Supporting Online Material for “A
reassessment of global bioenergy potential
in 2050”
The following material provides additional methodological detail and literature
references for the adjustment factors described in the main text.
Available land area
The land area sustainably available for bioenergy production depends on [1] how
much land is required for other uses, mainly agriculture, and [2] what types of
land can be converted to bioenergy plantations in a “sustainable” world.
Land required for other uses includes cropland, pasture, urban areas, and
plantations and forests harvested for wood products. Agricultural area (cropland
and pasture) together comprises about 38% of the world’s surface area
(Organization, 2013). The world’s agricultural area has historically expanded to a
lesser degree than the increase in population (FAO, 2003) – this is because
yields of agricultural crops, or the amount of food produced per unit land, have
steadily and linearly increased from the mid-20th century to the present
(Alexandratos, 1999, Balmford et al., 2005, Calderini & Slafer, 1998, Evans,
1997, Finger, 2010, Hafner, 2003) (before this, yield increases were much slower
(Calderini & Slafer, 1998)). Recent studies have shown that yields of cereal
crops in developed countries have begun to stagnate (Brisson et al., 2010,
Calderini & Slafer, 1998, Finger, 2010, Kucharik & Ramankutty, 2005, Lin &
Huybers, 2012) – yields may still be increasing, but at a slower rate than over the
past half century. This is because farmers have exhausted many techniques for
improving yields (fertilizer, irrigation, pesticides and herbicides, and many
breeding techniques such as dwarfing and increasing the harvest index) (ADAS
et al., Bell et al., 1995, FAO, 2003), and future yield improvements will come at a
greater cost. Thus, yields of major crops are expected to slow in the coming
decades (Cassman, 1999, Evans, 1997, FAO, 2003, OECD-FAO, 2012).
Additionally, climate change may already be impacting yields (Brisson et al.,
2010, Lobell et al., 2011) and this effect is expected to increase over time (Parry
et al., 2004).
Yields tend to be lower in developing countries as farmers in these regions have
not yet employed all the techniques described above – there is arguably some
room to catch up. But the factors that have slowed yield increases in developing
countries, such as lack of education and infrastructure, are likely to persist in the
future. Some studies have shown that farmers in developing countries actually
choose not to grow high-yielding strains because they require fertilizer and
irrigation the farmer cannot afford, and produce less straw for animal feed (Parikh
& Krömer, 1985, Yevich & Logan, 2003).
In addition, some studies include scenarios with a globally vegetarian population
(e.g. Wolf et al., 2003). Animal products (meat, dairy, eggs) require more land to
produce than vegetables or grains, because the animal feed must be produced
on additional land. The production of one kilogram of animal product can take 490 kg of feed (Bouwman et al., 2005, FAO, 2003). Thus, by assuming lower meat
consumption, one would project a much smaller land area required to feed a
global population than with continued meat consumption. Indeed, the global
average meat consumption per capita has been rising, led by an increase in
meat consumption in developing countries (Daniel et al., 2011, FAO, 2003,
Institute, 2011), requiring more resources to feed each person. At the same time,
per capita meat consumption in the U.S. has stopped increasing; in particular
Americans have been consuming less beef (Meyer & Steiner, 2011), the most
land-intensive animal product (Bouwman et al., 2005, FAO, 2003), suggesting
there may be a limit on how much animal products (relatively affluent) people are
willing to eat. Thus it is reasonable to assume that per capita meat consumption
will either remain steady or slowly increase to 2050.
Due to the above factors, it is likely that global agricultural area will still expand
as population grows. Estimates of the increase in cropland expected from 2000
to 2050 include 4.7% (Bruinsma, 2009) and 8-14% (Balmford et al., 2005), while
studies that project pasture as well as cropland predict area increases of 18%
(Tilman et al., 2001) and 9% (Wirsenius et al., 2010). In addition, we calculate a
10.5% increase by 2050 by extrapolating FAO’s projection to 2030 (FAO, 2003),
assuming that cropland abandonment in the developed world continues at its
historical rate. Based on these estimates, we expect a global increase in
cropland and pasture of 10% by 2050. We assume that this expansion occurs
proportionally on different types of undisturbed land.
For our land area analysis, we use FAOSTAT data on land use in 2000: 11.7% of
Earth’s total land area is food crops, 30.1% is pasture, 29.5% forest, 3.3% inland
water, and the rest grassland, savannah, desert, and a relatively small amount of
rock or permanent ice cover. We combine this data with the Terrestrial
Ecoregions database (Olson et al., 2001) which breaks down non-forest natural
land into ecosystem types. We assumed that pastureland occurs evenly on all
types of non-forested land (which likely overestimates pasture in desert – most of
the world’s deserts are vegetated but dry – and underestimates the allocation of
more productive land to pasture). The remaining undisturbed land is, as a
percentage of total global land area, 30% forest, 4% tundra, 11% desert, 0.3%
wetlands, 1% woodlands, 2% mountainous grassland/shrubland, and 8% other
grassland and savannah.
All of the studies we review (Beringer et al., 2011, Field et al., 2008, Fischer &
Schrattenholzer, 2001, Hoogwijk et al., 2009, Hoogwijk et al., 2005, Smeets et
al., 2007, van Vuuren et al., 2009, WBGU, 2009, Wolf et al., 2003, Yamamoto et
al., 2001) assume that global forest area must be conserved in a sustainable
world. To be consistent with this assumption, we exclude forest area from land
availability. We also exclude ecosystem types with high carbon stock: tundra,
wetlands, and woodlands. It would not be practicable to attempt production of
bioenergy on desertland*, so we exclude this category as well. The remaining
area of grassland, savannah, and montane grassland/shrubland that we consider
available for bioenergy production totals 124 Mha, or about 10% of the Earth’s
surface. We apply an accessibility factor of 0.75, following Van Vuuren et al.
(2009); the result is 0.93 Mha available. This should be considered the maximum
amount of land that could be converted to bioenergy production, as some, such
as the mountainous grassland, may be inaccessible. Converting this much land
would result in widespread losses in ecosystem services, would likely affect
water supply and quality, and would result in a substantial loss of biodiversity;
thus calling this scenario “sustainable” may not adequately recognize the
potential negative environmental consequences. Moreover, land conversion on
this scale is likely to incentivize conversion of forest and other high carbon stock
land as well – even with relatively robust land use planning regulation,
experience suggests that it is unlikely to be possible to prevent all abuses.
We applied the adjustment factor for land availability by multiplying the global
biomass potential in each study by the ratio of available land area assumed in
that study to 0.93 Gha. For example, available land area in Fischer &
Schrattenholzer (2001) was assumed to be 3.3 Gha; we multiplied the global
biomass potential in this study by 0.93/3.3 or 0.28.
Energy crop yields
In Searle & Malins (submitted), we reviewed currently attainable yields of five
promising energy crops (Miscanthus, switchgrass, poplar, willow, and
Eucalyptus) as well as the potential for yield improvement of these crops.
Reported yields are as high as 44 t ha-1 yr-1 for Miscanthus, 35 t ha-1 yr-1 for
switchgrass, 21 t ha-1 yr-1 for willow, 35 t ha-1 yr-1 for poplar, and 51 t ha-1 yr-1 for
Eucalyptus (references in Searle & Malins, submitted). But for all of these crops,
yields of 0 t ha-1 yr-1 have also been reported, reflecting limitations to geographic
range (e.g. growing Miscanthus x giganteus in northern Europe) or extremely low
yields on poor or degraded land (e.g. Eucalyptus on “skeletally dry” land). The
highest reported yields for energy crops are almost always measured on very
small experimental plots that are regularly irrigated, fertilized, and carefully hand
harvested. As explained in the review, yields are systematically lower when
grown at commercial scale on land that is marginal for agriculture (assuming all
arable land is needed for food production; see above section on land availability),
*
It may be possible to cultivate algae in enclosed ponds on desert land (i.e. greenhouses, to
avoid high evaporation), but the economic viability of such projects has been far from
proven and so we do not include this potential here.
due to biomass losses when drying perennial grasses in the field, edge effects
such as higher light availability on experimental plot margins, and unavoidable
harvesting losses when using commercial machinery. In Searle & Malins
(submitted), we provide reasonable yields that may be expected at scale on nonarable land: 3-15 t ha-1 yr-1 for Miscanthus and 2-10 t ha-1 yr-1 for switchgrass
after drying; 3-10 t ha-1 yr-1 for poplar and willow SRC; and 5-15 t ha-1 yr-1 for
Eucalyptus SRC.
In Searle & Malins (submitted), we also explore the potential for yield
improvement of the above crops. Barriers to yield improvement include low
investment (relative to food crops), lack of yield response to fertilizer, long
breeding periods, and lack of applicability of the harvest index. In particular,
Miscanthus is a sterile triploid that cannot be readily bred from its parent species,
severely hindering breeding efforts. Thus, we do not expect substantial yield
improvement for these energy crops to 2050.
Production costs
We largely follow the cost analysis performed by Van Vuuren et al. In this study,
the authors modeled the cost of biomass production and harvest in all locations
they projected would be available for energy crop cultivation, using a similar
methodology to that in Hoogwijk et al. (2009). It is difficult to project what the cost
viable price of biomass will be in 2050. Today it is high, at least in the U.S., with
estimates of $75-133 t-1 (National Research Council of the National Academies,
2011), $37.08 t-1 (Epplin, 1996), $74.30 t-1 (Duffy & Nanhou, 2001), and $41-58 t1 (excluding transportation costs) (Khanna et al., 2008). The DoE has projected
that biomass would be economically viable at $60 t-1 (Oak Ridge National
Laboratory, 2011), although it is not clear upon what they base this assumption.
These prices are currently too high for biofuel and bio-power producers to break
even without government subsidies.
We expect that biomass will have to be cost competitive with coal, today’s default
feedstock for energy generation, at least in the power sector. The U.S. average
price of coal in 2011 was $41 per ton (U.S. Energy Information Administration,
2011b), equivalent to $1.44 GJ-1.
Government subsidies for biomass energy exist today – for example the
Renewable Fuels Standard and production tax credits in the U.S., and the
Renewable Energy Directive and Fuel Quality Directive in the E.U., as well as tax
credits for certain member states. We expect some form of government support
for clean energy to persist in the coming decades. The $1.01 ga-1 tax credit for
cellulosic biofuel in the U.S. is roughly equivalent to a $33 tCO2-1 carbon price.
The Stern Review (2006) recommended that a carbon tax start at $25-30 t-1. A
meta-analysis found that the median estimated carbon price is $20 tCO2-1. These
estimates are consistent with currently implemented carbon prices: the EU
carbon price started at 30 Euros per ton in 2005; Australia’s began at $29 t-1 in
2012; and the U.S. EPA used an estimate of $21 tCO2-1 in their CAFE
regulations. Thus, we assume that a carbon price of $30 tCO2 ($2.18 GJ-1 using
HHV of 19 GJ t-1) will be used into the future. This estimate is far lower than the
actual social cost of a marginal ton of CO2 (Stern, 2006), but may be politically
feasible in implementation. Receiving a tax credit or other form of subsidy from
reducing CO2 emissions will allow bioenergy producers to pay more for biomass.
Thus, adding the carbon price to the price of coal we have $3.62 GJ-1.
Depending on the state of climate politics in the future, it is possible that no
widely implemented carbon tax will exist, or that the carbon price could be much
higher than this – these scenarios would reduce or increase the proportion of
physical biomass potential that would be economical.
Van Vuuren et al. (2009) show the fraction of biomass potential that could be
economically harvested by production cost (Fig. 9). At $3.62 GJ-1, this figure
shows 116.45 EJ yr-1 would be available, compared to an availability of 150 EJ yr1 at infinite price; 77.63% of total bioenergy availability would be cost viable at
$3.62 GJ-1.
We apply the cost adjustment factor by multiplying the global biomass potential
by 0.776 for all studies that do not account for cost. Hoogwijk et al. (2009)
performed a similar cost analysis and reported 48% of total biomass potential
would be available at a chosen price of $2 GJ-1; for this study, we multiply the
potential at $2 GJ-1 by 1.63 (77.6% divided by 48%). Like other adjustment
factors used here, this is a coarse analysis that does not account for differences
between studies in geographical distribution of biomass or other factors like
yields. This adjustment gives us an approximation of cost limitations that is
necessary for a plausible result.
We also calculate the fraction of total biomass potential that would be available at
$8.70 GJ-1, using a carbon price of $100 tCO2-1; 98.0% of total potential would be
cost viable at this price.
Governance quality
Government support around the globe will be needed for sustainable biomass
production to reach its full potential: to promote bioenergy through a carbon tax,
subsidies, or mandates, and to set and enforce environmental standards for this
production. In some developing countries, further government support will likely
be necessary to built necessary infrastructure and to attract foreign investment. If
this support is not available, the full potential of biomass production is likely to
either not be realized, or to be achieved through unsustainable means (e.g.
deforestation).
Environmental regulation, infrastructure development, and energy investment are
all weakened under poor governance. Environmental regulation has been found
to be weaker with corruption (Fredriksson & Svensson, 2003, Lopez & Mitra,
2000), political instability (Fredriksson & Svensson, 2003), and lack of political
and civil freedoms (Barrett & Graddy, 2000). The amount of private investment in
electricity infrastructure has been linked with the regulatory strength of the
country (Cubbin & Stern, 2006, Vagliasindi, 2012) and with the level of
corruption (Okafor et al., 2011).
We use the World Bank’s World Governance Indicators (World Bank, 2012) to
assess the strength of governance in world regions. The WGI have been used to
link regulatory strength with private investment in electricity infrastructure
(Vagliasindi, 2012) and the capacity of a country to prioritize environmental
protection (Cabral et al., 2012). The WGI has been correlated with the Human
Development index and with country GDP, two other indicators commonly used
as indicators of government capacity.
We sum scores of the six factors in the WGI, all of which appear relevant to the
linkages described above: Voice and Accountability, Political Stability/No
Violence, Government Effectiveness, Regulatory Quality, Rule of Law, and
Control of Corruption. For illustration, New Zealand has a score of 578, the U.S.
scores 503, China 215, Russia 167, and Somalia 5. We assume that all countries
scoring above 500 have 100% potential to develop biomass production
sustainably. We assume that a score of 0 be associated with a 50% potential.
This may well be optimistic (for instance, it seems hard to believe that Somalia
would currently be able to achieve anything like this, regardless of the market
value of sustainable biomass), but allows for some general improvement in
political stability, etc. over time. Of course, in the next 35 years, some stable
countries may become unstable, while some unstable countries may be turned
around – we do not intend to imply that relative governance quality will be static
to 2050, simply that the prevalence of governance problems now is indicative of
what may be anticipated in future. We assume a linear increase in potential with
scores from 0 to 500.
We calculate an area-weighted average of the WGI score of countries within
regions defined in each study. For example, the WGI score of North America
would be the area-weighted average of scores from Canada, the U.S., and
Mexico. There was relatively little variation in global WGI scores among studies
(0.68-0.82). For studies that did not specify regions used (Wolf et al., 2003; Field
et al., 2008; WBGU, 2009, Yamamoto et al. 2001), we applied the average
adjustment factor from the other studies (0.727).
Forestry and forestry residues
The reassessed studies that estimated the potential from forestry and/or forestry
residues were inconsistent in inclusion of various sub-categories (such as wood
from tree plantations, resides from natural forests, etc.) and in some cases did
not include enough methodological detail to re-assess. For these reasons, we do
not perform a reassessment of biomass from forestry and forestry residues as we
do for energy crops, but instead conduct our own assessment of the availability
of residues from forestry plantations, the only forestry sub-category that could be
sustainably harvested, as explained below.
Wood harvested from natural forests cannot be “sustainable” as per our use of
the word. Trees store relatively large amounts of carbon, and so use for
bioenergy would have a long payback time (Manomet Center for Conservation
Sciences, 2010). Even selective logging is unacceptably destructive (Thiollay,
1992, Uhl & Jordan, 1984) and would result in significant losses in carbon stock
and biodiversity (Bird & Chatarpaul, 1986, Gillman et al., 1985, Thiollay, 1992,
Vasconcelos et al., 2000). It is unlikely that plantation wood will be available for
bioenergy, as discussed below. Smeets et al. also include some potential from
roadsides and urban areas, but this would amount to at most 1 EJ yr-1 of biomass
availability (FAO, 1997, FAO, 1998).
We believe there is some additional potential from forestry residues. Use of
residues from logging in natural forests (presumably undertaken for wood
products) would negatively impact biodiversity (Bird & Chatarpaul, 1986), soil
carbon (Smith et al., 1994), and soil nutrients (Hendrickson et al., 1989,
Jacobson et al., 2000, Merino & Edeso, 1999, Merino et al., 2003, Smith et al.,
1994), which would result in reduced growth in the next cycle (Alam et al., 2012,
Jacobson et al., 2000, Merino & Edeso, 1999, Merino et al., 2003, Olsson &
Staaf, 1995, Proe et al., 1996, Proe & Dutch, 1994, Smith et al., 1994, Walmsley
et al., 2009). Residue harvest from forestry plantations would incur the same
nutrient deficit, but this could be addressed by adding fertilizer to plantations
(Oak Ridge National Laboratory, 2011).
To assess the potential of wood and residues from forestry plantations, we use
FAOSTAT data to project global production and consumption of plantation
forestry products. We use FAOSTAT data on world total plantation area in 1990,
2000, 2005, and 2010, and data on global consumption of roundwood in 1990,
2000, and 2005 (2010 data on roundwood not available at the time of writing).
In 2005, total roundwood consumption was 1.70 Gm3, and total wood harvests
from plantations is estimated to be 1.05 Gm3 (assuming a typical standing stock
of 186.9 m3 ha-1 (Cuevas et al., 1991, Peichl & Arain, 2006), a typical density of
plantation wood of 0.5 g cc-1 or 0.5 t m3 (Seeley, 2013), a residue generation
factor of 0.3 (Koopmans & Koppejan, 1997, University of Montana, 2011), and
typical harvest age of 30 yrs (Monroe Timber Consultants, 2007, Rawlings
Consulting Forestry, 2009, University of Florida, 2013). By these calculations,
roundwood consumption exceeded wood harvests from plantations, and must
have been supplemented with wood harvested from natural forests.
Since roundwood consumption is unlikely to decrease in the future (with a
growing global population it seems more likely that demand will increase), it
seems likely that with the same plantation area all wood harvested from
plantations will be needed to satisfy demand for industrial and other activities
(here, “roundwood” excludes fuelwood). Expanding plantation area for the
purpose of supplying bioenergy would likely be inefficient because yields of
short-rotation coppice (which is included in our energy crop potential) generally
exceed those of traditional forestry (see “Energy crop” section); thus we assume
that plantation area will stay roughly constant to 2050.
We do consider residues from trees harvested from plantations to be available for
bioenergy, as discussed above. Following the assumptions above, we calculate
residue generation in 2050 to be 0.28 Gm3 yr-1, which, assuming 20 GJ t-1 (see
section below on heating values) is equivalent to 1.5 EJ yr-1. We apply the
“political stability” adjustment for a final forestry residue availability of 1.1 EJ yr-1.
Crop residues
Crop residues are the above-ground parts of the plant that are not the primary
product for which the crop was grown. Examples are the stalk, leaves, and cobs
of corn, or the stalk of cotton plants. Biomass potential from crop residues was
included in Fischer & Scrattenholzer (2001) and Smeets et al. (2007). Because
their calculations and data sources differed, we do not reassess their estimates
and instead generate our own as follows.
We calculate global residue production for the present using FAOSTAT data on
production of the world’s top 12 crops. The residue ratio describes the quantity of
residue produced per unit crop; in the case of wheat, this can be thought of as
straw:wheat. We use residue ratios from the following sources: field residues
(stalks and leaves) of rice, barley, maize, wheat from Scarlat et al. (2010), with
process residues (corn cobs, hulls, etc.) from Koopman & Kopejan (1997) and
Collins et al. (2000); soybeans, oil palm fruit and cassava from Koopman &
Kopejan (1997); tomatoes from (Mingo et al., 2004); potato from (Milbrandt,
2009); sugarcane from (Kim & Dale, 2004). We assumed the sweet potato
residue ratio to be the same as potato. The residue ratio for sugarbeet was
calculated from an estimate of 38 t ha-1 residues at the central location in (Beeri
et al., 2005) and 10-year average U.S. sugarbeet yields (U.S. Department of
Agriculture, 2013).
Not all residues produced can be considered available. Some fraction of residues
should be left in the field for sustainable best practice farming, to reduce erosion.
Also, some residues are currently used for animal bedding and small-scale
horticultural uses, and these uses should not be displaced because any
replacement material (e.g. woodchips) would drive resource demand in another
sector (in this example forestry).
A number of experimental studies have shown that residue retention in the field is
effective at reducing erosion and loss of soil carbon and nutrients. The U.S.
Department of Agriculture conducted a comprehensive review on residues and
erosion control (Andrews, 2006) and found that generally 70% residue retention
is required, based on findings that erosion levels off at higher than 70% retention
% (Lindstrom, 1986, as cited in Andrews, 2006), a similar finding to that in
(Papendick & Moldenhauer, 1995). Similar results are found in the lierature: 70%
in (Graham et al., 2007); 100% for conventional till, 82% for reduced till, and 55%
for no till in the U.S. Department of Energy’s Billion Ton Study (Oak Ridge
National Laboratory, 2011); 75% for corn with conservation tillage at typical
yields, and 100% for corn-soybean rotations or conventional till with any crop in
(Wilhelm et al., 2007). Thus, here we reserve 70% of crop residues for soil
quality. We reduce residue availability by a further 10% (of total residue
production) to account for harvesting losses such as stubble than cannot be
reasonably harvested.
Scarlat et al. (2010) estimated that 11% of residues are used in animal
husbandry over the whole of the EU. Off-farm residue use has been estimated at
5% (Kadam & McMillan, 2003) and 6% (Glassner et al., 1999, as cited in Kim &
Dale, 2004). Based on these findings, we reserve 10% of residues for other uses
such as animal bedding.
We calculate net availability of crop residues as:
Availability = ([crop production] x [residue ratio]) – [unharvestable fraction] –
[fraction for SOC] – [fraction for other uses]
Total residue production and net availability are shown for the top 12 produced
crops globally in Table 1.
Table 1
Global production and availability of residues from top 12
crops.
TOTAL CROP
PRODUCTION
IN 2011
†
(MTONNES)
RESIDUE
RATIO‡
TOTAL RESIDUE
PRODUCTION
(MTONNES)
Sweet
potatoes
104
0.11
12
Barley
140
1.18
Tomatoes
146
Oil palm fruit
213
CROP
TOTAL RESIDUE
AVAILABILITY
(MTONNES)
TOTAL
RESIDUE
AVAILABILITY
(EJ/YR)§
1
0.02
165
16
0.29
1.19
174
17
0.31
0.26
56
6
0.10
†
Data from FAOSTAT
‡
Here, residue ratio is shown as dry mass of residues : fresh mass of crop.
§
Based on a higher heating value of 17.5 MJ kg-1; see section below on heating values.
Cassava
234
0.52
121
12
0.21
Soybeans
237
3.50
829
83
1.45
Sugar beet
242
0.27
65
7
0.11
Potatoes
334
0.11
38
4
0.07
Wheat
657
1.18
776
78
1.36
Rice
683
1.58
1081
108
1.89
Maize
813
1.27
1036
104
1.81
Sugar cane
1658
0.16
261
26
0.46
Sum
5461
11
4614
461
8
This assessment of global residue availability is similar to Kim & Dale (2004) who
projected 26 EJ yr-1; that study assumes a 60% residue retention rate and does
not account for other uses of residues. Bloomberg New Energy Finance (2012)
calculates 16 EJ yr-1 of residue availability in 8 major world regions (covering a
majority of total land area and population) in 2030; this study uses similar
assumptions of field residue retention and other uses as the present study.
We then apply the adjustments used for energy crops on production and
harvesting cost and governance, as crop residues can be very expensive to
collect (National Research Council of the National Academies, 2011) and
collection systems and likely to be affected by political stability. This brings us to
4.6 EJ yr-1.
As discussed above, we project global cropland area to increase to 2050, but
since the harvest index of plants (the ratio of grain to residues) has increased
over time for major grains (Calderini et al., 1995) and will likely continue to do so,
we expect overall residue generation to be similar to the present.
Wastes
Many types of waste could potentially be available for energy, including municipal
solid waste, sewage, animal manure, and processing waste from various
industries. Sufficient information to analyze the potential from some of these
pathways is currently inadequate, and we lack the resources to cover every type
of waste. Thus, here we consider the potential of energy from animal manure and
municipal solid waste (MSW), two of the largest potential sources.
MSW is already collected for disposal in many cities, which pay money for
disposal or landfilling, and so diverting to energy use would likely result in
negative costs (Faaij et al., 1998). We rely on (Shi et al., 2009), who modeled the
global availability of waste paper (paper comprises more than half of organic
material in MSW (Easterly & Burnham, 1996)). This study determined that 83
billion L per year of ethanol could be produced from waste paper. We calculate
this to be equivalent to about 5 EJ yr-1. We apply the governance adjustment
factor as MSW collection infrastructure is only likely to exist in relatively wellgoverned states; thus we arrive at 3.4 EJ yr-1.
Use of animal manure, or dung, could create sustainability concerns. In
developing countries significant amounts of dung are used as fertilizer for crop
fields, where farmers cannot afford or do not have access to inorganic fertilizers
(Habtetsion, 2000, Lupwayi et al., 2000)– dung is also widely used as fertilizer in
the EU (FAO, 2003). Crop yields would very likely suffer if this dung were
diverted to energy use (Habtetsion, 2000, Lupwayi et al., 2000, Mekonnen &
Kohlin, 1995, Saleque et al., 2004). As we implicitly assumed yield growth of food
crops in our land availability analysis, it is likely that dung will be needed to
maintain and improve yields of crops in developing countries and the EU. Thus,
we exclude the biomass potential from dung.
Heating values
The bioenergy potential studies reviewed here typically calculate biomass
availability in terms of mass, and then convert this to energy using a heating
value. We use higher heating values as these are more consistently reported in
the literature and are consistent with our conversion efficiencies below. Heating
values in the literature for poplar feed are 20.1(National Renewable Energy
Laboratory, 2011), 19.38 (Sannigrahi et al., 2010), 20.7-24.1 (Klasnja et al.,
2002), and 18.79 MJ kg-1 (Telmo & Lousada, 2011), and 22.5 MJ kg-1 for willow
(Klasnja et al., 2002). For Miscanthus reported HHVs are 18.04-18.92 MJ kg-1
(Lewandowski & Kicherer, 1997), and for Eucalyptus 18.16-19.67 (Lemenih &
Bekele, 2004), 19.1-19.5 (Lewandowski & Kicherer, 1997), and 17.63 MJ kg-1
(Telmo & Lousada, 2011). For crop residues, HHVs are 17.48-18.43 (Demirbaş,
2001), 16.12-16.81 (Mani et al., 2004), 24.5 (Yu et al., 2007), 13.39-23.73
(Pordesimo et al., 2005), 17.65 (Domalski et al., 1986), 16.1-20 (Raveendran &
Ganesh, 1996), and 17.65-17.51(Sannigrahi et al., 2010). Forestry, typically pine,
has reported HHVs of 20 (Demirbaş, 1997), 20.02 (Sannigrahi et al., 2010), and
20.178 MJ kg-1 (Singh & Kostecky, 1986). Some components of forestry
residues have been found to have slightly higher HHVs than whole trees, with
20.98 MJ kg-1 for foliage, 21.10 MJ kg-1 for treetops, while bark was measured to
have an HHV of 19.56 MJ kg-1 and stumps of 19.65 MJ kg-1 (Demirbaş, 1997).
MSW has been reported to have an HHV of 17.2 (Singh & Kostecky, 1986) and
10 MJ kg-1 (Kathiravale et al., 2003), while organic waste was found to have an
HHV of 16 MJ kg-1 and waste paper of 19 MJ kg-1 (Faaij et al., 1998).
Based on this literature, we chose values of 19 MJ kg-1 for an energy crop mix of
Miscanthus, poplar, willow, and Eucalyptus, 17.5 MJ kg-1 or crop residues, 20 MJ
kg-1 for forestry and forest residues, and 17 MJ kg-1 for MSW.
We applied adjustments for HHVs in a similar fashion to the other adjustments.
For example, Hoogwijk et al. (2005, 2009) use an HHV of 15 MJ kg-1 for their
energy crops, while we believe it should be 19 MJ kg-1. Thus we multiplied the
total biomass potential from these studies by 19/15 or 1.27.
Conversion
The biomass potential estimates we have discussed to this point are estimates of
the primary energy in available biomass. The efficiency of conversion determines
the amount of final energy products (e.g. electricity, heat, biofuel) available.
Current typical conversion efficiencies are 30% for biofuel (not accounting for
coproducts) (U.K. Renewable Fuels Agency, 2012) and 80% for combined heat
and power (CHP) (IEA, 2008). With technological advance, it has been projected
that biofuel conversion efficiency could reach 53-68% including combustion of
coproducts (Hamelinck et al., 2005, Hedegaard et al., 2008, IEA, 2008, National
Renewable Energy Laboratory, 2002). Based on this range we chose a central
estimate of 60% efficiency. CHP efficiency has been reported to be as high as
88% (IEA, 2008) and has been projected to be 90% in 2030 (Hedegaard et al.,
2008), and so we believe an average efficiency of 90% should be achievable by
2050. These values were based on lower heating values. IEA (2008) reports that
HHVs are 2-5% lower than LHVs, and so we calculate an HHV for CHP of 90% x
0.965 = 87%.
Importantly, these projections account for the efficiencies of the conversion
processes themselves, and do not include energy used in feedstock production
and transport. The efficiency of bioenergy production would be significantly lower
in a life cycle approach.
We used current policy trends to predict the allocation of biomass to biofuel vs.
biopower and heat. Based on trends in EU member states’ National Renewable
Energy Action Plans (European Union Member States, 2010), the EU will use
22% of its biomass for biofuel and the remainder as electricity and heat. In the
U.S., the Energy Information Administration projects that the U.S. will continue
using much more biomass (9x more) for biofuel than power and heat (U.S.
Energy Information Administration, 2011a). Combining these two projections,
global biomass will be used 32% as biofuel and 68% as heat and power (current
CHP plants are capable of delivering the electricity:heating split in the EU
projection). This would lead to an overall conversion efficiency of biomass to
energy of 80% in 2050.
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