic of interest for local and national groups (Kaplan et
al., 2009; Morris, 2010; CCST, 2011), however detailed MSW-to-energy modeling and planning
efforts remains in infancy. For example, the conversion of plastic waste to energy is quickly
becoming a topic of research interest due to the lower heating value (LHV) of some plastic
wastes (Table 1), however most published work on this topic describes pilot-scale plastic to
energy conversion (Arena et al. 2011; UC Riverside, 2009).
Table 1. Biomass fuel sources and their lower heating values.
Biomass Fuel LHV (MJ/kg) Reference
Polyethylene 42.80 Arena et al. 2011
Household mixed plastic waste 27.00 Arenaet al. 2011
Selected mixed plastic waste 30.50 Arena et al. 2011
Paper/Cardboard 13.00 Arenaet al. 2011
Petroleum 42.30 Arena et al. 2011
Corn stover 16.37 Wang, 2011
Forest residue 15.41 Wang, 2011
Sugar cane bagasse 15.06 Wang, 2011
Preliminary work in the area of biomass-to-energy analysis has begun to explore the
economic and environmental tradeoffs of bioelectricity versus biofuel production. For example,
in 2010, Campbell and Block evaluated the competing pathways of waste sugarcane cellulose
(bagasse) to bioelectricity and bagasse to cellulosic ethanol on a Brazilian nationwide basis using
a linear approach. The study concluded that converting biomass to electric power could provide
a substantial portion of the nation’s imported electricity as opposed to the bagasse-to-ethanol
pathway, which would only meet a small fraction of the typical amount of Brazil’s exported
ethanol, suggesting that conversion of waste sugarcane biomass to electricity would be more
strategic. In 2009, Campbell et al. conducted a life-cycle assessment comparing GHG emissions
and the land use efficiency of energy crop biomass as an ultimate energy source for electric
vehicles versus ethanol-fueled vehicles. They observed greater net transportation energy output
per hectare and greater life cycle GHG emissions reductions for the 100% bioelectricity-fueled
vehicle than for the 100% ethanol-fueled vehicle. These initial studies begin to examine some of
the important economic and environmental tradeoffs between biomass to electricity versus liquid
fuels, generally employing sophisticated linear system modeling in tandem with spreadsheet
model calculations. However, unlike the WBEM, they are not able to capture energy system
dynamics such as supply chain biomass availability and required feedstock transportation
infrastructure together with the costs and efficiencies of the appropriate conversion technologies.
Model Description
The WBEM accounts for MSW chemical and physical composition variability that is
geographically categorized in terms of carbon content, LHV, required pre-processing, and other
factors that affect its conversion chemistry according to the available literature. The California
Department of Resources Recycling and Recovery completed Waste Characterization studies
that include the rate of waste generation, landfill size and location, where all MSW is transported
to and from, and the type of waste generated. As model input, the supply of potentially available
MSW is described by mass accumulation rate, composition, and collection network as a function
of population. National Renewable Energy Laboratory’s (NREL) thermodynamic combustion
database, Argonne National Lab’s Greenhouse Gases, Regulated Emissions and the Energy Use
in Transportation (GREET) model, and other literature sources were referenced to determine
detailed chemical compositions for all MSW types (Arena et al., 2011; Domalski et al., 1987;
Wang, 2011). Although transportation and processing of MSW will have associated costs as
adapted from Thorneloe et al. 2007, the MSW feedstock itself is assumed to have zero cost.
Figure 1 shows a high-level model representation of the WBEM, which is designed to
capture the potential system dynamics of the three competing pathways of waste biomass to 1)
landfill, 2) electricity, and 3) liquid fuel from 2011 into 2050.
a Air Space Displacement and Landfill Gas Generation
Competition
J MSW to Landfill
we Electricity Displacement
MSW Biomass Supply per Person oi MSW to Electricity
Landfill Space & Landfill Gas Reduction
MSW to Ethanol
Baseline Ethanol/liquid Fue! Displacement
Figure 1. High-level Waste Biomass to Energy Pathway model (W BEM) representation.
These three pathways have economic costs, energy requirements, and environmental impacts,
such as GHG emissions, associated with them. The described modeling approach can consider
all of these pathway factors simultaneously in order to determine which waste biomass pathway
is the most beneficial given a specific objective, e.g. reduce greenhouse gas emissions. As MSW
is transported and deposited into landfill, the WBEM describes the complex stock and flow
behavior of MSW accumulation in landfill and its generation of landfill gases over time due to
decomposition, as well as land and air volume taken up by the waste over time which is
described by a displaced air space metric. Some MSW may be converted to electricity or to
ethanol, reducing MSW accumulation in landfill space and the resulting landfill GHGs, while
providing an alternative electricity or liquid fuel source.
Waste Supply Chain and Landfill Use
Over the past 50 years the state of Califomia has made substantial progress in waste diversion,
diverting over 60% of generated MSW from landfills into compost and recycling programs
which are organized at the municipality level. Despite these successes, approximately 30 million
tons of waste was transported to Califomia landfills in 2009, 60% of which was either paper,
organic materials such as food or other plant material, or mixed plastics (CA Waste
Characterization Study, 2009). The 2008 California Waste Characterization Study was
referenced to determine the supply of MSW biomass available for energy conversion (CA Waste
Characterization Study, 2009). MSW types that are considered divertible for energy conversion
include paper, organic material, and plastic. Mixed, special, and inert waste types are not
considered divertible to energy due to their chemical and physical composition or due to the
unknown nature of the waste (CA Waste Characterization Study, 2009). The WBEM calculates
the MSW biomass supply on a per person basis, calculating population growth according to
current and historical US Census records (U.S. Census Bureau, Population Division, 2009). Itis
generally accepted among the MSW-to-energy research community that some degree of pre-
sorting of MSW at the household or commercial level may be assumed to include the separation
of paper, organics, and sub categories of plastic including recyclables and non-recyclables prior
to curbside collection (McDougall et al., 2001). Asa result, the WBEM assumes that paper,
organic materials, and plastics may be diverted from landfills separately. The amount of each
type of divertible waste to be designated to energy conversion may be determined by the model
user. Prior to diversion, a model user may input parameters for the diversion of these three waste
types for local recycling and/or composting programs prior to other pathways. It is assumed that
mixed, special, and inert wastes are not able to be diverted and always continue to landfill as a
default. MSW is generated at the city level from 411 jurisdictions and is transported to 130
active landfills, each landfill receiving waste from multiple jurisdictions. MSW network tonnage
data was collected from the CalRecycle website (CalRecycle, 2011). Emissions and fuel costs
associated with the collection and transportation of MSW by heavy duty truck, as well as those
associated with landfill equipment operations were calculated as described in Thorneloe et al.,
2007 and in Wang, 2011.
Displaced air space is a commonly used metric for representing the land and atmospheric
area and volume taken up by landfill waste. The WBEM calculates displaced air space over time
as MSW is generated and deposited in landfill, incorporating a 10% compaction rate, from
landfill opening to closing (Figure 2).
MSW GENERATION
LANORIL Waste
ZONTRBUTION
ROM ALL
SURISDICTIONS &- <
EXCEPT ADELANTO
‘To LaNDrLLS
ADRANTO USES
COMPACTION
PERCENT
>=
total dvertable ms —
ot wo (
oe INITIAL REMAINING
'AIRSPACE 2009
Figure 2. Portion of WBEM model. One community, Adelanto, and all MSW landfills it
utilizes.
Opening dates and estimated closing dates for landfills were determined by CalRecycle
(CalRecycle, 2011). Fees associated with MSW landfill disposal are also considered, including
tipping fees paid at MSW transfer stations, as well as fees paid by municipalities per ton of
MSW for landfill disposal. Landfill-associated emission calculations were modeled as described
by the Environmental Protection Agency’s (EPA) Landfill Gas Emissions Model (LandGEM)
(LandGEM, 2005). Historical landfill GHG emissions were determined for each Califomia
landfill according to available historical landfill age, landfill capacity, and landfill environmental
conditions. LandGEM settings for potential methane generation capacity, projected methane
generation rate, environmental conditions, and landfill type may be input as user-specified model
parameters. These data are incorporated with model-projected future landfill GHG emissions
that are based on continual MSW deposits in landfill under the assumption that waste generation
per person remains constant over time. A preliminary sample output of landfill methane quantity
over time from one community calculated by LandGEM is shown in Figure 3.
methane quantity
2049 2039 2028 2019 2012
Figure 3. Preliminary sample landfill methane quantity model output from landfills
receiving MSW from one community: Adelanto, CA. Calendar year is represented on the
x-axis. In 2049 for example, methane landfill emissions include those from MSW deposited
in landfill during 2049, as predicted by the model, plus landfill emissions resulting from
previous MSW deposited in landfill in previous years as it continues to decay.
LandGEM is commonly used for MSW landfill planning estimates of GHG emission
rates for total landfill gas, methane, carbon dioxide, non-methane organic compounds, and other
air pollutants from MSW landfills. Under LandGEM default conditions, landfill gas composition
is approximately 50% methane, 50% carbon dioxide, with trace amounts of 50 additional volatile
organic and/or hazardous atmospheric pollutants.
MSW per MSW diversion
capita attempts
INITIAL AVAILABLE
AIRSPACE
+
usw t a
generation - +
_—— Available
+ “—_ usw in Airspace
Landfill 2
TAM demand for
additional MSW
landfills
Population +
+
compaction
I New MSW
Landfills
impact of landfill +
mass on compaction Land Available for
MSW Lanfills
Figure 4. WBEM MSW supply chain causal loop relationships.
Figure 4 highlights some of the MSW supply chain causal loops found in the WBEM. As
MSW is generated on a per person basis, it contributes to MSW in landfill where it displaces air
space as it accumulates and compacts over time. Diversion of MSW to either energy conversion
or to local recycling and composting programs decreases MSW going to landfill, increasing the
available landfill space. The demand for additional landfills increases as MSW fills up the
initially available air space available, creating a demand for new landfills.
Energy Conversion
Organics and Paper to Electricity
Waste organic and paper material that is diverted from the landfill for energy conversion
purposes may be converted to either liquid fuel or to electricity. For the conversion of waste
organic matter and paper biomass to electricity, gasification and direct combustion conversion
technologies were considered. Although direct combustion is by far the most common
conversion technology used to date for the conversion of biomass to electricity in Califomia (CA
Energy Almanac, 2009), many renewable portfolio standard programs, such as that in CA, only
allow electricity generated from gasification of MSW to be eligible for renewable energy credits.
A state or region may wish to explore biomass to energy options that are eligible for energy
credits, even if some technologies are still at a pilot stage of development; therefore the WBEM
allows the user to choose which conversion technology is used. All MSW-derived energy
feedstock biomass is considered to be zero cost.
Due to a lack of energy conversion data specific to paper and organic materials, these
MSW biomass feedstocks are represented by com stover for electricity and ethanol conversion
due to similarities in chemical composition and in LHVs. For example, the weighted average of
LHVs of the tons of the five most landfilled paper types is equal to 17.52 Megajoules per kg
(Domalski et al., 1987), compared to a corn stover LHV of 17.21 Megajoules per kg (Wang et
al., 2011). Percent carbon content by weight of the same paper products is 42.2% (Domalski et
al., 1987), and com stover carbon content by weight 43.7% (Wang et al., 2011). According to
the NREL thermodynamic database, the LHVs and carbon content is highly variable among food
types which is partly due to variations in water content (Domalski et al., 1987). Due to the lack
of granularity in organic waste biomass by type available, com stover is used as a proxy for
organic waste as well. However, if a model user has more detailed data on input biomass, the
model parameters can be adjusted accordingly. Energy requirements, GHGs, and energy
conversion efficiencies were determined by GREET (Wang, 2011).
As waste biomass is converted into electricity, it displaces current electricity sources.
Current baseline California state electric mix and demand was determined from the California
Energy Commission’s CA energy almanac and includes biomass, coal, geothermal,
hydroelectric, landfill gas, natural gas, nuclear, oil, photovoltaic, and wind electricity fuel
sources (CA Energy Almanac, 2009). GREET was used to determine energy requirements and
GHGs for each baseline electricity source except landfill gas, which was referenced by
Sanscartier et al., 2011 (Wang, 2011). In real-time application, it is unknown whether waste-
derived bioelectricity would offset baseline electrical mix, marginal electric mix, or future
electricity generation that is planned but not yet built. In order to address any and all of these
possibilities, the WBEM allows the user to determine what electricity sources it displaces in any
possible configuration. This approach provides flexibility to a wide range of model applications,
but also allows analysis for determining the most strategic allocation of biomass-derived
electricity resources. Costs associated with electricity fuels, electricity conversion, and the price
of electricity for baseline electricity sources were determined from the Energy Information
Administration (EIA) (U.S. Energy Information Administration, 201 1a).
Organics and Paper to Liquid Fuel
The WBEM also allows for the diversion of waste biomass for conversion into liquid fuel
for use in the transportation sector. For the conversion of waste organic matter and paper
biomass to electricity, gasification and fermentation conversion technologies were considered.
Similarly to electricity, due to a lack of liquid fuel conversion data specific to paper and organic
materials, and in order to quantitatively compare liquid fuel generation to electricity generation,
these MSW biomass feedstocks are represented by com stover for liquid fuel conversion due to
similarities in chemical composition and in LHVs. The model user may choose the conversion
technology to be used. Energy requirements, GHGs, and energy conversion efficiencies were
determined by GREET (Wang, 2011). Costs associated with the fermentation conversion of
cellulosic waste biomass to liquid fuel and resulting ethanol prices are as described by Humbird
et al, 2011.
As waste biomass is converted to liquid fuel, it displaces currently used transportation
fuel sources. Current baseline Califomia state ethanol and gasoline demand was determined by
information available from EIA to be approximately 2.5 million Megajoules per day in the
transportation sector (2011b). According to GREET, national US ethanol production consists of
a mix of approximately 90% dry milled corn and 10% wet milled com (Wang, 2011). This
baseline mix was used to approximate California state ethanol mix in the WBEM. If MSW
biomass is converted to ethanol energy for use in the transportation sector, the model user may
determine what baseline sources of ethanol production will be displaced. In addition, the current
California state gasoline fuel demand of approximately 4.9 billion Megajoules per day was also
incorporated into the WBEM in order to evaluate the costs and environmental consequences of
gasoline liquid fuel displacement with MSW-derived liquid fuel (EIA, 2011c). It is unknown
whether MSW-derived liquid fuel would displace fossil fuel-based transportation fuels, current
ethanol sources, or some combination of these options, the model allows the user to allocate
MSW-derived energy resources while also allowing for analysis to determine the most strategic
allocation of energy resources based on cost, environmental impact, and other parameters.
Conversion costs of baseline biomass resources to ethanol, ethanol prices, and costs associated
with gasoline production and use were determined by Humbird et al. and EIA respectively
(2011; EIA, 2011). Costs associated with gasoline feedstock, refining, and retail price were
determined by the EIA (2011c).
Discussion
This system dynamics methodology allows a quantitative exploration of tradeoffs
between these pathways by considering dynamics and feedback across them over time. For
example, the variety of current biomass to energy conversion technologies vary widely in terms
of cost. As these technologies mature as a function of the amount of biomass converted, they
may become more economical compared to others, shifting the flow of biomass types over time
as a function of cost-benefit. System dynamics is also ideal for analyzing these competing
pathways in the face of changing energy use and fuel price. For example, as the price of oil
fluctuates in the case of liquid fuel, and as the price of coal or Natural Gas fluctuates in the case
of electricity, which energy pathway would be better suited for waste biomass from a life-cycle
cost perspective? This dynamic approach may also be used to determine how biomass may be
able to make a significant environmental improvement. For example, diverting waste biomass to
either liquid fuel or to electricity may displace existing energy sources. This displacement will
have an environmental impact per amount of baseline energy demand displaced in either the
electricity or transportation sectors. This metric may vary depending on the carbon intensity of
the displaced energy fuel source. The carbon intensity of the displaced fuel source will vary
geographically in the US, and also perhaps over time. This dynamic approach will be able to
capture these phenomena, among others, as the WBEM nears completion. By capturing these
dynamics, we expect to see variations in the most cost-effective and the most environmentally-
effective uses of waste biomass over time. This capability will guide understanding of how
waste-to-energy technologies could more strategically advance bioenergy in one state, which
may be then extrapolated to consider waste to energy capabilities on a national level, and provide
a flexible framework able to apply to waste streams beyond MSW, and to the strategic planning
of other available biomass resources.
Acknowledgements
Supported by the Laboratory Directed Research and Development program at Sandia National
Laboratories, a multiprogram laboratory managed and operated by Sandia corporation, a wholly
owned subsidiary of Lockheed Martin Company, for the United States Department of Energy’s
National Nuclear Security Administration, under contract DE-AC04-94AL85000.
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