ArticlePDF Available

Abstract and Figures

Power utility companies in the United Kingdom are using imported wood pellets from the southern region of the United States for electricity generation to meet the legally binding mandate of sourcing 15% of the nation's total energy consumption from renewable sources by 2020. This study ascertains relative savings in greenhouse gas (GHG) emissions for a unit of electricity generated using imported wood pellet in the United Kingdom under 930 different scenarios: three woody feedstocks (logging residues, pulpwood, and logging residues and pulpwood combined), two forest management choices (intensive and non-intensive), 31 plantation rotation ages (year 10 to year 40 in steps of 1 year), and five power plant capacities (20–100 MW in steps of 20 MW). Relative savings in GHG emissions with respect to a unit of electricity derived from fossil fuels in the United Kingdom range between 50% and 68% depending upon the capacity of power plant and rotation age. Relative savings in GHG emissions increase with higher power plant capacity. GHG emissions related to wood pellet production and transatlantic shipment of wood pellets typically contribute about 48% and 31% of total GHG emissions, respectively. Overall, use of imported wood pellets for electricity generation could help in reducing the United Kingdom's GHG emissions. We suggest that future research be directed to evaluation of the impacts of additional forest management practices, changing climate, and soil carbon on the overall savings in GHG emissions related to transatlantic wood pellet trade.
This content is subject to copyright. Terms and conditions apply.
Environmental Research Letters
Environ. Res. Lett. 9(2014) 024007 (11pp) doi:10.1088/1748-9326/9/2/024007
Potential greenhouse gas benefits of
transatlantic wood pellet trade
Puneet Dwivedi1, Madhu Khanna2, Robert Bailis3and Adrian Ghilardi3
1Warnell School of Forestry and Natural Resources, University of Georgia, Building #4, Room #114,
180 E Green Street, Athens, GA 30602-2152, USA
2Energy Biosciences Institute, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
3School of Forestry & Environmental Studies, Yale University, New Haven, CT 06511, USA
E-mail: puneetd@uga.edu and puneetdwivedi@gmail.com
Received 21 August 2013, revised 9 December 2013
Accepted for publication 6 January 2014
Published 18 February 2014
Abstract
Power utility companies in the United Kingdom are using imported wood pellets from the
southern region of the United States for electricity generation to meet the legally binding
mandate of sourcing 15% of the nation’s total energy consumption from renewable sources by
2020. This study ascertains relative savings in greenhouse gas (GHG) emissions for a unit of
electricity generated using imported wood pellet in the United Kingdom under 930 different
scenarios: three woody feedstocks (logging residues, pulpwood, and logging residues and
pulpwood combined), two forest management choices (intensive and non-intensive), 31
plantation rotation ages (year 10 to year 40 in steps of 1 year), and five power plant capacities
(20–100 MW in steps of 20 MW). Relative savings in GHG emissions with respect to a unit of
electricity derived from fossil fuels in the United Kingdom range between 50% and 68%
depending upon the capacity of power plant and rotation age. Relative savings in GHG
emissions increase with higher power plant capacity. GHG emissions related to wood pellet
production and transatlantic shipment of wood pellets typically contribute about 48% and 31%
of total GHG emissions, respectively. Overall, use of imported wood pellets for electricity
generation could help in reducing the United Kingdom’s GHG emissions. We suggest that
future research be directed to evaluation of the impacts of additional forest management
practices, changing climate, and soil carbon on the overall savings in GHG emissions related
to transatlantic wood pellet trade.
Keywords: electricity generation, European markets, greenhouse gas emissions, life-cycle
assessment, southern United States, wood pellets
SOnline supplementary data available from stacks.iop.org/ERL/9/024007/mmedia
1. Introduction
Global demand for wood pellets is increasing as several power
utility companies in the Europe are using or planning to utilize
them as a feedstock for electricity generation [1]. It is expected
that the utilization of wood pellets will help in meeting national
mandates, where a certain percentage of total energy consumed
within the country needs to come from various renewable
Content from this work may be used under the terms of
the Creative Commons Attribution 3.0 licence. Any further
distribution of this work must maintain attribution to the author(s) and the
title of the work, journal citation and DOI.
energy sources, including biomass, by the end of 2020 [2,3]. In
recent years, the southern United States has become a major
exporter of wood pellets to several European countries [1].
Exports of wood pellets from this region are forecasted to
increase from 1.5 to 5.2 million metric tons between 2012 and
2015 [4].
Existing studies [57] demonstrate that the GHG intensity
of a unit of electricity generated in European countries using
imported wood pellets from the United States and Canada is
about 65%–80% lower than the GHG intensity of a unit of
grid electricity depending upon whether natural gas or wood
residues were used to dry wood pellets in a wood pellet plant.
1748-9326/14/024007+11$33.00 1 c
2014 IOP Publishing Ltd Printed in the UK
Environ. Res. Lett. 9(2014) 024007 P Dwivedi et al
Table 1. Distances traveled to source required feedstock for manufacturing of wood pellets.
Serial no. Details and distances References
1 Wood is transported to a wood pellet plant from forested area (81 km) [5]
2 Wood is transported to a sawmill from forestlands (110 km) [6]
Sawmill residues are transported to a wood pellet plant (27 km)
3 Wood is transported to a sawmill (75 km) [7]
Wood is transported to a chip mill (50 km)
Sawmill residues are transported to a wood pellet plant (0 km)
Wood chips are transported to a wood pellet plant (75 km)
These studies typically assume that the feedstock needed for
manufacturing of wood pellets was sourced from a nearby
forest area or a wood processing facility which was located at
a fixed distance from the wood pellet plant (table 1).
This is a limiting assumption for three main reasons. First,
several harvest tracts are needed to supply required wood
to a nearby wood pellet plant on an annual basis depending
upon the capacity of the wood pellet plant; second, wood is
immediately transported from a harvested tract to a wood pellet
plant by loggers to meet the daily needs of the wood pellet
plant and therefore, distance between each harvested tract and
a wood pellet plant must be summed for ascertaining GHG
emissions related with the transportation of required wood
for wood pellets production; and third, harvested tracts are
distributed across a landscape and chances that all harvested
tracts are located at a fixed distance from a wood pellet plant
are practically nil. These points are particularly valid for
the southern United States as 87% of forestland is privately
owned in this region [8], considerable variability exists among
forestland owners about the objectives of forest management
[9], and forestlands are part of a heterogeneous landscape
where competing land uses coexist [10].
Furthermore, existing studies consider only one harvest
cycle while determining GHG savings of electricity generated
from imported wood pellets in Europe. This raises concerns
among environmentalists and other stakeholders [11]. Again,
this is a limiting assumption as forestland owners repeatedly
use their forestlands for raising plantations especially in the
southern United States. Therefore, average annual quantities
of feedstocks available over time instead of quantities of
feedstocks available at the time of harvest should be considered
for determining GHG savings of electricity generated using
imported wood pellets.
This study combines a simulation-based landscape ap-
proach with life-cycle assessment [12,13] to ascertain rela-
tive savings in GHG emissions when imported wood pellets
from the southern United States are used as a feedstock for
electricity generation at a power plant located in Selby, United
Kingdom [14]. The largest coal-fired power plant in the United
Kingdom is situated at this location. Recently, the management
of this power plant decided to generate about 1000 MW of
electricity using imported wood pellets from the southern
United States [14].
The following seven steps were part of the transatlantic
wood pellet trade supply chain: (a) production of woody
feedstocks; (b) transportation of woody feedstocks from har-
vested tracts to a wood pellet plant using log-trucks; (c)
manufacturing of wood pellets at a wood pellet plant; (d)
transportation of wood pellets from a wood pellet plant to
New Orleans Seaport in the United States using railroads;
(e) transatlantic shipment of wood pellets from New Orleans
Seaport in the United States to Immingham Seaport in the
United Kingdom; (f) transportation of wood pellets from
Immingham Seaport in the United Kingdom to Selby, United
Kingdom using railroads; and (g) burning of wood pellets to
generate electricity at a power plant located in Selby, United
Kingdom. The functional unit selected for this study was a unit
of electricity generated from wood pellets at the power plant
located at Selby, United Kingdom. Individual GHG emissions
for each step present in the supply chain were summed up
and then divided by the total electricity generated at the power
plant to estimate GHG intensity of electricity generated using
imported wood pellets in the United Kingdom. This GHG
intensity was compared with the average GHG intensity of a
unit of grid electricity derived from fossil fuels in the United
Kingdom to determine relative savings in GHG emissions.
2. Methods
This study assumed that biomass obtained from slash pine
(Pinus elliottii) plantations was used for manufacturing wood
pellets. Slash pine is a popular commercial forest species of the
southern United States. In 2007, longleaf-slash pine occupied
about 5.2 million hectares in this region [8]. This species also
reflects general constitution of southern forest resources where
pine forests (planted and natural) occupy about 32% of total
forestland [8]. This study also assumed that the annual quantity
of wood pellets needed by the power plant was sourced from
a wood pellet plant located in the southern United States.
This assumption is valid for two reasons. First, the capacity
of wood pellet plants is rising in the southern United States.
For example, German Pellets announced a plan to build a new
wood pellet plant with an annual capacity of one million metric
tons at Urania, Louisiana [15]; and second, several European
power utilities are opening their own wood pellet plants in the
southern United States to ensure consistent supplies of wood
pellets for their power plants located in Europe [16].
A total of 930 different scenarios were selected for this
study: three feedstocks (logging residues only, pulpwood only,
and logging residues and pulpwood combined), two forest
2
Environ. Res. Lett. 9(2014) 024007 P Dwivedi et al
management choices (intensive and non-intensive), 31 rotation
ages (year 10 to year 40 in steps of 1 year), and five power
plant capacities (20–100 MW in steps of 20 MW). Unlike
non-intensive forest management, herbicides (at plantation
establishment year) and fertilizers (at 2nd and 12th year of
plantation) were applied under intensive forest management.
Utilization of pulpwood for manufacturing of wood pellets was
considered as evidence suggests that pulpwood is increasingly
being utilized for manufacturing of wood pellets to meet rising
export demand [17]. Total availability of timber products at a
harvest age was divided by the harvest age itself to determine
average annual availability of timber products over time. This
was done to consider the impact of multiple harvest cycles at a
given rotation age on the availability of feedstocks. Biogenic
GHG emissions related to burning of bark and wood pellets
were not considered under the assumption that harvested
tracts were immediately planted after harvest. This assumption
is valid as this study uses average annual availability of
feedstocks for wood pellet production. This study does not
consider above- and below-ground carbon sequestered on
forestlands assuming that a forestland owner will continue
to follow the same rotation age.
Procedures adopted for determining GHG emissions of
all the steps present within the supply chain of transatlantic
wood pellets trade are explained below. All distances used in
this study are approximate.
2.1. Production of woody feedstocks
A growth and yield model of slash pine was used to estimate
availability of three timber products: sawtimber, chip-n-saw,
and pulpwood, from a hectare of plantation under inten-
sive and non-intensive forest management choices [18]. The
availability of logging residues at a harvest age was calculated
as the difference between total biomass available in harvested
logs and total biomass present in sawtimber, chip-n-saw, and
pulpwood at the stand level plus 20% of all biomass present
in sawtimber, chip-n-saw, and pulpwood at the same harvest
age [19]. The additional 20% biomass was added as a proxy for
biomass available in branches and tree tops [19]. Total GHG
emission related to plantation management under intensive
forest management choice was 4803 kg CO2e ha1when
the harvest age was equal to or greater than 12 years4. It
was 2431 kg CO2e ha1when the harvest age was 10 and
11 years [5]5. For non-intensive forest management choice,
total GHG emission was 2200 kg CO2e ha1for the selected
range of harvest ages [5]6. An updated value of nitrous oxide
emissions was used based on GREET [20]. These GHG
emissions were divided by the harvest age and then allocated to
available timber products by the percentage weight contributed
4GHG emission related to site preparation, fertilizer application, and
harvesting was 1127.4 kg ha1, 2541.7 kg ha1and 1134.2 kg ha1,
respectively.
5GHG emission related to site preparation, fertilizer application, and
harvesting was 1127.4 kg ha1, 170.3 kg ha1and 1134.2 kg ha1,
respectively.
6GHG emission related to site preparation and harvesting was
1065.5 kg ha1and 1134.2 kg ha1, respectively.
by each timber product towards the combined weight of timber
products available at that harvest age. Percentages were based
on average annual availability of timber products. Collection
efficiency of logging residues was taken as 70% only [21].
No GHG emissions were allocated to logging residues when
only pulpwood was used as a feedstock under the assumption
that logging residues were left in field when not used as a
feedstock.
2.2. Transportation of selected feedstocks
The annual quantity of wood pellets required (WPreq in Mg
yr1) by the power plant was estimated using equation (1):
WPreq = [P(CF/100)24 365 1000]/[(CVWP/3.6)
(CE/100)](1)
where Pis the capacity of the power plant in MW, CF is
the power plant capacity factor in percentage, CVWP is the
calorific value of wood pellets in MJ kg1, and CE is the
percentage efficiency of converting heat into electricity. For
CF, a value of 66.9% based on the average capacity utilization
of the power sector in the United Kingdom was used [22].
For CE, steam cycle conversion efficiencies for 20, 40, 60,
80, and 100 MW power plants were taken as 23.4%, 26.9%,
29.1%, 30.6%, and 31.7%, respectively [23]. For CVWP, an
average value of 18.5 MJ kg1was used [24]. Total quantity
of green biomass required (GBreq in Mg yr1) was estimated
using equation (2):
GBreq =WPreq (1MCWP/100)(1+(MCSP /100))
(100/(100 BK)) (2)
where MCWP is the percentage moisture content of wood
pellets on oven dry basis, MCSP is the percentage moisture
content of slash pine on oven dry basis, and BK is the
percentage of bark weight. The values of MCWP, MCSP,
and BK were taken as 5% [5], 69% [25], and 18% [26],
respectively.
This study assumed that the shape of a harvest tract was
square. Total number of harvest tracts (HTtot) needed to supply
required wood was calculated using equation (3):
HTtot =GBreq/(WA HTsize)(3)
where WA is woody feedstock available for wood pellet
production (Mg ha1yr1) and HTsize is the average harvest
tract size in hectares. The average harvest tract size was
36.5 ha for the southern United States [27]. The value of
HTtot was rounded to the nearest greater integer. The value
of available feedstock was dependent on the type of timber
products considered for wood pellet production, harvest age,
and forest management choice.
This study assumed that the wood pellet plant was
located in the center of a woodshed surrounded by contiguous
harvest tracts of similar characteristics (species, age, forest
management choice, and size). A woodshed was defined as an
area from which wood was sourced for manufacturing of wood
pellets by an owner of a wood pellet plant. The shape of the
3
Environ. Res. Lett. 9(2014) 024007 P Dwivedi et al
woodshed was assumed to be square as well. The side length of
this woodshed (WSside), in terms of number of harvest tracts,
was determined using equation (4):
WSside =sqrt(HTtot)2+1.(4)
The value of WSside was rounded to the nearest greater integer
and then squared to ascertain total number of contiguous har-
vest tracts present in the woodshed. Then, Euclidian distances
between the wood pellet plant and all other harvest tracts
(WSside WSside 1) present in the woodshed were estimated
and multiplied by 1.35 individually [28]. This multiplication
was necessary to consider the impact of local terrain on the
distance between wood pellet plant and any harvest tract.
This study assumed that an owner of the wood pellet
plant will attempt to reduce total distance traveled to transport
required quantities of feedstocks from surrounding harvest
tracts present in the woodshed. Therefore, an owner would
follow the optimization rule given in equation (5) to select
required number of harvested tracts out of all harvest tracts
present in the woodshed:
min
i=k
X
i=1
XiDi,such that Xiis binary (0,1)
and XiBiGBreq (5)
where k=WSside WSside 1,Bi=WAiHTsize, and Dis
the distance of each harvest tract from the wood pellet plant
located in the center of the woodshed. An algorithm programed
in MS Excel c
was used to implement equation (5).
Total biomass availability on a harvested tract was di-
vided by the capacity of a log-truck (22.7 Mg) and rounded
off (upward) to estimate total trips needed for transporting
available feedstock from a harvested tract to a wood pellet
plant. The distance between a harvested tract and wood pellet
plant was multiplied with number of trips required and divided
by the fuel economy of a loaded log-truck (1.91 km l1) to
estimate total diesel consumption. The same procedure was
adopted to determine fuel consumption related to return trips.
The fuel economy of a returning unloaded log-truck was taken
as 2.34 km l1. Total diesel consumption (loaded and unloaded
log-truck) was added and multiplied with a GHG emission
factor (2.68 kg CO2e l1, [29]) to estimate GHG emissions
related to transportation of biomass from a harvested tract
to a wood pellet plant. This procedure was repeated for all
harvested tracts. Finally, all GHG emissions were added to
determine total GHG emissions related to the transportation of
a feedstock to a wood pellet plant.
2.3. Manufacturing of wood pellets
Total quantities of wood pellets produced were multiplied with
a GHG emission factor (155.7 g CO2e kg1, [5]) to ascertain
total GHG emissions related with wood pellet production.
Non-biogenic GHG emissions related with bark burning at
the wood pellet plant were also considered (34.4 g CO2e kg1
of burned material, [30]).
2.4. Transportation of wood pellets in the United States
The average distance between a wood pellet plant and New
Orleans Seaport in the United States was 150 km [14].
The product of total distance traveled and total biomass
transported was multiplied with a GHG emission factor (0.022
kg CO2e Mg1km1, [31]) to determine GHG emission
related with the transportation of required wood pellets to
New Orleans Seaport in the United States using railroads.
2.5. Transatlantic shipment of wood pellets
The average distance between New Orleans Seaport in the
United States to Immingham Seaport in the United Kingdom
was 11050 km [32]. The product of total distance traveled
and total wood pellets transported was multiplied with a GHG
emission factor (0.009 kg CO2e Mg1km1, [33]) to ascertain
GHG emissions related with the transatlantic shipment of
wood pellets.
2.6. Transportation of wood pellets in the UK
The average distance between a power plant at Selby, United
Kingdom and Immingham Seaport in the United Kingdom was
112 km [14]. The product of total distance traveled and total
wood pellets transported was multiplied with a GHG emission
factor (0.022 kg CO2e Mg1km1, [33]) to determine GHG
emissions related with the transportation of wood pellets using
railroads.
2.7. Electricity generation
Non-biogenic GHG emissions related with wood pellet burn-
ing at the power plant was 34.4 g CO2e kg1of burned material
[30]. The GHG intensity of a unit of grid electricity derived
from fossil fuels was taken as 690 g CO2e kWh1in the United
Kingdom [22].
3. Results
The availability of logging residues was higher under intensive
than non-intensive forest management. The availability of
pulpwood was higher under intensive forest management only
until the 15th year of plantation with respect to non-intensive
forest management. However, the combined availability of
both pulpwood and logging residues was greater under inten-
sive than non-intensive forest management for all plantation
ages considered (figure 1(a)). Average annual availability of
pulpwood was higher at early plantation years and declined
with an increase in plantation age (figure 1(b)). Average annual
availability of logging residues initially increased with a rise
in plantation age but started to decrease with a further rise
in plantation age. The weight of logging residues relative to
the total weight of all timber products stabilized at about 12%
after the 12th year of plantation under both forest management
choices (figure S1 available at stacks.iop.org/ERL/9/024007/m
media). GHG emissions related with the production of woody
feedstocks were higher under intensive than non-intensive
forest management choice after the 12th year of plantation
4
Environ. Res. Lett. 9(2014) 024007 P Dwivedi et al
Figure 1. Availability of timber products with respect to plantation age. (a) shows quantities of timber products available at a harvest age. (b)
shows average availability of timber products per year for a rotation age. Values in (b) are obtained after dividing values in (a) by the
corresponding harvest age. Combined availability of pulpwood and logging residues is shown separately. Site index is about 21 m at 25th
year of a slash pine plantation. Initial plantation density is 1235 seedlings ha1.
because of application of fertilizers at the same year under
intensive forest management (figure S2 available at stacks.iop
.org/ERL/9/024007/mmedia).
Total electricity generated was proportional to the ca-
pacity of the power plant (table 2). Total wood and wood
pellets needed to generate electricity were proportional to the
power plant capacity as well (table 3). For a given power
plant capacity, total number of harvested tracts was inversely
proportional to the average annual feedstock availability per
unit forestland—a function of rotation age, forest management
5
Environ. Res. Lett. 9(2014) 024007 P Dwivedi et al
Figure 2. Total distance covered to source required feedstock from surrounding harvested tracts. Extra distance covered to transport excess
feedstock from the last harvested tract is not considered. LR: logging residues; PW: pulpwood; intensive: intensive forest management; and
non-intensive: non-intensive forest management.
Table 2. Total electricity generated at a power plant. Reported numbers are based on the numerator in equation (1).
Power plant capacity (MW) 20 40 60 80 100
Electricity generated (million kWh yr1) 117.2 234.4 351.6 468.8 586.0
Table 3. Quantities of required wood and wood pellets. Reported numbers are based on equations (1) and (2).
Power plant capacity (MW) 20 40 60 80 100
Wood pellets (1000 Mg yr1) 97.5 169.1 235.4 298.6 359.7
Wood (green, 1000 Mg yr1) 190.9 331.1 460.9 584.7 704.3
choice, and feedstock type considered for manufacturing of
wood pellets (figure S3 available at stacks.iop.org/ERL/9/02
4007/mmedia). For instance, total number of harvested tracts
for scenarios when only pulpwood was used as a feedstock was
higher under intensive than non-intensive forest management
choice from the 16th year of rotation age because the average
annual availability of pulpwood was lower under intensive than
non-intensive forest management choice after the 15th year of
plantation. Total number of trips needed to transport feedstocks
from a harvested tract to wood pellet plant decreased with a
decline in feedstock availability per unit forestland (figure
S4 available at stacks.iop.org/ERL/9/024007/mmedia). These
trips remained the same across different power plant capacities.
We found that an owner of the wood pellet plant procured
required quantities of feedstocks only from those harvested
tracts which were located in the vicinity of the wood pellet
plant starting from the nearest harvest tract. The distance of the
last harvested tract from the wood pellet plant is shown in figure
S5 (available at stacks.iop.org/ERL/9/024007/mmedia). Har-
vested tracts were arranged in a circular shape around the wood
pellet plant. The radius of the procurement area was inversely
proportional to the average annual feedstock availability per
unit forestland and directly proportional to the quantities
6
Environ. Res. Lett. 9(2014) 024007 P Dwivedi et al
Figure 3. Total GHG emissions related with transatlantic wood pellet trade. Emissions from any extra distance covered to transport excess
feedstock from the last harvested tract are not considered. The same is true for GHG emissions related to any excess forestland area present
in the last harvested tract. LR: logging residues; PW: pulpwood; intensive: intensive forest management; and non-intensive: non-intensive
forest management.
Table 4. GHG emissions of steps present in the supply chain of transatlantic wood pellet trade. Reported numbers are based steps explained
in the methods section starting from equation (3) onwards.
Power plant capacity (MW) 20 40 60 80 100
Steps present in the supply chain (1000 Mg CO2e)
Manufacturing of wood pellets 15.3 26.5 36.9 46.8 56.4
Transportation of wood pellets using railroads in United States 0.3 0.6 0.8 1.1 1.3
Transatlantic shipment of wood pellets 9.7 16.8 23.4 29.7 35.8
Transportation of wood pellets using railroads in United Kingdom 0.2 0.4 0.6 0.7 0.9
Burning of wood pellets at Selby, United Kingdom 3.4 5.8 8.1 10.3 12.4
of wood pellets manufactured (figure S5 available at stack
s.iop.org/ERL/9/024007/mmedia). Total distance covered to
transport feedstocks to a wood pellet plant increased with an
increase in the power plant capacity (figure 2). Total distance
traveled to source sufficient feedstock was directly dependent
on feedstock availability per unit forestland area mediated by
the required number of trips. Total distance traveled to source
required wood was inherently variable in nature and much
larger than previously published estimates [57].
Total GHG emissions increased with an increase in power
plant capacity (figure 3). Total GHG emissions were lowest
when both pulpwood and logging residues were used as a feed-
stock for wood pellet production for a given power plant capac-
ity because of higher feedstock availability per unit forestland
area relative to a situation when only pulpwood or only logging
residues were used for wood pellet production. Similarly,
total GHG emissions under non-intensive forest management
choice were typically lower than intensive forest management
choice. This was mostly because of higher allocation of GHG
emissions at the time of wood production to feedstocks under
intensive than non-intensive forest management. This higher
allocation compensated any reduction in GHG emissions due
to a decrease in number of harvested tracts needed to source
sufficient wood or total distance covered to source sufficient
quantities of feedstock for wood pellet production.
7
Environ. Res. Lett. 9(2014) 024007 P Dwivedi et al
Figure 4. Relative contribution (percentage) of different steps present within the supply chain of transatlantic wood pellet trade towards total
GHG emission.
Contribution of five out of seven steps present within
the supply chain of transatlantic wood pellet trade towards
total GHG emission remained constant independent of harvest
age, forest management choice, and feedstock type considered
for wood pellet production for a given power plant capacity
(table 4). However, GHG emissions related with steps wood
production and transportation of wood to a wood pellet plant
were dependent on rotation age, forest management choice,
and feedstock type used for wood pellet production, and
therefore were primarily responsible for any variability in
total GHG emissions for a given power plant capacity (fig-
ure 4). GHG emissions arising from wood pellet production
contributed most significantly towards total emissions (about
48%), followed by transatlantic transportation of wood pellets
(about 31%) and burning of wood pellets (about 10%). The
contribution of GHG emissions related to transportation of
required feedstock from harvested tracts to a wood pellet plant
was only about 1%–3%. GHG emissions related to feedstock
production were at least three times higher than GHG emis-
sions related to transportation of required feedstocks to a wood
pellet plant. Additionally, GHG emissions related to feedstock
production decreased smoothly with an increase in harvest
age contrary to GHG emissions related to transportation of
feedstocks to a wood pellet plant. Therefore, distribution
of total GHG emission was relatively smooth without any
noticeable variability between any two consecutive harvest
ages.
A comparison of GHG intensities of electricity generated
from imported wood pellets (figure 5) and the United King-
dom’s current mix of fossil fuel-based grid electricity revealed
that relative savings in GHG emissions increased with a rise
in power plant capacity (figure 6). This contradicts a general
belief that high capacity wood pellet plants should not be
promoted in the United Kingdom and elsewhere as they do
not provide any GHG benefits [11]. Figure 6 also shows that
relative savings in GHG emissions start to flatten out with a rise
in the capacity of a power plant responding to the behavior of
conversion efficiency which initially increases at an increasing
rate but then flattens out with a further rise in the power plant
capacity [23].
8
Environ. Res. Lett. 9(2014) 024007 P Dwivedi et al
Figure 5. GHG intensity of a unit of generated electricity at Selby, United Kingdom. LR: logging residues; PW: pulpwood; intensive:
intensive forest management; and non-intensive: non-intensive forest management.
4. Discussions and conclusions
This study extends our understanding about the impact of
transatlantic wood pellet trade on the United Kingdom’s
electricity-related GHG emissions by combining a simulation-
based approach with life-cycle assessment under realistic
assumptions at landscape level. The GHG intensity of a unit
of electricity generated using imported wood pellets in the
United Kingdom is at least 50% lower than the GHG intensity
of grid electricity derived from fossil fuels. Therefore, use of
imported wood pellets from the southern United States for
electricity generation could help in reducing GHG emissions
in the United Kingdom.
Relative savings in GHG emissions were only higher by
up to 2% for wood pellets manufactured using feedstocks
obtained from non-intensive than intensive forest management
choice especially when the age of non-intensively managed
plantations was greater than 12 years. This implies that feed-
stock obtained from both intensive and non-intensively man-
aged forest plantations can be used for manufacturing wood
pellets to achieve reductions in GHG emissions without any
significant drop in relative savings of GHG emissions. Addi-
tionally, relative savings in GHG emissions were almost sim-
ilar irrespective of type of feedstock used for manufacturing
of wood pellets. This implies that the use of logging residues
along with other feedstocks for manufacturing of wood pellets
in the southern United States and subsequent utilization of
manufactured wood pellets for electricity generation in the
United Kingdom could save a significant amount of GHG
emissions.
Logging residues and pulpwood derived from mature
plantations should be used as a feedstock to ensure highest
savings in GHG emissions for any power plant capacity.
However, relative savings in GHG emissions were at least
50% even at lower rotation ages. These results contradict
a general belief that the use of wood pellets, manufactured
from feedstocks (mostly pulpwood and logging residues)
obtained from 10 to 15 year old pine plantations in the
southern United States do not provide any GHG savings over
electricity generated from fossil fuels in the United Kingdom
[13]. Relative savings in GHG emissions increased with a
rise in the capacity of power plant mostly because of higher
conversion efficiencies of high capacity power plants. This
further suggests that high capacity power plants will be much
better for reducing GHG emissions than low capacity power
plants.
The approach adopted in this study for determining total
distance covered to source sufficient feedstock for wood pellet
9
Environ. Res. Lett. 9(2014) 024007 P Dwivedi et al
Figure 6. Relative savings in GHG emissions with respect to grid electricity derived from fossil fuels. LR: logging residues; PW: pulpwood;
intensive: intensive forest management; and non-intensive: non-intensive forest management.
production assumes that forestland owners are willing to sell
logging residues and pulpwood to an owner of wood pellet
plant only. Additionally, this study assumes that all harvested
tracts are similar in terms of planted species, plantation age,
and located contiguously. Dynamics of sourcing required
wood for manufacturing of wood pellets or any other wood-
based product is much more complex at the landscape level.
This study acknowledges this complexity and suggests that
results of this study should be considered as a best case
only. However, relative contribution of GHG emission related
with the transportation of feedstocks is relatively small (<3%)
towards overall GHG emissions. Therefore, it is very unlikely
that relative percentage savings in GHG emissions will change
a lot even after relaxing these assumptions.
In this study, the average annual feedstock yield remains
constant. However, yields may change over time, which creates
a need to analyze the impact of future changes in feedstock
yields on overall GHG savings. Additionally, much insight
would be gained from integrating the model developed in
this study with market equilibrium models [34] to analyze
the consequences of an increase in demand for feedstocks for
wood pellet production on the rotation age. This is especially
true as a change in rotation age could affect carbon benefits
of transatlantic wood pellet trade [35]. Furthermore, it will
be interesting to explore the potential of other technologies
like combined heat and power [36] to determine GHG savings
of wood pellets not only in Europe but in the United States
as well. We have analyzed only two scenarios of biomass
production in this study. Forestland owners practice multiple
ways to manage their plantations. Thus, future research should
consider the impact of multiple forest management practices
on the relative savings in GHG emissions associated with
transatlantic wood pellet trade. Finally, a better understanding
of soil carbon behavior especially for short rotation cycles is
also needed. We hope that findings of this study will help in
guiding the debate on sustainability of wood-based bioenergy
products at local, regional, national, and global levels. We
also hope that this study will be able to guide future research
appropriately.
Acknowledgments
Authors are thankful for the funding provided by Energy
Biosciences Institute @ University of Illinois at Urbana-
Champaign/University of California, Berkeley. Authors are
thankful to Shawn Baker at Warnell School of Forestry and
Natural Resources, University of Georgia for his help with
data on log-trucks.
10
Environ. Res. Lett. 9(2014) 024007 P Dwivedi et al
References
[1] Goetzl A 2012 Pellet Power—Global Trade in Wood Pellets
(Internet) (Washington, DC: United States International
Trade Commission) Available from: www.usitc.gov/publica
tions/332/executive briefings/EBOT Wood Pellets Final.p
df
[2] DECC 2011 UK Renewable Energy Roadmap (Internet)
(London: Department of Energy & Climate Change)
Available from: www.gov.uk/government/uploads/system/u
ploads/attachment data/file/48128/2167-uk-renewable-ener
gy-roadmap.pdf
[3] Lovell J 2013 Europe’s 2nd-biggest coal-fired power plant will
turn to wood from North America ClimateWire (Internet)
Available from: www.eenews.net/stories/1059979005
[4] Ekstrom H 2012 The US Surpassed Canada as the Largest
Wood Pellet Exporter in the World in the First Half of 2012
(Bothell, WA: Wood Resources International LLC)
Available from: www.pr.com/press-release/447430
[5] Dwivedi P, Bailis R, Bush T G and Marinescu M 2011
Quantifying GWI of wood pellet production in the southern
United States BioEnergy Res. 4180–92
[6] Magelli F, Boucher K, Bi H T, Melin S and Bonoli A 2009
An environmental impact assessment of exported wood
pellets from Canada to Europe Biomass Bioenergy
33 434–41
[7] Damen K and Faaij A 2006 A greenhouse gas balance of two
existing international biomass import chains Mitig. Adapt.
Strateg. Glob. Change 11 1023–50
[8] Smith W, Miles P, Perry C and Pugh S 2009 Forest Resources
of the United States, 2007: A Technical Document
Supporting the Forest Service 2010 RPA Assessment
(Washington, DC: United States Department of Agriculture
Forest Service (Available from http://www.nrs.fs.fed.us/pub
s/rn/rn nrs38.pdf))
[9] Butler B 2008 Family Forest Owners of the United States,
2006 (Newton Square, PA: United States Department of
Agriculture Forest Service)
[10] Homer C, Huang C, Yang L, Wylie B K and Coan M 2004
Development of a 2001 national land-cover database for the
United States Photogram. Eng. Remote Sens. 70 829–40
[11] Harrabin R 2013 Biomass fuel subsidies to be capped says
energy secretary BBC News (London) Available from
http://www.bbc.co.uk/news/business-23334466
[12] ISO 2006 Environmental Management—Life Cycle
Assessment—Principles and Framework (Geneva:
International Organization for Standardization)
[13] ISO 2006 Environmental Management—Life Cycle
Assessment—Requirements and Guidelines (Geneva:
International Organization for Standardization)
[14] Lundgren K and Morales A 2012 Biggest English Polluter
Spends $1 Billion to Burn Wood. www.bloomberg.com
(Internet) (London) Available from: www.bloomberg.com/n
ews/2012-09-25/biggest-english-polluter-spends-1-billion-t
o-burn-wood-energy.html
[15] Simet A 2013 German Pellets plans second giant wood pellet
plant in US (internet). Biomass Mag. (cited 25 July
2013). Available from: http://biomassmagazine.com/articles
/8904/german-pellets-plans-second-giant-wood-pellet-plant
-in-u-s/
[16] Kinney S 2011 US industrial pellet market prepares for
Europe’s 20 ×2020 renewable energy mandate (internet)
www.forest2market.com (cited 25 July 2013). Available
from: www.forest2market.com/blog/US-Industrial-Pellet-M
arket-Prepares-for-Europes-20-x-2020-Renewable-Energy
[17] Spelter H and Toth D 2009 North America’s Wood Pellet
Sector (Madison, WI: United States Department of
Agriculture Forest Service)
[18] Yin R, Pienaar L and Aronow M 1998 The productivity and
profitability of fiber farming J. Forest 96 13–8
[19] Jenkins J, Chojnacky D, Heath L and Birdsey R 2003 National
scale biomass estimators for United States tree species
Forest Sci. 49 12–35
[20] Wang M 2001 Development and Use of GREET 1.6
Fuel-Cycle Model for Transportation Fuels and Vehicle
Technologies (Argonne, IL: Argonne National Laboratory)
[21] ORNL 2011 US Billion-Ton Update: Biomass Supply for a
Bioenergy and Bioproducts Industry (Oak Ridge, TN: Oak
Ridge National Laboratory) p 227
[22] DECC 2013 Digest of UK Energy Statistics’ (DUKES)
(Internet) (London: Department of Energy & Climate
Change). Available from: www.gov.uk/government/organis
ations/department-of-energy-climate-change/series/digest-o
f-uk-energy-statistics-dukes
[23] Bridgwater A V, Toft A J and Brammer J G 2002 A
techno-economic comparison of power production by
biomass fast pyrolysis with gasification and combustion
Renew. Sustain. Energy Rev. 6181–246
[24] Dwivedi P, Bailis R and Khanna M 2013 Is use of both
pulpwood and logging residues instead of only logging
residues for bioenergy development a viable carbon
mitigation strategy? BioEnergy Res. Available from:
http://link.springer.com/10.1007/s12155-013-9362-z
[25] Gibson M D, McMillin C W and Shoulders E 1986 Moisture
content and specific gravity of the four major southern pines
under the same age and site conditions Wood Fiber Sci.
18 428–35
[26] Miles P and Smith W 2009 Specific Gravity and Other
Properties of Wood and Bark for 156 Tree Species Found in
Noth America (Newton Square, PA: United States
Department of Agriculture Forest Service) Available from
http://www.nrs.fs.fed.us/pubs/rn/rn nrs38.pdf
[27] Baker S, Greene D and Harris T 2012 Impact of timber sale
characteristics on harvesting costs. Proc. South. For. Econ.
Work (Charlotte, NC: Mississippi State University)
pp 94–105
[28] Ravula P P 2007 Design, simulation, analysis and optimization
of transportation system for a biomass to ethanol conversion
plant PhD Thesis Virginia Polytechnic Institute and State
University
[29] EIA 2011 Fuel Emission Coefficients (Internet) Volunt.
Report. Greenh. Gases Progr. (Washington, DC: Energy
Information Administration, United States Department of
Energy) Available from: www.eia.gov/oiaf/1605/coefficient
s.html#tbl2
[30] WDNR 2010 Forest Biomass and Air Emissions (Olympia,
WA: Washington Department of Natural Resources)
[31] PR´
e-Consultants 2013 US LCI Database Simapro LCA
Software (Amersfoort: PR´
e-Consultants)
[32] Anonymous 2013 Sea route and distance (Internet).
www.ports.com (cited 15 June 2013) Available from:
http://ports.com/sea-route/
[33] PR´
e-Consultants 2013 Ecoinvent Database Simapro LCA
Software (Amersfoort: PR´
e-Consultants)
[34] Galik C, Abt R and Wu Y 2009 Forest biomass supply in the
southeastern United States: implications for industrial
roundwood and bioenergy production J. Forest
107 69–77
[35] Mitchell S R, Harmon M E and O’Connell K E B 2012
Carbon debt and carbon sequestration parity in forest
bioenergy production GCB Bioenergy 4818–27
[36] Bernotat K and berg T 2004 Biomass fired small-scale CHP in
Sweden and the Baltic States: a case study on the potential
of clustered dwellings Biomass Bioenergy 27 521–30
11
... Refs. [19][20][21]). This divergence cannot be pinpointed solely to the use of a specific type of forest biomass, e.g. ...
... • Afforestation with naturally regenerating forests managed with lower intensity (Pathways nr. [16][17][18][19][20]: 'Unlikely mediumterm' qualifier because growth rates are assumed to be slower compared to plantations. A range of uncertainty is considered due to the lack of studies and the likely variation in productivity. ...
Article
Full-text available
The debate on forest bioenergy sustainability has been so far dominated by assessments made through the carbon emissions lens. The biodiversity perspective has been largely missing. The European Green Deal's ambitious targets have brought biodiversity and ecosystem condition restoration and conservation to the core of the EU's legislative portfolios. An opportunity to revisit some important governing texts with a biodiversity lens has therefore presented itself. In this study, we review the impacts on biodiversity and carbon emissions of specific bioenergy pathways that may be used to supply additional forest-based energy. We then synthesize our findings in a nexus matrix, plotting the pathways along a gradient of benefits through to detriments on the two dimensions to highlight win-win and lose-lose options. We found that some pathways do mitigate carbon emissions in the short-term while not deteriorating ecosystem condition. These include collecting fine woody debris within limits of locally established thresholds. We highlight the pathways that do little to mitigate carbon emissions and that are detrimental to ecosystems as well. These include removal of coarse woody debris and low stumps or the conversion of semi-natural, primary and old-growth forests to plantation forests with the purpose to produce bioenergy. We conclude that in the currently polarised debate an approach which unambiguously eliminates negative options is more fruitful than trying to find agreement on best options. Consequently, we present several governance measures that could limit the uptake of clearly undesirable pathways within Europe and we show that some lose-lose pathways are still considered “sustainable” within the European Green Deal.
... It is commonly perceived that bioenergy supply chain emissions are substantial, particularly when biomass is transported internationally, and could negate the climate benefits of fossil fuel substitution. However, fossil energy use along domestic forest biomass supply chains, from harvest, processing and transport, is generally small compared to the energy content of the bioenergy product and, with efficient handling and shipping, even when traded internationally (Batidzirai et al., 2014;Dwivedi et al., 2014;Ehrig & Behrendt, 2013;Gustavsson et al., 2011;Hamelinck et al., 2005;Jonker et al., 2014;Mauro et al., 2018;Miedema et al., 2017;Porsö et al., 2018;Uslu et al., 2008). The European Commission's Joint Research Centre determined that shipping pellets between North America and Europe increases supply chain emissions by 3-6 g CO 2 /MJ, from around 3-15 g CO 2 /MJ for wood chips or pellets dried using bioenergy and transported 500 km by truck (Giuntoli et al., 2017). ...
... This underscores the importance of assessing actual supply chains. For example, the international pellet supply chain between the southeast United States and Europe has been intentionally designed to minimize trucking and associated handling costs, with pellet mills and large end users such as power plants located near rail lines, waterways and ports, thereby minimizing transport emissions and increasing net climate benefits (Dwivedi et al., 2014;Favero et al., 2020;Kline et al., 2021). ...
Article
Full-text available
The scientific literature contains contrasting findings about the climate effects of forest bioenergy, partly due to the wide diversity of bioenergy systems and associated contexts, but also due to differences in methods. The climate effects of bioenergy must be accurately assessed to inform policy‐making, but the complexity of bioenergy systems and associated land, industry and energy systems raises challenges for assessment. We examine misconceptions about climate effects of forest bioenergy and discuss important considerations in assessing these effects and devising measures to incentivise sustainable bioenergy as a component of climate policy. The temporal and spatial system boundary and the reference (counterfactual) scenarios are key methodology choices that strongly influence results. Focussing on carbon balances of individual forest stands, and comparing emissions at the point of combustion, neglect systems‐level interactions that influence the climate effects of forest bioenergy. We highlight the need for a systems approach, in assessing options and developing policy for forest bioenergy, that: 1) considers the whole life cycle of bioenergy systems, including effects of the associated forest management and harvesting on landscape carbon balances; 2) identifies how forest bioenergy can best be deployed to support energy system transformation required to achieve climate goals; and 3) incentivises those forest bioenergy systems that augment the mitigation value of the forest sector as a whole. Emphasis on short‐term emissions reduction targets can lead to decisions that make medium‐ to long‐term climate goals more difficult to achieve. The most important climate change mitigation measure is the transformation of energy, industry, and transport systems so that fossil carbon remains underground. Narrow perspectives obscure the significant role that bioenergy can play by displacing fossil fuels now, and supporting energy system transition. Greater transparency and consistency is needed in greenhouse has reporting and accounting related to bioenergy.
... The Development of RES is very high in Greece, because the geomorphological and climatic characteristics that allow for the high energy and economic effi- The use of biomass for electricity generation is very interesting because it is RES, but it is limited by the cascade principle, which is a key EU strategy [38] According the principle of the sequence suggests that biomass should be used in the following order of priority: reuse, recycling, bio-energy, and disposal. The rationale behind the principle of sequencing is that the life cycle of biomass needs to be maximized in order to ensure the viability of the bio-economy, but also to bring some balance to the market due to subsidies in the field of bioenergy [39]. tones at an annual basis [44] [45] [46]. ...
Article
Full-text available
Biomass is a renewable, economic and readily available resource of energy that has potential to substitute fossil fuels in many applications such as heat, electricity and biofuels. The increased use of the agricultural biomass can help the agricultural based societies in achieving energy security and creating employment without causing environmental degradation. However, the viability and feasibility of electricity generation from agricultural biomass depends upon the availability of biomass supply at a competitive cost. The present study investigates the availability of agricultural biomass for distributed power generation in Greece (Kozani). The study concludes with a discussion on significance and challenges of decentralized electricity generation for rural energy supply, including brief description about economical, social, environmental and technical aspects of bioelectricity. With the application of the life cycle analysis applied, the environmental and economic impacts that will occur in the region of Kozani in Greece, where a biomass wood pellets production workshop is operating, have been assessed. The total annual emission of CO 657.9 gr, HC 22.36 gr, PM 67.94 and NOx 8.832,2 gr was calculated. The economic evaluation estimated the payback period for the investment in this plant to be approximately 3 years.
... A 2013 study that appeared in Environmental Research Letters looked at the greenhouse gas consequences of Drax's consumption of trees in the US South (Dwivedi et al. 2014). They simulated pine plantation growth based on a forest similar to the simple example above, but assumed the wood came from off-site plantations. ...
Article
Full-text available
Over the last 20 years, IPPC reports have made it clear that the world must move beyond simply reducing the amount of carbon dioxide emitted into the atmosphere to actively removing it from the skies. (Solar and wind can reduce carbon emissions, but they do not remove greenhouse gases from the atmosphere). New BioEnergy Carbon Capture and Storage (BECCS) technologies have been emerging that can remove carbon dioxide emissions from the atmosphere and sequester them permanently underground. Indeed, many long-term scenarios for transitioning from today’s fossil fuel-dependent society to a future net zero society hinge on BECCS. But a key question is what bioenergy feedstock to use. In some cases, powering these facilities by burning biomass that comes from plantations in the US South is an option. Consequently, the study of the origins, production, and use of the fuel consumed by the world’s largest biomass-fired power plant in Drax, England, provides a useful case study of the potential advantages and disadvantages of the burning of biomass – wood pellets made from trees, bark, roots, stumps, millwaste, sawdust, and other woody vegetation – in place of fossil fuel to generate power for processes such as BECCS.
... Furthermore, addressing SDG 9, by expanding the use of sustainable, renewable woody biomass for energy, can provide a means to tackle SDG 13: to "take urgent action to combat climate change and its impacts", for life-cycle CO 2 emissions are reduced relative to alternatives based on fossil fuels [27,61,62]. Transport of pellets to Europe from the SE US is facilitated by improved and more efficient port and rail facilities, and carbon-and cost-efficient maritime shipping, and because pellets displace coal, the supply chain results in significant net greenhouse gas reductions [27,63]. SDG 12 is to "ensure sustainable consumption and production patterns". ...
Article
Full-text available
Wood-based pellets are produced in the southeastern United States (SE US) and shipped to Europe for the generation of heat and power. Effects of pellet production on selected Sustainability Development Goals (SDGs) are evaluated using industry information, available energy consumption data, and published research findings. Challenges associated with identifying relevant SDG goals and targets for this particular bioenergy supply chain and potential deleterious impacts are also discussed. We find that production of woody pellets in the SE US and shipments to displace coal for energy in Europe generate positive effects on affordable and clean energy (SDG 7), decent work and economic growth (SDG 8), industry innovation and infrastructure (SDG 9), responsible consumption and production (SDG 12), and life on land (SDG 15). Primary strengths of the pellet supply chain in the SE US are the provisioning of employment in depressed rural areas and the displacement of fossil fuels. Weaknesses are associated with potential impacts on air, water, and biodiversity that arise if the resource base and harvest activities are improperly managed. The SE US pellet supply chain provides an opportunity for transition to low-carbon industries and innovations while incentivizing better resource management.
... The nonrenewable energy consumption of feedstock transportation was also significant, attributable to the long collection radius for biomass feedstock (see Table S6). Plant construction is typically excluded when assessing the environmental impacts of biomass energy [67]. However, previous studies estimated that the NEIED of plant construction could be as high as 29%-39% of the total. ...
Article
As China continues to focus on renewable energy in its future development, the energy performance of biofuels has become a hot research topic. However, existing bioenergy assessments have used diverse indexes and inconsistent system boundaries, hindering the comparative analysis of different technologies. Generally, improvements in energy quality (e.g., from solid to gaseous fuel) are accompanied by increases in nonrenewable energy investment. To quantify this trade-off, this study examined the energy return on investment (EROI) of typical biomass conversion systems in China—namely, biomass compression, biodiesel, bioethanol, biogas, biomass gasification, and biomass power generation. Various feedstocks were considered, including first-generation (e.g., corn), second-generation (e.g., corn straw), and third-generation (e.g., algae) feedstock options. The system boundaries of previous biomass footprint calculations are unified to make the results comparable. The results showed that converting raw biomass feedstock to solid fuel had the highest EROI (8.06-24.13), followed by biomass power (2.07-16.48), biogas (1.24-11.05), biodiesel (1.28-2.23), second-generation bioethanol (1.18-9.90), first-generation bioethanol (0.68-3.12), and biomass gasification (1.12-1.57). Compared with fossil fuels (e.g., gasoline, diesel), biofuels had a higher average EROI, indicating obvious energy-saving benefits. Among all biomass conversion pathways, pyrolysis gasification had the highest EROI opportunity cost for both straw and wood residues. This study's findings highlight the need for consistent system boundaries in bioenergy technology deployment to quantify the EROI opportunity cost of each biomass conversion pathway, and recognize the importance of energy efficiency promotion to enhance the economic feasibility of biomass energy industries.
... The same analysis revealed that when comparing steel construction against timber, energy and global warming the potential is 17% and 26% less for timber when compared to steel structures (Lippke et al. 2004). Other studies in the bioenergy sector indicate that the use of forest biomass to produce wood pellets has a lower environmental impact than using fossil fuels, even when accounting for transportation, logistics, and the actual burning of biomass (Dwivedi et al. 2014). ...
Article
Full-text available
According to several sources, CLT construction systems are an excellent structural choice for tall commercial and residential buildings, have excellent environmental performance, and provide an additional market for softwood and hardwood lumber. Besides and because of its engineered nature, CLT panels can be an excellent market for low value timber (lesser known species, diseased trees, infested trees, and low-grade timber). However, the US construction industry is not yet taking full advantage of the benefits of CLT construction systems due to several limiting factors including market and code acceptance, lack of knowledge, and local CLT panel manufacturing capacity. This last limiting factor is considered critical for the expansion of the US CLT market. Therefore, this research aims to investigate through a case study methodology the main challenges and barriers that CLT panel manufacturers in Western Europe had to overcome to successfully manufacture and commercialize CLT panels. It is expected that current engineered wood products firms, investors, and policy-makers will benefit from these results. Learning from failures, successes, and best practices of leading CLT companies in Western Europe can help support the potential development of CLT manufacturing capacity elsewhere.
... account for 48% of the total 100-year GHG emissions and justify the carbon benefits of converting residues to bioenergy products (e.g. biofuel, pellets, biochar) [36,76,[119][120][121][122][123][124][125]. Figure 4 shows the life-cycle GHG footprints (all fossil-and biogenic-based GHG emissions minus the total CO 2 sequestrated from the atmosphere) for 1-ha land over 100 years. The site productivity or growth rate has the dominant impact, as shown by the significant differences between slower growing GC1 scenarios (Scenario 1-4) and faster growing GC2 scenarios (Scenario 5-8). ...
Article
Full-text available
Life Cycle Assessment (LCA) has been used to understand the carbon and energy implications of manufacturing and using cross-laminated timber (CLT), an emerging and sustainable alternative to concrete and steel. However, previous LCAs of CLT are static analyses without considering the complex interactions between the CLT manufacturing and forest systems, which are dynamic and largely affected by the variations in forest management, CLT manufacturing, and end-of-life options. This study fills this gap by developing a dynamic life-cycle modeling framework for a cradle-to-grave CLT manufacturing system across 100 years in the Southeastern United States. The framework integrates process-based simulations of CLT manufacturing and forest growth as well as Monte Carlo simulation to address uncertainty. On 1-ha forest land basis, the net greenhouse gas (GHG) emissions ranges from-954 to-1445 metric tonne CO2 eq. for a high forest productivity scenario compared to-609 to-919 metric tonne CO2 eq. for a low forest productivity scenario. All scenarios showed significant GHG emissions from forest residues decay, demonstrating the strong needs to consider forest management and their dynamic impacts in LCAs of CLT or other durable wood products (DWP). The results show that using mill residues for energy recovery has lower fossil-based GHG (59%-61% reduction) than selling residues for producing DWP, but increases the net GHG emissions due to instantaneous release of biogenic carbon in residues. In addition, the results were converted to 1 m 3 basis with a cradle-to-gate system boundary to be compared with literature. The results, 113-375 kg CO2 eq./m 3 across all scenarios for fossil-based GHG emissions, were consistent with previous studies. Those findings highlight the needs of system-level management to maximize the potential benefits of CLT. This work is an attributional LCA, but the presented results lay a foundation for future consequential LCAs for specific CLT buildings or commercial forest management systems.
Article
Full-text available
Major objectives of this study were to produce low-emitting wood pellet biofuel from selected agro-forest tree species, i.e., Kikar (Acacia nilotica), Oak (Quercus semicarpifolia), and Mes-quite (Prosopis juliflora), grown in the southern part of the Khyber Pakhtunkhwa (KP) province of Pakistan using indigenously developed technology (pelletizer machine). Primary raw material, such as sawdust of the selected agro-forest tree species, was obtained from sawmills located in southern part of KP. Life cycle inventory (LCI) was sourced for entire production chain of the wood pellet biofuel by measuring quantities of various inputs consumed and output produced. In addition , the wood pellets were characterized to examine diameter, length, moisture content, ash content , bulk density, high heating value (HHV), low heating value (LHV), as well as nitrogen and sulphur contents. A comprehensive life cycle assessment was performed for wood pellet biofuel production chain using SimaPro v9.1 software. A functional unit of one (01) kilogram (kg) wood pellet biofuel was applied following a gate-to-gate approach. The results of the present study were in accordance with the recommended Italian standard CTI-R 04/5 except for pellet bulk density and nitrogen content. The bulk density for all wood pellets, manufactured from the saw dust of three different agro-forest tree species, were lower than the recommended Italian standard, while for nitrogen content, the results were higher than the recommended Italian standard. Among the environmental impacts, Kikar (Acacia nilotica) wood pellets were the major contributor to fossil fuel depletion, followed by ecotoxicity, mineral depletion and acidification/eutrophication. This was primarily due to lubricating oil and urea-formaldehyde (UF) resin used as inputs in the wood pellets biofuel manufacture. Likewise, human health and ecosystem quality was also affected by lubricating oil, UF resin, and saw dust, respectively. In cumulative exergy demand of 1 kg wood pellets biofuel, the highest impact was from Kikar wood pellets for non-renewable fossils, mainly due to lubricating oil used. Difference in environmental impacts, damage assessment, and exergy were examined in three different scenarios for major hotspot inputs by reducing 20% lubricating oil in case 1, 20% UF resin in case 2, and without usage of UF resin in case 3, while marked reduction was observed in ecotoxicity, fossil fuel, and mineral depletion, as well as acidification/eutrophication impact category. Moreover, a pronounced reduction was also noted in the non-renewable fossil fuel category of cumulative exergy demand of one kg of wood pellets biofuel produced. Citation: Rashedi, A.; Muhammadi, I.U.; Hadi, R.; Nadeem, S.G.; Khan, N.; Ibrahim, F.; Hassan, M.Z.; Khanam, T.; Jeong, B.; Hussain, M.
Article
Full-text available
Biomass occupies a very important place among renewable energy sources, and the residual biomass recovery chain represents a sector of fundamental importance. Our work focused on the production of pellets by pruning residues from two of the most important woody crops in Italy: hazelnut and olive groves. We found a higher value of bulk density for the hazelnut pellet (581.30 kg m−3 vs. 562.38 kg m−3) and a higher value of length for the olive pellet (16.66 mm vs. 10.47 mm). The percentages of durability were very similar (98%). The low heating value and ash content of hazelnut and olive were 17.21 MJ kg−1 and 3.1%, and 16.83 MJ kg−1 and 2.5%. A higher concentration of Cu, Pb, and Ni was observed in the hazelnut. The contrary was observed for the concentration of Zn. N content was 0.77% and 1.24% for the hazelnut and the olive, respectively. The concentration of S was 0.00% for both. The quality parameters that do not meet current standards could be improved by mixing these materials with different types of wood.
Article
Full-text available
Multi-Resolution Land Characterization 2001 (MRLC 2001) is a second-generation Federal consortium designed to create an updated pool of nation-wide Landsat 5 and 7 imagery and derive a second-generation National Land Cover Database (NLCD 2001). The objectives of this multi-layer, multi-source database are two fold: first, to provide consistent land cover for all 50 States, and second, to provide a data framework which allows flexibility in developing and applying each independent data component to a wide variety of other applications. Components in the database include the following: (1) normalized imagery for three time periods per path/row, (2) ancillary data, including a 30 m Digital Elevation Model (DEM) derived into slope, aspect and slope position, (3) perpixel estimates of percent imperviousness and percent tree canopy, (4) 29 classes of land cover data derived from the imagery, ancillary data, and derivatives, (5) classification rules, confidence estimates, and metadata from the land cover classification. This database is now being developed using a Mapping Zone approach, with 66 Zones in the continental United States and 23 Zones in Alaska. Results from three initial mapping Zones show single-pixel land cover accuracies ranging from 73 to 77 percent, imperviousness accuracies ranging from 83 to 91 percent, tree canopy accuracies ranging from 78 to 93 percent, and an estimated 50 percent increase in mapping efficiency over previous methods. The database has now entered the production phase and is being created using extensive partnering in the Federal government with planned completion by 2006.
Article
Full-text available
Since 1995, with funds from the U.S. Department of Energy's (DOE's) Office of Transportation Technologies (OTT), Argonne National Laboratory has been developing the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model. The model is intended to serve as an analytical tool for use by researchers and practitioners in estimating fuel-cycle energy use and emissions associated with alternative transportation fuels and advanced vehicle technologies. Argonne released the first version of the GREET mode--GREET 1.0--in June 1996. Since then, it has released a series of GREET versions with revisions, updates, and upgrades. In February 2000, the latest public version of the model--GREET 1.5a--was posted on Argonne's Transportation Technology Research and Development Center (TTRDC) Web site (www.transportation.anl.gov/ttrdc/greet).
Article
Full-text available
Standard site preparation for pine plantations in south Georgia was combined with fertilization, bedding, and herbicide treatments. These intensified silvicultural practices can boost volume by 128 percent and the rate of return by 12 percent. Combining the growth-and-yield data with a forest-level analytic framework shows the cost structure of timber production and its intra- and inter-regime changes. The high yields possible from fiber farming could allow changes in land use, from timber production to other uses, while maintaining supplies of low-cost fiber.
Article
Family forest owners own more forestland in the United States than any other group. There have been no national studies of racial and ethnic minority family forest owners in the United States, in spite of increasing attention to diversity in forestry. Using the US Forest Service’s National Woodland Owner Survey data, we sought to better understand minority owners by looking at their characteristics, attitudes, and behaviors. Of the over 4 million family forest ownerships with 10+ ac in the United States, minorities comprise 6.6 percent of the ownerships and own 5.1 percent of the 265 million ac. Although many similarities exist between minority and nonminority owners, such as reasons for owning land and concerns, minority landowners tend to be more regionally located, have smaller forest holdings, are less likely to manage their forests, and are less likely to have participated in assistance programs. Broad insight into the attitudes and behaviors of minority family forest owners can help policymakers, program directors, and outreach coordinators begin to understand the needs of minority landowners, providing this historically underserved group with tools they need to attain their forest management and land-use goals. By increasing minority landowner engagement, we can hopefully slow the loss of land by minority landowners.
Article
Large changes have taken place in the forest industry in the past decade with record high and low home construction levels, the dissolution of vertically integrated forest products companies, and record high fuel costs. All of these shifts have impacted the timber harvesting workforce. We gathered data on timber sales from across the southeastern United States from 2000 through 2008 to examine what changes had occurred in harvest tract characteristics. Among the trends observed were an increase in average tract acreage and substantial increases in partial harvesting. These data were then used to model harvesting costs in the Auburn Harvesting Analyzer, in an effort to determine what trends existed. Little long-term impact to harvesting costs could be attributed to timber sale characteristics. Introduction Across much of the country, forestland ownership patterns have shifted dramatically. Lands previously owned by vertically integrated forest products companies have been divested, typically to land management organizations seeking to provide competitive financial returns to company shareholders. It has been theorized that the management approach of these new landowners will be different. We undertook a project to determine what changes have occurred in the characteristics of harvested tracts since 2000, and ultimately, what impact this may have had on harvesting costs over the same timeframe.
Article
The use of trade or firm names in this publication is for reader information and does not imply endorsement by the United States Department of Agriculture (USDA) of any product or service. The USDA prohibits discrimination in all its programs and activities on the basis of race, color, national origin, age, disability, and where applicable, sex, marital status, familial status, parental status, religion, sexual orienta-tion, genetic information, political beliefs, reprisal, or because all or a part of an individual's income is derived from any public assistance program. (Not all prohibited bases apply to all programs.) Persons with disabilities who require alternative means for communication of program informa-tion (Braille, large print, audiotape, etc.) should contact USDA's TARGET Center at (202) 720–2600 (voice and TDD). To file a complaint of discrimi-nation, write to USDA, Abstract The North American wood pellet sector is profiled in this paper. A small pellet industry has existed since the 1930s, but its main growth occurred in the wake of the energy crisis in the 1970s. Its current spurt is even greater, growing from 1.1 million metric tonnes in 2003 to 4.2 million 2008. It is set to reach 6.2 million in 2009. Most plants are small, relying on sawmill residues for fiber and thus are limited to 100,000 tonnes or less per year. A number of new mills have been built to process chipped roundwood and have capacities three to four times as large. Most pellets made in the United States are consumed domestically, but a growing offshore market is boosting exports. By contrast, most Cana-dian pellets are shipped overseas. The reliance on sawmill residues led to imbalances between supply and demand for fiber as the sawmilling sector retrenched in the 2008–2009 recession. This has led mills to turn to roundwood or other non-sawmill sources of fiber. The wood pellet industry and use of wood pellets as energy are in their relative infancy in North America and the recent growth of both has been fueled by increases in the cost of fossil energy. However, policies aimed at reducing carbon dioxide emissions into the atmosphere could loom as bigger factors in the future.
Article
This study adopts an integrated life-cycle approach to assess overall carbon saving related with the utilization of wood pellets manufactured using pulpwood and logging residues for electricity generation. Carbon sequestered in wood products and wood present in landfills and avoided carbon emissions due to substitution of grid electricity with the electricity generated using wood pellets are considered part of overall carbon savings. Estimated value of overall carbon saving is compared with the overall carbon saving related to the current use of pulpwood and logging residues. The unit of analysis is a hectare of slash pine (Pinus elliottii) plantation in southern USA. All carbon flows are considered starting from forest management to the decay of wood products in landfills. Exponential decay function is used to ascertain carbon sequestered in wood products and wood present in landfills. Non-biogenic carbon emissions due to burning of wood waste at manufacturing facilities, wood pellets at a power plant, and logging residues on forestlands are also considered. Impacts of harvest age and forest management intensity on overall carbon saving are analyzed as well. The use of pulpwood for bioenergy development reduces carbon sequestered in wood products and wood present in landfills (up to 1.6 metric tons/ha) relative to a baseline when pulpwood is used for paper making and logging residues are used for manufacturing wood pellets. Avoided carbon emissions because of displacement of grid electricity from the electricity generated using wood pellets derived from pulpwood fully compensate the loss of carbon sequestered in wood products and wood present in landfills. The use of both pulpwood and logging residues for bioenergy development is beneficial from carbon perspective. Harvest age is more important in determining overall carbon saving than forest management intensity.
Article
The capacity for forests to aid in climate change mitigation efforts is substantial but will ultimately depend on their management. If forests remain unharvested, they can further mitigate the increases in atmospheric CO2 that result from fossil fuel combustion and deforestation. Alternatively, they can be harvested for bioenergy production and serve as a substitute for fossil fuels, though such a practice could reduce terrestrial C storage and thereby increase atmospheric CO2 concentrations in the near‐term. Here, we used an ecosystem simulation model to ascertain the effectiveness of using forest bioenergy as a substitute for fossil fuels, drawing from a broad range of land‐use histories, harvesting regimes, ecosystem characteristics, and bioenergy conversion efficiencies. Results demonstrate that the times required for bioenergy substitutions to repay the C Debt incurred from biomass harvest are usually much shorter ( Document Type: Research Article DOI: http://dx.doi.org/10.1111/j.1757-1707.2012.01173.x Publication date: November 1, 2012 $(document).ready(function() { var shortdescription = $(".originaldescription").text().replace(/\\&/g, '&').replace(/\\, '<').replace(/\\>/g, '>').replace(/\\t/g, ' ').replace(/\\n/g, ''); if (shortdescription.length > 350){ shortdescription = "" + shortdescription.substring(0,250) + "... more"; } $(".descriptionitem").prepend(shortdescription); $(".shortdescription a").click(function() { $(".shortdescription").hide(); $(".originaldescription").slideDown(); return false; }); }); Related content In this: publication By this: publisher By this author: Mitchell, Stephen R. ; Harmon, Mark E. ; O'Connell, Kari E. B. GA_googleFillSlot("Horizontal_banner_bottom");
Article
The US Department of Energy has set an ambitious goal of replacing 30% of current petroleum consumption with biomass and its products by the year 2030. To achieve this goal, various systems capable of handling biomass at this magnitude have to be designed and built. The transportation system for a cotton gin was studied and modeled with the current management policy (FIFO) used by the gin to gain understanding of a logistic system where the processing plant (gin) pays for the transportation of the feedstock. Alternate management policies for transporting cotton modules showed significant time savings of 24% in days-to-haul. To design a logistics system and management strategy that will minimize the cost of biomass delivery (round bales of switchgrass), a seven-county region in southern Piedmont region of Virginia was selected as the location for a 50 Mg/h bioprocessing plant which operates 24 h/day, 7 days/week. Some of the equipment are not be commercially available and need to be developed. The transport equipment (trucks, loaders and unloaders) was defined and the operational parameters estimated. One hundred and fifty-five secondary storage locations (SSLs) along with a 3.2-km procurement area for each SSL were determined for the region. The travel time from each SSL to the plant was calculated based on a network flow analysis. Seven different policies (strategies) for scheduling loaders were studied. The two key variables were maximum number of trucks required and the maximum at-plant inventory. Five policies were based on "Shortest Travel Time - Longest Travel Time" allocation and two policies were based on "Sector-based" allocation. Policies generating schedules with minimum truck requirement and at-plant storage were simulated. A discrete event simulation model for the logistic system was constructed and the productive operating times for system equipment and inventory was computed. Lowest delivered cost was 14.68/Mg with truck cost averaging 8.44/Mg and loader cost averaging $2.98/Mg. The at-plant inventory levels were held to a maximum of 390 loads. The loaders operated less than 9,500 hours and the unloaders operated for a total of 2,700 hours for both systems simulated.