Environmental Research Letters
Does replacing coal with wood lower CO2 emissions? Dynamic lifecycle
analysis of wood bioenergy
To cite this article: John D Sterman et al 2018 Environ. Res. Lett. 13 015007
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Environ. Res. Lett. 13(2018) 015007
Does replacing coal with wood lower CO2 emissions?
Dynamic lifecycle analysis of wood bioenergy
29 August 2017
John D Sterman1,4
, Lori Siegel2 and Juliette N Rooney-Varga3
MIT Sloan School of Management, 100 Main Street, Cambridge, MA 02139, United States of America
1 December 2017
Climate Interactive, 1201 Connecticut Avenue NW, Suite 300, Washington, DC, 20036, United States of America
UMass Lowell Climate Change Initiative and Deptartment of Environmental, Earth, and Atmospheric Sciences, 265 Riverside Street,
4 January 2018
Lowell, MA 01854, United States of America
Author to whom any correspondence should be addressed.
18 January 2018
E-mail: jsterman@mit.edu
Original content from
Keywords: bioenergy, biofuels, wood pellets, greenhouse gas emissions, climate change, system dynamics
this work may be used
under the terms of the
Supplementary material for this article is available online
Creative Commons
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of this work must
maintain attribution to
Bioenergy is booming as nations seek to cut their greenhouse gas emissions. The European Union
the author(s) and the
title of the work, journal
declared biofuels to be carbon-neutral, triggering a surge in wood use. But do biofuels actually reduce
citation and DOI.
emissions? A molecule of CO2 emitted today has the same impact on radiative forcing whether it
comes from coal or biomass. Biofuels can only reduce atmospheric CO2 over time through
post-harvest increases in net primary production (NPP). The climate impact of biofuels therefore
depends on CO2 emissions from combustion of biofuels versus fossil fuels, the fate of the harvested
land and dynamics of NPP. Here we develop a model for dynamic bioenergy lifecycle analysis. The
model tracks carbon stocks and fluxes among the atmosphere, biomass, and soils, is extensible to
multiple land types and regions, and runs in1s, enabling rapid, interactive policy design and
sensitivity testing. We simulate substitution of wood for coal in power generation, estimating the
parameters governing NPP and other fluxes using data for forests in the eastern US and using
published estimates for supply chain emissions. Because combustion and processing efficiencies for
wood are less than coal, the immediate impact of substituting wood for coal is an increase in
atmospheric CO2 relative to coal. The payback time for this carbon debt ranges from 44-104 years
after clearcut, depending on forest type—assuming the land remains forest. Surprisingly, replanting
hardwood forests with fast-growing pine plantations raises the CO2 impact of wood because the
equilibrium carbon density of plantations is lower than natural forests. Further, projected growth in
wood harvest for bioenergy would increase atmospheric CO2 for at least a century because new
carbon debt continuously exceeds NPP. Assuming biofuels are carbon neutral may worsen
irreversible impacts of climate change before benefits accrue. Instead, explicit dynamic models should
be used to assess the climate impacts of biofuels.
1. Introduction
Stupak et al 2007). The United Kingdom subsidizes
wood pellets for electric power generation and has
Limiting global warming to no more than 2 C requires
become the world’s largest pellet importer
large, rapid cuts in fossil fuel consumption by mid-
et al 2017). The US federal government and a number
century (Figueres et al 2017, IPCC 2014). In response,
of US states are considering whether to declare wood
governments around the world are promoting biomass
fuels carbon-neutral or to promote their use (Corn-
to reduce their greenhouse gas (GHG) emissions. The
wall 2017), while at COP23 in Bonn ‘China and 18
European Union declared biofuels to be carbon-neutral
other nations representing half the world’s population
to help meet its goal of 20% renewable energy by
saidthey planned to increase the use of wood...to gen-
2020, triggering a surge in use of wood for heat and
erate energy as part of efforts to limit climate change’
electricity (European Commission 2003, Leturcq 2014,
(Biofuture Platform 2017, Doyle and Roche 2017).
© 2018 The Author(s). Published by IOP Publishing Ltd
Environ. Res. Lett. 13 (2018) 015007
But do biofuels actually reduce GHG emissions?
Dynamic analysis is required to answer the second
The appeal is intuitive: fossil fuels inject carbon
question (e.g. Helin et al 2013). The carbon cycle and
sequestered in geological reservoirs for millions of years
climate impacts of bioenergy involve multiple stocks
into the atmosphere, where it accumulates and causes
of carbon (e.g. in biomass, soils and dead organic
global warming (IPCC 2013). In contrast, biofuels recy-
matter, and the atmosphere) and the processes that
cle carbon from the atmosphere, helping to keep fossil
control the flow of carbon among those stocks includ-
carbon in the ground (IPCC 2013).
ing NPP, transfer of carbon from biomass to soil,
However, a molecule of CO2 added to the atmo-
decomposition of organic matter, consumption and
sphere today has the same impact on radiative forcing
respiration of carbon in biomass and soils, etc. Tools
and warming whether it came from coal millions of
are needed to assess the dynamic climate impact of
years old or biomass grown last year. Biofuels can only
bioenergy over policy-relevant time horizons. Because
reduce atmospheric CO2 over time by increasing net
of the uncertainty and debate over the impacts of biofu-
primary production (NPP) above what it otherwise
els, such tools should allow users to examine alternative
would have been (DeCicco 2013). Assessing the climate
assumptions and scenarios easily and quickly, and
impact of wood and other biofuels therefore depends
would avoid the need to use static summary metrics
on two critical questions: first, at the point of combus-
such as global warming potentials (GWP) and con-
tion, do biofuels generate more or less CO2 per unit of
tentious debate over the appropriate time horizon for
end-use energy than fossil fuels? Second, what are the
these approximations, e.g. whether to use GWP20 or
dynamics of biomass (re)growth and how do NPP and
GWP100 (Ocko et al 2017).
carbon fluxes from biomass and soils depend on the
To address this need we developed an interactive
fate of the harvested land?
decision-support model that enables policymakers and
Confusion over these questions has caused the sci-
other stakeholders to explore the dynamic impact of
entific debate over the climate impact of bioenergy and,
biofuels on carbon emissions and climate. The model
especially wood, to remain ‘contentious’ (Creutzig et al
is fully documented, freely available, runs in about a
2015, Ter-Mikaelian et al 2015). The wood industry
second on ordinary laptops and is extensible to any
and many governments promote wood as a renewable,
number of land use categories and spatial scales. Users
carbon-neutral fuel, while many environmental groups
receive immediate feedback on the impacts of their sce-
oppose wood bioenergy because it causes deforesta-
narios and assumptions. Here we describe the model
tion, harming natural carbon sinks, ecosystems, and
and use it to explore the dynamics of substituting
biodiversity (Cornwall 2017). Advocates emphasize a
wood for coal in electric power production, using wood
long time horizon to evaluate the impact of biofu-
sourced from a range of forest types in the US to esti-
els, a century or more, by which time it is assumed
mate model parameters governing NPP and carbon
forests will regrow, offsetting initial emissions. Oppo-
nents point to the potential for wood energy to increase
CO2 levels in the short run, incurring a ‘carbon debt’
that can only be paid off slowly, and worry that the
2. Methods
resulting increase in atmospheric CO2
will worsen
global warming and lead to irreversible impacts before
2.1. Model structure
the benefits of new growth can occur (Brack 2017,
We build on the widely-used C-ROADS climate policy
Buchholz et al 2016, Cornwall 2017).
model (Sterman et al 2012, Sterman et al 2013), devel-
Life cycle analysis is commonly used to answer
oping a more detailed representation of land use, the
the first question. Results vary with the assumed sys-
carbon stocks associated with different types of land
tem boundary and biofuel harvesting, processing and
and the fluxes arising from them. C-ROADS is a mem-
transport methods (e.g. Buchholz et al 2016). How-
ber of the family of simple climate models, consisting
ever, although wood has approximately the same
of a system of differential equations representing the
carbon intensity as coal (0.027 vs. 0.025 tC GJ−1 of pri-
carbon cycle, budgets and stocks of GHGs, radiative
mary energy; see supplementary material), combustion
forcing and the heat balance of the Earth. C-ROADS
efficiency of wood and wood pellets is lower (Nether-
closely replicates GHG concentrations, global mean
lands Enterprise Agency; IEA 2016). Estimates also
surface temperature, and other climate metrics from
suggest higher processing losses in the wood supply
1850, and matches CMIP5 model projections through
chain (Röder et al 2015). Consequently, wood-fired
2100 across a wide range of Representative Concen-
power plants generate more CO2 per kWh than coal
tration Pathways (RCPs) (Knutti and Sedlacek 2013,
(supplementary table S5 available at stacks.iop.org/
Vuuren et al 2011). C-ROADS has been used by pol-
ERL/13/015007/mmedia ). Burning wood instead of
icymakers (Sterman et al 2012) and is freely available
coal therefore creates a carbon debt—an immedi-
(www.climateinteractive.org ).
ate increase in atmospheric CO2 compared to fossil
The carbon cycle in the original C-ROADS model
energy—that can be repaid over time only as—and
includes globally aggregated stocks of carbon in fossil
if— NPP rises above the flux of carbon from biomass
fuels, the atmosphere, terrestrial biomass and soils, and
and soils to the atmosphere on the harvested lands.
a four-layer ocean. Here we disaggregate the treatment
Environ. Res. Lett. 13(2018) 015007
C in Atmosphere
Net Flux C
CH4 From
CO2 From
C to Atm
CH4 From
CO2 From
from Atm to
Net Primary
CO2 from
Respiration &
Respiration &
from Fossil
Respiration &
Respiration &
Fire, Soils to
Fire, Soils to
Fire, Biomass
Fire, Biomass
Atm u,r
Atm u,r
to Atm u,r
to Atm u,r
C in Fossil
C in Biomass u,r
C in Soils/Dead Organic Matter u,r
C from
Biomass to
C in Ocean (5
Soil u,r
C in Lumber & Structures
C Biomass to
C Lumber &
Lumber &
Structures to Atm
Structures u,r
Figure 1. Modified carbon cycle in extended C-ROADS model. Carbon in biomass, soils, and structures (e.g. lumber in buildings),
and fluxes among these compartments, are disaggregated by land type, u, and region, r. Carbon can flow from biomass and soils
from each patch, u, r, to the atmosphere as CO2 or CH4. In addition, bioenergy harvest and combustion generate CO2 . CO2 and
CH4 fluxes associated with changes in land use, e.g. from forest to pasture, cropland or developed land are included in the model but
not shown here. On the policy-relevant time scale (e.g. through 2100), creation of new fossil fuels from terrestrial or oceanic carbon
sources assumed to be negligible. Note: as described in the text and supplementary material, CH4 fluxes from biomass and soils are
set to zero for forest scenarios considered here to isolate the impact of bioenergy in the scenarios tested.
of terrestrial carbon stocks both geographically and by
Although the model can be configured for any
land type (e.g. forest, pasture, cropland, developed land,
number of land types and uses, here we focus on wood
etc.). For each region, the model represents the area
harvested for electricity generation. For simplicity, we
of each type of land and changes in land use result-
configure the model to represent one region with three
ing from natural processes and human activity, along
categories of land: unmanaged forest, recently har-
with the carbon stocks and fluxes associated with each.
vested forest, and ‘other,’ which includes all other land
The model is extensible to any number of land/land
use categories (cropland, pasture, developed land, etc.).
use categories and geographic areas. For example, one
could configure the model to represent different types
2.2. Parameter estimation
of forests, with similar disaggregation for other land
Each unit of end-use bioenergy displaces the same end-
types, and at geographic scales from regions to nations
use energy generated from fossil fuels, so net CO2
to, if data are available, even smaller areas.
emissions from biomass at the point of combustion
Figure 1 shows an overview of the carbon cycle
depend on which energy source is more efficient overall,
in the extended model. As in the original model,
given fuel carbon intensity, combustion efficiency, pro-
combustion of fossil fuels injects carbon into the atmo-
cessing losses, and emissions from their supply chains.
sphere. Unlike the original model, carbon stocks in
Typical combustion efficiencies for wood are approx-
biomass and soil are now represented for each cate-
imately 25%, compared to 35% for coal (Netherlands
gory of land and geographical area. The model also
Enterprise Agency 2011, IEA 2016). Published esti-
includes a compartment for carbon stored in lumber
mates vary with the process examined and the system
and structures. Consistent with reporting approaches
boundary considered, but processing losses (in energy
for the IPCC, FAO, and US Forest Service (FAO 2016,
content) for the wood pellet supply chain are on the
Penman et al 2003, Smith et al 2006), biomass in forest
order of approximately 27% if biomass is used in the
land includes living trees, including stems, branches,
drying process (Röder et al 2015), compared to losses
foliage, and coarse roots in both mature and under-
of approximately 11% for coal (IEA 2016). Differences
story trees; the stock denoted ‘soil carbon’ includes soil
in supply chain emissions from extraction/harvest,
organic matter, dead roots, litter (dead foliage, dead
and transportation are uncertain but relatively small
branches, etc), downed and standing dead trees, and liv-
compared to the large differences in combustion and
ing fine roots (Woodall et al 2015). Biomass is increased
processing efficiencies (e.g. Odeh and Cockerill 2008,
by net primary production. Carbon in biomass can
Röder et al 2015). Consequently, wood pellets emit
return to the atmosphere as CO2 or CH4 and is trans-
approximately 0.071 tC more CO2 per GJ of end-use
ferred to the soil stock via litterfall and tree mortality.
energy than coal (see supplementary material).
Carbon is also lost from both biomass and dead organic
The determinants of NPP and carbon fluxes from
matter by fire. Carbon in the soil stock is transferred
biomass and soil to the atmosphere are therefore critical
to the atmosphere through the activity of decom-
toassessing thedynamic impact of bioenergy including
posers and other heterotrophs (Fahey et al 2005). The
the carbon debt payback period and long-run reduc-
supplementary material provides full documentation.
tion in atmospheric CO2. To estimate the parameters
Environ. Res. Lett. 13 (2018) 015007
South Central Oak-Hickory
Soils and Dead Organic Matter
South Central Managed Shortleaf Loblolly
Soils and Dead Organic Matter
Figure 2. Growth curves showing carbon density (tC ha−1) for oak-hickory (top) and managed shortleaf loblolly pine plantations
(bottom) in the south-central US, comparing Smith et al (2006) growth curves (dashed lines with data points) to the model (solid
lines), with best-fit parameters. Supplementary figure S2 and tables S2-S3 show results for all forest types estimated.
governing NPP and these fluxes we use the post-
curves closely: the mean absolute error relative to the
harvest growth curves in Smith et al (2006), which
mean ranges from 0.008%-0.065% for biomass and
span many regions and species in US forests. To illus-
from 0.006%-0.074% for soils (figure 2, table S2).
trate, figure 2 shows the Smith et al growth curves
for south-central US oak-hickory forest and managed
shortleaf loblolly pine plantations. The growth patterns
3. Results
differ markedly in both their shape and time required to
reach maximum biomass. After harvest, the managed
In the scenarios below, we adopt assumptions that
loblolly plantation regrows quickly, following a classic
favor bioenergy. Specifically, we assume bioenergy
S-shaped curve and reaching maximum biomass after
from wood pellets is used to offset coal, the most
about three decades, while the hardwood forest grows
carbon intensive fossil fuel; if wood offsets power gen-
roughly linearly for about 50 years and is still growing
erated from natural gas its carbon debt would be much
after a century. Note that in both cases, soil carbon
larger. Estimates of net CH4 fluxes from forest biomass
declines for several decades after harvest because the C
and soils are poorly constrained and considered to
flux from biomass to soils is cut while heterotrophic
be insignificant in most global methane budgets (e.g.
respiration continues to release C from soils and dead
Ito and Inatomi 2012, Saunois et al 2016, Shoemaker
organic matter to the atmosphere.
et al 2014); we therefore assume them to be zero. We
To model NPP we specify a variant of the Richards
assume all land harvested for bioenergy is allowed
(1959) growth model, widely used in forest growth
to regrow without any fire (Buchholz et al 2016),
modeling. The US wood pellet industry is growing
erosion, disease, unplanned logging, or other ecolog-
rapidly, and much of the production is exported to
ical disturbances, including climate change impacts,
the EU and UK. We therefore estimate the carbon
that could limit regrowth or inject GHGs into the
cycle parameters from growth curves for temperate US
atmosphere beyond the direct impact of the bioen-
forests reported by Smith et al (2006). We estimate the
ergy harvest. We further assume that the decline in
parameters of NPP jointly with those governing fluxes
coal use resulting from wood does not lower coal
of CO2 from biomass to soil and from each compart-
prices, increasing coal demand elsewhere, an effect
ment to the atmosphere using nonlinear least squares
estimated to be large (e.g. York 2012).
and Markov Chain Monte Carlo methods (supplemen-
To isolate the dynamic impact of bioenergy on CO2
tary material). The model fits the Smith et al growth
emissions we run the model from an initial equilibrium
Environ. Res. Lett. 13(2018) 015007
Figure 3. Change in atmospheric CO2 concentration resulting from displacement of coal by wood. Δ[CO2] is relative to continued
coal use. All scenarios show the change in atmospheric CO2 (ppmv) resulting from a single 1 EJ pulse of end-use energy from biomass
used to displace coal in year 0. Top: south-central (SC) oak-hickory forest; bottom: SC managed shortleaf loblolly plantation. The
bioenergy pulse causes an immediate increase in CO2 concentration (the initial carbon debt) in scenarios 2-5 due to lower combustion
and processing efficiencies for wood compared to coal. The year in which Δ[CO2] falls below zero is the carbon debt payback time.
Supplement figure S3 shows the results for all eight forest types examined. S0: Benchmark showing impact of 1 EJ pulse of zero carbon
energy. S1: Bioenergy assumed to have the same combustion and processing efficiency as coal, and the same supply chain emissions;
with 25% of biomass removed from the land harvested through thinning. S2: Actual efficiencies and supply chain emissions for wood
pellets; 25% of biomass harvested through thinning. S3: S2 with 95% of biomass harvested (clear cut). S4: S3 with clear cut and no
regrowth of harvested land and no C released from soil stocks. S5: S4 with C released from soil stocks at the estimated fractional rate.
in which the carbon fluxes from biomass and soils to
electricity generated from coal (total world energy use
the atmosphere are balanced by NPP, and in which net
exceeds 550 EJ yr−1, US EIA 2016).
CO2 flux to the ocean is zero throughout, identifying
Scenario 0 provides a benchmark showing how
the impacts of bioenergy separate from other sources
atmospheric CO2 would change if 1 EJ of end-use
of disequilibrium, e.g. prior logging and marine uptake
energy from coal were offset by a zero-carbon energy
of CO2. Including ocean CO2 uptake would moder-
source, such as solar or wind (and assuming zero
ate increases in atmospheric CO2 from bioenergy but
emissions from the supply chain). Displacing 1 EJ of
worsen ocean acidification and other impacts. These
end-use energy from coal with a zero C alternative
effects are left for future work.
keeps 0.07 GtC of fossil carbon in the ground, imme-
shows the results for a set of sce-
diately and permanently lowering atmospheric CO2 by
narios using parameters estimated for oak-hickory
approximately 0.04 ppm relative to continued coal use.
forest in the south-central US (supplementary fig-
Scenario 1 simulates the counterfactual case in
ure S3, table S7 provide results for all eight forest
which bioenergy is assumed to have the same carbon
types we estimated). All scenarios examine a 1 exa-
emissions per EJ of end-use energy as coal, includ-
joule (EJ) pulse of end-use electric energy generated
ing the same combustion and processing efficiency
from wood pellets in year 0, offsetting 1 EJ of end-use
and supply chain emissions. We assume that 25%
Environ. Res. Lett. 13 (2018) 015007
of the biomass is removed from each hectare of the
should speed the repayment of the carbon debt. As
harvested forest by thinning, not clear cutting, that
expected, atmospheric CO2 initially falls faster in the
the forest is allowed to regrow with no subsequent
plantation case compared to regrowth of the oak-
harvest, fire, disease, or other disturbances. Because
hickory forest. However, the concentration bottoms
emissions are counterfactually assumed to be the same
out after approximately 20 years and then starts to rise,
as coal, there is no immediate change in atmospheric
exceeding the CO2 level when the forest is allowed
CO2. However, as the forest grows back, carbon is
to regrow. The explanation lies in the different maxi-
gradually removed from the atmosphere to biomass
mum carbon densities of the two forest types: loblolly
and soils. After 100 years, the forest has recovered
plantation grows faster but reaches a lower equilib-
enough to lower atmospheric CO2 by 0.026 ppm, still
rium carbon density compared to the unmanaged
34% above the zero C case.
(figure 4), with estimated equilibrium values
Scenario 2 shows the realistic case with the combus-
of 130 tC ha−1 for loblolly plantation vs. 211 tC ha−1
tion efficiency and supply chain emissions estimated for
for oak-hickory. Consequently, although plantations
wood pellets (supplementary table S5), again assuming
grow faster, they do not remove as much C from the
25% of the biomass is harvested by thinning. Because
atmosphere as was lost when the hardwood forest was
production and combustion of wood generate more
harvested, even if allowed to grow to their maximum
CO2 than coal, the first impact of bioenergy use is
biomass and remain unharvested. In reality, planta-
an increase in atmospheric CO2. Regrowth gradually
tions are thinned every few years and harvested about
transfers C from the atmosphere to biomass and soil
every decade (US Forest Service 2000), further lower-
C stocks, leading to a carbon debt payback time of
ing their average C density and increasing atmospheric
52 years; after 100 years CO2 remains 62% above the
CO2. Furthermore, repeated harvests can degrade the
zero C case.
productivity of the soils, lowering NPP. To compen-
Scenario 3 is the same as S2 except we now assume
sate, managed plantations are typically fertilized several
the land is clear cut instead of thinned, with 95% of
times per rotation, increasing N2O emissions that
the biomass removed. Near-complete biomass removal
would further worsen the climate impact of Scenario 6
reflects the growing practice of harvesting whole trees
(Schulze et al 2012).
and residues (branches, litter, etc) (Achat et al 2015). A
The supplementary material reports the 95% con-
95% clear cut requires only 26% as much land as in S2,
fidence intervals (CIs) for the estimated parameters
but the carbon debt payback time increases to 82 years;
(table S4), and sensitivity analysis across the eight
after 100 years CO2 remains 86% above the zero C case.
forest types arising from parameter uncertainty, com-
Scenario 4 shows the impact of assuming that the
puted by Markov Chain Monte Carlo (table S8). The
harvested area is clear cut as in S3 but never allowed to
95% CIs for the carbon debt payback times vary from
regrow, for example, because it is developed, with the
74-110 years for the hardwood species under clear cut
additional assumption that the flux of C from soils and
(Scenario 3) and 11.25-12 years for the managed plan-
dead organic matter to the atmosphere is set to zero.
tations. The supplementary material also reports the
Without regrowth, the carbon debt is never repaid and
long-run CO2 reductions for Scenarios 1-5 (table S7).
atmospheric CO2 remains permanently higher.
For Scenario 3, after 100 years CO2 falls an average of
Scenario 5 is the same as S4 except the flux of C
51% of the maximum possible reduction (the differ-
to the atmosphere from soils and dead organic mat-
ence between the initial carbon debt and the zero-C
ter continues at the original fractional rate. Without
level in Scenario 0) for the forests and 92% for the
regrowth, there is no flux of CO2 from the atmo-
sphere to terrestrial biomass or soils, but continued
The supplementary material also reports sensitivity
C flux from soils to atmosphere, causing CO2 concen-
analysis of combustion efficiencies and supply chain
trations to rise beyond the immediate impact of the
emissions. Clearly, innovation that improves the com-
bioenergy. After a century atmospheric CO2 has risen
bustion and processing efficiencies of wood relative
by 0.076 ppm, 2.3 times more than the initial impact.
to coal reduces the initial carbon debt of wood and
The actual impact of converting harvested forests to
reduces the carbon debt payback time and climate
other uses will likely lie between the results of Scenarios
impacts of wood. However, innovations that improve
4 and 5, but could rise further if conversion of for-
the efficiencies of both fuels yield smaller benefits.
est to other uses increases C fluxes from soils above
For example, combined heat and power systems offer
the values estimated from the Smith et al (2006) data.
substantially higher combustion efficiency than con-
Such an outcome could result from disturbances to
ventional boilers, but would still cause an initial carbon
soils from, e.g. plowing, development, fire or increasing
debt since the combustion and processing efficien-
methanogenesis, all of which we assume to be zero.
cies of wood remain lower than coal in such systems
In Scenario 6 (figure 4) oak-hickory forest is clear
(supplementary figures S56).
cut and replanted as a shortleaf loblolly pine managed
The wood pellet industry is expanding rapidly and
plantation. Loblolly pine grows faster than hardwoods
many projections call for substantial growth through
(figure 2), so intuitively the conversion from unman-
2030 or beyond (IEA 2012, IRENA 2015). Scenario
aged hardwood forest to managed pine plantation
5) shows the impact of linear growth in
Environ. Res. Lett. 13(2018) 015007
Figure 4. Scenario 6: replanting harvested oak-hickory forest after clear cut with managed plantation of shortleaf loblolly pine (south-
central US), compared to allowing the oak-hickory forest to regrow (Scenario 3 in figure 2). Top: change in atmospheric CO2 (ppmv)
resulting from a single 1 EJ pulse of end-use energy from biomass used to displace coal in year. Δ[CO2] is relative to continued coal
use. Bottom: carbon in biomass (tC ha−1). For the first 20 years, faster-growing loblolly pine lowers atmospheric CO2 compared to
regrowth of the oak-hickory forest, but the estimated maximum carbon density of oak-hickory forest is larger than the managed
loblolly plantation (211 vs. 131 tC ha−1, respectively; supplementary table S3). Consequently, the carbon debt is never repaid even if
the loblolly plantation is never harvested. Due to CO2 flux from soils, atmospheric CO2 rises after approximately 20 years, exceeding
the level from regrowth of oak-hickory after approximately 50 years.
Figure 5. Change in atmospheric CO2 concentration resulting from growth in end-use energy supplied by wood, displacing coal.
Δ[CO2] is relative to continued coal use. Scenario 7 (solid line): linear growth in end-use energy supplied by US wood pellet production,
from the 2016 value of 0.028 EJ to 0.28 EJ yr−1 by 2050 and continuing linearly thereafter. Parameters estimated for south-central US
oak-hickory forest, with harvest by clearcut. Scenario 8 (dashed line): the same as S7 except growth in end-use energy supplied by
wood ceases in 2050. Supplementary figure S4 reports results for all forest types considered.
Environ. Res. Lett. 13 (2018) 015007
end-use bioenergy; Scenario 8 is the same except growth
The carbon debt incurred when wood displaces coal
ceases in 2050. Growth in wood supply causes steady
may never be repaid if development, unplanned log-
growth in atmospheric CO2 because more CO2 is
ging, erosion or increases in extreme temperatures,
added to the atmosphere every year in initial car-
fire, and disease (all worsened by global warming) limit
bon debt than is paid back by regrowth, worsening
regrowth or accelerate the flux of carbon from soils to
global warming and climate change. The qualitative
the atmosphere. Further, lower coal prices caused by
result that growth in bioenergy raises atmospheric
the drop in power sector demand may stimulate coal
CO2 does not depend on the parameters: as long as
use elsewhere, offsetting even the potential long-run
bioenergy generates an initial carbon debt, increasing
benefits of bioenergy (e.g. York 2012).
harvests mean more is ‘borrowed’ every year than is
Fifth, counter to intuition, harvesting existing
paid back. More precisely, atmospheric CO2 rises as
forests and replanting with fast-growing species in
long as NPP remains below the initial carbon debt
managed plantations can worsen the climate impact of
incurred each year plus the fluxes of carbon from
wood biofuel. Although managed loblolly pine grows
biomass and soils to the atmosphere. Note further
faster than hardwood, speeding the initial recovery of
that in Scenario 8, CO2 continues to rise for 56 years
forest biomass, the equilibrium carbon density of man-
after bioenergy production growth stops and only falls
aged plantations is lower than unmanaged forest, so
below initial levels 144 years after growth stops. Results
carbon sequestered in plantations never offsets the car-
for the other forest types are similar (supplementary
bon taken from the original forest. This is true even
figure S4).
if the managed plantation is never reharvested, and
worse if the plantation is periodically reharvested. Fur-
ther, typical plantations require periodic fertilization,
increasing N2O emissions and worsening their climate
4. Discussionand conclusion
impact beyond what we report here (Schulze et al 2012).
We extended the carbon cycle model in the C-ROADS
Sixth, growth in wood harvest for bioenergy causes
climate policy model to account for different land and
a steady increase in atmospheric CO2 because the initial
land use types, by region. The model explicitly treats
carbon debt incurred each year exceeds what is repaid.
stocks of carbon in fossil fuels, biomass, soils and
With the US forest parameters used here, growth in the
dead organic matter, the atmosphere, and the fluxes
wood pellet industry to displace coal aggravates global
among them including combustion, supply chain emis-
warming at least through the end of this century, even
sions, and regrowth of harvested lands. The model is
if the industry stops growing by 2050.
extensible to any number of land types and uses, and
Seventh, using wood in electricity generation wors-
geographic scales. To demonstrate the approach, we
ens climate change for decades or more even though
analyzed the dynamic impact of displacing coal with
many of our assumptions favor wood, including: wood
wood in electricity production, finding:
displaces coal (the most carbon intensive fossil fuel);
First, yet contrary to the policies of the EU and
all harvested land is allowed to regrow as forest with
other nations, biomass used to displace fossil fuels
no subsequent conversion to pasture, cropland, devel-
injects CO2 into the atmosphere at the point of com-
opment or other uses; no subsequent harvest, fire or
bustion and during harvest, processing and transport.
disease; no increase in coal demand resulting from
Reductions in atmospheric CO2 come only later, and
lower prices induced by the decline in coal use for
only if the harvested land is allowed to regrow.
electric power; no increase in N2O from fertilization
Second, the combustion and processing efficien-
of managed plantations; and no increase in CO2 emis-
cies of wood in electricity generation are lower than
sions or methanogenesis from disturbed land. Relaxing
for coal (supplementary material). Consequently, the
any of these assumptions worsens the climate impact
first impact of displacing coal with wood is an increase
of wood bioenergy.
in atmospheric CO2 relative to continued coal use,
In sum, although bioenergy from wood can lower
creating an initial carbon debt.
long-run CO2 concentrations compared to fossil fuels,
Third, after the carbon debt is repaid, atmospheric
its first impact is an increase in CO2, worsening global
CO2 is lower, showing the potential long-run benefits
warming over the critical period through 2100 even if
of bioenergy. However, before breakeven, atmospheric
the wood offsets coal, the most carbon-intensive fos-
CO2 ishigherthanitwouldhavebeenwithouttheuseof
sil fuel. Declaring that biofuels are carbon neutral as
bioenergy, increasing radiative forcing and global aver-
the EU and others have done, erroneously assumes
age temperatures, worsening climate change, including
forest regrowth quickly and fully offsets the emissions
potentially irreversible impacts that may arise before
from biofuel production and combustion. The neu-
the long-run benefits are realized.
trality assumption is not valid because it ignores the
Fourth, biofuels are only beneficial in the long run
transient, but decades to centuries long, increase in
if the harvested land is allowed to regrow to its pre-
CO2 caused by biofuels.
harvest biomass and maintained there. Natural forests
Methodologically, we demonstrate the feasibility
have high carbon density compared to pasture, crop-
of integrating static life cycle considerations around
land, developed land and managed tree plantations.
the efficiencies of and emissions from biofuels with
Environ. Res. Lett. 13(2018) 015007
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