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5
Environmental Effects and
Tradeoffs of Biofuels
P
etroleum extraction, transport, refining, and combustion have many known negative
environmental effects, including disruption of sensitive ecological habitats and high
greenhouse-gas (GHG) emissions. Biofuels, too, have their environmental costs (NRC,
2003, 2010a), but displacing petroleum-based fuels with biofuels can reduce the nation’s de-
pendence on imported oil and potentially reduce overall environmental harm (Robertson
et al., 2008). Each stage in a biofuel’s life cycle uses nonrenewable resources and generates
emissions that affect land, air, and water. Hence, the environmental benefits and negative
effects over the life cycle of petroleum-based fuels and biofuels would have to be compared
against each other so that policymakers can decide which tradeoffs are acceptable. There
is neither a simple nor single means of comparing biofuels and petroleum-derived fuels
over their full life cycles and over their entire suites of environmental effects, yet decades
of research on this topic have revealed that some ways of producing biofuels from certain
feedstocks offer distinct advantages over others and thus have greater potential for provid-
ing environmental benefits over petroleum-derived fuels. Furthermore, certain stages in
the life cycle of biofuels have greater environmental effects than others, and thus deserve
particular attention in targeting strategies for optimizing environmental outcomes.
This chapter covers the following topics on the potential environmental effects of in-
creasing biofuel production:
• It provides an overview of the life-cycle assessment methodology typically used to
assess environmental effects of biofuel production and use.
• It examines the current state of knowledge about key environmental effects. Each
environmental effect is discussed, when applicable, in the context of feedstock
production, conversion to fuels, and combustion and over the life cycle of bio-
fuel production and use. Methods for assessing effects and the anticipated results
or observed effects reported in the published literature are presented. Gaps in
data availability and deficiencies in existing modeling platforms, each of which
181
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182 RENEWABLE FUEL STANDARD
contributes to uncertainty in assessing environmental effects, are also pointed out
in the following areas:
• GHG emissions
• Air quality
• Water quality
• Water quantity and consumptive use
• Soil
• Biodiversity
• Ecosystem services
• It uses regional environmental assessments of biofuel production as an illustration
because the effects of biofuel production are location-specific, and conclusions
drawn from regional environmental assessments could differ from an assessment
of cumulative effects across the nation.
• It discusses opportunities to minimize negative environmental effects at the end of
the chapter.
Although the committee stresses the importance of comparing environmental effects
of biofuels to petroleum-based fuels, environmental effects of petroleum-based fuels have
been covered in other publications (NRC, 2003, 2010a) and are beyond the scope of this
study.
LIFE-CYCLE APPROACH FOR ASSESSING
ENVIRONMENTAL EFECTS: AN OVERVIEW
Biofuels affect the environment at all stages of their production and use. Some effects
are easily noticed (for example, odors emanating from an ethanol plant). Others are less
apparent, including those that result from activities along the biofuel supply chain (for
example, nitrate leaching into surface waters as a result of nitrogen fertilizer application
on corn fields) and those that could occur beyond the supply chain via market-mediated
effects (for example, loss of biodiversity upon land-use change induced by higher corn
prices). Different effects can occur at local, regional, national, or global scales. Some of these
effects are easily quantified while others are difficult to measure.
To better understand the suite of environmental effects associated with biofuels, re-
searchers commonly turn to the method of life-cycle assessment (LCA). At the outset,
researchers need to define the goal and scope of LCA. For example, researchers need to
consider whether the goal is to assess the effects of biofuel produced at an individual bio-
fuel production facility, the average effect of biofuel produced for the entire nation, or the
effect of biofuel produced as a result of a policy mandating additional production. Then,
an inventory of the resources used and net quantities of substances emitted as a result of
biofuel production and use is compiled. This inventory is used to prepare an impact assess-
ment that quantifies the ultimate effects on human health, ecosystem function, and natural
resource depletion. Numerous methods for compiling inventories and conducting impact
assessments exist, all of which have particular strengths and limitations in their modeling
of specific processes and the availability and quality of data used to populate these models.
LCA is a valuable tool for quantifying the environmental effects of biofuels, yet wide-
spread misinterpretation of the results from studies using different assessment methods has
led to great confusion. More often than not, this confusion arises when conclusions from these
studies are reported without mention of the particular framework and assumptions under
which the analyses were conducted. For example, statements such as “this biofuel releases
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ENVIRONMENTAL EFFECTS AND TRADEOFFS OF BIOFUELS
less of this pollutant than gasoline” are by themselves meaningless and often misleading
unless the goal and scope of the study cited in support of this statement are presented. (See
Box 5-1 for a description of the importance of care when reporting results from LCA studies.)
A common problem is confusion over two different approaches of LCA—attributional
and consequential—and their appropriate use when evaluating biofuels. Attributional
LCA, the more traditional form, traces the material and energy flows of a biofuel supply
chain and seeks to attribute environmental impact to a biofuel based upon these flows.
Consequential LCA, on the other hand, considers the environmental effects of the cascade
of events that occur as a result of a decision to produce or not to produce a given biofuel.
Many differences between these two approaches of LCA arise because of their distinct ap-
plications (Ekvall and Weidema, 2004; Ekvall and Andræ, 2006). Attributional LCA makes
use of process-specific or average data, while consequential LCA uses marginal data. Attri-
butional LCA does not consider the market-mediated effects of a given biofuel, such as en-
vironmental effects caused by changes in crop or petroleum prices as a result of biofuel pro-
duction. Consequential LCA, similar to a cost-benefit analysis, includes market-mediated
effects. In essence, attributional LCA takes as a given the total environmental effect of all
human activities and seeks to assign responsibility for a portion of the effect to a particular
biofuel. Consequential LCA also takes as a given the total environmental effect of all human
activities, but it assigns to a particular biofuel the change in total effect caused by a decision
and the resulting action of whether to implement, expand, or contract biofuel production.
As such, attributional LCA is useful in improving efficiency along a biofuel supply chain,
and consequential LCA is appropriate in the evaluation of policy and regulation.
Both attributional and consequential LCA make use of knowledge of biofuel supply
chains, but conducting the latter is far more complicated as it requires marginal data and
modeling of market-mediated effects (Kløverpris et al., 2008; Finnveden et al., 2009). In ad-
dition, consequential LCA requires preparation of two alternate scenarios (that is, scenarios
that represent “yes” and “no” to a decision) whereas attributional LCA requires only one
scenario be described (that is, an actual or a projected scenario). Similarly, when measuring
the direct environmental effects of supply chains themselves, attributional LCA can rely
on actual, measured data, whereas consequential LCA requires that at least one set of data
be estimated: When evaluating policies already fully implemented, one set would have to
be estimated (that is, the scenario that did not occur) and when evaluating policies with
future effects, two sets would have to be estimated (that is, the scenarios for both the “yes”
and “no” to a decision). In total, the uncertainty surrounding the results from consequential
LCA is compounded compared to attributional LCA, complicating its use in policy deci-
sions, even where LCA is mandated such as in the Renewable Fuel Standard as amended
in the Energy Independence and Security Act of 2007 (RFS2).
This discussion of LCA methodology is important to understanding the environmen-
tal effects of biofuels. To date, a large number of studies have used attributional LCA to
evaluate individual biofuel production streams and the biofuels industry as a whole. Such
studies are helpful for assessing the environmental performance of biofuel supply chains,
but they do not consider the broader range of effects from increased biofuel production,
such as the effects mediated by markets. Only studies that specifically estimate the environ-
mental effects resulting from the marginal increase in fuel production caused by RFS2 are
appropriate for assessing the environmental effects of increasing biofuel production due to
its implementation. Studies that have used consequential LCA as a means of quantifying
the marginal impact of increased biofuel production are sparse and much needed. In this
chapter, results using both methods are presented, with the caveat that what might have
been found under one set of circumstances may not hold under other conditions.
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ENVIRONMENTAL EFFECTS AND TRADEOFFS OF BIOFUELS
GREENHOUSE-GAS EMISSIONS
Feedstock Production
One of the most debated topics surrounding the environmental effect of biofuels is the
net GHG emissions from producing various feedstocks. Potential GHG emissions from
bioenergy feedstock production include carbon dioxide (CO2), nitrous oxide (N2O), and
methane (CH4).1 As elaborated below, the key factors that affect GHG emissions from
bioenergy feedstock production are site-specific and depend on the type of feedstocks pro-
duced, the management practices used to produce them, and any land-use changes that
their production might incur.
Type of Feedstock and Management Practices
Potential bioenergy feedstocks mentioned in Chapter 2 can be categorized as annual,
herbaceous perennial, short-rotation woody crops (SRWCs), and residue from other sys-
tems such as corn stover or forest residue. Choice of feedstock is an important factor in
determining the GHG effect of biofuels. For example, perennial herbaceous biomass could
increase soil carbon sequestration compared to annual crops (Anderson-Teixeira et al., 2009;
Blanco-Canqui, 2010; NRC, 2010b). The GHG implications of a particular feedstock depend
on the relationship between that feedstock and site properties such as soil type and climate.
As with any agricultural crop, management practices affect the net GHG balance of bioen-
ergy feedstock production in several ways: cropping patterns, amount of agrichemical use,
tillage practices, and farm equipment use.
Farmers and foresters select management practices on the basis of crops grown, soil
conditions, precipitation patterns, slope, exposure, available equipment, and their knowl-
edge and preferences. In general, choices are made to maximize yield per dollar of input
and are not made on the basis of GHG emissions. Yet, choices of management practices have
a major influence on GHG emissions (NRC, 2010b). CO2 released from fossil fuel combus-
tion in the manufacturing, transport, and application of agricultural inputs (for example,
fertilizers, pesticides, seed, and agricultural lime), N2O released during nitrogen fertilizer
production (Snyder et al., 2009), and N2O released because of nitrification and denitrifica-
tion stimulated by nitrogen fertilizer application (Bouwman et al., 2010) contribute to GHG
emissions. Therefore, producers who choose to cultivate bioenergy feedstocks that require
higher agrichemical input in place of crops that require less agrichemical input would incur
increases in GHG fluxes. Some bioenergy energy feedstock such as forest residue would
have no GHG contribution from agrichemical input.
Agricultural soil management accounted for about 68 percent of the total N2O emis-
sions in the United States in 2008 (EPA, 2010c). Emission of N2O is predominantly a result
of microbial processes of nitrification and denitrification; therefore, emission generally
increases with nitrogen availability, or the extent to which nitrogen input exceeds crops’
needs (Bouwman et al., 1993, 2002; McSwiney and Robertson, 2005). The type and timing of
nitrogen fertilizer used also affects N2O fluxes (Bavin et al., 2009). Technologies for precise
application of fertilizers can potentially reduce fertilizer use without compromising yield
(Snyder et al., 2009; Gebber and Adamchuk, 2010; Millar et al., 2010), but those technologies
are not widely adopted because of socioeconomic, agronomic, and technological reasons
1 Globalwarming potential of a GHG is the warming caused by emission of 1 ton of that GHG compared to 1
ton of CO2 over a specific time interval. The global warming potentials over a 100-year period are 1 for CO2, 25
for CH4, and 298 for N2O.
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186 RENEWABLE FUEL STANDARD
(Robert, 2002; Lamb et al., 2008; USDA-NIFA, 2009). Precision management of nitrogen
fertilization can also improve biomass quality for cellulosic biofuels (Gallagher et al., 2011).
The environmental benefits of crop rotations include enhanced control of weeds, pests,
and diseases; increased availability of nutrients; accumulation of soil carbon; and higher
yields (NRC, 2010b). Those benefits, if combined with higher yields, contribute to reduc-
ing agrichemical input and GHG emissions. Increased diversity of crops planted in a field
(either at once or over the course of a year) could also reduce the amount of pesticide appli-
cation needed (GAO, 2009). For example, mixtures that include grasses and nitrogen-fixing
legumes can also reduce nitrogen fertilizer needs (Tilman et al., 2006; Fornara and Tilman,
2008; NRC, 2010b). Gardiner et al. (2010) compared preexisting corn, switchgrass, and
mixed prairie crops in Michigan and found that switchgrass and mixed prairie crops sup-
ported greater abundance of arthropod generalist natural enemies of crop pests. Even crop
rotation between corn and soybean can help control pests and reduce the use of pesticides
by breaking the pattern of pests and disease that can be present in monocultures. Integrated
pest management can potentially contribute to reducing pesticide input (Trumble et al.,
1997; Reitz et al., 1999; NRC, 2010b).
The effect of no-till and reduced tillage on soil organic carbon (SOC) storage is incon-
sistent and depends on depth of soil sampling and crop management (Dolan et al., 2006;
Baker et al., 2007; Johnson et al., 2007; Luo et al., 2010; Kravchenko and Robertson, 2011).
Studies that assess carbon content in the entire soil profile (0-60 cm) did not find higher
soil carbon in no-till fields than in conventionally tilled fields (Blanco-Canqui and Lal, 2008;
Christopher et al., 2009). Nonetheless, no-till and reduced tillage may contribute to reduc-
ing GHG emissions because those practices require less fossil-fuel inputs for machinery that
perform the tilling (Adler et al., 2007) and emissions of N2O might be lower (Omonode et
al., 2011). No-till and reduced tillage also have other environmental benefits because they
enhance soil water retention and microbial activity and diversity, reduce soil erosion and
sediment runoff, and improve air quality compared to conventional tillage (NRC, 2010b).
Methods of Assessment
Over the past several decades, ecosystem ecologists have estimated carbon storage and
GHG consequences of land-use management practices on regional and continental scales,
using spatial databases to represent key driving variables, including soils (for example,
STATSGO), average climatic data, satellite imagery (for example, MODIS), and current
or projected land-use management, combined with simulation models. This strategy has
been used to assess consequences of cropping (Campbell et al., 2005; Del Grosso et al.,
2005; Izaurralde et al., 2006), forest management (Adams et al., 1999; Sohngen and Sedjo,
2000; Murray et al., 2005; Johnson et al., 2010), and climate change (Paustian et al., 1997;
Lu and Zhuang, 2010). Notably, simulation results (and indeed the biological processes re-
sponsible for GHG fluxes) are very sensitive to site-specific factors that are variable. Those
site-specific factors, including fertilization practices, cultivation and residue management,
and forest age classes, are rarely available as input data. Thus, potential error increases for
scaled-up estimates, based on the presence, accuracy, and spatial resolution of input data,
and the ability of simulation models to accurately estimate fluxes.
Zhang et al. (2010) used this strategy to assess environmental effects including GHG
emissions that might occur based on spatially explicit scenarios of bioenergy feedstock
expansion, including annual crops, herbaceous perennial crops, SRWC, and residue har-
vest. They predicted locations for different bioenergy crops and management options in a
nine-county region in southwestern Michigan that would minimize GHG emissions while
maintaining certain minimum yields and maximum nitrate runoff levels. They presented
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ENVIRONMENTAL EFFECTS AND TRADEOFFS OF BIOFUELS
sample results involving the minimization of GHG flux per unit area, although the flex-
ibility of their framework allows for the calculation of other variables of interest, such as
GHG flux per unit of energy produced, which may be more useful for integration with full
LCAs. In addition, Zhang et al. (2010) noted that their framework could be extended into
a spatially explicit LCA in which, for example, optimal locations for biorefineries could be
modeled simultaneously with feedstock production locations.
Anticipated or Observed Results
As mentioned above, the effects of bioenergy feedstock production on GHG emissions
depend on feedstock choice, management practices, and changes in land use and land cover
so that any quantitative estimates of GHG emissions are site specific. This section discusses
the anticipated or observed effects of feedstock production on GHG emission as organized
by major feedstock categories.
For corn and soybean production, fertilizer use generates GHGs as a result of fossil-
fuel input in manufacturing and transporting fertilizers and of nitrogen from fertilizers
not taken up by plants and emitted as N2O. In 2005, about 95 percent of the corn acreage in
the United States received nitrogen fertilizer, and the average application rate was about
138 lb/acre (Table 5-1). Soybean requires less inputs (particularly nitrogen fertilizers) to
produce than corn on a per-acre basis (Schnepf, 2004). However, a comparison of GHG
contribution from fertilizer manufacture and use in feedstock production between biofuels
have to account for crop yield per acre,2 conversion yield from feedstock to biofuel,3 and
the energy content of biofuel.4
The opportunity offered by the future use of cellulosic feedstocks is that GHG emis-
sions could be reduced, but that benefits can only be achieved in some situations. Corn
stover, cereal straw, and other crop residues draw on existing crops so that their use as bio-
energy feedstock under best management practices might not contribute much additional
GHG emissions. However, overharvesting of crop residues could result in additional need
for agrichemical inputs and the loss of soil organic matter, which is critical for maintaining
soil structure and water retention capacity and for improving nutrient cycling and other
soil processes (Wilhelm et al., 2007; NAS-NAE-NRC, 2009; NRC, 2010b). Any additional
fuel use for collecting the residues that contributes to GHG emissions would also have to
be accounted for.
TABLE 5-1 Fertilizer Use for Corn and Soybean Production in the United States
Corna Soybeanb
Acreage fertilized receiving nitrogen fertilizer (percent) 96 18
Average rate of nitrogen fertilizer application (lbs/acre) 138 16
Acreage fertilized receiving phosphate fertilizer (percent) 81 23
Average rate of phosphate fertilizer application (lbs/acre) 58 46
Acreage fertilized receiving potash fertilizer (percent) 65 25
Average rate of potash fertilizer application (lbs/acre) 84 80
aLatest
data from source are for the year 2005.
bLatest
data from source are for the year 2006.
SOURCE: USDA-ERS (2010c).
2 Corn yield per acre is about 4 times higher than soybean yield (USDA-NASS, 2010).
3 About 1 bushel of soybean produces 1.5 gallons of biodiesel, while 1 bushel of corn produces about 2.7 gallons
of ethanol.
4 The energy content of corn-grain ethanol is about two-thirds of that of soybean biodiesel.
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188 RENEWABLE FUEL STANDARD
Growing perennial dedicated bioenergy crops could have less direct GHG emissions
than growing row crops because their root systems contribute to sequestration of carbon.
Surveys of common agronomic practices for growing Miscanthus show a broad range in
nitrogen fertilizer use, typically around 50-100 lbs per acre per year (Heaton et al., 2004;
Khanna et al., 2008). In their review of published literature, Parrish and Fike (2005) reported
that data on nitrogen requirements in switchgrass span a range of 0-200 lbs per acre, and
that the variations can be partly attributed to different harvest practices, within-plant nitro-
gen recycling, and site-specific soil nitrogen mineralization rates and atmospheric deposi-
tion and microbial fixation of nitrogen. Liebig et al. (2008) measured changes in soil organic
carbon (SOC) in the top 0-30 cm and 0-120 cm of soil in switchgrass fields on 10 farms that
were previously used for annual crop production in the central and northern Great Plains.
They reported accumulation of SOC over time, but the change in SOC varied considerably
across sites from –2.2 to 16 Mg CO2 eq per hectare per year in the top 0-30 cm. Garten et al.
(2010) found that a single harvest of switchgrass at the end of the growing season increased
SOC sequestration and system nitrogen balance on well-drained Alfisols in west Tennessee.
SOC sequestration rates in the top 15 cm of reconstructed tall grass prairies on previously
cultivated land in southern Iowa varied significantly with topography and age of the prai-
rie stand (Guzman and Al-Kaisi, 2010).
Using woody residues as a bioenergy feedstock can result in relatively low GHG emis-
sions compared to crops that are planted and harvested exclusively for bioenergy purposes
if they are a byproduct of existing harvesting operations and do not require fertilizer input.
In some regions of the United States, harvesting dead material from the forest floor and
forest thinning could reduce the potential for wildfires (Fight and Barbour, 2005; Busse et
al., 2009; Kalies et al., 2010) that also contribute much CO2 to the atmosphere.
SRWC can sequester SOC depending on trees grown, soil types, and prior land use,
according to a review of literature by Blanco-Canqui (2010). The author noted that nitrogen-
fixing trees sequester more SOC than other trees. Fertilization and irrigation can increase
SOC sequestration and yield increase, but CO2 emissions associated with these activities
may offset some SOC benefits (Blanco-Canqui, 2010).
Biofuel-Induced Land-Use Changes
Carbon is stored in soil and in above-ground and below-ground vegetation. Soil carbon
storage depends on soil characteristics and past disturbances. The amount of carbon stored
in vegetation depends on the vegetation type. Therefore, land-use changes that involve
removing or planting of vegetation could either release a large amount of carbon from soil
or store carbon depending on the conditions of the land prior to use, crop characteristics
(Fearnside, 1996; Guo and Gifford, 2002b; Woodbury et al., 2006), and management prac-
tices (as discussed above). Similarly, land-use change could disrupt or enhance the future
potential of land to store carbon.
Land use is defined by anthropogenic activities, such as agriculture, forestry, and urban
development, that alter land-surface processes, including biogeochemistry, hydrology, and
biodiversity. Land cover is the extent and type of physical and biological cover over the
surface of land. Some authors have divided land-use changes into two types when consid-
ering biofuel policy: direct land-use change and indirect land-use change. Biofuel-induced
land-use changes occur directly when land is dedicated from one use to the purpose of
growing biofuel feedstock. Biofuel-induced land-use changes can occur indirectly if land
use for production of biofuel feedstocks causes new land-use changes elsewhere through
market-mediated effects. The production of biofuel feedstocks can constrain the supply of
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ENVIRONMENTAL EFFECTS AND TRADEOFFS OF BIOFUELS
commodity crops and raise prices, thus triggering other agricultural growers to respond
to market signals (higher commodity prices) and to expand production of the displaced
commodity crop. This process might ultimately lead to conversion of nonagricultural land
(such as forests or grassland) to cropland. Because agricultural markets are intertwined
globally, production of bioenergy feedstock in the United States could result in land-use
and land-cover changes elsewhere in the world. If those changes reduce the carbon stock
in vegetation, carbon would be released in the atmosphere when land-use change occurs.
In particular, transition from forest to cropland or pasture emits a large amount of CO2 be-
cause of CO2 releases from decomposition of woody debris and short-lived wood products
(NRC, 2010c). Similarly, land-use change could disrupt or enhance the future potential of
land to store carbon.
Many economic studies have shown the “unintended” consequences of policy (Stavins
and Jaffe, 1990; Wu, 2000; Wear and Murray, 2004), and the principle from Wu’s study is
relevant to increasing biofuel production in United States. Wu (2000) showed cropland
enrolled in the U.S. Department of Agriculture’s (USDA) Conservation Reserve Program
(CRP) had a 20-percent slippage. That is, for every 5 acres of cropland enrolled in CRP, 1
acre of noncropland is added to cropland elsewhere. That study did not account for carbon
emissions, but it pointed out the rippling effects of shifting land uses. Other studies have
linked land-use changes to carbon changes and showed that projects and policies intended
to mitigate GHG emissions in the forestry or agricultural sector could lead to “leakage,”5
or responses to those projects and policies by other parties that also cause GHG emissions
(Sohngen and Brown, 2004; Murray et al., 2007).
Methods of Assessment
Land-Use and Land-Cover Changes. Remote sensing using satellite and aircraft sensors
can be used to map land cover and land use and provide information on above-ground
vegetation and residue cover (NRC, 2010c). Data from remote sensing can be coupled with
land monitoring to estimate GHG fluxes from land-use changes (Houghton, 2010; NRC,
2010c; West et al., 2010). Uncertainties of annual carbon fluxes from deforestation, refores-
tation, and forest degradation based on remote sensing vary from 25 to 100 percent (NRC,
2010c). Variations in plant residue, along with soil moisture and mineralogy and vegetation
cover, are a problem in estimating soil surface carbon. Even so, progress has been made in
assessing crop residue coverage using space-borne hyperspectral instruments (Daughtry et
al., 2006; NRC, 2010c). Estimates of N2O emissions from managed lands have about 50-per-
cent uncertainty even with the best inventory methods, and those estimates are even more
uncertain in developing countries than in developed countries (NRC, 2010c).
Market-Mediated Effects. A number of different types of economic models have been
used to calculate the global indirect effects of increasing biofuel production. An important
aspect emphasized by these models is global interaction. For example, shocks to supply
and demand in one region have well-defined price effects on global markets, as illustrated
by the market price fluctuations as a result of drought in Russia in 2010. Economic models
have been developed to capture this phenomenon. The short-term and long-term effects of
biofuel policy on global commodity markets are discussed in Chapter 4.
A second aspect emphasized by these models is the competition among different
land uses. Economic models are often best suited to account for the behavior of different
5 GHG leakage is the term that was introduced to refer to the conditions when an activity displaces GHG emis-
sions outside the boundaries of the activity area (Murray et al., 2007). For example, afforestation efforts in one
country could lead to market forces that encourage deforestation in another country (Meyfroidt et al., 2010).
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190 RENEWABLE FUEL STANDARD
competing demands for land, as well as the supply of land. A number of different economic
models, including general-equilibrium and partial-equilibrium models, have been used to
study indirect land changes, and the advantages and disadvantages of several approaches
have been discussed elsewhere (Kretschmer and Peterson, 2010). The estimates of indirect
land changes are then added to direct GHG models, such as GREET,6 to estimate total di-
rect and indirect GHG emissions. Although such analyses consider emissions as a result of
market-mediated effects on land use, they are not, strictly speaking, consequential LCAs.
Rather, they represent a hybrid approach in which marginal data for a specific parameter
(land use) are incorporated into an attributional LCA model. Among many differences,
comprehensive consequential LCA would, for example, also consider elasticity of petro-
leum markets.
GHG Emissions Estimated from Market-Mediated Land-Use Changes. GHG emissions
from indirect land-use or land-cover changes can be estimated by coupling estimates of
market-mediated land-use or land-cover changes with estimates of GHG emissions from
those projected land-use or land-cover changes. The resulting projection of GHG emissions
from indirect land-use changes has large uncertainty because of difficulty to establish a
causal link between direct-use changes and indirect-use changes that are separated spa-
tially and temporally. For example, many factors influence land-use changes, and showing
precisely that a price change induced by biofuel policy as the precipitating cause is difficult.
Even if an economic linkage can be shown, calculating the carbon change is difficult be-
cause there is substantial heterogeneity in carbon on the landscape. If the indirect land-use
change involves removing tropical forests, the carbon emissions could be high, but if the
indirect land-use change involves converting pasture or fallow land to cropland, then the
carbon effects could be smaller.
Several concerns have been raised about the existing estimates of the indirect effects of
land use. One concern relates to the many steps that need to be undertaken to show indi-
rect land-use change and uncertainty associated with all those steps. For example, the first
step in any analysis of the effects of U.S. policy is to determine what crops besides corn are
displaced as a result of increased biofuel production. The second step is to determine how
much these changes in U.S. markets influence prices in other countries (Babcock, 2009; Zil-
berman et al., 2010). The key concern with these calculations is that U.S. economists have an
idea of U.S. farmers’ responses to price change on the basis of historic trends, but Babcock
(2009) argued that the response of farmers in other parts of the world to price changes is
much less certain. Similar concerns have been raised by Kim and Dale (2011), who were un-
able to find correlative evidence between increased demand for corn and land-use change
from 2001-2007. O’Hare et al. (2011) argued that Kim and Dale’s analysis was flawed. The
committee advocates that additional data and analyses are needed to assess net changes
in land use as a result of market-mediated effects of feedstock production for biofuels. A
second concern is that simulations from economic models use point estimates of various
parameters, each of which varies temporally and spatially (Zilberman et al., 2010). A third
concern is that other factors that contribute to land-use change decisions, including cul-
tural, political, and ecological factors (Geist and Lambin, 2002; Turner et al., 2007), are not
accounted for in economic models. Finally, one response to rising prices is intensification
of existing croplands. The different models discussed later account for cropland intensifica-
tion to different extents. For example, the study by Searchinger et al. (2008) assumes that
increased yields from intensification will be offset by lower yields on lower-quality lands
6 The Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation Model by Argonne National
Laboratory.
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ENVIRONMENTAL EFFECTS AND TRADEOFFS OF BIOFUELS
brought into production. The results from Hertel et al. (2010) directly incorporate intensifi-
cation of crop management as a result of rising prices. Cropland intensification helps reduce
the overall indirect effects.
Anticipated Effects
Direct conversion of native ecosystems to producing corn for ethanol releases large
amounts of GHG into the atmosphere (Fargione et al., 2008; Gibbs et al., 2008; Ravindra-
nath et al., 2009). Based on the definition in RFS2, only planted crops and crop residue from
agricultural land cleared prior to December 19, 2007, and actively managed or fallow on
that date are considered compliant feedstocks. This definition discourages land clearing of
native ecosystems for bioenergy feedstock production so that GHG emissions from direct
land-use change could be minimized. However, some farmers could use existing cropland
to produce bioenergy feedstocks.
Conversely, converting from annual to perennial bioenergy crops can enhance carbon
sequestration on that piece of land (Fargione et al., 2008). The perennial bioenergy crops
are considered RFS-compliant feedstock. However, the carbon storage could be offset by
market-mediated effects on land-use and land-cover changes elsewhere as a result of bio-
fuel production in the United States.
A few authors estimated GHG emissions from indirect land-use change as a result of
increasing corn-grain ethanol production in the United States. Their simulations represent
changes in GHG emissions from land-use changes with or without U.S. biofuel production.
Other drivers of land-use changes were not considered. Searchinger et al. (2008) estimated
that GHG emissions from indirect land-use change in Brazil, China, India, and the United
States from U.S. corn-grain ethanol production to be 104 g CO2 eq per MJ. Searchinger et
al. (2008) projected land-use changes on the basis of historical data from 1990 to 1999. They
estimated GHG emissions from the land-use change would be offset by GHG benefits ac-
crued from substituting gasoline with corn-grain ethanol only after 167 years.
Dumortier et al. (2010) demonstrated that differences in the economic model and data
source did not alter the estimate of GHG emission from indirect land-use change much
when they used the same assumptions of increase in ethanol production over time and
types of land cover converted as Searchinger et al. (2008). In contrast, changes in assump-
tions on the type of land converted, net land displacement factor,7 crop yield, and increase
in ethanol production had large effects on estimated GHG emissions (Dumortier et al., 2010;
Plevin et al., 2010).
The model of the Global Trade Analysis Project (GTAP) has been used to estimate
biofuel-induced land-use change emission estimates for the California Air Resources Board
(Tyner et al., 2010). To evaluate the land-use implications of U.S. ethanol production, they
developed three groups of simulations. In the first group, they calculated the land-use im-
plications of U.S. ethanol production off the 2001 database. This is version 6 of the GTAP
global database, which is updated every 2-3 years. This approach isolates effects of U.S.
ethanol production from other changes that shape the world economy. In the second group
of simulations, Tyner et al. (2010) first constructed a baseline that represents changes in the
world economy during the time period of 2001-2006. Then they calculated the land-use
impact of U.S. ethanol production based on the updated 2006 database. Finally, in the third
group of simulations, they used the updated 2006 database obtained from the second group
7 Net land displacement factor is the ratio of land acreage brought into crop production anywhere in the world
as a result of market-mediated effects of bioenergy feedstock production to land acreage dedicated to bioenergy
feedstock production.
OCR for page 252
252 RENEWABLE FUEL STANDARD
Evans, A.M., R.T. Perschel, and B.A. Kittler. 2010. Revised Assessment of Biomass Harvesting and Retention
Guidelines. Santa Fe, NM: Forest Guild.
Evans, J.M., and M.J. Cohen. 2009. Regional water resource implications of bioethanol production in the south-
eastern United States. Global Change Biology 15(9):2261-2273.
Fargione, J., J. Hill, D. Tilman, S. Polasky, and P. Hawthorne. 2008. Land clearing and the biofuel carbon debt.
Science 319(5867):1235-1238.
Fargione, J.E., T.R. Cooper, D.J. Flaspohler, J. Hill, C. Lehman, T. McCoy, S. McLeod, E.J. Nelson, K.S. Oberhauser,
and D. Tilman. 2009. Bioenergy and wildlife: Threats and opportunities for grassland conservation. BioSci-
ence 59(9):767-777.
Fargione, J.E., R.J. Plevin, and J.D. Hill. 2010. The ecological impacts of biofuels. Annual Review of Ecology and
Systematics 41:351-377.
Farrell, A.E., R.J. Plevin, B.T. Turner, A.D. Jones, M. O’Hare, and D.M. Kammen. 2006. Ethanol can contribute to
energy and environmental goals. Science 311(5760):506-508.
Fearnside, P.M. 1996. Amazonian deforestation and global warming: Carbon stocks in vegetation replacing Brazil’s
Amazon forest. Forest Ecology and Management 80(1-3):21-34.
Feng, H., O.D. Rubin, and B.A. Babcock. 2010. Greenhouse gas impacts of ethanol from Iowa corn: Life cycle as-
sessment versus system wide approach. Biomass and Bioenergy 34(6):912-921.
Fight, R.D., and R.J. Barbour. 2005. Financial Analysis of Fuel Treatments. Portland, OR: U.S. Department of Ag-
riculture - Forest Service - Pacific Northwest Research Station.
Fingerman, K.R., M.S. Torn, M.H. O’Hare, and D.M. Kammen. 2010. Accounting for the water impacts of ethanol
production. Environmental Research Letters 5(1).
Finnveden, G., M.Z. Hauschild, T. Ekvall, J. Guinee, R. Heijungs, S. Hellweg, A. Koehler, D. Pennington, and S.
Suh. 2009. Recent developments in life cycle assessment. Journal of Environmental Management 91(1):1-21.
Fischer, G., E. Hizsnyik, S. Prieler, M. Shah, and H. van Velthuizen. 2009. Biofuels and Food Security. Vienna: The
OPEC Fund for International Development.
Flaspohler, D.J., R.E. Froese, and C.R. Webster. 2009. Bioenergy, biomass and biodiversity. Pp. 133-162 in Renewable
Energy from Forest Resources in the United States, B.D. Solomon and V.A. Luzadis, eds. New York: Routledge.
Foley, J.A., R. DeFries, G.P. Asner, C. Barford, G. Bonan, S.R. Carpenter, F.S. Chapin, M.T. Coe, G.C. Daily, H.K.
Gibbs, J.H. Helkowski, T. Holloway, E.A. Howard, C.J. Kucharik, C. Monfreda, J.A. Patz, I.C. Prentice, N. Ra-
mankutty, and P.K. Snyder. 2005. Global consequences of land use. Science 309(5734):570-574.
Fornara, D.A., and D. Tilman. 2008. Plant functional composition influences rates of soil carbon and nitrogen ac-
cumulation. Journal of Ecology 96(2):314-322.
Fortier, J., D. Gagnon, B. Truax, and F. Lambert. 2010. Biomass and volume yield after 6 years in multiclonal hybrid
poplar riparian buffer strips. Biomass and Bioenergy 34(7):1028-1040.
Foust, T., A. Aden, A. Dutta, and S. Phillips. 2009. An economic and environmental comparison of a biochemical
and a thermochemical lignocellulosic ethanol conversion processes. Cellulose 16(4):547-565.
Frey, H.C., H. Zhai, and N.M. Rouphail. 2009. Regional on-road vehicle running emissions modeling and
evaluation for conventional and alternative vehicle technologies. Environmental Science and Technology
43(21):8449-8455.
FSCUS (Forest Stewardship Council United States). 2010. The Forest Stewardship Council. Available online at
http://www.fscus.org/. Accessed November 10, 2010.
Gallagher, M.E., W.C. Hockaday, C.A. Masiello, S. Snapp, C.P. McSwiney, and J.A. Baldock. 2011. Biochemical
suitability of crop residues for cellulosic ethanol: Disincentives to nitrogen fertilization in corn agriculture.
Environmental Science and Technology 45(5):2013-2020.
GAO (U.S. Government Accountability Office). 2009. Biofuels: Potential Effects and Challenges of Required In-
creases in Production and Use. Washington, DC: U.S. Government Accountability Office.
Gardiner, M.A., J.K. Tuell, R. Isaacs, J. Gibbs, J.S. Ascher, and D.A. Landis. 2010. Implications of three biofuel crops
for beneficial arthropods in agricultural landscapes. BioEnergy Research 3(1):6-19.
Garten, C.T., J.L. Smith, D.D. Tyler, J.E. Amonette, V.L. Bailey, D.J. Brice, H.F. Castro, R.L. Graham, C.A. Gunder-
son, R.C. Izaurralde, P.M. Jardine, J.D. Jastrow, M.K. Kerley, R. Matamala, M.A. Mayes, F.B. Metting, R.M.
Miller, K.K. Moran, W.M. Post, R.D. Sands, C.W. Schadt, J.R. Phillips, A.M. Thomson, T. Vugteveen, T.O. West,
and S.D. Wullschleger. 2010. Intra-annual changes in biomass, carbon, and nitrogen dynamics at 4-year old
switchgrass field trials in west Tennessee, USA. Agriculture Ecosystems and Environment 136(1-2):177-184.
GBEP (Global Bioenergy Partnership). 2010. Second draft of GBEP sustainability criteria and indicators for bioen-
ergy. Available online at http://www.globalbioenergy.org/fileadmin/user_upload/gbep/docs/partners_
only/sust_docs/2nd_DRAFT_of_GBEP_Criteria_Indicators_with_TEMPLATES.doc. Accessed November
15, 2010.
Gebber, R., and V.I. Adamchuk. 2010. Precision agriculture and food security. Science 327(5967):828-831.
OCR for page 253
253
ENVIRONMENTAL EFFECTS AND TRADEOFFS OF BIOFUELS
Geist, H.J., and E.F. Lambin. 2002. Proximate causes and underlying driving forces of tropical deforestation. Bio-
Science 52(2):143-150.
Gell, K., J.W. van Groenigen, and M.L. Cayuela. 2011. Residues of bioenergy production chains as soil amend-
ments: Immediate and temporal phytotoxicity. Journal of Hazardous Materials 186(2-3):2017-2025.
George, N., Y. Yang, Z. Wang, R. Sharma-Shivappa, and K. Tungate. 2010. Suitability of canola residue for cellulosic
ethanol production. Energy and Fuels 24(8):4454-4458.
Georgescu, M., D.B. Lobell, and C.B. Field. 2011. Direct climate effects of perennial bioenergy crops in the United
States. Proceedings of the National Academy of Sciences of the United States of America 108(11):4307-4312.
Gibbs, H.K., M. Johnston, J.A. Foley, T. Holloway, C. Monfreda, N. Ramankutty, and D. Zaks. 2008. Carbon pay-
back times for crop-based biofuel expansion in the tropics: The effects of changing yield and technology.
Environmental Research Letters 3(3):034001.
Gilliom, R.J., J.E. Barbash, C.G. Crawford, P.A. Hamilton, J.D. Martin, N. Nakagaki, L.H. Nowell, J.C. Scott, P.E.
Stackelberg, G.P. Thelin, and D.M. Wolock. 2007. Pesticides in the Nation’s Streams and Ground Water, 1992-
2001. Reston, VA: U.S. Geological Survey.
Ginnebaugh, D.L., J.Y. Liang, and M.Z. Jacobson. 2010. Examining the temperature dependence of ethanol (E85)
versus gasoline emissions on air pollution with a largely-explicit chemical mechanism. Atmospheric Envi-
ronment 44(9):1192-1199.
Gollany, H.T., R.W. Rickman, Y. Liang, S.L. Albrecht, S. Machado, and S. Kang. 2011. Predicting agricultural
management influence on long-term soil organic carbon dynamics: Implications for biofuel production.
Agronomy Journal 103(1):234-246.
Graham, L.A., S.L. Belisle, and C.L. Baas. 2008. Emissions from light duty gasoline vehicles operating on low blend
ethanol gasoline and E85. Atmospheric Environment 42(19):4498-4516.
Guo, L.B., and R.M. Gifford. 2002. Soil carbon stocks and land use change: A meta analysis. Global Change Biol-
ogy 8(4):345-360.
Guzman, J.G., and M. Al-Kaisi. 2010. Landscape position and age of reconstructed prairies effect on soil organic
carbon sequestration rate and aggregate associated carbon. Journal of Soil and Water Conservation 65(1):9-21.
Hammerschlag, R. 2006. Ethanol’s energy return on investment: A survey of the literature 1990 - Present. Environ-
mental Science and Technology 40(6):1744-1750.
Harto, C., R. Meyers, and E. Williams. 2010. Life cycle water use of low-carbon transport fuels. Energy Policy
38:4933-4944.
Heaton, E., T. Voigt, and S.P. Long. 2004. A quantitative review comparing the yields of two candidate C4 perennial
biomass crops in relation to nitrogen, temperature and water. Biomass and Bioenergy 27(1):21-30.
Hecht, A., D. Shaw, R. Bruins, V. Dale, K. Kline, and A. Chen. 2009. Good policy follows good science: Using criteria
and indicators for assessing sustainable biofuel production. Ecotoxicology 18(1):1-4.
Heltman, J., and E. Martinson. 2011. States grapple with new EPA push to adopt strict numeric nutrient limits.
Water Policy Report (April 11). Available online at https://environmentalnewsstand.com/Water-Policy-
Report/Water-Policy-Report-04/11/2011/menu-id-304.html. Accessed April 18, 2011.
Hertel, T.W., A.A. Golub, A.D. Jones, M. O’Hare, R.J. Plevin, and D.M. Kammen. 2010. Effects of US maize etha-
nol on global land use and greenhouse gas emissions: Estimating market-mediated responses. BioScience
60(3):223-231.
Hess, P., M. Johnston, B. Brown-Steiner, T. Holloway, J.B. de Andrade, and P. Artaxo. 2009. Air quality issues associ-
ated with biofuel production and use. Pp. 169-194 in Biofuels: Environmental Consequences and Interactions
with Changing Land Use, R.W. Howarth and S. Bringezu, eds. Ithaca, NY: Cornell University.
Hettinga, W.G., H.M. Junginger, S.C. Dekker, M. Hoogwijk, A.J. McAloon, and K.B. Hicks. 2009. Understanding the
reductions in US corn ethanol production costs: An experience curve approach. Energy Policy 37(1):190-203.
Hewitt, C.N., A.R. MacKenzie, P. Di Carlo, C.F. Di Marco, J.R. Dorsey, M. Evans, D. Fowler, M.W. Gallagher,
J.R. Hopkins, C.E. Jones, B. Langford, J.D. Lee, A.C. Lewis, S.F. Lim, J. McQuaid, P. Misztal, S.J. Moller, P.S.
Monks, E. Nemitz, D.E. Oram, S.M. Owen, G.J. Phillips, T.A.M. Pugh, J.A. Pyle, C.E. Reeves, J. Ryder, J. Siong,
U. Skiba, and D.J. Stewart. 2009. Nitrogen management is essential to prevent tropical oil palm plantations
from causing ground-level ozone pollution. Proceedings of the National Academy of Sciences of the United
States of America 106(44):18447-18451.
Hill, J., E. Nelson, D. Tilman, S. Polasky, and D. Tiffany. 2006. Environmental, economic, and energetic costs and
benefits of biodiesel and ethanol biofuels. Proceedings of the National Academy of Sciences of the United
States of America 103(30):11206-11210.
Hill, J., S. Polasky, E. Nelson, D. Tilman, H. Huo, L. Ludwig, J. Neumann, H.C. Zheng, and D. Bonta. 2009. Climate
change and health costs of air emissions from biofuels and gasoline. Proceedings of the National Academy
of Sciences of the United States of America 106(6):2077-2082.
OCR for page 254
254 RENEWABLE FUEL STANDARD
Hochman, G., D. Rajagopal, and D. Zilberman. 2010. The effect of biofuels on crude oil markets. AgBioForum
13(2):112-118.
Hoefnagels, R., E. Smeets, and A. Faaij. 2010. Greenhouse gas footprints of different biofuel production systems.
Renewable and Sustainable Energy Reviews 14(7):1661-1694.
Houghton, R.A. 2010. How well do we know the flux of CO2 from land-use change? Tellus B 62(5):337-351.
Hsu, D.D., D. Inman, G.A. Heath, E.J. Wolfrum, M.K. Mann, and A. Aden. 2010. Life cycle environmental impacts
of selected U.S. ethanol production and use pathways in 2022. Environmental Science and Technology
44(13):5289-5297.
Huffaker, R. 2010. Protecting water resources in biofuels production. Water Policy 12:129-134.
Huggins, D.R., R.S. Karow, H.P. Collins, and J.K. Ransom. 2011. Introduction: Evaluating long-term impacts of
harvesting crop residues on soil quality. Agronomy Journal 103(1):230-233.
Huo, H., M. Wang, C. Bloyd, and V. Putsche. 2009. Life-cycle assessment of energy use and greenhouse gas emis-
sions of soybean-derived biodiesel and renewable fuels. Environmental Science and Technology 43(3):750-756.
Hutchinson, K.J. 2008. Human impacted water environment classes. M.S. thesis, University of Iowa, Iowa City.
Ice, G.G., E.G. Schilling, and J.G. Vowel. 2010. Trends for forestry best management practices implementation.
Journal of Forestry 108(6):267-273.
ISO (International Organization for Standardization). 2006. Environmental Management—Life Cycle Assessment—
Principles and Framework. Geneva: International Organization for Standardization.
Izaurralde, R.C., J.R. Williams, W.B. McGill, N.J. Rosenberg, and M.C.Q. Jakas. 2006. Simulating soil C dynamics
with EPIC: Model description and testing against long-term data. Ecological Modelling 192(3-4):362-384.
Jackson, R.B., E.G. Jobbagy, R. Avissar, S.B. Roy, D.J. Barrett, C.W. Cook, K.A. Farley, D.C. le Maitre, B.A. McCarl,
and B.C. Murray. 2005. Trading water for carbon with biological sequestration. Science 310(5756):1944-1947.
Jacobson, M.Z. 2007. Effects of ethanol (E85) versus gasoline vehicles on cancer and mortality in the United States.
Environmental Science and Technology 41(11):4150-4157.
Janowiak, M.K., and C.R. Webster. 2010. Promoting ecological sustainability in woody biomass harvesting. Journal
of Forestry 108(1):16-23.
Jenkins, T.L., and J.W. Sutherland. 2009. An integrated supply system for forest biomass. Pp. 92-115 in Renew-
able Energy from Forest Resources in the United States, B.D. Solomon and V.A. Luzadis, eds. New York:
Routledge.
Johnson, G., C. Sheaffer, H.J. Jung, U. Tschirmer, S. Banerjee, K. Petersen, and D.L. Wyse. 2008. Landscape and spe-
cies diversity: Optimizing the use of land and species for biofuel feedstock production systems. Paper read
at the Agronomy Society of America, Crop Science Society of America, and Soil Science Society of America
Annual Meeting October 5-9, Houston, TX.
Johnson, J.M.F., A.J. Franzluebbers, S.L. Weyers, and D.C. Reicosky. 2007. Agricultural opportunities to mitigate
greenhouse gas emissions. Environmental Pollution 150(1):107-124.
Johnson, K., F.N. Scatena, and Y.D. Pan. 2010. Short- and long-term responses of total soil organic carbon to har-
vesting in a northern hardwood forest. Forest Ecology and Management 259(7):1262-1267.
Jones, D.L. 2010. Potential air emission impacts of cellulosic ethanol production at seven demonstration refineries
in the United States. Journal of the Air and Waste Management Association 60(9):1118-1143.
Jordaan, S.M., D.W. Keith, and B. Stelfox. 2009. Quantifying land use of oil sands production: A life cycle perspec-
tive. Environmental Research Letters 4(2):024004.
Kalies, E.L., C.L. Chambers, and W.W. Covington. 2010. Wildlife responses to thinning and burning treatments in
southwestern conifer forests: A meta-analysis. Forest Ecology and Management 259(3):333-342.
Kaliyan, N., R.V. Morey, and D.G. Tiffany. 2011. Reducing life cycle greenhouse gas emissions of corn ethanol by
integrating biomass to produce heat and power at ethanol plants. Biomass and Bioenergy 35(3):1103-1113.
Kalogo, Y., S. Habibi, H.L. MacLean, and S.V. Joshi. 2006. Environmental implications of municipal solid waste-
derived ethanol. Environmental Science and Technology 41(1):35-41.
Karlen, D.L. 2010. A landscape vision for integrating industrial crops into biofuel systems. Paper read at the As-
sociation for the Advancement of Industrial Crops Conference September 22, Fort Collins, CO.
Karlen, D.L., R. Lal, R.F. Follett, J.M. Kimble, J.L. Hatfield, J.M. Miranowski, C.A. Cambardella, A. Manale, R.P.
Anex, and C.W. Rice. 2010. Crop residues: The rest of the story. Environmental Science and Technology
43(21):8011-8015.
Kendall, A., B. Chang, and B. Sharpe. 2009. Accounting for time-dependent effects in biofuel life cycle greenhouse
gas emissions calculations. Environmental Science and Technology 43(18):7142-7147.
Khanal, S.K., M. Rasmussen, P. Shrestha, H. Van Leeuwen, C. Visvanathan, and H. Liu. 2008. Bioenergy and
biofuel production from wastes/residues of emerging biofuel industries. Water Environment Research
80(10):1625-1647.
OCR for page 255
255
ENVIRONMENTAL EFFECTS AND TRADEOFFS OF BIOFUELS
Khanna, M., B. Dhungana, and J. Clifton-Brown. 2008. Costs of producing Miscanthus and switchgrass for bioen-
ergy in Illinois. Biomass and Bioenergy 32(6):482-493.
Khanna, M., H. Önal, B. Dhungana, and M. Wander. 2010. Economics of herbaceous bioenergy crops for electricity
generation: Implications for greenhouse gas mitigation. Biomass and Bioenergy 35(4):1474-1484.
Kim, S., and B.E. Dale. 2011. Indirect land use change for biofuels: Testing predictions and improving analytical
methodologies. Biomass and Bioenergy 35(7):3235-3240.
King, C.W., and M.E. Webber. 2008. Water intensity of transportation. Environmental Science and Technology
42(21):7866-7872.
Kitchen, N.R., K.A. Sudduth, D.B. Myers, R.E. Massey, E.J. Sadler, and R.N. Lerch. 2005. Development of a con-
servation-oriented precision agriculture system: Crop production assessment and plan of implementation.
Journal of Soil and Water Conservation 60:421-430.
Kløverpris, J., H. Wenzel, and P. Nielsen. 2008. Life cycle inventory modelling of land use induced by crop con-
sumption. The International Journal of Life Cycle Assessment 13(1):13-21.
Kravchenko, A.N., and G.P. Robertson. 2011. Whole-profile soil carbon stocks: The danger of assuming too much
from analyses of too little. Soil Science Society of America Journal 75(1):235-240.
Kretschmer, B., and S. Peterson. 2010. Integrating bioenergy into computable general equilibrium models—A
survey. Energy Economics 32(3):673-686.
Kusiima, J.M., and S.E. Powers. 2010. Monetary value of the environmental and health externalities associated
with production of ethanol from biomass feedstocks. Energy Policy 38(6):2785-2796.
Lal, R. 2004. Soil carbon sequestration impacts on global climate change and food security. Science 304:1623-1627.
Lal, R., F. Follett, B.A. Stewart, and J.M. Kimble. 2007. Soil carbon sequestration to mitigate climate change and
advance food security. Soil Science Society of America Journal 172:943-956.
Lamb, D.W., P. Frazier, and P. Adams. 2008. Improving pathways to adoption: Putting the right P’s in precision
agriculture. Computers and Electronics in Agriculture 61(1):4-9.
Lamm, F.R., H.L. Manges, L.R. Stone, A.H. Khan, and D.H. Rogers. 1995. Water requirement of subsurface drip-
irrigated corn in Northwest Kansas. Transactions of the American Society of Agricultural and Biological
Engineers 38(2):441-448.
Landis, D.A., and B.P. Werling. 2010. Arthropods and biofuel production systems in North America. Insect Science
17(3):220-236.
Landis, D.A., M.M. Gardiner, W. van der Werf, and S.M. Swinton. 2008. Increasing corn for biofuel production
reduces biocontrol services in agricultural landscapes. Proceedings of the National Academy of Sciences of
the United States of America 105(51):20552-20557.
Lee, J.W., M. Kidder, B.R. Evans, S. Paik, A.C. Buchanan, C.T. Garten, and R.C. Brown. 2010. Characterization of bio-
chars produced from cornstovers for soil amendment. Environmental Science and Technology 44(20):7970-7974.
Lemoine, D.M., R.J. Plevin, A.S. Cohn, A.D. Jones, A.R. Brandt, S.E. Vergara, and D.M. Kammen. 2010. The climate
impacts of bioenergy systems depend on market and regulatory policy contexts. Environmental Science and
Technology 44(19):7374-7350.
Lerch, R.N., R.J. Kitchen, W.W. Kremer, E.E. Donald, E.J. Alberts, K.A. Saddler, D.B. Sudduth, D.B. Meyers, and
F. Ghidey. 2005. Development of a conservation-oriented precision agriculture system: Water and soil quality.
Journal of Soil and Water Conservation 60:411-421.
Levasseur, A., P. Lesage, M. Margni, L. Deschênes, and R.J. Samson. 2010. Considering time in LCA: Dynamic
LCA and its application to global warming impact assessments. Environmental Science and Technology
44(8):3169-3174.
Lewandowski, I., J.M.O. Scurlock, E. Lindvall, and M. Christou. 2003. The development and current status of
perennial rhizomatous grasses as energy crops in the US and Europe. Biomass and Bioenergy 25(4):335-361.
Leytem, A.B., P. Kwanyuen, and P. Thacker. 2008. Nutrient excretion, phosphorus characterization, and phospho-
rus solubility in excreta from broiler chicks fed diets containing graded levels of wheat distillers grains with
solubles. Poultry Science 87(12):2505-2511.
Liebig, M.A., M.R. Schmer, K.P. Vogel, and R.B. Mitchell. 2008. Soil carbon storage by switchgrass grown for bio-
energy. BioEnergy Research 1(3-4):215-222.
Liska, A.J., and K.G. Cassman. 2009a. Response to Plevin implications for life cycle emissions regulations. Journal
of Industrial Ecology 13(4):508-513.
Liska, A.J., and K.G. Cassman. 2009b. Responses to “Comment on ‘Response to Plevin: Implications for life cycle
emissions regulations’” and “Assessing corn ethanol: relevance and responsibility.” Journal of Industrial
Ecology 13(6):994-995.
Liska, A.J., H.S. Yang, V.R. Bremer, T.J. Klopfenstein, D.T. Walters, G.E. Erickson, and K.G. Cassman. 2009. Im-
provements in life cycle energy efficiency and greenhouse gas emissions of corn-ethanol. Journal of Industrial
Ecology 13(1):58-74.
OCR for page 256
256 RENEWABLE FUEL STANDARD
Liu, Y., M.A. Evans, and D. Scavia. 2010. Gulf of Mexico hypoxia: Exploring increasing sensitivity to nitrogen
loads. Environmental Science and Technology 44(15):5836-5841.
Lu, X.L., and Q.L. Zhuang. 2010. Evaluating climate impacts on carbon balance of the terrestrial ecosystems in the
Midwest of the United States with a process-based ecosystem model. Mitigation and Adaptation Strategies
for Global Change 15(5):467-487.
Luo, Z., E. Wang, and O.J. Sun. 2010. Can no-tillage stimulate carbon sequestration in agricultural soils? A meta-
analysis of paired experiments. Agriculture, Ecosystems and Environment 139:224-231.
Machado, S. 2011. Soil organic carbon dynamics in the Pendleton long-term experiments: Implications for biofuel
production in Pacific Northwest. Agronomy Journal 103(1):253-260.
Malcolm, S., and M. Aillery. 2009. Growing crops for biofuels has spillover effects. Amber Waves 7(1):10-15.
Marshall, L. 2009. Biofuels and the Time Value of Carbon: Recommendations for GHG Accounting Protocols.
Washington, DC: World Resources Institute.
McCormick, R.L. 2007. The impact of biodiesel on pollutant emissions and public health. Inhalation Toxicology
19(12):1033-1039.
McKechnie, J., S. Colombo, J. Chen, W. Mabee, and H.L. MacLean. 2010. Forest bioenergy or forest carbon? Assess-
ing trade-offs in greenhouse gas mitigation with wood-based fuels. Environmental Science and Technology
45(2):789-795.
McKone, T.E., W.W. Nazaroff, P. Berck, M. Auffhammer, T. Lipman, M.S. Torn, E. Masanet, A. Lobscheid, A. Santero,
U. Mishra, A. Barrett, M. Bomberg, K. Fingerman, C. Scown, B. Strogen, and A. Horvath. 2011. Grand chal-
lenges for life-cycle assessment of biofuels. Environmental Science and Technology 45(5):1751-1756.
McSwiney, C.P., and G.P. Roberstson. 2005. Nonlinear response of N2O flux to incremental fertilizer addition in a
continuous maize (Zea mays L.) cropping system. Global Change Biology 11:1712-1719.
Meehan, T.D., A.H. Hurlbert, and C. Gratton. 2010. Bird communities in future bioenergy landscapes of the
Upper Midwest. Proceedings of the National Academy of Sciences of the United States of America
107(43):18533-18538.
Mehta, R.N., M. Chakraborty, P. Mahanta, and P.A. Parikh. 2010. Evaluation of fuel properties of butanol-biodiesel-
diesel blends and their impact on engine performance and emissions. Industrial and Engineering Chemistry
Research 49(16):7660-7665.
Melamu, R., and H. von Blottnitz. 2011. 2nd generation biofuels a sure bet? A life cycle assessment of how things
could go wrong. Journal of Cleaner Production 19(2-3):138-144.
Melillo, J.M., J.M. Reilly, D.W. Kicklighter, A.C. Gurgel, T.W. Cronin, S. Paltsev, B.S. Felzer, X.D. Wang, A.P. Sokolov,
and C.A. Schlosser. 2009. Indirect emissions from biofuels: How important? Science 326(5958):1397-1399.
Meyfroidt, P., T.K. Kudel, and E.F. Lambin. 2010. Forest transitions, trade, and the global displacement of land
use. Proceedings of the National Academy of Sciences of the United States of America 107(49):20917-20922.
Millar, N., G.P. Robertson, P.R. Grace, R.J. Gehl, and J.P. Hoben. 2010. Nitrogen fertilizer management for nitrous
oxide (N2O) mitigation in intensive corn (Maize) production: An emissions reduction protocol for US Mid-
west agriculture. Mitigation and Adaptation Strategies for Global Change 15(2):185-204.
Millennium Ecosystem Assessment. 2005. Ecosystems and Human Well Being: Synthesis. Washington, DC: World
Resources Institute.
Miller, S.A. 2010. Minimizing land use and nitrogen intensity of bioenergy. Environmental Science and Technol-
ogy 44(10):3932-3939.
Monsanto. 2008. Monsanto will undertake three-point commitment to double yield in three major crops, make
more efficient use of natural resources and improve farmer lives. Available online at http://monsanto.me-
diaroom.com/index.php?s=43&item=607. Accessed April 13, 2011.
Morais, S., A.A. Martins, and T.M. Mata. 2010. Comparison of allocation approaches in soybean biodiesel life cycle
assessment. Journal of the Energy Institute 83:48-55.
Morgan, J.A., R.F. Follett, L.H. Allen, S. del Grosso, J.D. Derner, F. Dijkstra, A. Franzluebbers, R. Fry, K. Paustian,
and M.M. Schoeneberger. 2010. Carbon sequestration in agricultural lands of the United States. Journal of
Soil and Water Conservation 65(2):6A-13A.
Mubako, S., and C. Lant. 2008. Water resource requirements of corn-based ethanol. Water Resources Research
44(7):W00A02.
Mueller, S. 2010. Detailed Report: 2008 National Dry Mill Corn Ethanol Survey. Chicago: University of Illinois.
Mullins, K.A., W.M. Griffin, and H.S. Matthews. 2010. Policy implications of uncertainty in modeled life-cycle
greenhouse gas emissions of biofuels. Environmental Science and Technology 45(1):132-138.
Murray, B.C., B.L. Sohngen, A.J. Sommer, B.M. Depro, K.M. Jones, B.A. McCarl, D. Gillig, B. DeAngelo, and K. An-
drasko. 2005. Greenhouse Gas Mitigation Potential in U.S. Forestry and Agriculture. Washington, DC: U.S.
Environmental Protection Agency.
OCR for page 257
257
ENVIRONMENTAL EFFECTS AND TRADEOFFS OF BIOFUELS
Murray, B.C., B. Sohngen, and M.T. Ross. 2007. Economic consequences of consideration of permanence, leakage
and additionality for soil carbon sequestration projects. Climatic Change 80(1-2):127-143.
Murray, L., and L. Best. 2010. Bird use of switchgrass fields harvested for bioenergy in the Midwestern U.S. Paper
read at the Reshaping Landscapes: Bioenergy and Biodiversity, April 8, Athens, GA.
NAS-NAE-NRC (National Academy of Sciences, National Academy of Engineering, National Research Council).
2009. Liquid Transportation Fuels from Coal and Biomass: Technological Status, Costs, and Environmental
Impacts. Washington, DC: National Academies Press.
NCGA (National Corn Growers Association). 2010. Corn production trends. Available online at http://www.ncga.
com/corn-production-trends. Accessed September 10, 2010.
Nebraska Corn Board. 2011. Advantage: Nebraska. Available online at http://www.nebraskacorn.org/main-
navigation/grain-traders/advantage-nebraska/. Accessed February 11, 2011.
Nelson, N.O., S.C. Agudelo, W.Q. Yuan, and J. Gan. 2011. Nitrogen and phosphorus availability in biochar-
amended soils. Soil Science 176(5):218-226.
Nelson, R., M. Langemeier, J. Williams, C. Rice, S. Staggenborg, P. Pfomm, D. Rodgers, D. Wang, and J. Nippert.
2010. Kansas Biomass Resource Assessment: Assessment and Supply of Select Biomass-based Resources.
Manhattan: Kansas State University.
Nelson, R.G., J.C. Ascough II, and M.R. Langemeier. 2006. Environmental and economic analysis of switchgrass
production for water quality improvement in northeast Kansas. Journal of Environmental Management
79(4):336-347.
Newman, J.K., A.L. Kaleita, and J.M. Laflen. 2010. Soil erosion hazard maps for corn stover management using
national resources inventory data and the water erosion prediction project. Journal of Soil and Water Con-
servation 65(4):211-222.
Ng, T.L., J.W. Eheart, X.M. Cai, and F. Miguez. 2010. Modeling Miscanthus in the Soil and Water Assessment Tool
(SWAT) to simulate its water quality effects as a bioenergy crop. Environmental Science and Technology
44(18):7138-7144.
Niemi, G.J., and M.E. McDonald. 2004. Application of ecological indicators. Annual Review of Ecology Evolution
and Systematics 35:89-111.
Nolan, B.T., K.J. Hitt, and B.C. Ruddy. 2002. Probability of nitrate contamination of recently recharged groundwa-
ters in the conterminous United States. Environmental Science and Technology 36(10):2138-2145.
NRC (National Research Council). 1999. Ozone-Forming Potential of Reformulated Gasoline. Washington, DC:
National Academy Press.
NRC (National Research Council). 2003. Cumulative Environmental Effects of Oil and Gas Activities on Alaska’s
North Slope. Washington, DC: National Academies Press.
NRC (National Research Council). 2008. Water Implications of Biofuels Production in the United States; Commit-
tee on Water Implications of Biofuels Production in the United States, National Research Council. Washing-
ton, DC: National Academies Press.
NRC (National Research Council). 2010a. Hidden Costs of Energy: Unpriced Consequences of Energy Production
and Use. Washington, DC: National Academies Press.
NRC (National Research Council). 2010b. Toward Sustainable Agricultural Systems in the 21st Century. Washing-
ton, DC: National Academies Press.
NRC (National Research Council). 2010c. Verifying Greenhouse Gas Emissions: Methods to Support International
Climate Agreements. Washington, DC: National Academies Press.
O’Hare, M., R.J. Plevin, J.I. Martin, A.D. Jones, A. Kendall, and E. Hopson. 2009. Proper accounting for time
increases crop-based biofuels’ greenhouse gas deficit versus petroleum. Environmental Research Letters
4(2009):024001.
O’Hare, M., M. Delucchi, R. Edwards, U. Fritsche, H. Gibbs, T. Hertel, J. Hill, D. Kammen, L. Marelli, D. Mulligan,
R. Plevin, and W. Tyner. 2011. Comment on “Indirect land use change for biofuels: Testing predictions and
improving analytical methodologies” by Kim and Dale: Statistical reliability and the definition of the indirect
land use change (iLUC) issue. Biomass and Bioenergy 35(10):4485-4487.
Odum, E.P. 1969. The strategy of ecosystem development. Science 164(3877):262-270.
Ogle, S.M., F.J. Breidt, M. Easter, S. Williams, and K. Paustian. 2007. An empirically based approach for estimating
uncertainty associated with modelling carbon sequestration in soils. Ecological Modelling 205(3-4):453-463.
Ohlrogge, J., D. Allen, B. Berguson, D. DellaPenna, Y. Shachar-Hill, and S. Stymne. 2009. Driving on biomass.
Science 324(5930):1019-1020.
Omonode, R.A., D.R. Smith, A. Gál, and T.J. Vyn. 2011. Soil nitrous oxide emissions in corn following three decades
of tillage and rotation treatments. Soil Science Society of America Journal 75(1):152-163.
Osterman, L.E., R.Z. Poore, P.W. Swarzenski, and R.E. Turner. 2005. Reconstructing a 180 yr record of natural and
anthropogenic induced hypoxia from the sediments of the Louisiana continental shelf. Geology 33(4):329-332.
OCR for page 258
258 RENEWABLE FUEL STANDARD
Overmars, K.P., E. Stehfest, J.P.M. Ros, and A.G. Prins. 2011. Indirect land use change emissions related to EU
biofuel consumption: An analysis based on historical data. Environmental Science and Policy 14(3):248-257.
Pang, S.-H., H.C. Frey, and W.J. Rasdorf. 2009. Life cycle inventory energy consumption and emissions for
biodiesel versus petroleum diesel fueled construction vehicles. Environmental Science and Technology
43(16):6398-6405.
Parker, N., Q. Hart, P. Tittman, M. Murphy, R. Nelson, K. Skog, E. Gray, A. Schmidt, and B. Jenkins. 2010. National
Biorefinery Siting Model: Spatial Analysis and Supply Curve Development. Washington, DC: Western Gov-
ernors Association.
Parkin, G., P. Weyer, and C. Just. 2007. Riding the bioeconomy wave: Smooth sailing or rough water for the
environment and public health. Paper read at the Iowa Water Conference - Water and Bioenergy, March 6,
Ames, IA.
Parrish, D.J., and J.H. Fike. 2005. The biology and agronomy of switchgrass for biofuels. Critical Reviews in Plant
Sciences 24:423-459.
Pate, R., M. Hightower, C. Cameron, and W. Einfeld. 2007. Overview of Energy-Water Interdependencies and the
Emerging Energy Demands on Water Resources. Los Alamos, NM: Sandia National Laboratories.
Paustian, K., E.T. Elliott, and K. Killian. 1997. Modeling soil carbon in relation to management and climate change
in some agroecosystems in central North America. Pp. 459-471 in Soil Processes and the Carbon Cycle, R. Lal,
J.M. Kimble, R.F. Follett, and B.A. Stewart, eds. Boca Raton, FL: CRC Press.
Perlack, R.D., L.L. Wright, A.F. Turhollow, R.L. Graham, B.J. Stokes, and D.C. Erbach. 2005. Biomass as Feedstock
for a Bioenergy and Bioproducts Industry: The Technical Feasibility of a Billion-Ton Annual Supply. Oak
Ridge, TN: U.S. Department of Energy, U.S. Department of Agriculture.
Persson, T., A.G.Y. Garcia, J.O. Paz, C.W. Fraisse, and G. Hoogenboom. 2010. Reduction in greenhouse gas emis-
sions due to the use of bio-ethanol from wheat grain and straw produced in the south-eastern USA. The
Journal of Agricultural Science 148(05):511-527.
Phillips, S., A. Aden, J. Jechura, D. Dayton, and T. Eggeman. 2007. Thermochemical Ethanol via Indirect Gasifi-
cation and Mixed Alcohol Synthesis of Lignocellulosic Biomass. Golden, CO: National Renewable Energy
Laboratory.
Plevin, R. 2009a. Comment on “Response to Plevin: Implications for life cycle emissions regulations.” Journal of
Industrial Ecology 13(6):992-993.
Plevin, R.J. 2009b. Modeling corn ethanol and climate. Journal of Industrial Ecology 13(4):495-507.
Plevin, R.J., M. O’Hare, A.D. Jones, M.S. Torn, and H.K. Gibbs. 2010. Greenhouse gas emissions from biofuels’
indirect land use change are uncertain but may be much greater than previously estimated. Environmental
Science and Technology 44(21):8015-8021.
Powers, S.E., R. Dominguez-Faus, and P.J.J. Alvarez. 2010. The water footprint of biofuel production in the USA.
Biofuels 1(2):255-260.
Pradhan, A., D.S. Shrestha, J. Van Gerpen, and J. Duffield. 2008. The energy balance of soybean oil biodiesel
production: A review of past studies. Transactions of the American Society of Agricultural and Biological
Engineers 51(1):185-194.
Quinn, L.D., D.J. Allen, and J.R. Stewart. 2010. Invasiveness potential of Miscanthus sinensis: Implications for bio-
energy production in the United States. Global Change Biology Bioenergy 2(6):310-320.
Rabalais, N.N., and R.E. Turner. 2001. Coastal hypoxia: Consequences for living resources and ecosystems. Pp.
1-36 in Coastal and Estuarine Studies, N.N. Rabalais and R.E. Turner, eds. Washington, DC: American Geo-
physical Union.
Rabalais, N.N., R.E. Turner, and W.J. Wiseman. 2002. Gulf of Mexico hypoxia, aka “The dead zone.” Annual Re-
view of Ecology and Systematics 33:235-263.
Rabotyagov, S., T. Campbell, M. Jha, P.W. Gassman, J. Arnold, L. Kurkalova, S. Secchi, H.L. Feng, and C.L. Kling.
2010. Least-cost control of agricultural nutrient contributions to the Gulf of Mexico hypoxic zone. Ecological
Applications 20(6):1542-1555.
Raghu, S., R.C. Anderson, C.C. Daehler, A.S. Davis, R.N. Wiedenmann, D. Simberloff, and R.N. Mack. 2006. Add-
ing biofuels to the invasive species fire? Science 313(5794):1742.
Randall, J.M., L.E. Morse, N. Benton, R. Hiebert, S. Lu, and T. Killeffer. 2008. The invasive species assessment
protocol: A tool for creating regional and national lists of invasive nonnative plants that negatively impact
biodiversity. Invasive Plant Science and Management 1(1):36-49.
Rausch, K.D., and R.L. Belyea. 2006. The future of coproducts from corn processing. Applied Biochemistry and
Biotechnology 128(1):47-86.
Ravindranath, N.H., R. Mauvie, J. Fargione, J.G. Canadell, G. Berndes, J. Woods, H. Watson, and J. Sathaye. 2009.
Greenhouse gas implications of land use change and land conversion to biofuel crops. Pp. 111-125 in Biofuels:
Environmental Consequences and Interactions with Changing Land Use, R.W. Howarth and S. Bringezu,
eds. Ithaca, NY: Cornell University.
OCR for page 259
259
ENVIRONMENTAL EFFECTS AND TRADEOFFS OF BIOFUELS
Reitz, S.R., G.S. Kund, W.G. Carson, P.A. Phillips, and J.T. Trumble. 1999. Economics of reducing insecticide
use on celery through low-input pest management strategies. Agriculture Ecosystems and Environment
73(3):185-197.
RFA (Renewable Fuels Association). 2011. Biorefinery locations. Available online at http://www.ethanolrfa.org/
bio-refinery-locations/. Accessed January 26, 2011.
Riffell, S., J. Verschuyl, D. Miller, and T.B. Wigley. 2010. Reshaping landscapes: Bioenergy and biodiversity. Paper
read at Reshaping Landscapes: Bioenergy and Biodiversity, April 8, Athens, GA.
Robert, P.C. 2002. Precision agriculture: A challenge for crop nutrition management. Plant and Soil 247(1):143-149.
Roberts, K.G., B.A. Gloy, S. Joseph, N.R. Scott, and J. Lehmann. 2010. Life cycle assessment of biochar systems:
Estimating the energetic, economic, and climate change potential. Environmental Science and Technology
44(2):827-833.
Robertson, B.A., P.J. Doran, L.R. Loomis, J.R. Robertson, and D.W. Schemske. 2011a. Perennial biomass feedstocks
enhance avian diversity. GCB Bioenergy 3(3):235-246.
Robertson, G.P., V.H. Dale, O.C. Doering, S.P. Hamburg, J.M. Melillo, M.M. Wander, W.J. Parton, P.R. Adler, J.N.
Barney, R.M. Cruse, C.S. Duke, P.M. Fearnside, R.F. Follett, H.K. Gibbs, J. Goldemberg, D.J. Mladenoff,
D. Ojima, M.W. Palmer, A. Sharpley, L. Wallace, K.C. Weathers, J.A. Wiens, and W.W. Wilhelm. 2008. Sustain-
able biofuels redux. Science 322(5898):49-50.
Robertson, G.P., S.K. Hamilton, W.J. Parton, and S.J.D. Grosso. 2011b. The biogeochemistry of bioenergy land-
scapes: Carbon, nitrogen, and water considerations. Ecological Applications 21(4):1055-1067.
Robins, J.G. 2010. Cool-season grasses produce more total biomass across the growing season than do warm-
season grasses when managed with an applied irrigation gradient. Biomass and Bioenergy 34(4):500-505.
Roth, A.M., D.W. Sample, C.A. Ribic, L. Paine, D.J. Undersander, and G.A. Bartelt. 2005. Grassland bird response
to harvesting switchgrass as a biomass energy crop. Biomass & Bioenergy 28(5):490-498.
RSB (Roundtable on Sustainable Biofuels). 2010. Principles and Criteria. Available online at http://rsb.epfl.ch/
page-24929.html. Accessed November 15, 2010.
Sage, R.F., H.A. Coiner, D.A. Way, G. Brett Runion, S.A. Prior, H. Allen Torbert, R. Sicher, and L. Ziska. 2009. Kudzu
[Pueraria montana (Lour.) Merr. Variety lobata]: A new source of carbohydrate for bioethanol production.
Biomass and Bioenergy 33(1):57-61.
Sahu, M., and R.R. Gu. 2009. Modeling the effects of riparian buffer zone and contour strips on stream water qual-
ity. Ecological Engineering 35(8):1167-1177.
Scavia, D., and Y. Liu. 2009. Gulf of Mexico hypoxia forecast and measurement. Available online at http://
www.snre.umich.edu/scavia/wp-content/uploads/2009/11/2009_gulf_of_mexico_hypoxic_forecast_and_
observation.pdf. Accessed August 17, 2010.
Scavia, D., N.N. Rabalais, R.E. Turner, D. Justic, and W.J. Wiseman, Jr. 2003. Predicting the response of Gulf of Mex-
ico hypoxia to variations in the Mississippi River nitrogen load. Limnology and Oceanography 48:951-956.
Schill, S.R. 2007. 300-bushel corn is coming. Available online at http://www.ethanolproducer.com/
articles/3330/300-bushel-corn-is-coming/. Accessed April 13, 2011.
Schilling, E. 2009. Compendium of Forestry Best Management Practices for Controlling Nonpoint Source Pollution
in North America. Research Triangle Park, NC: National Council for Air and Stream Improvement.
Schilling, K.E., and J. Spooner. 2006. Effects of watershed-scale land use change on stream nitrate concentrations.
Journal of Environmental Quality 35(6):2132-2145.
Schilling, K.E., and C.F. Wolter. 2008. Water Quality Improvement Plan for Raccoon River, Iowa: Total Maximum
Daily Load for Nitrate and Escherichia coli. Iowa City: Iowa Department of Natural Resources - Geological
Survey.
Schmit, T.M., R.N. Boisvert, D. Enahoro, and L.E. Chase. 2009. Optimal dairy farm adjustments to increased utiliza-
tion of corn distillers dried grains with solubles. Journal of Dairy Science 92(12):6105-6115.
Schnepf, R. 2004. Energy Use in Agriculture: Background and Issues. Washington, DC: Congressional Research
Service.
Schweizer, P., H. Jager, and L. Baskaran. 2010. Forecasting changes in water quality and aquatic biodiversity in
response to future bioenergy landscapes in the Arkansas-White-Red River basin. Paper read at Reshaping
Landscapes: Bioenergy and Biodiversity, April 8, Athens, GA.
Searchinger, T., R. Heimlich, R.A. Houghton, F. Dong, A. Elobeid, J. Fabiosa, S. Tokgoz, D. Hayes, and T.-H. Yu.
2008. Use of U.S. croplands for biofuels increases greenhouse gases through emissions from land-use change.
Science 319(5867):1238-1240.
Searchinger, T.D. 2010. Biofuels and the need for additional carbon. Environmental Research Letters 5(2).
Secchi, S., P. Gassman, M. Jha, L. Kurkalova, and C. Kling. 2011. Potential water quality changes due to corn expan-
sion in the Upper Mississippi River Basin. Ecological Applications 21:1068-1084.
SFI (Sustainable Forestry Initiative). 2010. Emerging themes: Bioenergy and carbon. Available online at http://
www.sfiprogram.org/forest-conservation/bioenergy-carbon.php. Accessed November 18, 2010.
OCR for page 260
260 RENEWABLE FUEL STANDARD
Shi, A.Z., L.P. Koh, and H.T.W. Tan. 2009. The biofuel potential of municipal solid waste. GCB Bioenergy 1(5):317-320.
Siemens, M.C., and D.E. Wilkins. 2006. Effect of residue management methods on no-till drill performance. Ap-
plied Engineering in Agriculture 22(1):51-60.
Simpson, T.W., A.N. Sharpley, R.W. Howarth, H.W. Paerl, and K.R. Mankin. 2008. The new gold rush: Fueling
ethanol production while protecting water quality. Journal of Environmental Quality 37(2):318-324.
Singh, A., D. Pant, N.E. Korres, A.-S. Nizami, S. Prasad, and J.D. Murphy. 2010. Key issues in life cycle assessment
of ethanol production from lignocellulosic biomass: Challenges and perspectives. Bioresource Technology
101(13):5003-5012.
Snyder, C.S., T.W. Bruulsema, T.L. Jensen, and P.E. Fixen. 2009. Review of greenhouse gas emissions from
crop production systems and fertilizer management effects. Agriculture Ecosystems and Environment
133(3-4):247-266.
Sohngen, B., and S. Brown. 2004. Measuring leakage from carbon projects in open economies: a stop timber
harvesting project in Bolivia as a case study. Canadian Journal of Forest Research-Revue Canadienne De
Recherche Forestiere 34(4):829-839.
Sohngen, B., and R. Sedjo. 2000. Potential carbon flux from timber harvests and management in the context of a
global timber market. Climatic Change 44(1-2):151-172.
Solomon, B.D. 2009. Regional economic impacts of cellulosic ethanol development in the North Central states. Pp.
281-298 in Renewable Energy from Forest Resources in the United States, B.D. Solomon and V.A. Luzadis,
eds. New York: Routledge.
Solomon, B.D., J.R. Barnes, and K.E. Halvorsen. 2009. From grain to cellulosic ethanol: History, economics and
policy. Pp. 49-66 in Renewable Energy from Forest Resources in the United States, B.D. Solomon and V.A.
Luzadis, eds. New York: Routledge.
Spatari, S., and H.L. MacLean. 2010. Characterizing model uncertainties in the life cycle of lignocellulose-based
ethanol fuels. Environmental Science and Technology 44(22):8773-8780.
Spatari, S., D.M. Bagley, and H.L. MacLean. 2010. Life cycle evaluation of emerging lignocellulosic ethanol conver-
sion technologies. Bioresource Technology 101(2):654-667.
Sprague, L.A., R.M. Hirsch, and B.T. Aulenbach. 2011. Nitrate in the Mississippi River and its tributaries, 1980 to
2008: Are we making progress? Environmental Science and Technology. Available online at http://pubs.acs
.org/doi/abs/10.1021/es201221s. Accessed August 31, 2011.
Stavins, R.N., and A.B. Jaffe. 1990. Unintended impacts of public-investments on private decisions—The depletion
of forested wetlands. American Economic Review 80(3):337-352.
Stone, K.C., P.G. Hunt, K.B. Cantrell, and K.S. Ro. 2010. The potential impacts of biomass feedstock production on
water resource availability. Bioresource Technology 101(6):2014-2025.
Tilman, D., J. Hill, and C. Lehman. 2006. Carbon-negative biofuels from low-input high-diversity grassland bio-
mass. Science 314(5805):1598-1600.
Tolbert, V. 1998. Special issue - Environmental effects of biomass crop production. What do we know? What do
we need to know? Guest editorial. Biomass and Bioenergy 14(4):301-306.
Tolbert, V.R., and L.L. Wright. 1998. Environmental enhancement of US biomass crop technologies: Research
results to date. Biomass and Bioenergy 15(1):93-100.
Traviss, N., B.A. Thelen, J.K. Ingalls, and M.D. Treadwell. 2010. Biodiesel versus diesel: A pilot study comparing
exhaust exposures for employees at a rural municipal facility. Journal of the Air and Waste Management
Association 60(9):1026-1033.
Trumble, J.T., W.G. Carson, and G.S. Kund. 1997. Economics and environmental impact of a sustainable integrated
pest management program in celery. Journal of Economic Entomology 90(1):139-146.
Turner, B.L., E.F. Lambin, and A. Reenberg. 2007. The emergence of land change science for global environmental
change and sustainability. Proceedings of the National Academy of Sciences of the United States of America
104(52):20666-20671.
Turner, R.E., N.N. Rabalais, and D. Justic. 2006. Predicting summer hypoxia in the northern Gulf of Mexico: Riv-
erine N, P, and Si loading. Marine Pollution Bulletin 52(2):139-148.
Tyner, W.E., F. Taheripour, Q. Zhuang, D. Birur, and U. Baldos. 2010. Land Use Changes and Consequent CO2
Emissions due to US Corn Ethanol Production: A Comprehensive Analysis. West Lafayette, IN: Purdue
University.
Uherek, E., T. Halenka, J. Borken-Kleefeld, Y. Balkanski, T. Berntsen, C. Borrego, M. Gauss, P. Hoor, K. Juda-Rezler,
J. Lelieveld, D. Melas, K. Rypdal, and S. Schmid. 2010. Transport impacts on atmosphere and climate: Land
transport. Atmospheric Environment 44(37):4772-4816.
UNL (University of Nebraska, Lincoln). 2007. Nebraska water map/poster. Available online at http://water.unl.
edu/watermap/watermap. Accessed June 11, 2010.
OCR for page 261
261
ENVIRONMENTAL EFFECTS AND TRADEOFFS OF BIOFUELS
UNL (University of Nebraska, Lincoln). 2009. Groundwater-level changes in Nebraska. Available online at http://
snr.unl.edu/data/water/groundwatermaps.asp. Accessed February 10, 2011.
U.S. Congress Office of Technology Assessment. 1987. Technologies to Maintain Biological Diversity. Washington,
DC: U.S. Government Printing Office.
USDA-ERS (U.S. Department of Agriculture - Economic Research Service). 2004. Irrigation and Water Use. Avail-
able online at http://www.ers.usda.gov/Briefing/WaterUse/. Accessed September 20, 2010.
USDA-ERS (U.S. Department of Agriculture - Economic Research Service). 2010a. Feed grains database: Custom
queries. Available online at http://www.ers.usda.gov/Data/FeedGrains/CustomQuery/. Accessed June
24, 2010.
USDA-ERS (U.S. Department of Agriculture - Economic Research Service). 2010b. Feed grains database: Yearbook
tables. Available online at http://www.ers.usda.gov/data/FeedGrains/FeedYearbook.aspx. Accessed Sep-
tember 9, 2010.
USDA-ERS (U.S. Department of Agriculture - Economic Research Service). 2010c. Fertilizer use and price. Avail-
able online at http://www.ers.usda.gov/Data/FertilizerUse/. Accessed October 26, 2010.
USDA-NASS (U.S. Department of Agriculture - National Agricultural Statistics Service). 2010. Data and statistics:
Quick stats. Available online at http://www.nass.usda.gov/Data_and_Statistics/Quick_Stats/index.asp.
Accessed June 24, 2010.
USDA-NASS (U.S. Department of Agriculture - National Agricultural Statistics Service). 2009. Irrigated corn for
grain, harvested acres: 2007. Available online at http://www.agcensus.usda.gov/Publications/2007/On-
line_Highlights/Ag_Atlas_Maps/Crops_and_Plants/index.asp. Accessed on June 24, 2010.
USDA-NASS (U.S. Department of Agriculture - National Agricultural Statistics Service). 2011. Prospective Plant-
ings. Washington, DC: U.S. Department of Agriculture.
USDA-NIFA (U.S. Department of Agriculture - National Institute of Food and Agriculture). 2009. Precision, geo-
spatial and sensor technologies: Adoption of precision agriculture. Available online at http://www.csrees.
usda.gov/nea/ag_systems/in_focus/precision_if_adoption.html. Accessed November 19, 2010.
USDA-NRCS (U.S. Department of Agriculture - Natural Resources Conservation Service). 2009. Planting and
Managing Switchgrass as a Biomass Energy Crop. Washington, DC: U.S. Department of Agriculture.
USFS (U.S. Department of Agriculture - Forest Service). 2001. U.S. Forest Facts and Historical Trends. Washington,
DC: U.S. Department of Agriculture.
USGS (U.S. Geological Survey). 2011. WaterWatch. Available online at http://waterwatch.usgs.gov/new/. Ac-
cessed February 10, 2011.
van Dam, J., M. Junginger, A. Faaij, I. Jürgens, G. Best, and U. Fritsche. 2008. Overview of recent developments in
sustainable biomass certification. Biomass and Bioenergy 32(8):749-780.
van der Voet, E., R.J. Lifset, and L. Luo. 2010. Life-cycle assessment of biofuels, convergence and divergence.
Biofuels 1(3):435-449.
Van Groenigen, J.W., G.L. Velthof, O. Oenema, K.J. Van Groenigen, and C. Van Kessel. 2010. Towards an agronomic
assessment of N(2)O emissions: A case study for arable crops. European Journal of Soil Science 61(6):903-913.
VanLoocke, A., C.J. Bernache, and T.E. Twine. 2010. The impacts of Miscanthus × giganteus production on the
Midwest US hydrologic cycle. GCB Bioenergy 2:180-191.
Vaquer-Sunyer, R., and C.M. Duarte. 2008. Thresholds of hypoxia for marine biodiversity. Proceedings of the
National Academy of Sciences of the United States of America 105(40):15452-15457.
Volk, T.A., and V.A. Luzadis. 2009. Willow biomass production for bioenergy, biofuels and bioproducts in New
York. Pp. 238-260 in Renewable Energy from Forest Resources in the United States, B.D. Solomon and V.A.
Luzadis, eds. New York: Routledge.
Wang, M.Q., J. Han, Z. Haq, W.E. Tyner, M. Wu, and A. Elgowainy. 2011a. Energy and greenhouse gas emission
effects of corn and cellulosic ethanol with technology improvements and land use changes. Biomass and
Bioenergy 35(5):1885-1896.
Wang, M., H. Huo, and S. Arora. 2011b. Methods of dealing with co-products of biofuels in life-cycle analysis and
consequent results within the U.S. context. Energy Policy 39(10):5726-5736.
Wang, M., M. Wu, and H. Huo. 2007. Life-cycle energy and greenhouse gas emission impacts of different corn
ethanol plant types. Environmental Research Letters 2(2):024001.
Wear, D.N., and B.C. Murray. 2004. Federal timber restrictions, interregional spillovers, and the impact on US
softwood markets. Journal of Environmental Economics and Management 47(2):307-330.
Webster, C.R., D.J. Flaspohler, R.D. Jackson, T.D. Meehan, and C. Gratton. 2010. Diversity, productivity and land-
scape-level effects in North American grasslands managed for biomass production. Biofuels 1(3):451-461.
Weidema, B. 2003. Market information in life cycle assessment. Copenhagen: Danish Environmental Protection
Agency.
OCR for page 262
262 RENEWABLE FUEL STANDARD
West, T.O., C.C. Brandt, L.M. Baskaran, C.M. Hellwinckel, R. Mueller, C.J. Bernacchi, V. Bandaru, B. Yang, B.S.
Wilson, G. Marland, R.G. Nelson, D.G.D. Ugarte, and W.M. Post. 2010. Cropland carbon fluxes in the United
States: Increasing geospatial resolution of inventory-based carbon accounting. Ecological Applications
20(4):1074-1086.
Wiegmann, K., K.R. Hennenberg, and U.R. Fritsche. 2008. Degraded Land and Sustainable Bioenergy Feedstock
Production. Darmstadt, Germany: Öko-Institut.
Wilhelm, W.W., J.M.E. Johnson, D.L. Karlen, and D.T. Lightle. 2007. Corn stover to sustain soil organic carbon
further constrains biomass supply. Agronomy Journal 99(6):1665-1667.
Wilkie, A.C., K.J. Riedesel, and J.M. Owens. 2000. Stillage characterization and anaerobic treatment of ethanol
stillage from conventional and cellulosic feedstocks. Biomass and Bioenergy 19(2):63-102.
Williams, P.R.D., D. Inman, A. Aden, and G.A. Heath. 2009. Environmental and sustainability factors associated
with next-generation biofuels in the U.S.: What do we really know? Environmental Science and Technology
43(13):4763-4775.
Wise, M., K. Calvin, A. Thomson, L. Clarke, B. Bond-Lamberty, R. Sands, S.J. Smith, A. Janetos, and J. Edmonds.
2009. Implications of limiting CO2 concentrations for land use and energy. Science 324(5931):1183-1186.
Woodbury, P.B., L.S. Heath, and J.E. Smith. 2006. Land use change effects on forest carbon cycling throughout the
southern United States. Journal of Environmental Quality 35(4):1348-1363.
Wright, L., and A. Turhollow. 2010. Switchgrass selection as a “model” bioenergy crop: A history of the process.
Biomass and Bioenergy 34(6):851-868.
Wu, J.J. 2000. Slippage effects of the conservation reserve program. American Journal of Agricultural Economics
82(4):979-992.
Wu, M., M. Mintz, M. Wang, and S. Arora. 2009a. Consumptive Water Use in the Production of Ethanol and Pe-
troleum Gasoline. Argonne, IL: Argonne National Laboratory.
Wu, M., M. Mintz, M. Wang, and S. Arora. 2009b. Water consumption in the production of ethanol and petroleum
gasoline. Environmental Management 44(5):981-997.
Wu, M., Y. Wu, and M. Wang. 2006. Energy and emission benefits of alternative transportation liquid fuels derived
from switchgrass: A fuel life cycle assessment. Biotechnology Progress 22(4):1012-1024.
Wu, X., S. Staggenborg, J.L. Propheter, W.L. Rooney, J. Yu, and D. Wang. 2010. Features of sweet sorghum juice and
their performance in ethanol fermentation. Industrial Crops and Products 31(1):164-170.
Wu-Haan, W., W. Powers, R. Angel, and T.J. Applegate. 2010. The use of distillers dried grains plus solubles as a
feed ingredient on air emissions and performance from laying hens. Poultry Science 89(7):1355-1359.
Yanowitz, J., and R.L. McCormick. 2009. Effect of E85 on tailpipe emissions from light-duty vehicles. Journal of
the Air and Waste Management Association 59(2):172-182.
Yeh, S., S.M. Jordaan, A.R. Brandt, M.R. Turetsky, S. Spatari, and D.W. Keith. 2010. Land use greenhouse
gas emissions from conventional oil production and oil sands. Environmental Science and Technology
44(22):8766-8772.
Zhang, X., R.C. Izaurralde, D. Manowitz, T.O. West, W.M. Post, A.M. Thomson, V.P. Bandaruw, J. Nichols, and J.R.
Williams. 2010. An integrative modeling framework to evaluate the productivity and sustainability of biofuel
crop production systems. Global Change Biology Bioenergy 2(5):258-277.
Zilberman, D., G. Hochman, and D. Rajagopal. 2010. On the inclusion of direct land use in biofuel regulations.
University of Illinois Law Review 2011:413-434.
Zimmerman, A.R., B. Gao, and M.Y. Ahn. 2011. Positive and negative carbon mineralization priming effects among
a variety of biochar-amended soils. Soil Biology and Biochemistry 43(6):1169-1179.
