Question:
You are given the full text of a scientific research paper.

    Your task is to generate a structured **policy brief** that includes the following components:

    - A concise, descriptive **title** that captures the central theme or policy issue addressed in the paper (do not label it with “Title:”).
    - **Policy Problem** - What societal or strategic challenge is the paper addressing?
    - **Scientific Research Findings** - What are the key results relevant to this issue?
    - **Scientific Research Study Methods** - What methodology or data supports these findings?
    - **Policy Implications** - How might the findings guide or influence policy?

    Write each section in a clear, accessible style suitable for policymakers. Avoid overly technical language, but use essential terms when necessary. Structure the output as a labeled five-part policy brief document.

    Scientific Research Paper:
    Analysis
https://doi.org/10.1038/s41560-019-0430-2
1Department of Urban Planning, University of California, Los Angeles, CA, USA. 2Institute of the Environment and Sustainability, University of California,
Los Angeles, CA, USA. *e-mail: rdeepak@ioes.ucla.edu
A
t the beginning of the new millennium, energy insecurity,
global climate change and stagnant rural economies led to
policies supporting domestic biofuels as a renewable alter-
native fuel in more than 60 countries worldwide1. As a consequence,
global production of ethanol and biodiesel combined almost qua-
drupled (from about 35 billion litres to 135 billion litres) in the short
span from 2005 to 2016 (ref. 2). However, these policies had two
major flaws. First, appropriation of edible crops for biofuel (mainly
corn and sugarcane for ethanol, and soybean, canola and palm for
biodiesel) was an important factor responsible for food price infla-
tion alongside other factors such as rising income that drove rapid
growth in food demand (especially meat demand), rising energy
prices, adverse weather shocks, currency fluctuations and trade
policies1,3–6, the consequences of which were particularly severe for
poorer households in developing countries7. Second, these crops
required intensive use of land, water, nitrogen and other farm
chemicals, which meant low, and in the worst case uncertain, net
environmental benefits8–12.
Being widely available and replenishable, wastes and biomass
residues from agricultural, dairy, forestry and household activi-
ties seem to contain the basic attributes of a sustainable energy
resource, in stark contrast to bioenergy from food crops13–15. The US
Department of Energy 2016 Billion-Ton Study estimates an annual
availability of 233 million tonnes (Mt) of dry waste16. To put this
in perspective, the approximately 60 billion litres of corn ethanol
produced in the United States in 2017 required about 150 Mt of corn
(assuming a yield of 402 l ethanol per Mt). Furthermore, wastes and
biomass residues can be used to derive a number of alternative
energy products, including electricity along with heat, biomethane
(or renewable natural gas), ethanol, renewable diesel or bio jet fuel,
each through various conversion pathways, which currently are at
different stages of technical and economic maturity14,15,17–21. Beyond
energy production and mitigation of climate change, efficient use
of wastes and residues is integral to the achievement of sustain-
able development22, and to redesigning our economies to minimize
material and energy throughput, that is, towards becoming a circu-
lar economy23,24. However, at the same time, sustainable use of this
resource hinges on overcoming some challenges. The collection,
transport and storage of biomass feedstocks are costly and could
account for over 50% of total cost in the supply chain of bioenergy
products25. The composition of wastes also varies from one location
to another, and their processing requires substantial energy inputs.
In addition, national-scale policies tend to ignore local trade-offs,
leading to suboptimal use of scarce resources26. Harnessing the full
energetic and environmental potential of this resource, therefore,
requires a holistic assessment of alternative competing pathways
to their utilization taking into account the spatial distribution of
each specific type of waste and the local conditions under which
the wastes will be processed. The majority of previous life-cycle
assessment (LCA) studies have focused on either a smaller number
of waste types14,27–35, certain types of bioenergy product15,19,20,36–38 or
certain conversion technologies29,31,37,39–45. Comparing the effective-
ness and environmental impacts of all feasible conversion pathways
for all types of waste from a systems perspective is necessary for
policies that address the best use of wastes and biomass residues.
Here, we determine the net energy gain and the global warming
potential (GWP) of energy recovery from waste; which pathways
simultaneously maximize renewable energy production, net energy
gain and climate benefits for each type of waste and how this var-
ies given the spatial distribution of their availability (specifically, in
the contiguous United States); and what are the aggregate energy
and climate benefits when all available wastes and biomass resi-
dues across the contiguous United States are dedicated for a specific
policy objective such as maximizing renewable energy production,
maximizing net energy gain or maximizing climate benefits. These
questions are aimed at deriving both general insights on the optimal
use of wastes and biomass residues, and also illustrating their overall
climate-change mitigation potential in the context of a large country,
specifically the United States. To this end, we quantify life-cycle GHG
emissions and net energy gain for 15 conversion pathways (detailed
Life-cycle energy and climate benefits of energy
recovery from wastes and biomass residues in the
United States
Bo Liu1 and Deepak Rajagopal   2*
Agricultural and forestry residues, animal manure and municipal solid waste are replenishable and widely available. However,
harnessing these heterogeneous and diffuse resources for energy requires a holistic assessment of alternative conversion path-
ways, taking into account spatial factors. Here, we analyse, from a life-cycle assessment perspective, the potential renewable
energy production, net energy gain and greenhouse gas (GHG) emission reduction for each distinct type of waste feedstock
under different conversion technology pathways. The utilization of all available wastes and residues in the contiguous United
States can generate 3.1–3.8 exajoules (EJ) of renewable energy, but only deliver 2.4–3.2 EJ of net energy gain, and displace
103–178 million tonnes of CO2-equivalent GHG emissions. For any given waste feedstock, looking across all US counties where
it is available, except in rare instances, no single conversion pathway simultaneously maximizes renewable energy production,
net energy gain and GHG mitigation.
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Analysis
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Table 1 | Description and attributes of conversion pathways
Conversion
pathway
Label
Description
Feedstock feasibility
Energy input
Energy output (main)
Energy output
(coproducts)
Displaced
products
Refs.
CHP
E1
Thermal combustion through biomass CHP plants
All
Electricity, heat, diesel
Electricity
Heat
State power grids,
natural gas-based
heat
15, 39,40
Gasification +
CHP
E2
Syngas is produced through gasification and is then
combusted in gas engines to produce electricity and heat
All
Electricity, heat
Electricity
Heat
State power grids,
natural-gas-based
heat
15, 33,61
Integrated
gasification
combined cycle
E3
Electricity generation through combined gas and steam
turbines with no heat recovery
All
Electricity, heat
Electricity
N/A
State power grids
15, 33,50
Anaerobic
digestion + CHP
E4
Biogas is produced through anaerobic digestion and is
then combusted in gas engines to produce electricity
and heat
Animal manure, MSW
(except plastics, rubber
and leather, and textiles)
Natural gas, diesel
Electricity
Heat
State power grids,
natural-gas-based
heat
28, 29, 40, 43,50
Gasification
M1
Syngas is produced through gasification and is then
upgraded and purified to produce methane.
All
Electricity, heat
Methane
N/A
Natural gas
15,61
Anaerobic
digestion
M2
Biogas is produced through anaerobic digestion and is
then upgraded and compressed for pipeline transmission
Animal manure, MSW
(except plastics, rubber
and leather, and textiles)
Electricity, heat, diesel
Methane
N/A
Natural gas
28, 40, 43,50
Enzymatic
hydrolysis +
fermentation
Eth1
Ethanol production through pretreatment, enzymatic
hydrolysis and fermentation
Ag. and forest residues,
construction and
demolition (CD) waste,
MSW wood, paper, yard
trimmings
Natural gas, diesel
Ethanol
Electricity
Petroleum-based
gasoline, state
power grids
36, 50,62
Gasification
Fischer–Tropsch
(FT) synthesis
Rd1
Gasification to decompose biomass into syngas, and
FT synthesis to convert syngas into liquid fuels with the
presence of catalysts; excess steam is used for electricity
generation
Ag. and forest residues,
CD waste, MSW wood,
paper, plastics, yard
trimmings
Electricity
Renewable diesel
Renewable gasoline, bio jet
fuel, methane, electricity
Petroleum-based
diesel, gasoline
and jet fuel,
natural gas, state
power grids
20, 34, 44,50
Pyrolysis +
hydroprocessing
Rd2
Thermochemical conversion of a feedstock into bio-oil,
bio-char and pyrolysis gas; integrated with hydrocracking
and hydrotreatment processes for liquid fuel production
Ag. and forest residues,
CD waste, food waste,
MSW wood, paper,
plastics, yard trimmings
Electricity, natural gas
Renewable diesel
Renewable gasoline
Petroleum-
based diesel and
gasoline
35,37
Alcohol-to-jet
(ethanol)
Bj1
Bio jet fuel production with ethanol as the intermediate
product
Ag. and forest residues,
CD waste, MSW wood,
paper, yard trimmings
Hydrogen, electricity
Bio jet fuel
Renewable diesel,
renewable gasoline
Petroleum-based
diesel, gasoline
and jet fuel
50
Sugar-to-jet
(fermentation)
Bj2
Sugar is separated from waste feedstock and is
then converted into hydrocarbon or hydrocarbon
intermediates through fermentation
Ag. and forest residues,
CD waste, MSW wood,
paper, yard trimmings
Hydrogen
Bio jet fuel
N/A
Petroleum-based
jet fuel
50
Pyrolysis in situ
Bj3
Feedstock is dried, ground and then converted to a
mixture of bio-oil, gas and char at high temperature
(above 500 °C). The conversion is continued by
hydrodeoxygenating the bio-oil with hydrogen, which is
produced through steam methane reforming (SMR) of
process off-gases
Forest residues, CD waste,
MSW wood, paper, yard
trimmings
Electricity
Bio jet fuel
Renewable diesel,
renewable gasoline
Petroleum-based
diesel, gasoline
and jet fuel
19, 20,45
Pyrolysis ex situ
Bj4
Same process as Bj3 except that hydrogen is produced
from SMR of natural gas
Forest residues, CD waste,
MSW wood, paper, yard
trimmings
Hydrogen
Bio jet fuel
Renewable diesel,
renewable gasoline
Petroleum-based
diesel, gasoline
and jet fuel
19, 20,45
HTL in situ
Bj5
Wet feedstock is converted into biocrude at a
temperature of 250–550 °C (with water as a medium),
and is then hydrodeoxygenated with hydrogen, which
is produced through SMR of process off-gases and also
anaerobic digestion of wastewater
Forest residues, CD waste,
MSW wood, paper, yard
trimmings
Electricity
Bio jet fuel
Renewable diesel,
renewable gasoline
Petroleum-based
diesel, gasoline
and jet fuel
19, 20,45
HTL ex situ
Bj6
Same process as Bj5 except that hydrogen is produced
from SMR of natural gas
Forest residues, CD waste,
MSW wood, paper, yard
trimmings
Electricity, hydrogen
Bio jet fuel
Renewable diesel, renewable
gasoline
Petroleum-based
diesel, gasoline and
jet fuel
19, 20,45
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Analysis
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description in Table 1) and 29 waste feedstocks with spatially explicit
estimates of waste potential for the United States. We find that the
source of electricity consumed during processing and the environ-
mental footprint of the displaced products are key in determining
the best use of wastes and biomass residues. The utilization of all
available wastes and residues in the contiguous United States can
generate 3.1–3.8 EJ of renewable energy, but deliver only 2.4–3.2 EJ
of net energy gain, and displace 103–178 Mt of CO2-equivalent
(MtCO2e) GHG emissions. For any given waste feedstock, looking
across all US counties where it is available, except in rare instances,
no single conversion pathway simultaneously maximizes renewable
energy production, net energy gain and GHG mitigation.
Ag. residues
Animal manure
Forest residues
MSW
E1
E2
E3
M1
Eth1
Rd1
Bj1
Bj2
E1
E2
E3
E4
M1
M2
E1
E2
E3
M1
Eth1
Rd1
Rd2
Bj1
Bj2
Bj3
Bj4
Bj5
Bj6
E1
E2
E3
E4
M1
M2
Eth1
Rd1
Rd2
Bj1
Bj2
Bj3
Bj4
Bj5
Bj6
−5
0
5
10
15
GJ per Mg ww
Energy production/main product
Energy production/coproduct(s)
Net energy
Ag. residues
Animal manure
Forest residues
MSW
E1
E2
E3
M1
Eth1
Rd1
Bj1
Bj2
E1
E2
E3
E4
M1
M2
E1
E2
E3
M1
Eth1
Rd1
Rd2
Bj1
Bj2
Bj3
Bj4
Bj5
Bj6
E1
E2
E3
E4
M1
M2
Eth1
Rd1
Rd2
Bj1
Bj2
Bj3
Bj4
Bj5
Bj6
0
5
10
15
20
Ag. residues
Animal manure
Forest residues
MSW
E1
E2
E3
M1
Eth1
Rd1
Bj1
Bj2
BAU1
E1
E2
E3
E4
M1
M2
BAU2
E1
E2
E3
M1
Eth1
Rd1
Rd2
Bj1
Bj2
Bj3
Bj4
Bj5
Bj6
BAU3
E1
E2
E3
E4
M1
M2
Eth1
Rd1
Rd2
Bj1
Bj2
Bj3
Bj4
Bj5
Bj6
BAU4
BAU5
−1
0
1
2
tCO2e per Mg ww
Collection
Transport to facility
Processing
Transmission & distribution
End use
Displacement/main product
Displacement/coproduct(s)
Net GWP
Current management practices
Ag. residues
Animal manure
Forest residues
MSW
E1
E2
E3
M1
Eth1
Rd1
Bj1
Bj2
BAU1
E1
E2
E3
E4
M1
M2
BAU2
E1
E2
E3
M1
Eth1
Rd1
Rd2
Bj1
Bj2
Bj3
Bj4
Bj5
Bj6
BAU3
E1
E2
E3
E4
M1
M2
Eth1
Rd1
Rd2
Bj1
Bj2
Bj3
Bj4
Bj5
Bj6
BAU4
BAU5
−1
0
1
2
tCO2e per Mg ww
Collection
Transport to facility
Processing
Transmission & distribution
End use
Biogenic CO2
Displacement/main product
Displacement/coproduct(s)
Net GWP
Current management practices
a
b
c
d
Fig. 1 | Energy, net energy and emissions from waste biomass utilization in the United States. a, Energy production and net energy by waste type and
conversion pathway. b, Energy return on investment by waste type and conversion pathway (the horizontal line refers to an energy return on investment of
1). c, Life-cycle emissions when biogenic CO2 is excluded. d, Life-cycle emissions when biogenic CO2 is included. ww, wet weight. Electricity pathways: E1—
CHP, E2—gasification + CHP, E3—integrated gasification combined cycle, E4—anaerobic digestion + CHP. Methane pathways: M1—gasification, M2—
anaerobic digestion. Ethanol pathway: Eth1—enzymatic hydrolysis + fermentation. Renewable-diesel pathways: Rd1—gasification + FT synthesis, Rd2—
pyrolysis + hydroprocessing. Bio jet fuel pathways: Bj1—alcohol-to-jet (ethanol), Bj2—sugar-to-jet (fermentation), Bj3—pyrolysis (in situ), Bj4—pyrolysis
(ex situ), Bj5—HTL (in situ), Bj6—HTL (ex situ). Business-as-usual (BAU) practices: BAU1—left on field (agricultural residues), BAU2—direct land
application (animal manure), BAU3—burning on site (forest residues), BAU4—landfilling without methane flaring or capture (MSW), BAU5—landfilling
with 75% of methane capture and use for on-site CHP (MSW). See Table 1 for additional details of conversion pathways.
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Analysis
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Technical comparison of conversion pathways. We first estimate
the renewable energy production, net energy gain and GHG foot-
print of different conversion pathways on a per unit wet weight basis
for various types of waste. Feedstock-level results are depicted in
Supplementary Figs. 5–7. Methods explains how we first calculate
these for each distinct waste biomass source at the US county level,
and subsequently compute a mass-weighted average for each of the
four broad categories of wastes at the national level. The renew-
able energy yield across conversion pathways ranges from 0.2 to
13.1 gigajoules (GJ) per megagram (Mg) of waste, while net energy
gain ranges from −2.4 to 11.6 GJ Mg−1 (Fig. 1a,b). It is clear that
the energy value of coproducts is critical to achieving positive net
energy for a number of conversion pathways and waste feedstocks.
Except for animal-manure-related pathways, all conversion path-
ways result in positive net energy gains and considerable energy
return on investment. For animal manure, only anaerobic digestion
(M2) yields positive net energy, and its energy return on investment
is only slightly greater than 1. The net GWP across the pathways
ranges from −0.9 to 0.7 tCO2e Mg−1 (Fig. 1d). As with the impor-
tance of coproducts in net energy gain, emissions avoided by the
resulting coproduct(s) displacing a substitute accounts for a sub-
stantial portion of the climate benefits for most pathways.
Looking into each broad waste category, for agricultural and for-
est residues, combined heat and power generation (CHP) offers both
the greatest net energy gain and the greatest climate benefits. For
municipal solid waste (MSW), CHP offers the highest net energy gain
while anaerobic digestion returns more climate benefits than other
pathways. When compared with current management practices, all
conversion pathways result in climate benefits for agricultural resi-
dues. For animal manure, only anaerobic digestion producing either
methane (M2) or electricity and heat (E4) yields climate benefits.
This corresponds to previous studies, which indicate that anaerobic
digestion is the optimal conversion pathway for animal manure15,27,28.
Although some pathways appear not to contribute to climate-change
mitigation (that is, result in positive net GWP), all conversion path-
ways for forest residues yield smaller net GWP relative to burning
them on site. When compared with landfilling without any methane
flaring or capture, all conversion pathways for MSW result in smaller
negative effects on the climate. However, landfilling with methane
capture and on-site CHP would greatly reduce the GHG emissions
of landfilling and become more attractive than renewable-diesel-
related conversion pathways (Fig. 1c,d).
Breakdown of GHG emission sources. Disaggregating the con-
tribution to total GHG emissions from the different stages in the
production chain shows that emissions during the processing stage,
which requires electricity and heat input, and credits for avoided
emissions attributable to displaced products, are key determinants
of GHG emissions for most conversion pathways (Fig. 1). This is
generally in line with results from a number of recent studies, such
as refs. 15,20,34. For agricultural residues, current management prac-
tice (that is, left and decayed on field) entail no GWP due to the
fact that the GWPbio index for annual crops is zero. While the same
GWPbio index applies to animal feed, methane and N2O emissions
from animal farm operations contribute to total emissions from
direct land application of manure. For MSW, the major sources of
non-biogenic carbon are contained in plastics, rubber and leather,
and textiles. For non-electricity pathways, non-biogenic carbon in
MSW feedstocks would be transferred into energy products and
eventually be emitted into the atmosphere as CO2 during end use.
This explains a large amount of emissions during the end-use stage
for these pathways. For electricity-related pathways (E1–E4), non-
biogenic carbon would be emitted as CO2 during the processing
phase. For other types of MSW feedstock, biogenic carbon would
be emitted as biogenic CO2 in various phases. Thus, we treated bio-
genic CO2 as a separate source of GHG emissions.
Sensitivity analysis of emission estimates. Given that electric-
ity consumption during biomass processing is the major source of
energy inputs and emissions across most conversion pathways, a
sensitivity analysis on the emission intensities of state power grids
was conducted. Note that, even though biomass processing requires a
substantial amount of heat energy, it is typically derived from natural
gas, whose emission intensity is much less variable across regions rel-
ative to the emission intensity of electricity. Results show that cleaner
power grids in general would yield less climate benefit for electric-
ity pathways and more climate benefit for non-electricity pathways
(Fig. 2). For cleaner power grids, electricity-related pathways would
on one hand result in lower emissions during the processing stage,
but on the other hand lead to less climate benefit from the displace-
ment of grid electricity. For the majority of non-electricity pathways,
electricity is only an input, so cleaner power grids would result in
lower emissions during the processing stage and the overall life cycle.
For instance, whereas converting agricultural and forest residues
into electricity through CHP (E1) and into biomethane through
gasification (M1) appear equally beneficial under current condi-
tions, M1 becomes more beneficial when power grids are cleaner.
Another sensitivity analysis on transportation distance was also con-
ducted (Supplementary Fig. 8). However, a distance ranging from
25 to 150 km negligibly affects results on GHG emissions. Thus, we
Ag. residues
Animal manure
Forest residues
MSW
E1
E2
E3
M1
Eth1
Rd1
Bj1
Bj2
E1
E2
E3
E4
M1
M2
E1
E2
E3
M1
Eth1
Rd1
Rd2
Bj1
Bj2
Bj3
Bj4
Bj5
Bj6
E1
E2
E3
E4
M1
M2
Eth1
Rd1
Rd2
Bj1
Bj2
Bj3
Bj4
Bj5
Bj6
−1.5
−1.0
−0.5
0
0.5
1.0
tCO2e per Mg ww
Cleaner power (−50% carbon intensity)
Current state power grids
Fossil rollback (+50% carbon intensity)
Fig. 2 | Sensitivity analysis of emission estimates. Electricity pathways: E1—CHP, E2—gasification + CHP, E3—integrated gasification combined cycle,
E4—anaerobic digestion + CHP. Methane pathways: M1—gasification, M2—anaerobic digestion. Ethanol pathway: Eth1—enzymatic hydrolysis +
fermentation. Renewable diesel pathways: Rd1—gasification + FT synthesis, Rd2—pyrolysis + hydroprocessing. Bio jet fuel pathways: Bj1—alcohol-to-jet
(ethanol), Bj2—sugar-to-jet (fermentation), Bj3—pyrolysis (in situ), Bj4—pyrolysis (ex situ), Bj5—HTL (in situ), Bj6—HTL (ex situ).
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assumed 150 km as the transportation distance in order to provide
conservative estimates for net energy gain as well as GHG emissions.
Maximizing aggregate energy and climate benefits. We next
describe the maximum energy and climate benefits achievable at a
national scale through optimal utilization of waste biomass gener-
ated in each county within the United States taking into account
spatial variation in the electricity mix. As noted earlier, about
233 Mt of dry waste resources is available annually in the contigu-
ous United States16. The spatial distribution of this total resource
base is depicted in Supplementary Figs. 1 and 2. Approximately 25%
of this total is concentrated in 115 counties, 50% is in 374 coun-
ties and 75% is in 884 counties (Supplementary Figs. 1 and 2 and
Supplementary Note 1). Agricultural states in the Pacific West, the
Midwest and the South in general stand out with more agricultural
residues than other regions. Counties in the Mountain West and the
South are endowed with substantial forest residues. The availability
of animal manure corresponds to livestock and poultry production,
which is concentrated in California and the Midwest. The avail-
ability of MSW is concentrated in densely populated regions such
as Southern California, Florida and parts of the Northeast. Overall,
however, some of the largest metropolitan areas stand out in terms
of the availability of total waste resources.
Searching for the conversion pathway that is optimal with respect
to all three criteria—renewable energy, net energy and GWP—we
find that, except in rare instances, no single pathway exists for any
given type of waste across all US counties and states (Table 2). Across
different types of agricultural residue, CHP (E1) consistently stands
out with respect to all three objectives for a substantial fraction of
counties and states. For animal manure, no single pathway satis-
fies all three objectives. For forest residues and municipal wastes,
optimal conversion pathways that satisfy all three objectives vary by
specific waste feedstocks. The percentage of locations where there is
a single optimal pathway varies substantially.
Since a single pathway that achieves all three objectives for any
given waste feedstock across locations is lacking, there is a need to
consider three distinct scenarios of optimal use of biomass wastes—
maximum energy production (MEP), maximum net energy (MNE)
and maximum emission reduction (MER). For each county in the
United States, we first select the conversion pathway for each type
Table 2 | Synergies between renewable energy, net energy and GWP at the county and state levels
Waste type
Feedstock
Total number
of counties
with feedstock
available
All three criteria aligned
Total number
of states with
feedstock
available
All three criteria aligned
Optimal
pathway
Number of
counties
Percentage
(%)
Number of
states
Percentage
(%)
Ag. residues
Barley straw
136
52
38
14
5
36
E1
Citrus residues
118
53
45
9
3
33
E1
Corn stover
1,276
793
62
36
22
61
E1
Cotton gin trash
815
329
40
17
6
35
E1
Cotton residues
796
305
38
17
6
35
E1
Non-citrus residues
1,686
795
47
48
20
42
E1
Oat straw
12
4
33
2
1
50
E1
Rice hulls
144
77
53
6
3
50
E1
Rice straw
148
80
54
6
3
50
E1
Sorghum stubble
191
161
84
9
6
67
E1
Sugarcane bagasse
29
11
38
3
2
67
E1
Sugarcane trash
29
11
38
3
2
67
E1
Tree-nut residues
620
234
38
40
14
35
E1
Wheat straw
696
207
30
32
11
34
E1
Animal manure
Hogs, 1,000+ head
934
0
0
37
0
0
—
Milk cows, 500+ head
639
0
0
44
0
0
—
Forest residues
Primary mill residues
488
178
36
44
12
27
E1
Secondary mill
residues
2,418
590
24
49
11
22
E1
Other forest residues
1,256
588
47
35
15
43
E1
Other forest thinnings
304
96
32
11
5
45
E1
MSW
CD waste
3,109
0
0
49
0
0
—
Food waste
2,792
0
0
48
0
0
—
MSW wood
3,109
2,487
80
49
39
80
Bj5
Paper and paperboard
3,109
0
0
49
0
0
—
Plastics
3,109
0
0
49
0
0
—
Rubber and leather
3,109
0
0
49
0
0
—
Textiles
3,109
0
0
49
0
0
—
Yard trimmings
3,066
0
0
49
0
0
—
Other MSW
3,109
0
0
49
0
0
—
Note: E1—CHP; Bj5—HTL (in situ).
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Analysis
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of waste under each of the three scenarios. The national results
are the aggregation of county-level results. The calculations are
described in Methods and results are depicted in Table 3 and Fig.
3. Scenario results suggest that there is substantial benefit from uti-
lizing wastes and biomass residues to either displace energy pro-
duction or reduce GHG emissions or both. As one would expect,
MEP results in the highest potential of renewable energy produc-
tion, which totals 3.8 EJ—3.7% of total US energy demand in 2016
(ref. 46), and MER results in the highest potential of emissions
reduction, 178 MtCO2e—2.7% of total US GHG emissions in 2016
(ref. 47). The MNE scenario indicates the highest potential of net
energy as well as a moderate amount of emissions reduction (75% of
MER). A breakdown of scenario results by waste feedstock reveals
the preferred conversion pathways under each of the three scenar-
ios (Supplementary Table 4). CHP (E1) is the preferred option for
agricultural resides under both the MEP and MNE scenarios, while
either CHP (E1) or gasification (M1) may maximize GHG emis-
sion reduction depending on specific feedstock. For dairy manure,
CHP (E1) is the preferred option that maximizes renewable energy
production, but anaerobic digestion to biomethane (M2) maximizes
both the net energy gains and climate benefits. For forest residues,
CHP (E1) results in the largest amount of renewable energy and
net energy gain, while either hydrothermal liquefaction (HTL) with
in situ hydrogen production (Bj5) or gasification (M1) maximizes
GHG emission reduction. In contrast to other categories of wastes,
optimal use of MSW feedstocks would require a greater number of
conversion technology pathways depending on specific feedstock.
Non-biogenic carbon in MSW is concentrated in three feedstocks—
plastics, rubber and leather, and textiles. Thus, the non-biogenic
carbon is immediately emitted into the atmosphere when process-
ing these feedstocks instead of being stored in landfills. While the
inclusion of biogenic CO2 reduces net GWP for forest residues and
MSW (Fig. 1c,d), it does not change the ranking of conversion path-
ways under the three scenarios.
The county-level distribution of renewable energy production,
net energy gain and its associated climate benefits also indicates
that most counties would lose a relatively small amount of energy
production potential from MEP to MER, while most coun-
ties would see a greater increase in terms of emission reduction
(Fig. 3). Maximizing energy production would result in negative
net energy in 125 counties and emission increase in 532 counties
(Fig. 3b,c). Therefore, maximizing either net energy or emission
reduction would lead to better utilization of wastes and residues
relative to maximizing renewable energy. Given that the terms
renewable energy and clean energy tend to often be used inter-
changeably by policy makers, this analysis shows that there exist
potential trade-offs between different criteria relevant to sustain-
able development.
Conclusions
Maximizing the benefits of waste conversion requires attention to
first the life-cycle implications of different technology pathways,
second the spatial distribution of waste feedstocks, and third the
local conditions under which waste feedstocks will be processed.
The policy insight that emerges from this analysis is that national
mandates such as the US Renewable Fuel Standard might not
maximize even renewable energy production let alone environ-
mental benefits. Likewise, renewable portfolio standards, a widely
employed policy in the electricity sector, could lead to suboptimal
use of waste biomass. In the literature, bioenergy and biofuel poli-
cies have been analysed mainly from the perspective of climate-
change mitigation, food security or cost, but this analysis shows that
Table 3 | Total renewable energy production, net energy gain
and GWP across scenarios
Policy
scenarios
Renewable
energy
production
Net
energy
gain
GWP
EJ
Index
(%)
EJ
Index
(%)
MtCO2e
Index
(%)
MEP
3.8
100
2.9
89
−103
58
MNE
3.7
96
3.2
100
−133
75
MER
3.1
81
2.4
76
−178
100
TJ
<100
100–500
500–1,000
1,000–2,000
2,000–5,000
5,000–10,000
10,000–20,000
20,000–40,000
>40,000
Renewable energy production—MEP scenario
a
TJ
<–1,000
–1,000–0
0–500
500–1,000
1,000–2,000
2,000–5,000
5,000–10,000
10,000–20,000
>20,000
TJ
<–1,000
–1,000–0
0–500
500–1,000
1,000–2,000
2,000–5,000
5,000–10,000
10,000–20,000
>20,000
TJ
<–1,000
–1,000–0
0–500
500–1,000
1,000–2,000
2,000–5,000
5,000–10,000
10,000–20,000
>20,000
Net energy—MEP scenario
b
ktCO2e
<−1,000
−1,000 to −500
−500 to −200
−200 to −100
−100 to −50
−50 to 0
0 to 50
50 to 200
>200
ktCO2e
<−1,000
−1,000 to −500
−500 to −200
−200 to −100
−100 to −50
−50 to 0
0 to 50
50 to 200
>200
ktCO2e
<−1,000
−1,000 to −500
−500 to −200
−200 to −100
−100 to −50
−50 to 0
0 to 50
50 to 200
>200
GWP (w. biogenic CO2)—MEP scenario
c
TJ
<100
100−500
500−1,000
1,000−2,000
2,000−5,000
5,000−10,000
10,000−20,000
20,000−40,000
>40,000
Renewable energy production—MNE scenario
d
Net energy—MNE scenario
e
GWP (w. biogenic CO2)—MNE scenario
f
TJ
<100
100−500
500−1,000
1,000−2,000
2,000−5,000
5,000−10,000
10,000−20,000
20,000−40,000
>40,000
Renewable energy production—MER scenario
g
Net energy—MER scenario
h
GWP (w. biogenic CO2)—MER scenario
i
Fig. 3 | County-level renewable energy production, net energy and emissions. a–c, The MEP scenario. d–f, The MNE scenario. g–i, The MER scenario.
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705

Analysis
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they also do not optimize energy production. From a methodologi-
cal perspective, this analysis illustrates the value of combining LCA
with spatial analytical techniques for multicriterion assessment of
alternative conversion pathways and the identification of hotspots
for the refinement of existing energy policies. Indexing volumetric
targets and mandates as well as financial subsidies for renewable
energy to life-cycle emission-based performance measures will lead
to more sustainable use of wastes and biomass residues.
This study is a first step towards using a common system bound-
ary for a consistent comparison of a large variety of waste conver-
sion technologies from the twin perspectives of net energy gain and
climate benefits. Incorporating non-GHG environmental consider-
ations including air quality impacts and freshwater use and water
quality impacts, as well as an assessment of the levelized life-cycle
cost of energy for the different pathways, are two important direc-
tions for future research.
Methods
An overview of conversion technology pathways. The 15 conversion technology
pathways included in this study can be categorized into five groups: electricity
pathways (E1–E4), methane pathways (M1, M2), an ethanol pathway (Eth1),
renewable diesel pathways (Rd1, Rd2) and bio jet fuel pathways (Bj1–Bj6). Details
of the conversion pathways including process description, feedstock feasibility,
energy inputs and outputs, coproducts, displaced products and references are
presented in Table 1.
Approach to energy and emission accounting. We conducted an LCA to estimate
the energy balances and GHG emissions associated with the conversion of a given
feedstock to the final energy product(s) in each county. The different phases
of the life cycle that are accounted for include collection of waste, transport to
the conversion facility, processing (including pretreatment), transmission and
distribution, and end use (Supplementary Note 2 and Supplementary Fig. 3).
Thornley et al. showed that different functional units would result in varying
outcomes when comparing alternative uses of biomass, and the functional unit
should correspond to “the actual nature of the research questions”48. Since this
study mainly focuses on the optimal use of wastes, the functional unit of this LCA
is thus 1 Mg of wet waste.
Energy and emissions from collection and transport of feedstock are estimated
on the basis of this activity requiring heavy-duty diesel trucks. Feedstock-specific
technology data (including lower heating values, moisture content, non-biogenic
carbon content, energy inputs and outputs by the conversion pathway) were
collected from the literature to calculate energy and emission flows in each phase
as well as the overall net energy gains15,39,42,49–52. Table 1 shows additional data
sources. Losses during transmission and distribution were taken into account.50
Emissions associated with the provision of energy inputs were based on life-cycle
emission intensities of electricity generation and other fossil-based fuel production
(heat, natural gas, diesel, hydrogen)53–55. Emission intensities of the production of
electricity and fossil-based fuels vary geographically, and variation across states
in such emission intensities was taken into account (Supplementary Note 3 and
Supplementary Table 1). Life-cycle GHG emission intensities of state power grids
were estimated by multiplying a state’s generation mix from the Emissions &
Generation Resource Integrated Database with life-cycle GHG emission intensities
of respective electricity generation technologies from the LCA Harmonization
project56,57. The GWP for non-CO2 GHG is based on IPCC Fifth Assessment
Report 100-year conversion factors58.
Comparing the burdens associated with converting a given feedstock to
different end products does not, however, paint a complete picture of the benefits
of choosing one conversion pathway over another. The ultimate environmental
benefit of any given pathway is also a function of the process(es) or product(s)
that it displaces. For instance, if conversion of manure to renewable natural gas
for pipeline injection entails more GHG emissions relative to conversion to biogas
for on-site power generation, it is plausible that the former is more beneficial
if electricity from biogas displaces clean electricity while renewable natural gas
displaces diesel used in trucks or displaces fossil natural gas. Supplementary
Fig. 4 illustrates a simple schematic representation of this concept. Posen et al.
illustrate this idea in the context of converting cellulosic biomass to ethanol and
displacing gasoline vis-à-vis producing bioethylene and displacing fossil-fuel-
derived ethylene59. For the handling of coproducts, we chose the displacement
method over allocation methods based on energy or economics for the following
reasons. First, the International Standards Organization advocates the use of the
displacement method60 and it has been adopted as the default method in many
LCA models and in biofuel regulation development in the United States. Second,
many pathways yield a number of different types of energy product—electricity,
heat, methane and/or liquid fuels. The conventional products to be displaced can
easily be defined. Third, the distinction between main product and coproducts in
this study is mainly to categorize the pathways into five groups. We intended to
examine the conversion pathways from a systems perspective, that is, all types of
energy product through each conversion pathway instead of the main products
only. The displacement method represents the idea of system expansion and is
more suitable for our analysis. Fourth, the characteristics (utility, energy form
and so on) of electricity are different from those of other types of energy product,
and so are those of each other type of energy product. Allocation simply based
on energy content may result in distorted results. In addition, the price ratios
for an economic allocation may be challenging, as some of the energy products
from waste conversion may be non-commoditized and the prices may fluctuate
and vary greatly by geographic location. Net GHG emissions were calculated by
subtracting displaced emissions from the life-cycle emissions of each conversion
pathway. Biogenic CO2 emissions are included throughout life cycles. The GWP
of biogenic CO2 emissions was estimated by multiplying the GWPbio indices by
biogenic CO2 emissions. Additional details on the method and data sources for
biogenic CO2 emissions are listed in Supplementary Note 4 and Supplementary
Table 2. Thus, the net GWP of a given feedstock converted through a given
pathway is equivalent to the sum of net GHG emissions and the GWP of biogenic
emissions. Emissions and energy related to material use (such as enzymes and
catalysts) are not included in the analysis.
The basic county-level calculations we performed in order to assess the
potentials of energy production and life-cycle GWP are the following:
∑
=
−
EP
WW
(EO
(1 TD ))
(1)
i j c
i c
k
i j k
k
, ,
,
, ,
∑
=
−
+
+
(
)
E
E
D
NE
EP
WW
EI
(2)
i j c
i j c
i c
l
i j l
i
, ,
, ,
,
, ,
collection,
transport
1
∑
=
+
+
+
+
+
+
−
E
E
D
W
D
GWP
WW (
)
EmissI
(EI
EmissI ))
Emiss
EmissI
Emiss
GWP
EP
EmissI
(3)
i j c
i c
i
c
l
i j l
l c
i j k
c
i
i j k
m c
, ,
,
collection,
transport
1
diesel,
, ,
,
process
, ,
diesel,
2
enduse
bioCO2
, ,
,
=
GWP
GWP
Emiss
(4)
i
i
i
bioCO2
bio,
bioCO2,
where EPi,j,c is the renewable energy production (MJ) of feedstock i through
conversion pathway j in county c; WWi,c the wet weight (kg) of feedstock i in
county c; EOi,j,k energy output k (MJ kg−1) of feedstock i through conversion
pathway j; TDk the transmission and distribution loss of energy output k (6.5%
assumed for electricity, 20% for heat and 2% for methane), NEi,j,c the net energy
(MJ) of feedstock i through conversion pathway j in county c; EIi,j,l energy input
l (MJ kg−1) of feedstock i through conversion pathway j; GWPi,j,c the net GWP
(gCO2e) of feedstock i through conversion pathway j in county c; Ecollection,i the
energy consumption rate (MJ kg−1) of collecting feedstock i; Etransport the energy
consumption rate (MJ kg−1 km−1) of transporting feedstock i to the conversion
facility, D1 the transport distance (km) from the temporary storage or collection
site to the conversion facility (150 km assumed), EmissIdiesel,c the life-cycle GHG
emission intensity (gCO2e MJ−1) of petroleum-based diesel in county c, EmissIl,c
the life-cycle GHG emission intensity (gCO2e MJ−1) of energy input l in county c,
Emissprocess the direct GHG emissions (excluding biogenic CO2) during processing,
Wi,j,k the physical weight (kg) of energy output k of feedstock i through conversion
pathway j; D2 the transport distance (km) for distribution (150 km assumed),
Emissenduse the direct GHG emissions (excluding biogenic CO2) during end use,
GWPi
bioCO2 the GWP (gCO2e) of biogenic carbon in feedstock i, EPi,j,k the energy
production (MJ) of output k of feedstock i through conversion pathway j; EmissIm,c
the life-cycle GHG emission intensity (gCO2e MJ−1) of energy product m (which
output k can substitute) in county c, GWPbio,i the biogenic CO2 global warming
index with full impulse response functions for feedstock i and Emissbioco2,i the
biogenic CO2 emissions of feedstock i.
For the comparison of conversion pathways, county-level results were first
aggregated to the national level and by feedstock. Weighted averages (by weight) of
results by feedstock in each of the four broader categories of waste resources were
calculated for the comparison by waste type (as shown in Fig. 1). For the current
management of wastes and residues (that is, BAU practices in Fig. 1), we used the
same emission accounting method and life-cycle framework to estimate the GWP
(Supplementary Note 5 and Supplementary Table 3).
Sensitivity analysis. A sensitivity analysis of net GHG emissions was conducted
to explore the impacts of the emission intensity of current state power grids and
transportation distance. For the sensitivity analysis on electricity, two additional
electricity generation scenarios were constructed: ‘cleaner power’—assuming
a 50% reduction in emission intensity of power grids in all states; and ‘fossil
rollback’—assuming a 50% increase in emission intensity of power grids in all
states. In addition, a range of 25–150 km was examined to test the sensitivity to
transportation distance.
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706

Analysis
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Technical availability of waste resources. County-level waste availability data
were obtained from the base-year estimates under the reference scenario in the US
Department of Energy’s BT16. BT16 estimates the biophysical potential, spatial
distribution, economic constraints and environmental impacts associated with
existing and potential biomass resources16. Waste resources included in this study
comprise four types of waste: agricultural residues (14 feedstocks, including both
primary and secondary agricultural residues as defined in BT16), animal manure
(2 feedstocks), forest residues (4 feedstocks) and MSW (9 feedstocks, including
food waste). Technical availability was defined as the maximum potential of waste
resources without taking into account feedstock costs. BT16 reports dry weight of
waste feedstocks, and wet weight was calculated with moisture content for a more
precise estimation of energy consumption and emissions during the collection and
transport stages.
Scenario analysis. To explore the optimal utilization of waste biomass resources,
we developed three alternative scenarios: MEP, MNE and MER. For all scenarios,
the optimal conversion pathway for each feedstock was selected on the basis of the
maximum value of energy or emission reduction. Under each scenario, the county-
level results were then added up to obtain the potentials for total renewable energy
production, net energy and emission reduction at the national level.
Data availability
The data that support the findings of this study are available at https://github.com/
labyseson/Waste-LCA
Code availability
Codes for energy and emission accounting as well as data visualization are available
at https://github.com/labyseson/Waste-LCA
Received: 30 November 2018; Accepted: 6 June 2019;
Published online: 22 July 2019
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Acknowledgements
This study would not have been possible without financial support from the UCLA
Grand Challenges—Sustainable LA programme.
Author contributions
D.R. conceived and designed the study, guided data collection, modelling and analysis
and co-wrote the manuscript. B.L. contributed to the study design, collected the data,
conducted the modelling and analysis and co-wrote the manuscript.
Competing interests
The authors declare no competing interests.
Additional information
Supplementary information is available for this paper at https://doi.org/10.1038/
s41560-019-0430-2.
Reprints and permissions information is available at www.nature.com/reprints.
Correspondence and requests for materials should be addressed to D.R.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
© The Author(s), under exclusive licence to Springer Nature Limited 2019
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    Policy Brief:

Answer:
**The United States can generate up to 3.2 EJ of energy annually from waste**

**Policy Problem**Wastes and biomass residues can be used to derive a number of alternative useful products through different conversion pathways and are widely available and replenishable. The various conversion pathways are currently at different stages of technical and economic maturity. Identifying the optimum product to derive or pathway to use based on varying goals from emission reduction to economic efficiency is complex. From a policy perspective, it is important to understand what factors determine the energy and climate benefits of waste conversion, the potential aggregate energy and climate benefits of waste conversion, which pathways simultaneously maximize energy and climate benefits, and how this varies given the differing availability and composition of waste in differing locations. Such information is needed to design policies that lead to the best use of biomass resources while mitigating unintended negative consequences.

**Scientific Research Findings**We find that the type and quantity of energy consumed during biomass processing and the environmental footprint of the displaced products are key to determining the most environmentally beneficial use of any given biomass resource. We estimate that the utilization of all available wastes and biomass residues in the contiguous US can generate 3.1–3.8 EJ of renewable energy but deliver only 2.4–3.2 EJ of net energy gain if energy generation is maximized, and displace 103–178 million tonne CO2e of Greenhouse Gas (GHG) emissions. For any given waste feedstock, looking across all US counties where it is available, no single conversion pathway simultaneously maximizes renewable energy production, net energy gain and GHG mitigation except in rare instances. Maximizing the energetic and environmental benefits of waste conversion requires a life cycle assessment based of different technology pathways taking into consideration the spatial distribution of biomass resources and local conditions (such as the electricity mix).

**Scientific Research Study Methods**This analysis compares the energy and climate benefits of a large set of feasible technology pathways for energy recovery from waste from a systems perspective — using a life cycle assessment with a consistent system boundary and region-varying inputs. This analysis quantifies life cycle GHG emissions and energy production for 15 conversion pathways and 29 waste feedstocks at both the county and national levels in the US. It also identifies the most efficient pathways for utilizing each distinct type of waste and biomass residue with respect to renewable energy production, net energy gain or GHG emissions reduction. In addition, it estimates the aggregate energy and climate benefits when all available wastes and biomass residues across the contiguous United States are dedicated for specific policy objectives.

**Policy Implications**• Maximizing either net energy or emissions reduction from waste-to-energy generation would lead to better utilization of wastes and residues relative to simply maximizing the quantity of renewable energy.
• National-scale mandates on specific types of bioenergy or biofuels could lead to inefficient use of biomass resources.
• Complementing renewable fuel targets with GHG taxes or life cycle emissions-based performance standards would lead to better outcomes in terms of clean energy production and emissions reduction.