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Pr
epared for Members and Committees of Congress
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ȱ
ž––Š›¢ȱ
In the United States, the agriculture and forestry sectors account for less than 10% of current
estimated total U.S. greenhouse gas (GHG) emissions annually. Combined, these sectors are
estimated to emit nearly 600 million metric tons CO2 equivalent (MMT CO2-Eq.) each year, most
of which is emitted from the agriculture sector.
Current estimates of the combined amount of carbon sequestered by the agriculture and forestry
sectors is reported at about 800 MMT CO2-Eq. per year, most of which is attributable to carbon
stocks and uptake by trees in the forestry sector.
Numerous studies estimate the additional GHG mitigation potential of farm and forestry
activities. Among these, two commonly cited studies are those conducted by the U.S. Department
of Agriculture (USDA) and the U.S. Environmental Protection Agency (EPA).
Compared to current estimated mitigation potential levels, USDA and EPA projections provide a
mostly positive picture of the potential for farm and forestry activities to mitigate GHG
emissions. USDA and EPA project added mitigation potential of 590 to 990 MMT CO2-Eq.
annually, thus increasing to roughly double current levels, assuming a high-end value or market
price for carbon. At lower carbon prices, estimated additional mitigation potential is lower, but
could still add about 40 to 160 MMT CO2-Eq. annually above current sequestration levels.
These estimates are useful indicators of the potential for carbon storage in the agriculture and
forestry sectors, which some in Congress see as potentially available for carbon offset allowances
as part of a cap-and-trade program. A cap-and-trade system—as part of a GHG emissions
reduction and trading program—is one possible approach being considered by Congress to
address GHG emissions in the ongoing climate change debate.
For policy decision-making, however, the results of studies such as those conducted by EPA and
USDA to assess the carbon mitigation potential of farms and forests should be viewed with
caution. These results are derived using complicated simulation models. The available input data
and modeling assumptions are limited in the extent to which they are able to accurately reflect
both actual current conditions and longer-term future conditions. Given that these studies were
developed using data and information for the early 2000s—prior to a variety of recent policy,
market, and economic changes—some researchers now acknowledge that the published results of
these studies are almost certainly outdated. Other related concerns include criticisms by
prominent researchers of these modeling approaches and estimates. In addition, in the absence of
defined policies outlining how an emission trading system would be designed and implemented,
these models are limited in the extent to which they can depict future conditions under a
regulatory system for sequestering carbon on farms and forests. Most likely the results of these
studies reflect an upper bound of the carbon storage potential in the farm and forestry sectors.
˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ
œ’–ŠÂŽœȱ˜ÂȱŠ›‹˜—ȱ’Â’Š’˜—ȱ˜ÂŽ—Â’Š•ȱ›˜–ȱ›’Œž•Âž›Š•ȱŠ—Âȱ˜›ŽœÂ›¢ȱŒÂ’Ÿ’Â’Žœȱ
ȱ
˜—ÂŽ—Âœȱ
Introduction ..................................................................................................................................... 1
Estimated Current Emissions and Sequestration ............................................................................. 1
Estimated Additional Potential Sequestration ................................................................................. 3
Potential Additional Storage by Practice................................................................................... 3
Potential Additional Storage in Aggregate ................................................................................ 6
Estimated Current versus Potential Additional Sequestration................................................... 9
Limitations of Mitigation Potential Estimates............................................................................... 10
General Caveat on Market Models.......................................................................................... 10
National Energy Policy Provisions ..........................................................................................11
Farm-Based Energy Policy Provisions.................................................................................... 12
Agriculture Market Conditions ............................................................................................... 13
Forestry Sector Uncertainties .................................................................................................. 14
Regulatory Framework and Future GHG Policies/Programs.................................................. 16
Considerations for Congress.......................................................................................................... 17
’ž›Žœȱ
Figure 1. CBO Estimates of the Amount of Carbon That Would Be Sequestered Annually
Through Afforestation in the United States at Different CO2 Prices............................................ 8
Figure 2. CBO Estimates of the Amount of Carbon That Would Be Sequestered Annually
In Cropland Soil in the United States at Different CO2 Prices ..................................................... 9
Š‹•Žœȱ
Table 1. Estimated Current GHG Emissions and Carbon Sequestration: U.S. Agricultural
and Forestry Activities, Average (2001-2005).............................................................................. 2
Table 2. Estimated Sequestration Potential by Practice (Annual per Acre): Selected Land
Use and Production Practice Changes.......................................................................................... 5
Table 3. Estimated Sequestration Potential in Aggregate, Annual Tonnage: Net Emission
Reductions Below Baseline at a Range of Carbon Prices ............................................................ 6
˜—ŠŒÂœȱ
Author Contact Information .......................................................................................................... 18
˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ
œ’–ŠÂŽœȱ˜ÂȱŠ›‹˜—ȱ’Â’Š’˜—ȱ˜ÂŽ—Â’Š•ȱ›˜–ȱ›’Œž•Âž›Š•ȱŠ—Âȱ˜›ŽœÂ›¢ȱŒÂ’Ÿ’Â’Žœȱ
ȱ
—›˜ÂžŒÂ’˜—ȱ
Numerous theoretical and empirical studies estimate the greenhouse gas (GHG) mitigation
potential of farm and forestry activities, and suggest that the potential for carbon uptake in
agricultural soils and forest lands is much greater than current rates. Among these studies, two
commonly cited reports by the U.S. Department of Agriculture (USDA) and the U.S.
Environmental Protection Agency (EPA) take a comprehensive approach to assessing the
mitigation potential in the agriculture and forestry sectors:
• USDA, Economics of Sequestering Carbon in the U.S. Agricultural Sector, April
2004, http://www.ers.usda.gov/publications/tb1909/; and
• EPA, Greenhouse Gas Mitigation Potential in U.S. Forestry and Agriculture,
November 2005, http://www.epa.gov/sequestration/pdf/greenhousegas2005.pdf.
Each of these studies provide estimates that are useful in approximating the potential for
agricultural and forestry activities to mitigate GHGs and store carbon, beyond current estimated
sequestration rates. Some in Congress are considering including certain agricultural and forestry
activities as carbon offset allowances under a cap-and-trade program,1 making these activities and
estimates of their mitigation potential relevant to the ongoing climate change debate.2
Following a discussion of the estimated current emissions and carbon sequestration by the
agricultural and forestry sectors, this report presents a brief overview of the available estimates
from USDA and EPA carbon mitigation studies, and then discusses some of the limitations of the
available data and modeling results. The report is organized into three parts. The first provides a
brief overview of the role of the agriculture and forestry sectors within the broader climate
change debate, describing available estimates of current GHG emissions and carbon sequestration
in the farm and forestry sectors. The second describes available data and information on the
potential for carbon storage (tonnage) by type of farming and forestry activity, and presents
available estimates of the carbon sequestration potential in these sectors. The final part discusses
some of the limitations of available estimates of GHG mitigation potential in the agriculture and
forestry sectors, focusing on recent policy and market changes and other types of modeling
uncertainties that could limit the accuracy of available mitigation projections. Information
presented in this report is compiled from selected GHG mitigation studies and derived from
model simulations, estimated across a range of assumed carbon market prices.
œ’–ŠÂÂŽÂȱž››Ž—Âȱ–’œœ’˜—œȱŠ—ÂȱŽšžŽœÂ›ŠÂ’˜—ȱ
Farm and forestry activities are a both a source and a sink of greenhouse gases, generating
emissions that enter the atmosphere and removing carbon dioxide (CO2) from the atmosphere
through photosynthesis and storing it in vegetation and soils (a process known as sequestration).
1 A cap-and-trade program provides a market-based policy tool for reducing emissions by setting a cap, or maximum
emissions limit, for certain industries. Sources covered by the cap can choose to reduce their own emissions, or can
choose to buy emission credits that are generated from reductions made by other sources.
2 For information on the current policy debate and legislative proposals, see CRS Report RL33846, Greenhouse Gas
Reduction: Cap-and-Trade Bills in the 110th Congress, and CRS Report RL34067, Climate Change Legislation in the
110th Congress.
˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ
ŗȱ
œ’–ŠÂŽœȱ˜ÂȱŠ›‹˜—ȱ’Â’Š’˜—ȱ˜ÂŽ—Â’Š•ȱ›˜–ȱ›’Œž•Âž›Š•ȱŠ—Âȱ˜›ŽœÂ›¢ȱŒÂ’Ÿ’Â’Žœȱ
ȱ
As reported by EPA, the agriculture and forestry sectors currently account for less than 10% of
estimated total U.S. greenhouse gas (GHG) emissions annually. Combined, these sectors are
estimated to emit nearly 600 million metric tons CO2 equivalent (MMT CO2-Eq.) each year, most
of which is from the agricultural sector.3 Current estimates of the combined amount of carbon
sequestered by the agricultural and forestry sectors is reported at about 800 MMT CO2-Eq. per
year, most of which is attributable to carbon stocks and uptake by trees in the forestry sector.
Combined, carbon sequestration on farm and forested lands is currently estimated to mitigate
about 11% of total annual GHG emissions in the United States. Growth in forest stocks account
for the majority of this estimated sequestration, with agricultural soils accounting for a small
share of this total.4 (See Table 1.)
Table 1. Estimated Current GHG Emissions and Carbon Sequestration: U.S.
Agricultural and Forestry Activities, Average (2001-2005)
(million metric tons CO equivalent (MMT CO -Eq.))
2
2
Source Emissions
Sequestrationa Net
Agricultural Activities
582.0
(31.5)
550.5
Forestry Activities
9.8
(767.7)
(757.9)
Subtotal 591.8
(799.2)
(207.4)
U.S. Total, All Sources
7,132.0
(808.9)
6,323.1
% U.S. Total, Agriculture Share
8%
4%
—
% U.S. Total, Forestry Share
<0.5%
95%
—
Source: Compiled by CRS from EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005, April 2007
(Table 2-14), http://epa.gov/climatechange/emissions/usinventoryreport.html.
Notes:
a. Measured agricultural sequestration categories include land converted to grassland, grassland remaining
grassland, land converted to cropland, and cropland remaining cropland. Forestry includes change in forest
stocks and carbon uptake from urban trees. Total also includes landfilled yard trimmings and food scraps.
Compared to total national GHG emissions, the U.S. forestry sector offsets about 10% of all
emissions annually, more than offsetting the less than 1% of annual GHG emissions associated
with the sector.5 The U.S. agricultural sector, however, remains a net source of GHG emissions
and sequesters only about 4% of the carbon-equivalent GHG emissions generated by the sector
each year. Compared to total national GHG emissions, the U.S. agriculture sector offsets well
under 1% of all emissions annually.6
3 GHG emissions from agriculture are associated with livestock operations (as part of the natural digestive process of
animals and manure management) and crop production (soil management, commercial fertilizer and manure
application, and from the production of nitrogen-fixing crops). The two key types of GHG emissions are methane
(CH4) and nitrous oxide (N2O). Estimated emissions are expressed on a CO2-equivalent basis. See CRS Report
RL33898, Climate Change: The Role of the U.S. Agriculture Sector.
4 Calculated as total agricultural and forestry sector sequestration (799 MMT CO2-Eq.) divided by total emissions from
all sources (7132 MMT CO2-Eq.) See Table 1.
5 GHG emissions from forestry are associated with usually from timber cutting, wildfires, and tree decomposition. See
CRS Report RL31432, Carbon Sequestration in Forests.
6 Calculated as estimated sequestration from agricultural activities (31.5 MMT CO2-Eq.) divided by total emissions
(continued...)
˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ
Řȱ
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ȱ
œ’–ŠÂÂŽÂȱÂÂÂ’Â’˜—Š•ȱ˜ÂŽ—Â’Š•ȱŽšžŽœÂ›ŠÂ’˜—ȱ
˜ÂŽ—Â’Š•ȱÂÂÂ’Â’˜—Š•ȱ˜›ŠÂŽȱ‹¢ȱ›ŠŒÂ’ŒŽȱ
The types of individual farm and forestry practices that sequester carbon, and thus help mitigate
GHG emissions, include a range of commonly used land management, agricultural conservation,
and other farmland practices. Examples are shown in the text box.
Agricultural and Forestry Practices
That Reduce Emissions and/or Sequester Carbon
Land retirement, conversion, and restoration. Includes conversion/restoration to grasslands, wetlands, or
rangelands; and selected structural barriers, such as vegetative and riparian buffers, setbacks, windbreaks.
Cropland tillage practices. Includes reduced/medium-till, no-till, ridge/strip-till versus conventional tillage, soil
management/conservation, soil supplements/amendments, soil erosion controls, precision agriculture practices, and
recognized best management practices.
Cropping techniques. Includes crop rotations, cover cropping, precision agriculture practices, efficient
fertilizer/nutrient (including manure), and chemical application.
Manure and feed management. Includes improved manure storage (e.g., anaerobic digestion) and methane
recovery; improved feed efficiency; and dietary supplements.
Grazing management. Includes rotational grazing and improved forage practices.
Bioenergy/biofuels substitution. Includes on-farm use; replacing fossil fuels or deriving bioenergy from land-based
feedstocks (renewable energy); and on-farm energy efficiency/conservation.
Afforestation/Reforestation. Includes establishing forested areas by planting trees or their seeds, or creating
forested areas through conversion of pastureland and cropland.
Forest management. Includes practices to increase growth on some stems while releasing some carbon (total
biomass growth change could be positive or negative); harvest for long-term wood products; reduced impact logging;
certified sustainable forestry; thinning/release (mechanical, chemical, prescribed burning); fertilization; and pruning.
Avoided deforestation/forest degradation. Includes emissions when (mostly tropical) forests are burned,
degraded, or cleared, and large amounts of carbon are released into the atmosphere.
This list reflects the range of agricultural and forestry practices that could potentially either
reduce or abate GHG emissions and/or sequester carbon. However, the verifiability of agricultural
and forestry sequestration within a carbon trading program can be problematic and implies the
need for a high standard for what can be counted. Many of these mitigation practices may not be
practicable for an emission trading program because they might not be able to meet convincing
standards for quantifying, monitoring, and verifying the emission reduction or carbon storage
(and, therefore, may have questionable GHG reduction potential in practice).7
The inclusion of these or any mitigation practice as part of a federal emissions trading regime will
depend on the feasibility of developing protocols to ensure that these types of practices are able to
be quantified, monitored, and verified. In fact, a relatively narrow list of farm and forestry
(...continued)
from all sources (7132 MMT CO2-Eq.) See Table 1.
7 See CRS Report RS22964, Measuring and Monitoring Carbon in the Agricultural and Forestry Sectors.
˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ
řȱ
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ȱ
practices are being considered as offsets under some of the active or emerging regional climate
change initiatives, such as the Regional Greenhouse Gas Initiative (RGGI), the Western Climate
Initiative, and California’s climate change statute. These programs allow or are considering
allowing certain types of agricultural and forestry projects as part of their offset/allowance
programs. However, the list of eligible agricultural and forestry activities tends to focus on either
high-end, tested technologies (e.g., anaerobic digesters) and/or projects that are fairly easy to
measure, verify, and monitor (afforestation and reforestation, manure management, etc.). Many
offset/allowance projects under these initiatives tend to be outside the agricultural and forestry
sectors, such as landfill gas and wastewater management, reduced CO2 and sulfur hexafluoride
(SF6) emissions from energy production, and various energy efficiency measures.8
Table 2 provides the estimated sequestration rates for selected types of practices, based on the
current literature as summarized by USDA and EPA. The estimates show the potential for carbon
storage (tonnage) by type of farming and forestry activity.9
As shown, estimated sequestration rates vary widely, illustrating differences in the literature and
uncertainty because of varying site-specific conditions across production regions, differences in
the management and implementation of the various practices, and also differences in how these
rates are measured across studies, among other factors.
Avoided deforestation is reported to have the greatest estimated potential to sequester carbon,
estimated to range from 84 to 172 metric tons of CO2 -equivalent sequestered per acre annually,
as reported by EPA. Other land use practices, such as afforestation, conversion and restoration
activities, and pasture and rangeland management are reported to have the potential to sequester
between about 1 to nearly 10 metric tons of CO2 -equivalent per acre annually. Various changes in
cropland and animal production practices are reported to sequester less than, but up to, about 1
metric ton of CO2 -equivalent per acre annually.
For other information on the potential to sequester carbon by selected agricultural and forestry
practices, and for more background on the types of farm and forestry activities that may reduce
and/or sequester carbon, see CRS Report RL33898, Climate Change: The Role of the U.S.
Agriculture Sector, and CRS Report RL31432, Carbon Sequestration in Forests.
8 Stockholm Environment Institute, A Review of Offset Programs: Trading Systems, Funds, Protocols, Standards and
Retailers, October 2008, http://www.sei-us.org/climate-and-energy/SEIOffsetReview08.pdf]; RGGI, “Overview of
RGGI CO2 Budget Trading Program,†Oct. 2007, http://www.rggi.org/docs/program_summary_10_07.pdf; Western
Climate Initiative, Design Recommendations for the WCI Regional Cap-and-Trade Program, September 2008,
http://www.westernclimateinitiative.org/; and California Environmental Protection Agency, Expanded List of Early
Action Measures to Reduce Greenhouse Gas Emissions in California Recommended for Board Consideration, Oct.
2007, http://www.arb.ca.gov/cc/ccea/meetings/ea_final_report.pdf.
9 EPA and USDA used different units to measure the rate of sequestered carbon: USDA’s rates are reported in terms of
metric tons of carbon sequestered per acre per year (MT C/acre/year), whereas EPA’s rates are in metric tons of CO2
per acre per year (MT CO2 /acre/year). To convert from EPA-reported CO2 units to carbon equivalent units, multiply
CO2 by 0.2727. To convert from carbon to CO2 equivalent units, multiply by 3.667. Where applicable, CRS converted
rates of carbon to CO2 equivalent units. Most of the current legislative proposals that are being considered use CO2 as
the unit of measurement.
˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ
Śȱ
œ’–ŠÂŽœȱ˜ÂȱŠ›‹˜—ȱ’Â’Š’˜—ȱ˜ÂŽ—Â’Š•ȱ›˜–ȱ›’Œž•Âž›Š•ȱŠ—Âȱ˜›ŽœÂ›¢ȱŒÂ’Ÿ’Â’Žœȱ
ȱ
Table 2. Estimated Sequestration Potential by Practice (Annual per Acre):
Selected Land Use and Production Practice Changes
(MT CO2-Eq. sequestered per acre per year)
Activity
EPA (2005)
USDA (2004)
Forestry
Afforestation (previously cropland/pasture)
2.2 - 9.5
2.7 - 7.7
Reforestation
1.1 - 7.7
—
Avoided deforestation
83.7 - 172.1a —
Changes in forest management
2.1 - 3.1
—
Cropland/Land Use changes
Afforestation of croplands
—
2.9 - 6.3
Afforestation of pastureland
—
2.7 - 7.7
Cropland conversion to grasslands
0.9 - 1.9
0.9 - 1.9
Restoration of wetlands
0.4
—
Riparian or conservation buffers (non-forest)
0.4 - 1.0
0.5 - 0.9
Production/Grazing Practice Changes
Reduced/conservation tillage
0.6 - 1.1
0.3 - 0.7
Improved crop rotations, cover crops, elimination of summer
fallow
—
0.2 - 0.4
Improved fertilizer management
—
0.1 - 0.2
Improved irrigation management
—
0.2
Use of manure/byproducts on pasture
—
0.7 - 1.8
Rangeland management
—
0.2 - 0.6
Pastureland management
—
0.4 - 1.8
Grazing management
0.1 - 1.9
1.1 - 4.8
Other
Biofuels substitutes for fossil fuels
4.8 - 5.5
—
Source: EPA, Greenhouse Gas Mitigation Potential in U.S. Forestry and Agriculture, Nov. 2005, Table 2-1,
http://www.epa.gov/sequestration/greenhouse_gas.html; and USDA, Economics of Sequestering Carbon in the
U.S. Agricultural Sector, Apr. 2004, Table 2.2, http://www.ers.usda.gov/publications/tb1909/. Applicable citations
and footnotes are available in the original studies. USDA values are converted from reported metric tons of
carbon sequestered per acre per year (multiplied by 3.667; see footnote 9), rounded to nearest tenth.
“—“ indicates that estimates were not reported by the studies.
Notes:
a. Values represent the assumed CO2 loss avoided by not cutting the forest. The amount remains the same
year after year, as long as the forest is not cut, and thus is comparable to annual estimates from other
options. Low and high national annual average per acre estimates based on acres deforested from National
Resource Inventory (NRI) data and carbon stock decline from the FORCARB model, from 1990 to 1997.
Reported in U.S. government submission documents: “United States Submission on Land-Use, Land-Use
Change, and Forestry,†August 2000, http://www.state.gov/www/global/global_issues/climate/
000801_unfccc1_subm.pdf.
˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ
śȱ
œ’–ŠÂŽœȱ˜ÂȱŠ›‹˜—ȱ’Â’Š’˜—ȱ˜ÂŽ—Â’Š•ȱ›˜–ȱ›’Œž•Âž›Š•ȱŠ—Âȱ˜›ŽœÂ›¢ȱŒÂ’Ÿ’Â’Žœȱ
ȱ
˜ÂŽ—Â’Š•ȱÂÂÂ’Â’˜—Š•ȱ˜›ŠÂŽȱ’—ȱ›ŽÂŠÂŽȱ
In addition to estimates of additional carbon storage potential by practice (Table 2), both the
USDA and EPA studies provide aggregate annual estimates of the additional carbon storage
potential for various agricultural and forestry activities (Table 3). These aggregate estimates are
in addition to current estimated sequestration rates in these sectors (Table 1).
Table 3. Estimated Sequestration Potential in Aggregate, Annual Tonnage:
Net Emission Reductions Below Baseline at a Range of Carbon Prices
(MMT CO2-Eq.)
$3-$5
$13-$15
$30-$34
Source
$/MTCO2-Eq.
$/MTCO2-Eq.
$/MTCO2-Eq.
USDA study
Afforestation
0 - 31
105 - 264
224 - 489
Agriculture Soil Carbon
0 - 4
3 - 30
13 - 95
Subtotal
0 - 35
108 - 295
237 - 587
EPA study
Afforestation 12
228
806
Agriculture Soil Carbon
149
204
187
Subtotal 161
432
994
Source: As reported by EPA, Greenhouse Gas Mitigation Potential in U.S. Forestry and Agriculture, Table 4-10, Nov.
2005, http://www.epa.gov/sequestration/greenhouse_gas.html.
Notes: Uses comparable estimates from USDA, Economics of Sequestering Carbon in the U.S. Agricultural Sector,
Apr. 2004, http://www.ers.usda.gov/publications/tb1909/. Net reduction below baseline at a range of carbon
prices (about $3- $30/MT CO2-Eq.). Estimates shown are annualized assuming a 15-year program.
Both the USDA and EPA studies estimated GHG mitigation potential using market optimization
models and available data to simulate net changes in carbon sequestration from adopting certain
types of agricultural and forestry practices, compared to current baseline conditions. The text box
below provides a brief summary of each study’s estimation model and approach.
Overview of USDA and EPA Models
USDA: The USDA study uses an adapted version of the U.S. Agricultural Sector Model (USMP), a spatial market
equilibrium model that depicts the U.S. farm sector by geography, crop production, farm-inputs, and production-
enterprise. The model uses recognized parameters of cropland and forestry management and conversion, and
simulates changes across a range of prices over a 15-year carbon storage program. Examined practices include
afforesting croplands and pasture, shifting cropland to permanent grasses, and increasing the use of production
practices, such as no-till and rotations that raise soil-carbon levels.
EPA: The EPA study uses the Forest and Agriculture Sector Optimization Model with Greenhouse Gases
(FASOMGHG), a partial equilibrium model of the U.S. forest and agriculture sectors that depicts land use competition
between the sectors and linkages to international trade, and tracks multiple forest product categories and production
possibilities for field crops, livestock, and biofuels for private lands (excluding public lands). The model simulates
changes across a range of prices over a 100-year period from afforestation, forest management, changes in tillage
practices, energy substitution, livestock management and fertilizer applications, and biofuel offsets of fossil fuels
derived from crops.
˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ
Ŝȱ
œ’–ŠÂŽœȱ˜ÂȱŠ›‹˜—ȱ’Â’Š’˜—ȱ˜ÂŽ—Â’Š•ȱ›˜–ȱ›’Œž•Âž›Š•ȱŠ—Âȱ˜›ŽœÂ›¢ȱŒÂ’Ÿ’Â’Žœȱ
ȱ
Both studies account for current conditions, as well as expected direct costs and opportunity costs
in modeling landowners’ decision-making. These estimates are measured in terms of carbon
storage over time (15 to 100 years) across a range of assumed carbon market prices (roughly $3
to $50/MT CO2-Eq.). These published results show a range of carbon prices by type of farming
and forestry activity. The presumed relationship between carbon sequestration and price shows
that as carbon prices rise, this will likely attract more investment and adoption of additional and
differing types of mitigation activities. These estimates are reported as a national total and are
also broken out by select U.S. regions. For more information on these models and for additional
modeling results, see the EPA and USDA studies.
Table 3 shows the estimated carbon mitigation potential reported by EPA and USDA for two
mitigation categories—afforestation and soil sequestration—across a range of assumed carbon
prices. In general, the low end of this price range indicates that carbon sequestration potential is
mostly associated with cropland management practices, whereas higher-end prices are mostly
associated with land retirement and conversion, and a longer sequestration tenure. EPA’s analysis
includes estimates of other mitigation activities, including forest management on private lands.
These estimates reflect the net reduction compared to baseline conditions, or current estimated
sequestration (Table 1).
USDA reports that the potential for net increases in carbon sequestration through afforestation
and in agricultural soils is estimated to range widely from 0 to 587 MMT CO2-Eq. per year,
following the implementation of a 15-year program (Table 3).10 Sequestration potential is
estimated to be greatest at the high end of the assumed price range for carbon (about $30/MT
CO2-Eq.). At this price level, USDA projects sequestration levels could increase by 587 MMT
CO2-Eq. annually. Even at lower prices (about $3/MT CO2-Eq.), the projected mitigation
potential is double the current estimated sequestration for these types of agricultural activities.
Comparable EPA estimates (15-year period) project a higher sequestration potential for the U.S.
agricultural sector across the range of assumed carbon prices, reported at 160 MMT CO2-Eq. per
year at lower carbon prices to 990 MMT CO2-Eq. per year at the higher price levels.11
Afforestation (creation of forested areas mostly through conversion of pastureland and cropland)
reflects the majority of the estimated uptake potential, with agricultural soil carbon sequestration
accounting for a smaller share at the high end of the estimated range. However, large projected
gains in mitigation from afforestation could be overly optimistic, given that afforestation is highly
dependent on land availability and may only come from available cropland or pastureland.
A notable difference between USDA and EPA estimates is that EPA estimates a significantly
greater mitigation potential for soil sequestration activities: USDA projects a potential ranging up
to 95 MMT CO2-Eq. per year, compared to EPA’s projected range of 149 to 187 MMT CO2-Eq.
per year. This difference points to potentially very different modeling assumptions between these
studies. USDA’s lower overall estimate for soil management activities is comparable to other
more recent independent estimates.12
10 Net reduction below baseline at a range of carbon prices from about $3 to $30/MT CO2-Eq., annualized assuming a
15-year program.
11 Reported by EPA, Greenhouse Gas Mitigation Potential in U.S. Forestry and Agriculture, Nov. 2005, Tables 4-10
(15-year), http://www.epa.gov/sequestration/greenhouse_gas.html. The resultant estimates may overlap between the
afforestation and forest management categories.
12 For example, see B. McCarl, “Agriculture in the Climate Change and Energy Price Squeeze: Part 2: Mitigation
Opportunities,†Feb. 2007, http://www-agecon.ag.ohio-state.edu/resources/docs/BruceMcCarlPaper.pdf.
˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ
Åȱ
œ’–ŠÂŽœȱ˜ÂȱŠ›‹˜—ȱ’Â’Š’˜—ȱ˜ÂŽ—Â’Š•ȱ›˜–ȱ›’Œž•Âž›Š•ȱŠ—Âȱ˜›ŽœÂ›¢ȱŒÂ’Ÿ’Â’Žœȱ
ȱ
Estimated mitigation potential varies significantly across the different studies. This is illustrated
in two graphs compiled by the Congressional Budget Office (CBO), showing a wide range of
reported estimates of the mitigation potential from afforestation and cropland soil sequestration
(Figure 1 and Figure 2).13
The EPA study also examines mitigation potential from other types of practices, including
mitigation through fossil fuel substitution, livestock manure management, and other mitigation
practices, and reports mitigation potential for various forest management activities on privately
owned lands. Including these practices, EPA projects these other practices could add another 150
to 830 MMT CO2-Eq. in annual mitigation, much of which would accrue over the longer term
(annualized over a 100-year time frame).14 However, as will be discussed further below, these
estimates include mitigation due to a reduction in fossil fuel use from increased biofuel use,
which would likely not be counted as an agricultural carbon offset, given changes in national
energy policies since the EPA study was completed.
Figure 1. CBO Estimates of the Amount of Carbon That Would Be Sequestered
Annually Through Afforestation in the United States at Different CO2 Prices
Source: Congressional Budget Office (CBO), The Potential for Carbon Sequestration in the United States, Sept.
2007, Figure 1, http://www.cbo.gov/ftpdocs/86xx/doc8624/09-12-CarbonSequestration.pdf.
Notes: EPA 2005 = EPA, Greenhouse Gas Mitigation Potential in U.S. Forestry and Agriculture, November
2005. ERS 2004 = USDA, Economics of Sequestering Carbon in the U.S. Agricultural Sector, Apr. 2004,
http://www.ers.usda.gov/publications/tb1909/. MS 2001 = Bruce A. McCarl and Uwe A. Schneider, “Greenhouse
Gas Mitigation in U.S. Agriculture and Forestry,†Science, vol. 294 (December 21, 2001), pp. 2481–2482. R 1997
= Kenneth R. Richards, Estimating Costs of Carbon Sequestration for a United States Greenhouse Gas Policy
(Boston: Charles River Associates, 1997). MR 1990 = Robert J. Moulton and Kenneth R. Richards, Costs of
Sequestering Carbon Through Tree Planting and Forest Management in the United States, General Technical
Report WO-58 (USDA, Forest Service, 1990).
13 CBO, The Potential for Carbon Sequestration in the United States, Sept. 2007, Figures 1 and 2, http://www.cbo.gov/
ftpdocs/86xx/doc8624/09-12-CarbonSequestration.pdf. The reduction in sequestration at higher CO2 prices reflects the
fact that alternative uses of land (such as for growing biofuel crops) become more cost-effective at higher CO2 prices.
14 Ibid, Table 4-5 (100-year time frame).
˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ
Şȱ
œ’–ŠÂŽœȱ˜ÂȱŠ›‹˜—ȱ’Â’Š’˜—ȱ˜ÂŽ—Â’Š•ȱ›˜–ȱ›’Œž•Âž›Š•ȱŠ—Âȱ˜›ŽœÂ›¢ȱŒÂ’Ÿ’Â’Žœȱ
ȱ
Figure 2. CBO Estimates of the Amount of Carbon That Would Be Sequestered
Annually In Cropland Soil in the United States at Different CO2 Prices
Source: Congressional Budget Office (CBO), The Potential for Carbon Sequestration in the United States, Sept.
2007, Figure 2, http://www.cbo.gov/ftpdocs/86xx/doc8624/09-12-CarbonSequestration.pdf.
Notes: The reduction in sequestration at higher CO2 prices reflects the fact that alternative uses of land (such
as for growing biofuel crops) become more cost-effective at higher CO2 prices. M 2007 = Bruce A. McCarl,
“Agriculture in the Climate Change and Energy Price Squeeze, Part 2: Mitigation Opportunities†(presentation
given at the 4th USDA Greenhouse Gas Conference, February 6-8, 2007). EPA 2005 = EPA, Greenhouse Gas
Mitigation Potential in U.S. Forestry and Agriculture, November 2005. ERS 2004 = USDA, Economics of Sequestering
Carbon in the U.S. Agricultural Sector, Apr. 2004, http://www.ers.usda.gov/publications/tb1909/. MS 2001 = Bruce A.
McCarl and Uwe A. Schneider, “Greenhouse Gas Mitigation in U.S. Agriculture and Forestry,†Science, vol. 294
(December 21, 2001), pp. 2481–2482.
USDA and EPA study results are also provided for selected regions. USDA’s simulation predicts
that the greatest mitigation potential is in areas projecting the most potential for afforested
croplands (Appalachian, Southeast, and Pacific regions), although at lower mitigation levels,
mitigation from soil management is expected in areas where crop production is greatest (Lake
States, Corn Belt, and Delta regions). EPA’s results are similar, albeit across differently named
U.S. regions: mitigation potential is greatest in areas projecting the most potential for
afforestation (South Central and Southeast), with additional mitigation from soil management in
crop-producing regions (Corn Belt, Lake States, and Plains States). Consistent with the national-
level results, the greatest gains in mitigation are at carbon prices exceeding $30/MT CO2-Eq.
œ’–ŠÂÂŽÂȱž››Ž—ÂȱŸŽ›œžœȱ˜ÂŽ—Â’Š•ȱÂÂÂ’Â’˜—Š•ȱŽšžŽœÂ›ŠÂ’˜—ȱ
Comparing estimated current carbon sequestration levels with projected future mitigation
potential is problematic. These projections are highly uncertain and dependent on the simplifying
assumptions and data used to model them, in an attempt to simulate possible future conditions.
Actual mitigation potential will ultimately depend on how an emissions trading program allows
farm and forestry carbon offsets to be defined and measured, what the program allows as offsets,
and the ultimate carbon price.
˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ
şȱ
œ’–ŠÂŽœȱ˜ÂȱŠ›‹˜—ȱ’Â’Š’˜—ȱ˜ÂŽ—Â’Š•ȱ›˜–ȱ›’Œž•Âž›Š•ȱŠ—Âȱ˜›ŽœÂ›¢ȱŒÂ’Ÿ’Â’Žœȱ
ȱ
Compared to current estimated mitigation potential levels, USDA and EPA projections provide a
mostly positive picture of the potential for farm and forestry activities to mitigate GHG
emissions. Current estimates of the amount of carbon sequestered by both the agricultural and
forestry sectors are about 800 MMT CO2-Eq. per year (Table 1). USDA and EPA project added
mitigation potential of 590 to 990 MMT CO2-Eq. annually, thus increasing to roughly double the
current levels (assuming the high end of the price range and a 15-year program). At lower prices,
estimated additional mitigation potential is lower, adding about 40 to 160 MMT CO2-Eq.
annually above current sequestration levels.
What these mitigation studies clearly illustrate, however, is that land availability is perhaps the
most critical factor for farm and forestry offset projects. Generally, a wider range of offset project
types becomes economically competitive at higher carbon prices. At certain price levels, one
offset type may replace another. At lower carbon prices, agricultural soil sequestration projects
(e.g., conservation tillage practices) are expected to provide the most cost-effective opportunities.
At higher prices, afforestation projects may become more cost-effective, depending on how much
more carbon is sequestered per acre compared to soil management practices. In theory, as
depicted by these models, lands that once sequestered carbon through soil management practices
could be replaced with afforestation projects (tree farms) at high carbon prices. However, these
practices are expected to be feasible only at higher price levels. Given constraints on land
availability and the myriad other market and nonmarket factors influencing land use, these types
of considerations are nearly impossible to model and predict with any certainty, making any
general conclusions derived from these models subject to a degree of skepticism.
’–’Š’˜—œȱ˜Âȱ’Â’Š’˜—ȱ˜ÂŽ—Â’Š•ȱœÂ’–ŠÂŽœȱ
The results of the USDA and EPA studies provide a useful tool for evaluating the additional
mitigation potential of the farm and forestry sectors. However, given the inherent limitations of
any modeling approach, these results need to be considered with careful qualification.
Ž—Ž›Š•ȱŠŸŽŠÂȱ˜—ȱŠ›”ŽÂȱ˜ÂŽ•œȱ
All simulation models are theoretical constructs intended to represent a system or group of
functionally interrelated elements forming a complex whole. At best, simulation models provide
for a simplified framework designed to illustrate highly complex spatial and temporal dynamics,
interrelationships, and processes. They depend highly on available data and, inevitably, on the
simplifying assumptions of the models necessary to depict the underlying relationships and
processes of a complex system. This complexity can be attributed to a number of factors that are
difficult to quantify, including resource limitations, environmental and geographical constraints,
site-specific conditions, individual and cooperative decision processes, institutional and legal
requirements, and general uncertainty and variability. Consequently models must often rely on
overly simplistic assumptions, such as perfect market competition or optimum behavioral
outcomes (e.g., assuming that all farmers and landowners act in a prescribed manner, and follow
required protocols and manage their operations in ways that achieve maximum on-site carbon
sequestration). Thus, simulation models are limited in the extent to which they are able to reflect
actual conditions accurately. Moreover, it is difficult to compare the results of various studies,
given differences in modeling approach and methodology, scope (geographic region, commodity
sector activities, assumptions about adoption of certain mitigation strategies, etc.), and other
underlying assumptions.
˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ
ŗŖȱ
œ’–ŠÂŽœȱ˜ÂȱŠ›‹˜—ȱ’Â’Š’˜—ȱ˜ÂŽ—Â’Š•ȱ›˜–ȱ›’Œž•Âž›Š•ȱŠ—Âȱ˜›ŽœÂ›¢ȱŒÂ’Ÿ’Â’Žœȱ
ȱ
In addition, available estimates have notable limitations, given certain policy and market
conditions that have occurred since these simulation models were developed. For example, in the
past few years, the agricultural and forestry sectors have been affected by major changes in
federal energy and farm policy, coupled with ongoing market changes, such as rising farmland
values, rising farm input costs, crop and consumer price volatility, and competition for land and
shifting land uses. These policy and market changes have in turn influenced farm and landowner
decisions regarding agricultural production, forest management, and land use. As a result, some
researchers believe that many of the underlying data and simplifying assumptions of these
simulation models may no longer be valid, making the resultant estimates of these studies
outdated.15
ŠÂ’˜—Š•ȱ—Ž›Â¢ȱ˜•’Œ¢ȱ›˜Ÿ’œ’˜—œȱ
USDA and EPA analyses were completed before the enactment of the Energy Policy Act of 2005
and the Energy Independence and Security Act (EISA) of 2007 and thus do not include the effects
of the Renewable Fuel Standard (RFS).16
The RFS requires the use of ethanol and other renewable fuels in transportation fuels.
Specifically, the current RFS requires the use of 9 billion gallons of renewable fuel in 2008,
increasing to 36 billion gallons in 2022. A large share of this mandate is currently being met using
corn-based ethanol. However, EISA requires that a growing share of the mandate—21 billion
gallons in 2022—be met using “advanced biofuels,†which are produced from feedstocks other
than corn starch. Advanced biofuels will likely include imported ethanol produced from sugar
cane and gasoline and diesel substitutes produced from cellulosic materials such as perennial
grasses and fast-growing trees.
The establishment of the RFS presents two key obstacles in projecting available land for GHG
mitigation activities. First, production of feedstocks to meet the RFS will require land that
otherwise could have been used for afforestation or other conservation practices. Second, the RFS
itself requires that corn-starch ethanol and advanced biofuels have lower lifecycle greenhouse gas
emissions than conventional (fossil) fuels. Therefore, any emission reductions resulting from
conservation practices used on feedstock-producing lands may be needed for compliance with the
RFS. A key component of “additionality†is that for an offset to be valid, the practice being
credited would not have been done in the absence of the offset market. Granting an offset in this
case would effectively allow producers to double-count their emissions reductions—once to meet
the RFS life-cycle standard and once for sale or credit as an offset.
Stated differently, mitigation potential from a reduction in fossil fuel use resulting from an
increase in biofuels use can no longer be counted toward the agricultural sector since it would be
instead counted by an upstream entity. However, EPA’s study includes mitigation potential from
substituting fossil fuel use with biofuels (derived from bioenergy crops such as switchgrass) as
part of its aggregate estimates.
15 See, e.g., Duke University, Nicholas Institute for Environmental Policy Solutions, Designing Offsets Policy for the
U.S. Principles, May 2008, http://www.env.duke.edu/institute/offsetspolicy.pdf.
16 Energy Policy Act of 2005 (P.L. 109-58, Sec. 203); Energy Independence and Security Act of 2007 (P.L. 110-140,
Title II, Subtitle A).
˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ
ŗŗȱ
œ’–ŠÂŽœȱ˜ÂȱŠ›‹˜—ȱ’Â’Š’˜—ȱ˜ÂŽ—Â’Š•ȱ›˜–ȱ›’Œž•Âž›Š•ȱŠ—Âȱ˜›ŽœÂ›¢ȱŒÂ’Ÿ’Â’Žœȱ
ȱ
Š›–ȬŠœŽÂȱ—Ž›Â¢ȱ˜•’Œ¢ȱ›˜Ÿ’œ’˜—œȱ
The USDA and EPA analyses were developed using data and assumptions of farm production
prior to 2003 and do not include the effects of increasing federal support for farm-based
bioenergy production in subsequent omnibus farm bills. Many of the implications are duplicative
of those discussed for the national energy policies, since many of the farm bill’s energy-related
policies similarly promote renewable fuels.
Starting with the 2002 farm bill, Congress included an energy title to support farm-based
renewable energy production. These policies were expanded in the 2008 farm bill.17 The 2008
farm bill contains provisions that coordinate and fund research on biobased energy technologies,
provide grants and loans to promote the development of cellulosic biorefinery capacity, and
support the development of alternative (non-food) feedstock resources and the infrastructure to
process them. Cellulosic feedstocks, such as switchgrass and woody biomass, are given high
priority in both research and funding. In addition, tax and trade provisions in the farm bill support
corn-starch ethanol and advanced biofuels through tax credits and the continuation of the import
tariff for ethanol. These enacted provisions specifically target farm-based energy production, in
conjunction with related, broader national policies, and affect estimates of the mitigation potential
of farm and forestry offsets, since many of the models and studies were developed and completed
before these policies were implemented.
The long-term cumulative impact of farm bill energy provisions and EISA are twofold. First,
corn-starch ethanol output will continue expanding rapidly and even more acres will be devoted
to cornstarch ethanol until the 15 billion gallon cap in the expanded RFS is reached in 2012.18
Second, increased production of cellulosic feedstocks could significantly alter land use patterns.
Production of cellulosic ethanol—assuming technical advances—likely will expand under the
correct set of economic conditions including strong government support (to offset market risk)
and a return to high energy prices. However, weak petroleum prices (under $50 per barrel) would
jeopardize the profitability of the U.S. ethanol sector and would likely constrain private sector
investment in new ethanol production capacity.
Cellulosic feedstocks, such as corn stover, switchgrass, or woody biomass, are residuals of
current production or are generally grown on marginal land. Growing these crops for biofuels
competes for available land, thus reducing the area available for other types of sequestration
practices, such as afforestation or land retirement or conversion. However, the use of perennial
crops, such as switchgrass, or fast-growing poplar or willow, will likely result in reduced GHG
emissions from croplands compared to growing corn for ethanol, because they need not be
planted annually and require fewer inputs.
The bioenergy provisions in omnibus farm and energy bills are expected to continue to influence
farm and landowner decision-making. Producers have already demonstrated a strong response to
relative price shifts in 2008/2009 that favor corn by expanding corn production to meet ethanol
needs, and by shifting acres to corn from crops such as soybeans and wheat. In the 2008/2009
crop marketing year, corn for ethanol is projected to account for 30% of total U.S. corn
17 Farm Security and Rural Investment Act of 2002 (P.L. 107-171, Title IX); Food, Conservation, and Energy Act of
2008 (P.L. 110-246, Title IX).
18 This is a cap on its application for the RFS. There is no limit on total corn-based production or ethanol tax credits—
the only cap is on corn ethanol’s role under the mandate.
˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ
ŗŘȱ
œ’–ŠÂŽœȱ˜ÂȱŠ›‹˜—ȱ’Â’Š’˜—ȱ˜ÂŽ—Â’Š•ȱ›˜–ȱ›’Œž•Âž›Š•ȱŠ—Âȱ˜›ŽœÂ›¢ȱŒÂ’Ÿ’Â’Žœȱ
ȱ
production.19 Biofuels policies and energy markets are likely to continue to influence U.S. and
global crop production patterns and land use, including decisions regarding land retirement and
other conservation-based land conversion (e.g., movement to pasture/range, timberland, and
developed uses), as well as various conservation practices. The USDA and EPA simulation
models, however, do not take into account these policies nor do they take into account other
production-related changes associated with expanding bioenergy production.
›’Œž•Âž›ŽȱŠ›”ŽÂȱ˜—ÂÂ’Â’˜—œȱ
The simulation models used by EPA and USDA were developed following a period of generally
declining agricultural prices, stable net farm income, and a reduction in land devoted to
agricultural production. These trends were fed into the simulations model forming the basis for
depicting future conditions and mitigation potential. For example, EPA’s model was developed
taking into account the following market conditions:
During this period, real agricultural prices (i.e., net of inflation) have trended downward; net farm
income has stayed about even; and, as discussed above, land devoted to agriculture has dropped.
Increases in agricultural productivity have reduced the amount of land needed for agriculture,
leading to land retirement and movement to pasture/range, timberland, or developed uses.20
Current market conditions have proven different, in part because of policy-induced renewable
energy production, as well as because of rapid macroeconomic shifts. In particular, the study’s
assumption that cropland areas are decreasing is potentially problematic given recent trends
showing that cropland acreage may be rising. Following a period of declines in crop acres from
the mid-1990s through 2005, USDA data show that acreage devoted to principal crops increased
by 3% from 2006 through 2008. 21 During this same period, corn for use in ethanol production
increased from 20% of the crop to 30% in 2008.22 Long-run commodity price projections from
USDA suggest that, when commodity prices return to equilibrium after the spikes of 2007 and
2008, the long-run average price for major program crops will settle at levels that are significantly
above the recent 10-year average. 23 Since 2006, demand for corn for ethanol has contributed to
higher crop acres and boosted food commodity prices. Consequently, USDA considered releasing
farmers from Conservation Reserve Program contracts for non-erodible land.
In recent years, producer incomes have reached record highs, in part reflecting increased demand
for corn as an energy source and all other uses. The past seven years are the seven highest farm
income years on record. This is largely attributable to higher commodity prices.24 These
conditions differ markedly from conditions assumed in the EPA and USDA analyses.
Alternatively, current economic conditions may significantly depress farm incomes in the near
19 USDA, World Agricultural Supply and Demand Estimates (WASDE), August 8, 2008.
20 EPA, Greenhouse Gas Mitigation Potential in U.S. Forestry and Agriculture, Nov. 2005, pp. 3-17,
http://www.epa.gov/sequestration/greenhouse_gas.html.
21 USDA, 2008 Acreage Report, June 2008.
22 USDA, World Agricultural Supply and Demand Estimates, February 10, 2009.
23 USDA Office of the Chief Economist, “USDA Agricultural Projections to 2018,†OCE-2009-1, February 2009.
Compares the 1997/98 and 2006/07 time period.
24 For more information, see CRS Report R40152, U.S. Farm Income.
˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ
ŗřȱ
œ’–ŠÂŽœȱ˜ÂȱŠ›‹˜—ȱ’Â’Š’˜—ȱ˜ÂŽ—Â’Š•ȱ›˜–ȱ›’Œž•Âž›Š•ȱŠ—Âȱ˜›ŽœÂ›¢ȱŒÂ’Ÿ’Â’Žœȱ
ȱ
term. USDA projects that for 2009 net farm income will be 20% below preliminary estimates for
2008, although still nearly 9% above the average earned in the previous 10 years.25
Higher carbon price levels and shifts in underlying competition for resources and land could
trigger further market effects. For example, additional pressures on crop production could raise
crop and food prices, which in turn could influence farm-level decisions that could counteract
intended mitigation efforts (e.g., more intensive and concentrated production, a focus on growing
certain crops, or encouraging use of certain inputs, such as chemicals and fertilizers).
˜›ŽœÂ›¢ȱŽŒÂ˜›ȱ—ŒŽ›ÂŠ’—Â’Žœȱ
Aside from policy and market changes that are affecting land availability for other conservation
and mitigation uses, various prominent researchers have criticized the model simulations of the
forestry sector within these GHG mitigation studies.
Three aspects of forestry raise significant questions about the validity of the various estimates of
the carbon offset potential of forest projects, including afforestation and sustainable forest
management. One aspect is the precision of the available tools for measuring forest carbon. The
tools—both tables26 and computer models27—use USDA Forest Service inventory data from the
Forest Inventory Analysis (FIA) program for annualized or periodic estimates of forest carbon in
a wide array of forested ecosystems in various regions of the United States. One analysis noted
that “these tools use the best available information, provide ready public access, and several allow
for frequent updating using the most recent surveys,†and that “these tools are appropriate for
coarse-scale comparisons of forest carbon storage across large regions.â€28 The analysis goes on to
note that the FIA data were developed to measure merchantable timber volume and provide “no
direct measurements of many important forest carbon pools.â€29 It also states that “available
measures cannot reliably estimate year-by-year additions to forest carbon stores, due to estimation
errors and data gaps.â€30 The authors of various reports estimating forest carbon acknowledge such
possible problems:
In some cases, definitional or procedural changes in collecting the underlying inventory data may
cause apparent shifts in carbon stocks. For example, the definitions of forest land or forest type
were not applied consistently for some National Forest lands in the West. Reported changes in
stocks may be the consequence of such inconsistencies rather than a reflection of actual change in
the forest resource.31
25 USDA, “Farm Income and Costs: 2009 Farm Sector Income Forecast,†http://www.ers.usda.gov/
Briefing/FarmIncome/nationalestimates.htm.
26 See, for example, J. E. Smith, L. S. Heath, K. E. Skog, and R. A. Birdsey, Methods for Calculating Forest Ecosystem
and Harvested Carbon with Standard Estimates for Forest Types of the United States, Gen. Tech. Rept. NE-343, April
2006), p. 216, http://nrs.fs.fed.us/pubs/8192.
27 See, for example, J. E. Smith, L. S. Heath, and M. C. Nichols, U.S. Forest Carbon Calculation Tool: Forest-Land
Carbon Stocks and Net Annual Stock Change, Gen. Tech. Rept. NRS-13, 2007, p. 28, http://nrs.fs.fed.us/pubs/2394;
and National Council for Air and Stream Improvement, COLE: Carbon On-Line Estimator, version 2.0,
http://ncasi.uml.edu/COLE.
28 A. Ingerson and W. Loya, Measuring Forest Carbon: Strengths and Weaknesses of Available Tools, Science &
Policy Brief, April 2008, http://www.wilderness.org/Library/Documents/Measuring-Forest-Carbon.cfm
29 Ibid.
30 Ibid.
31 R. A. Birdsey and G. M. Lewis, Carbon in U.S. Forests and Wood Products, 1987-1997: State-by-State Estimates,
(continued...)
˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ
ŗŚȱ
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Another reported inaccuracy is the alleged underestimate of carbon stored in old-growth forests.32
This criticism is supported by a separate report on old-growth forest carbon, which found that
untouched natural forests store three times more CO2 than previously estimated and 60% more
than replanted forests.33 The possible inaccuracies in measuring forest carbon raise significant
questions about the accuracy of projections of the results of possible forest carbon sequestration
projects.
A second aspect of the uncertainty of forest carbon offset potential relates to the causes of land
use changes, both increases and decreases in forest acreage. Historically, U.S. forest land area has
fluctuated roughly in inverse proportion to agricultural land area—forest lands cleared for
agriculture, and to a lesser extent crop or pasture lands abandoned and reverting to forest.34
Although forest area has been relatively stable since the 1920s, recent years have seen a
continued slow loss to development, especially residential and related uses.35 Both agricultural
land area and development have been relatively unaffected by forestry programs. The shift into
and out of agricultural production has largely been driven by agricultural policies and programs;
for example, tree planting data since 1950 show two significant, temporary increases in area
planted—the late 1950s and early 1960s under the Soil Bank Program and the late 1980s and
early 1990s under the Conservation Reserve Program.36
Thus, projections of potential forest carbon offsets must reflect agricultural programs; estimates
made prior to the enactment of the 2008 farm bill and other statutes, with new agricultural
bioenergy programs and other incentives to expand (or contract) pasture or crop lands, could
substantially overstate (or understate) forestry project potential. In contrast, development
pressures are related to population and economic growth, with such factors as interest rates and
immigration policies being significant.37 Thus, the economics of GHG mitigation in the forestry
sector are affected by a wide variety of factors, most of which are unrelated to forest policy. Many
of these have changed in recent years, and likely will continue to change.
The third aspect that raises questions about the validity of forest carbon offset projects is that
climate change is believed to be affecting forests. The existing tools for estimating forest carbon
changes all base their estimates on existing or past forest growth. However, climate change is
already significantly affecting forest productivity. Some have found that additional atmospheric
CO2 enhances forest growth.38 Others have reported limitations to growth-stimulating effects of
(...continued)
Gen. Tech. Rept. NE-310 USDA Forest Service and U.S. EPA, Aug. 2003, http://www.treesearch.fs.fed.us/pubs/5565.
32 Measuring Forest Carbon, pp. 2, 14-16.
33 Michael Perry, “Untouched Forests Store 3 Times More Carbon: Study,†ENN: Environmental News Network, Aug.
4, 2008, http://www.enn.com/ecosystems/article/37839/print.
34 D. W. MacCleery, American Forests: A History of Resiliency and Recovery, FS-540, USDA Forest Service and
Forest History Society, 1992, p. 15.
35 R. J. Alig and A. J. Plantinga, “Future Forestland Area: Impacts From Population Growth and Other Factors That
Affect Land Values,†Journal of Forestry, v. 102, no. 8, Aug. 2004.
36 R. J. Moulton, “Tree Planting in the United States, 1997,†Tree Planters’ Notes, USDA Forest Service, v. 49, no. 1,
1999, p. 6.
37 R. Alig, “Land-Base Changes in the United States: Long-Term Assessments of Forest Land Condition,†Proceedings
of the Sixth Annual Forest Inventory and Analysis Symposium (Denver, CO, Sept. 21-24, 2004), Gen. Tech. Rept.
WO-70, USDA Forest Service, 2006, pp. 9-19.
38 D. T. Tissue, R. B. Thomas, and B. R. Strain, “Atmospheric CO2 Enrichment Increases Growth and Photosynthesis
of Pinus taeda: A 4 Year Experiment in the Field,†Plant, Cell, and Environment, v. 20, no. 9, Sept. 1997, pp. 1123-
(continued...)
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CO2.39 Perhaps more significant than these impacts are the changes already seen in wildfire
magnitude and frequency and in insect and disease infestations.40 For example, the government of
British Columbia has estimated that 80% of the pine timber in BC’s interior forests (40% of all
timber) will be dead by 2013 from the current mountain pine beetle infestation.41 Impacts of this
magnitude raise serious questions about the reliability of projections of potential forest carbon
offsets based on historic ecological patterns and productivity.
Žž•ŠÂ˜›¢ȱ›Š–Ž ˜›”ȱŠ—ÂȱžÂž›Žȱ
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Finally, these simulation models are limited in that they might not accurately reflect conditions of
mitigation potential depending, in part, on how Congress ultimately designs its emissions trading
scheme. Regarding the role of the agriculture and forestry sectors, it is unclear what Congress
will specify in terms of the underlying requirements and protocols for any participating sector
designated as a supplier of carbon offsets, and also how the regulatory agencies will ultimately
implement the overall program.
With respect to estimates of mitigation potential in the agricultural and forestry sectors, CBO
states the following caveat:
[These modeling estimates] do not reflect the effects of whatever regulatory system might be used
to implement CO2 pricing for biological sequestration. Such regulation would probably be
relatively complex. To be effective, it would have to address the fact that biological sequestration
is not necessarily permanent. And it would need to take into account that biological sequestration
measures used on one piece of land could influence the use of other land in ways that could
increase greenhouse-gas emissions. Moreover, in measuring biological sequestration for
compensation purposes, regulators would have to factor in the amount of sequestration that would
have occurred anyway.42
Among the types of measurement and implementation issues associated with carbon offsets from
farms and forests are concerns about quantification, verification, and monitoring; accounting;
permanence; leakage; and additionality.43 These issues can affect estimates of potential
mitigation. For example, USDA’s researchers readily acknowledge the potential for “upward
bias†in their reported estimates because the models are limited in its treatments of permanence,
(...continued)
1134.
39 A. C. Finzi, D. J. P. Moore, E. H. DeLucia, J. Lichter, K. S. Hofmockel, R. B. Jackson, H. Kim, R. Matamala, H. R.
McCarthy, R. Oren, J. S. Pippen, and W. H. Schlesinger, “Progressive Nitrogen Limitation of Ecosystem Processes
Under Elevated CO2 in a Warm-Temperate Forest,†Ecology, v. 87, no. 1, 2006, pp. 15-25.
40 Respectively, see National Wildlife Federation, Increased Risk of Catastrophic Wildfires: Global Warming’s Wake-
Up Call for the Western United States, 2008, http://www.nwf.org/extremeweather/pdfs/NWF_WildfiresFinal.pdf; and
J.A. Logan and J.A. Powell, “Ecological Consequences of Climate Change Altered Forest Insect Disturbance
Regimes,†Climate Change in Western North America: Evidence and Environmental Effects, F.H. Wagner, ed.
41 British Columbia’s Mountain Pine Beetle Action Plan, 2006-2011, http://www.for.gov.bc.ca/
hfp/mountain_pine_beetle/actionplan/2006/Beetle_Action_Plan.pdf.
42 CBO, The Potential for Carbon Sequestration in the United States, Sept. 2007, p.8,
http://www.cbo.gov/ftpdocs/86xx/doc8624/09-12-CarbonSequestration.pdf.
43 For more detailed information on these types of concerns, see CRS Report RS22964, Measuring and Monitoring
Carbon in the Agricultural and Forestry Sectors.
˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ
ŗŜȱ
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carbon-stock equilibrium, and leakage.44 For a discussion of these regulatory and implementation
issues, see CRS Report RS22964, Measuring and Monitoring Carbon in the Agricultural and
Forestry Sectors; CRS Report RL34560, Forest Carbon Markets: Potential and Drawbacks; and
CRS Report RL33898, Climate Change: The Role of the U.S. Agriculture Sector.
Accordingly, these simulation models should be viewed as limited in their ability to reflect future
conditions based on how Congress ultimately designs a cap-and-trade program, how Congress
specifies the program’s underlying requirements and protocols for any participating sector, and
how the regulatory agencies implement the program. These issues begin to delve into areas more
suited to a discussion of carbon offsets within an emissions trading program. Given the often
intractable concerns surrounding the use of carbon offsets, some of the regional and state GHG
programs (e.g., RGGI and Western Climate Initiative, and California’s statute) are opting for a
narrower set of offset types, such as avoided emissions from livestock manure management
systems and on-farm diesel engines, in part to bypass most programmatic concerns about
quantifying, monitoring, and verifying carbon offsets from farms and forests.
With respect to the role of carbon offsets within an emissions trading system, various
programmatic design and implementation elements could affect offset supply in several ways,
from the overall structure of the cap and of program scope (e.g., which sources are covered) to
specific logistical details (e.g., monitoring and measuring protocols). The supply of offsets will
also be beset by similar issues of competition for resources and land, and questions about how to
treat biofuels, among other constraints. For a discussion of the types of issues facing policy
decision-makers in designing and implementing carbon offsets within a cap-and-trade program,
see CRS Report RL34436, The Role of Offsets in a Greenhouse Gas Emissions Cap-and-Trade
Program: Potential Benefits and Concerns.
˜—œ’ÂŽ›ŠÂ’˜—œȱ˜›ȱ˜—›Žœœȱ
Compared to current estimated mitigation potential levels, USDA and EPA projections provide a
mostly positive picture of the potential for farm and forestry activities to mitigate GHG
emissions. USDA and EPA project added mitigation potential of 590 to 990 MMT CO2-Eq.
annually, thus increasing to roughly double current levels, assuming a high-end value or market
price for carbon. At lower carbon prices, estimated additional mitigation potential is lower, but
could still add about 40 to 160 MMT CO2-Eq. annually above current sequestration levels.
As Congress continues to consider the legislative options for addressing climate change and,
more specifically, the role of the agricultural and forestry sectors within this debate, available
estimates of the GHG mitigation potential provide an indication of the potential for carbon
storage in these sectors. Based on bills introduced during the 110th Congress, the agricultural and
forestry sectors are being considered by some in Congress for inclusion under a cap-and-trade
program, given the potential of certain agricultural and forestry practices to store and sequester
carbon.
In summary, however, for policy decision-making, the results of studies such as those conducted
by EPA and USDA to assess the carbon mitigation potential of farms and forests should be
44 USDA, Economics of Sequestering Carbon in the U.S. Agricultural Sector, April 2004,
http://www.ers.usda.gov/publications/tb1909/.
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Å—Åȱ
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ȱ
viewed with caution. These results are derived using complicated simulation models. The
available input data and modeling assumptions are limited in the extent to which they are able to
accurately reflect both actual current conditions and longer-term future conditions. Given that
these studies were developed using data and information for the early 2000s—prior to a variety of
recent policy, market, and economic changes—some researchers now acknowledge that the
published results of these studies are almost certainly outdated. Other related concerns include
criticisms by prominent researchers of these modeling approaches and estimates. In addition, in
the absence of defined policies outlining how an emission trading system would be designed and
implemented, these models are limited in the extent to which they can depict future conditions
under a regulatory system for sequestering carbon on farms and forests. Most likely the results of
these studies reflect an upper bound of the carbon storage potential in the farm and forestry
sectors.
žÂ‘˜›ȱ˜—ŠŒÂȱ —˜›–ŠÂ’˜—ȱ
Renée Johnson
Brent D. Yacobucci
Specialist in Agricultural Policy
Specialist in Energy and Environmental Policy
rjohnson@crs.loc.gov, 7-9588
byacobucci@crs.loc.gov, 7-9662
Ross W. Gorte
Randy Schnepf
Specialist in Natural Resources Policy
Specialist in Agricultural Policy
rgorte@crs.loc.gov, 7-7266
rschnepf@crs.loc.gov, 7-4277
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ŗŞȱ