With the exception of Chapter and Section headings, all coloured text has been inserted by AccessIPCC. The non-coloured text is the IPCC original.

A number of emails from the Climate Research Unit (CRU) of the University of East Anglia were published on the Internet in November 2009. This has provided a window into the world of climate science.

We have identified a number of key individuals involved in the emails whom we have designated as Persons of Concern [PoC]; a Journal in which a PoC has published has been designated as a Journal of Concern [JoC].

This is not to suggest that we believe such papers are necessarily flawed, but rather that, as Joseph Alcamo noted at Bali in October 2009, "as policymakers and the public begin to grasp the multi-billion dollar price tag for mitigating and adapting to climate change, we should expect a sharper questioning of the science behind climate policy".

References occur in a list at the end of each chapter. Citations are within the normal text of sections and paragraphs.

Definition of Tags Used

Tag	Explanation	Where Used	References	Citations
PoC	Person of Concern Key individual involved in CRU emails as defined in this spreadsheet. NOTE: we anticipate that this definition will be expanded as more data is coded.	References, Citations, IPCC Roles	-	-
JoC	Journal of Concern A Journal which has published articles by one or more PoCs (Person of Concern)	References, Citations	46	49
MoS	Model or Simulation Reference appears to be a model or simulation, not observation or experiment	References, Citations	36	45
NPR	Non Peer Reviewed Reference has no Journal or no Volume or no Pages or it has Editors.	References, Citations	79	138
SRC	Self Reference Concern Author of a chapter containing references to own work.	References, Citations, IPCC Roles	59	100
ARC	Paper authored or co-authored by person who is also in list of Authors of another chapter.	References, Citations	18	28
2007	Paper dated 2007, when IPCC policy stated cutoff was December 2005 with mid-February 2006 for exceptions.	References, Citations	11	29
Ambiguous	The short inline citation matched with more than one reference; however, AccessIPCC will link to the first reference found.	Citations	-	1
NotFound	The short inline citation was not matched with any reference. Believed to be caused by typing errors.	Citations	-	2
Clean	The reference was probably peer reviewed. The reference was dated before the cutoff (2005-2006). Its authors were not members of the Team. It was not published in a Journal of Concern. Its authors were not AR4 Authors.	References, Citations	128	137

Chapter Table of Contents

Title	Clean	Tagged	NotFound	Ambiguous
Chapter 8: Agriculture	-	-	-	-
8.1 Introduction	2	7	-	-
8.10 Long-term outlook	8	10	-	-
8.2 Status of sector, development trends including production and consumption, and implications	3	11	-	-
8.3 Emission trends (global and regional)	-	9	-	-
8.3.1 Trends since 1990	-	3	-	-
8.3.2 Future global trends	1	10	-	-
8.3.3 Regional trends	-	9	-	-
8.4 Description and assessment of mitigation technologies and practices, options and potentials, costs and sustainability	-	-	-	-
8.4.1 Mitigation technologies and practices	9	13	-	-
8.4.1.1 Cropland management	33	40	-	1
8.4.1.2 Grazing land management and pasture improvement	17	18	-	-
8.4.1.3 Management of organic/peaty soils	4	5	-	-
8.4.1.4 Restoration of degraded lands	-	-	-	-
8.4.1.5 Livestock management	22	19	1	-
8.4.1.6 Manure management	11	4	-	-
8.4.1.7 Bioenergy	4	11	-	-
8.4.2 Mitigation technologies and practices: per-area estimates of potential	1	9	-	-
8.4.3 Global and regional estimates of agricultural GHG mitigation potential	-	-	-	-
8.4.3.1 Technical potential for GHG mitigation in agriculture	-	16	-	-
8.4.3.2 Economic potential for GHG mitigation in agriculture	-	24	1	-
8.4.4 Bioenergy feed stocks from agriculture	-	-	-	-
8.4.4.1 Residues from agriculture	-	1	-	-
8.4.4.2 Dedicated energy crops	-	9	-	-
8.4.5 Potential implications of mitigation options for sustainable development	1	8	-	-
8.5 Interactions of mitigation options with adaptation and vulnerability	-	5	-	-
8.6 Effectiveness of, and experience with, climate policies; potentials, barriers and opportunities/implementation issues	-	-	-	-
8.6.1 Impact of climate policies	1	10	-	-
8.6.2 Barriers and opportunities/implementation issues	3	10	-	-
8.7 Integrated and non-climate policies affecting emissions of GHGs	-	-	-	-
8.7.1 Other UN conventions	-	-	-	-
8.7.2 Macroeconomic and sectoral policy	-	4	-	-
8.7.3 Other environmental policies	-	-	-	-
8.8 Co-benefits and trade-offs of mitigation options	17	14	-	-
8.9 Technology research, development, deployment, diffusion and transfer	-	4	-	-
Number of citations of various credibilities	137	283	2	1
Percentages of citations of various credibilities	32.4%	66.9%	0.5%	0.2%

EXECUTIVE SUMMARY

Agricultural lands (lands used for agricultural production, consisting of cropland, managed grassland and permanent crops including agro-forestry and bio-energy crops) occupy about 40-50% of the Earth’s land surface.

Agriculture accounted for an estimated emission of 5.1 to 6.1 GtCO₂-eq/yr in 2005 (10-12% of total global anthropogenic emissions of greenhouse gases (GHGs)). CH₄ contributes 3.3 GtCO₂-eq/yr and N₂O 2.8 GtCO₂-eq/yr. Of global anthropogenic emissions in 2005, agriculture accounts for about 60% of N₂O and about 50% of CH₄ (medium agreement, medium evidence). Despite large annual exchanges of CO₂ between the atmosphere and agricultural lands, the net flux is estimated to be approximately balanced, with CO₂ emissions around 0.04 GtCO₂/yr only (emissions from electricity and fuel use are covered in the buildings and transport sector, respectively) (low agreement, limited evidence).

Globally, agricultural CH₄ and N₂O emissions have increased by nearly 17% from 1990 to 2005, an average annual emission increase of about 60 MtCO₂-eq/yr. During that period, the five regions composed of Non-Annex I countries showed a 32% increase, and were, by 2005, responsible for about three-quarters of total agricultural emissions. The other five regions, mostly Annex I countries, collectively showed a decrease of 12% in the emissions of these gases (high agreement, much evidence).

A variety of options exists for mitigation of GHG emissions in agriculture. The most prominent options are improved crop and grazing land management (e.g., improved agronomic practices, nutrient use, tillage, and residue management), restoration of organic soils that are drained for crop production and restoration of degraded lands. Lower but still significant mitigation is possible with improved water and rice management; set-asides, land use change (e.g., conversion of cropland to grassland) and agro-forestry; as well as improved livestock and manure management. Many mitigation opportunities use current technologies and can be implemented immediately, but technological development will be a key driver ensuring the efficacy of additional mitigation measures in the future (high agreement, much evidence).

Agricultural GHG mitigation options are found to be cost competitive with non-agricultural options (e.g., energy, transportation, forestry) in achieving long-term (i.e., 2100 ) climate objectives. Global long-term modelling suggests that non-CO₂ crop and livestock abatement options could cost-effectively contribute 270– 1520 MtCO₂-eq/yr globally in 2030 with carbon prices up to 20 US$/tCO₂-eq and 640– 1870 MtCO₂-eq/yr with C prices up to 50 US$/tCO₂-eq Soil carbon management options are not currently considered in long-term modelling (medium agreement, limited evidence).

Considering all gases, the global technical mitigation potential from agriculture (excluding fossil fuel offsets from biomass) by 2030 is estimated to be ~5500-6,000 MtCO₂-eq/yr (medium agreement, medium evidence). Economic potentials are estimated to be 1500 - 1600, 2500 - 2700, and 4000-4300 MtCO₂-eq/yr at carbon prices of up to 20, 50 and 100 US$/tCO₂-eq, respectively About 70% of the potential lies in non-OECD/EIT countries, 20% in OECD countries and 10% for EIT countries (medium agreement, limited evidence).

Soil carbon sequestration (enhanced sinks) is the mechanism responsible for most of the mitigation potential (high agreement, much evidence), with an estimated 89% contribution to the technical potantial. Mitigation of CH₄ emissions and N₂O emissions from soils account for 9% and 2%, respectively, of the total mitigation potential (medium agreement, medium evidence). The upper and lower limits about the estimates are largely determined by uncertainty in the per-area estimate for each mitigation measure. Overall, principal sources of uncertainties inherent in these mitigation potentials include: a) future level of adoption of mitigation measures (as influenced by barriers to adoption); b) effectiveness of adopted measures in enhancing carbon sinks or reducing N₂O and CH₄ emissions (particularly in tropical areas; reflected in the upper and lower bounds given above); and c) persistence of mitigation, as influenced by future climatic trends, economic conditions, and social behaviour (medium agreement, limited evidence).

The role of alternative strategies changes across the range of prices for carbon. At low prices, dominant strategies are those consistent with existing production such as changes in tillage, fertilizer application, livestock diet formulation, and manure management. Higher prices elicit land-use changes that displace existing production, such as biofuels, and allow for use of costly animal feed-based mitigation options. A practice effective in reducing emissions at one site may be less effective or even counterproductive elsewhere. Consequently, there is no universally applicable list of mitigation practices; practices need to be evaluated for individual agricultural systems based on climate, edaphic, social setting, and historical patterns of land use and management (high agreement, much evidence).

GHG emissions could also be reduced by substituting fossil fuels with energy produced from agricultural feed stocks (e.g., crop residues, dung, energy crops), which would be counted in sectors using the energy. The contribution of agriculture to the mitigation potential by using bioenergy depends on relative prices of the fuels and the balance of supply and demand. Using top-down models that include assumptions on such a balance the economic mitigation potential for agriculture in 2030 is estimated to be 70- 1260 MtCO₂-eq/yr at up to 20 US$/tCO₂-eq, and 560- 2320 MtCO₂-eq/yr at up to 50 US$/tCO₂-eq There are no estimates for the additional potential from top down models at carbon prices up to 100 US$/tCO₂-eq, but the estimate for prices above 100 US$/tCO₂-eq is 2720 MtCO₂-eq/yr. These potentials represent mitigation of 5-80%, and 20-90% of all other agricultural mitigation measures combined, at carbon prices of up to 20, and up to50 US$/tCO₂-eq, respectively. An additional mitigation of 770 MtCO₂-eq/yr could be achieved by 2030 by improved energy efficiency in agriculture, though the mitigation potential is counted mainly in the buildings and transport sectors (medium agreement, medium evidence).

Agricultural mitigation measures often have synergy with sustainable development policies, and many explicitly influence social, economic, and environmental aspects of sustainability. Many options also have co-benefits (improved efficiency, reduced cost, environmental co-benefits) as well as trade-offs (e.g., increasing other forms of pollution), and balancing these effects will be necessary for successful implementation (high agreement, much evidence).

There are interactions between mitigation and adaptation in the agricultural sector, which may occur simultaneously, but differ in their spatial and geographic characteristics. The main climate change benefits of mitigation actions will emerge over decades, but there may also be short-term benefits if the drivers achieve other policy objectives. Conversely, actions to enhance adaptation to climate change impacts will have consequences in the short and long term. Most mitigation measures are likely robust to future climate change (e.g., nutrient management), but a subset will likely be vulnerable (e.g., irrigation in regions becoming more arid). It may be possible for a vulnerable practice to be modified as the climate changes and to maintain the efficacy of a mitigation measure (low agreement, limited evidence).

In many regions, non-climate policies related to macro-economics, agriculture and the environment, have a larger impact on agricultural mitigation than climate policies (high agreement, much evidence). Despite significant technical potential for mitigation in agriculture, there is evidence that little progress has been made in the implementation of mitigation measures at the global scale. Barriers to implementation are not likely to be overcome without policy/economic incentives and other programmes, such as those promoting global sharing of innovative technologies.

Current GHG emission rates may escalate in the future due to population growth and changing diets (high agreement, medium evidence). Greater demand for food could result in higher emissions of CH₄ and N₂O if there are more livestock and greater use of nitrogen fertilizers (high agreement, much evidence). Deployment of new mitigation practices for livestock systems and fertilizer applications will be essential to prevent an increase in emissions from agriculture after 2030 . In addition, soil carbon may be more vulnerable to loss with climate change and other pressures, though increases in production will offset some or all of this carbon loss (low agreement, limited evidence).

Overall, the outlook for GHG mitigation in agriculture suggests that there is significant potential (high agreement, medium evidence). Current initiatives suggest that synergy between climate change policies, sustainable development and improvement of environmental quality will likely lead the way forward to realize the mitigation potential in this sector.

8.1 Introduction

Agriculture releases to the atmosphere significant amounts of CO₂, CH₄, and N₂O ( Cole et al., 1997 [MoS] ; IPCC, 2001a [NPR] ; Paustian et al., 2004 [SRC] ). CO₂ is released largely from microbial decay or burning of plant litter and soil organic matter ( Smith, 2004b [NPR, SRC] ; Janzen, 2004 [SRC] ). CH₄ is produced when organic materials decompose in oxygen-deprived conditions, notably from fermentative digestion by ruminant livestock, from stored manures, and from rice grown under flooded conditions ( Mosier et al. 1998 [JoC] ). N₂O is generated by the microbial transformation of nitrogen in soils and manures, and is often enhanced where available nitrogen (N) exceeds plant requirements, especially under wet conditions ( (Oenema et al., 2005; ) ( Smith and Conen, 2004 ) ). Agricultural greenhouse gas (GHG) fluxes are complex and heterogeneous, but the active management of agricultural systems offers possibilities for mitigation. Many of these mitigation opportunities use current technologies and can be implemented immediately.

This chapter describes the development of GHG emissions from the agricultural sector ( Section 8.2 ), and details agricultural practices that may mitigate GHGs ( Section 8.4.1 ), with many practices affecting more than one GHG by more than one mechanism. These practices include: cropland management; grazing land management/pasture improvement; management of agricultural organic soils; restoration of degraded lands; livestock management; manure/bio-solid management; and bio-energy production.

It is theoretically possible to increase carbon storage in long-lived agricultural products (e.g., strawboards, wool, leather, bio-plastics) but the carbon held in these products has only increased from 37 to 83 MtC per year over the past 40 years. Assuming a first order decay rate of 10 to 20 % per year, this is estimated to be a global net annual removal of 3 to 7 MtCO₂ from the atmosphere, which is negligible compared to other mitigation measures. The option is not considered further here.

Smith et al. 2007a [NPR, SRC, 2007] ) recently estimated a global potential mitigation of 770 MtCO₂-eq/yr by 2030 from improved energy efficiency in agriculture (e.g., through reduced fossil fuel use), However, this is usually counted in the relevant user sector rather than in agriculture and so is not considered further here. Any savings from improved energy efficiency are discussed in the relevant sections elsewhere in this volume, according to where fossil fuel savings are made, for example, from transport fuels ( Chapter 5 ), or through improved building design ( Chapter 6 ).

8.2 Status of sector, development trends including production and consumption, and implications

Population pressure, technological change, public policies, and economic growth and the cost/price squeeze have been the main drivers of change in the agricultural sector during the last four decades. Production of food and fibre has more than kept pace with the sharp increase in demand in a more populated world. The global average daily availability of calories per capita has increased ( (Gilland, 2002 ) ), with some notable regional exceptions. This growth, however, has been at the expense of increased pressure on the environment, and depletion of natural resources ( Tilman et al., 2001 [JoC, MoS] ; Rees, 2003 [JoC] ), while it has not resolved the problems of food security and child malnutrition suffered in poor countries ( Conway and Toenniessen, 1999 [JoC] ).

Agricultural land occupied 5023 Mha in 2002 ( FAOSTAT, 2006 [NPR] ). Most of this area was under pasture (3488 Mha, or 69%) and cropland occupied 1405 Mha (28%). During the last four decades, agricultural land gained almost 500 Mha from other land uses, a change driven largely by increasing demands for food from a growing population. Every year during this period, an average 6 Mha of forestland and 7 Mha of other land were converted to agriculture, a change occurring largely in the developing world ( Table 8.1 ). This trend is projected to continue into the future ( Huang et al., 2002 [JoC] ; Trewavas, 2002 [JoC] ;( Fedoroff and Cohen, 1999; ) Green et al., 2005 [JoC] and Rosegrant et al., 2001 [NPR] ) project that an additional 500 Mha will be converted to agriculture during 1997 - 2020, mostly in Latin America and Sub-Saharan Africa.

Technological progress has made it possible to achieve remarkable improvements in land productivity, increasing per-capita food availability ( Table 8.2 ), despite a consistent decline in per-capita agricultural land ( Figure 8.1 ). The share of animal products in the diet has increased consistently in the developing countries, while remaining constant in developed countries ( Table 8.2 ). Economic growth and changing lifestyles in some developing countries are causing a growing demand for meat and dairy products, notably in China where current demands are low. Meat demand in developing countries rose from 11 to 24 kg/capita/yr during the period 1967 - 1997, achieving an annual growth rate of more than 5% by the end of that period. Rosegrant et al. 2001 [NPR] ) forecast a further increase of 57% in global meat demand by 2020, mostly in South and Southeast Asia, and Sub-Saharan Africa. The greatest increases in demand are expected for poultry (83 % by 2020; ( Roy et al., 2002 ) ).

Annual GHG emissions from agriculture are expected to increase in coming decades (included in the baseline) due to escalating demands for food and shifts in diet. However, improved management practices and emerging technologies may permit a reduction in emissions per unit of food (or of protein) produced. The main trends in the agricultural sector with the implications for GHG emissions or removals are summarized as follows:

• Growth in land productivity is expected to continue, although at a declining rate, due to decreasing returns from further technological progress, and greater use of marginal land with lower productivity. Use of these marginal lands increases the risk of soil erosion and degradation, with highly uncertain consequences for CO₂ emissions (Lal, 2004a; Van Oost et al., 2004).
• Conservation tillage and zero-tillage are increasingly being adopted, thus reducing the use of energy and often increasing carbon storage in soils. According to FAO (2001), the worldwide area under zero-tillage in 1999 was approximately 50 Mha, representing 3.5% of total arable land. However, such practices are frequently combined with periodical tillage, thus making the assessment of the GHG balance highly uncertain.
• Further improvements in productivity will require higher use of irrigation and fertilizer, increasing the energy demand (for moving water and manufacturing fertilizer; Schlesinger, 1999). Also, irrigation and N fertilization can increase GHG emissions (Mosier, 2001).
• Growing demand for meat may induce further changes in land use (e.g., from forestland to grassland), often increasing CO₂ emissions, and increased demand for animal feeds (e.g., cereals). Larger herds of beef cattle will cause increased emissions of CH₄ and N₂O, although use of intensive systems (with lower emissions per unit product) is expected to increase faster than growth in grazing-based systems. This may attenuate the expected rise in GHG emissions.
• Intensive production of beef, poultry, and pork is increasingly common, leading to increases in manure with consequent increases in GHG emissions. This is particularly true in the developing regions of South and East Asia, and Latin America, as well as in North America.
• Changes in policies (e.g., subsidies), and regional patterns of production and demand are causing an increase in international trade of agricultural products. This is expected to increase CO₂ emissions, due to greater use of energy for transportation.
• There is an emerging trend for greater use of agricultural products (e.g., bio-plastics bio-fuels and biomass for energy) as substitutes for fossil fuel-based products. This has the potential to reduce GHG emissions in the future.

8.3 Emission trends (global and regional)

With an estimated global emission of non-CO₂ GHGs from agriculture of between 5120 MtCO₂-eq/yr ( Denman et al., 2007 [NPR, ARC, 2007] ) and 6116 MtCO₂-eq/yr ( US-EPA, 2006a [NPR] ) in 2005, agriculture accounts for 10-12 % of total global anthropogenic emissions of GHGs. Agriculture contributes about 47% and 58% of total anthropogenic emissions of CH₄ and N₂O, respectively, with a wide range of uncertainty in the estimates of both the agricultural contribution and the anthropogenic total. N₂O emissions from soils and CH₄ from enteric fermentation constitute the largest sources, 38% and 32% of total non-CO₂ emissions from agriculture in 2005, respectively ( US-EPA, 2006a [NPR] ). Biomass burning (12%), rice production (11%), and manure management (7%) account for the rest. CO₂ emissions from agricultural soils are not normally estimated separately, but are included in the land use, land use change and forestry sector (e.g., in national GHG inventories). So there are few comparable estimates of emissions of this gas in agriculture. Agricultural lands generate very large CO₂ fluxes both to and from the atmosphere ( IPCC, 2001a [NPR] ), but the net flux is small. US-EPA, 2006b [NPR] ) estimated a net CO₂ emission of 40 MtCO₂-eq from agricultural soils in 2000, less than 1% of global anthropogenic CO₂ emissions.

Both the magnitude of the emissions and the relative importance of the different sources vary widely among world regions ( Figure 8.2 ). In 2005, the group of five regions mostly consisting of non-Annex I countries was responsible for 74% of total agricultural emissions.

In seven of the ten regions, N₂O from soils was the main source of GHGs in the agricultural sector in 2005, mainly associated with N fertilizers and manure applied to soils. In the other three regions - Latin America and The Caribbean, the countries of Eastern Europe, the Caucasus and Central Asia, and OECD Pacific - CH₄ from enteric fermentation was the dominant source ( US-EPA, 2006a [NPR] ). This is due to the large livestock population in these three regions which, in 2004, had a combined stock of cattle and sheep equivalent to 36% and 24% of world totals, respectively ( FAO, 2003 [NPR] ).

Emissions from rice production and burning of biomass were heavily concentrated in the group of developing countries, with 97% and 92% of world totals, respectively. While CH₄ emissions from rice occurred mostly in South and East Asia, where it is a dominant food source (82% of total emissions), those from biomass burning originated in Sub-Saharan Africa and Latin America and the Caribbean (74% of total). Manure management was the only source for which emissions where higher in the group of developed regions (52%) than in developing regions (48%; US-EPA, 2006a [NPR] ).

The balance between the large fluxes of CO₂ emissions and removals in agricultural land is uncertain. A study by US-EPA 2006b [NPR] ) showed that some countries and regions have net emissions, while others have net removals of CO_2. Except for the countries of Eastern Europe, the Caucasus and Central Asia, which had an annual emission of 26 MtCO₂/yr in 2000, all other countries showed very low emissions or removals.

8.4 Description and assessment of mitigation technologies and practices, options and potentials, costs and sustainability

8.5 Interactions of mitigation options with adaptation and vulnerability

As discussed in Chapters 3 , 11 and 12 , mitigation, climate change impacts, and adaptation will occur simultaneously and interactively. Mitigation-driven actions in agriculture could have (a) positive adaptation consequences (e.g., carbon sequestration projects with positive drought preparedness aspects) or (b) negative adaptation consequences (e.g., if heavy dependence on biomass energy increases the sensitivity of energy supply to climatic extremes; see Chapter 12 , Subsection 12.1.4). Adaptation-driven actions also may have both (a) positive consequences for mitigation (e.g., residue return to fields to improve water holding capacity will also sequester carbon); and (b) negative consequences for mitigation (e.g., increasing use of nitrogen fertilizer to overcome falling yield leading to increased nitrous oxide emissions). In many cases, actions taken for reasons unrelated to either mitigation or adaptation (see Sections 8.6 and 8.7 ) may have considerable consequences for either or both(e.g., deforestation for agriculture or other purposes results in carbon loss as well as loss of ecosystems and resilience of local populations). Adaptation to climate change in the agricultural sector is detailed in ( IPCC, 2007 [NPR, 2007] ; Chapter 5).

For mitigation, variables such as growth rates for bioenergy feedstocks, the size of livestock herds, and rates of carbon sequestration in agricultural lands are affected by climate change ( Paustian et al., 2004 [SRC] ). The extent depends on the sign and magnitude of changes in temperature, soil moisture, and atmospheric CO₂ concentration, which vary regionally ( Christensen et al., 2007 [NPR, MoS, 2007] ). All of these factors will alter the mitigation potential; some positively and some negatively. For example: (a) lower growth rates in bioenergy feedstocks will lead to larger emissions from hauling and increased cost; (b) lower livestock growth rates would possibly increase herd size and consequent emissions from manure and enteric fermentation; and (c) increased microbial decomposition under higher temperatures will lower soil carbon sequestration potential. Interactions also occur with adaptation. Butt et al. 2006 [JoC, SRC] and Reilly et al. 2001 [NPR, SRC] ) found that modified crop mix, land use, and irrigation are all potential adaptations to warmer climates. All would alter the mitigation potential. Some of the key vulnerabilities of agricultural mitigation strategies to climate change, and the implications of adaptation on GHG emissions from agriculture are summarized in Table 8.9 .

8.6 Effectiveness of, and experience with, climate policies; potentials, barriers and opportunities/implementation issues

8.7 Integrated and non-climate policies affecting emissions of GHGs

Many policies other than climate policies affect GHG emissions from agriculture. These include other UN conventions such as Biodiversity, Desertification and actions on Sustainable Development (see Section 8.4.5 ), macroeconomic policy such as EU Common Agricultural Policy (CAP)/CAP reform, international free trade agreements, trading blocks, trade barriers, region-specific programmes, energy policy and price adjustment, and other environmental policies including various environmental/agro-environmental schemes. These are described further below.

8.8 Co-benefits and trade-offs of mitigation options

Many of the measures aimed at reducing GHG emissions have other impacts on the productivity and environmental integrity of agricultural ecosystems, mostly positive ( Table 8.12 ). These measures are often adopted mainly for reasons other than GHG mitigation (see Section 8.7.3 ). Agro-ecosystems are inherently complex and very few practices yield purely win-win outcomes; most involve some trade-offs (DeFries et al., 2004; Viner et al., 2006 [NPR] ) above certain levels or intensities of implementation. Specific examples of co-benefits and trade-offs among agricultural GHG mitigation measures include:

• Practices that maintain or increase crop productivity can improve global or regional food security (Lal, 2004a, b; Follett et al., 2005). This co-benefit may become more important as global food demands increase in coming decades (Sanchez and Swaminathan, 2005; Rosegrant and Cline, 2003; FAO, 2003; Millennium Ecosystem Assessment, 2005). Building reserves of soil carbon often also increases the potential productivity of these soils. Furthermore, many of the measures that promote carbon sequestration also prevent degradation by avoiding erosion and improving soil structure. Consequently, many carbon conserving practices sustain or enhance future fertility, productivity and resilience of soil resources (Lal, 2004a; Cerri et al., 2004; Freibauer et al., 2004; Paustian et al., 2004; Kurkalova et al., 2004; Díaz-Zorita et al., 2002). In some instances, where productivity is enhanced through increased inputs, there may be risks of soil depletion through mechanisms such as acidification or salinization (Barak et al., 1997; Díez et al., 2004; Connor, 2004).
• A key potential trade-off is between the production of bio-energy crops and food security. To the extent that bio-energy production uses crop residues, excess agricultural products or surplus land and water, there will be little resultant loss of food production. But above this point, proportional losses of food production will be strongly negative. Food insecurity is determined more by inequity of access to food (at all scales) than by absolute food production insufficiencies, so the impact of this trade-off depends among other things on the economic distributional effects of bio-energy production.
• Fresh water is a dwindling resource in many parts of the world (Rosegrant and Cline, 2003; Rockström, 2003). Agricultural practices for mitigation of GHGs can have both negative and positive effects on water conservation, and on water quality. Where measures promote water use efficiency (e.g., reduced tillage), they provide potential benefits. But in some cases, the practices could intensify water use, thereby reducing stream flow or groundwater reserves (Unkovich, 2003; Dias de Oliveira et al., 2005). For instance, high-productivity, evergreen, deep-rooted bio-energy plantations generally have a higher water use than the land cover they replace (Berndes, 2002, Jackson et al., 2005). Some practices may affect water quality through enhanced leaching of pesticides and nutrients (Freibauer et al., 2004; Machado and Silva, 2001).
• If bio-energy plantations are appropriately located, designed, and managed, they may reduce nutrient leaching and soil erosion and generate additional environmental services such as soil carbon accumulation, improved soil fertility; removal of cadmium and other heavy metals from soils or wastes. They may also increase nutrient recirculation, aid in the treatment of nutrient-rich wastewater and sludge; and provide habitats for biodiversity in the agricultural landscape (Berndes and Börjesson, 2002; Berndes et al. 2004; Börjesson and Berndes, 2006).
• Changes to land use and agricultural management can affect biodiversity, both positively and negatively (e.g., Xiang et al., 2006; Feng et al., 2006). For example, intensification of agriculture and large-scale production of biomass energy crops will lead to loss of biodiversity where they occur in biodiversity-rich landscapes (European Environment Agency, 2006). But perennial crops often used for energy production can favour biodiversity, if they displace annual crops or degraded areas (Berndes and Börjesson, 2002).
• Agricultural mitigation practices may influence non-agricultural ecosystems. For example, practices that diminish productivity in existing cropland (e.g., set-aside lands) or divert products to alternate uses (e.g., bio-energy crops) may induce conversion of forests to cropland elsewhere. Conversely, increasing productivity on existing croplands may ‘spare’ some forest or grasslands (West and Marland, 2003; Balmford et al., 2005; Mooney et al., 2005). The net effect of such trade-offs on biodiversity and other ecosystem services has not yet been fully quantified (Huston and Marland, 2003; Green et al., 2005).
• Agro-ecosystems have become increasingly dependent on input of reactive nitrogen, much of it added as manufactured fertilizers (Galloway et al., 2003; Galloway, 2004). Practices that reduce N₂O emission often improve the efficiency of N use from these and other sources (e.g., manures), thereby also reducing GHG emissions from fertilizer manufacture and avoiding deleterious effects on water and air quality from N pollutants (Oenema et al., 2005; Dalal et al., 2003; Olesen et al., 2006; Paustian et al., 2004). Suppressing losses of N as N₂O might in some cases increase the risk of losing that N via leaching. Curtailing supplemental N use without a corresponding increase in N-use efficiency will restrict yields, thereby hampering food security.
• Implementation of agricultural GHG mitigation measures may allow expanded use of fossil fuels, and may have some negative effects through emissions of sulphur, mercury and other pollutants (Elbakidze and McCarl, 2007).

The co-benefits and trade-offs of a practice may vary from place to place because of differences in climate, soil, or the way the practice is adopted. In producing bio-energy, for example, if the feedstock is crop residue, that may reduce soil quality by depleting soil organic matter. Conversely, if the feedstock is a densely rooted perennial crop that may replenish organic matter and thereby improve soil quality ( Paustian et al., 2004 [SRC] ).These few examples, and the general trends described in Table 8.12 , demonstrate that GHG mitigation practices on farm lands exert complex, interactive effects on the environment, sometimes far from the site at which they are imposed. The merits of a given practice, therefore, cannot be judged solely on effectiveness of GHG mitigation.

8.9 Technology research, development, deployment, diffusion and transfer

There is much scope for technological developments to reduce GHG emissions in the agricultural sector. For example, increases in crop yields and animal productivity will reduce emissions per unit of production. Such increases in crop and animal productivity will be implemented through improved management and husbandry techniques, such as better management, genetically modified crops, improved cultivars, fertilizer recommendation systems, precision agriculture, improved animal breeds, improved animal nutrition, dietary additives and growth promoters, improved animal fertility, bio-energy crops, anaerobic slurry digestion and methane capture systems. All of these depend to some extent on technological developments. Although technological improvement may have very significant effects, transfer of these technologies is a key requirement for these mitigations to be realized. For example, the efficiency of N use has improved over the last two decades in developed countries, but continues to decline in many developing countries due to barriers to technology transfer (International Fertilizer Industry Association, 2007 ). Based on technology change scenarios developed by Ewert et al. 2005 [MoS] ), and derived from extrapolation of current trends in FAO data, Smith et al. 2005b [SRC] ) showed that technological improvements could potentially counteract the negative impacts of climate change on cropland and grassland soil carbon stocks in Europe. This and other work ( Rounsevell et al., 2006 [MoS, SRC] ) suggest that technological improvement will be a key factor in GHG mitigation in the future.

In most instances, the cost of employing mitigation strategies will not alter radically in the medium term. There will be some shifts in costs due to changes in prices of agricultural products and inputs, but these are unlikely to be of significant magnitude. Likewise, the potential of most options for CO₂ reduction is unlikely to change greatly. There are some exceptions which fall into two categories: (i) options where the practice or technology is not new, but where the emission reduction potential has not been adequately quantified, such as improved nutrient utilization; and (ii) options where technologies are still being refined such as probiotics in animal diets, or nitrification inhibitors.

Many of the mitigation strategies outlined for agriculture employ existing technology (e.g., crop management, livestock management). With such strategies, the main issue is technology transfer, diffusion, and deployment. Other strategies involve new use of existing technologies. For example, oils have been used in animal diets for many years to increase dietary energy content, but their role as a methane suppressant is relatively new, and the parameters of the technology in terms of scope for methane reduction are only now being defined. Other strategies still require further research to allow viable systems to operate (e.g., bio-energy crops). Finally, many novel mitigation strategies are presently being refined, such as the use of probiotics, novel plant extracts, and the development of vaccines. Thus, there is still a major role for research and development in this area.

Differences between regions can arise due to the state of development of the agricultural industry, the resources available and legislation. For example, the scope to use specific agents and dietary additives in ruminants is much greater in developed than in the developing regions because of cost, opportunity (e.g., it is easier to administer products to animals in confined systems than in free ranging or nomadic systems), and availability of the technology ( US-EPA, 2006a [NPR] ). Furthermore, certain technologies are not allowed in some regions, for example, ionophores are banned from use in animal feeding in the EU, and genetically modified crops are not approved for use in some countries.

8.10 Long-term outlook

Trends in GHG emissions in the agricultural sector depend mainly on the level and rate of socio-economic development, human population growth, and diet, application of adequate technologies, climate and non-climate policies, and future climate change. Consequently, mitigation potentials in the agricultural sector are uncertain, making a consensus difficult to achieve and hindering policy making. However, agriculture is a significant contributor to GHG emissions ( Section 8.2 ). Mitigation is unlikely to occur without action, and higher emissions are projected in the future if current trends are left unconstrained. According to current projections, the global population will reach 9 billion by 2050, an increase of about 50% over current levels ( Lutz et al., 2001 [JoC] ; Cohen, 2003 [JoC] ). Because of these increases and changing consumption patterns, some analyses estimate that the production of cereals will need to roughly double in coming decades ( Tilman et al., 2001 [JoC, MoS] ;( Roy et al., 2002; ) Green et al., 2005 [JoC] ). Achieving these increases in food production may require more use of N fertilizer, leading to possible increases in N₂O emissions, unless more efficient fertilization techniques and products can be found ( (Galloway, 2003; ) ( Mosier, 2002 ) ). Greater demands for food could also increase CH₄ emissions from enteric fermentation if livestock numbers increase in response to demands for meat and other livestock products. As projected by the IMAGE 2.2 model, CO₂, CH₄, and N₂O emissions associated with land use vary greatly between scenarios ( Strengers et al., 2004 [MoS, ARC] ), depending on trends towards globalization or regionalization, and on the emphasis placed on material wealth relative to sustainability and equity.

Some countries are moving forward with climate and non-climate policies, particularly those linked with sustainable development and improving environmental quality as described in Sections 8.6 and 8.7 . These policies will likely have direct or synergistic effects on GHG emissions and provide a way forward for mitigation in the agricultural sector. Moreover, global sharing of innovative technologies for efficient use of land resources and agricultural inputs, in an effort to eliminate poverty and malnutrition, will also enhance the likelihood of significant mitigation from the agricultural sector.

Mitigation of GHG emissions associated with various agricultural activities and soil carbon sequestration could be achieved through best management practices, many of which are currently available for implementation. Best management practices are not only essential for mitigating GHG emissions, but also for other facets of environmental protection such as air and water quality management. Uncertainties do exist, but they can be reduced through finer scale assessments of best management practices within countries, evaluating not only the GHG mitigation potential but also the influences of mitigation options on socio-economic conditions and other environmental impacts.

The long-term outlook for development of mitigation practices for livestock systems is encouraging. Continuous improvements in animal breeds are likely, and these will improve the GHG emissions per kg of animal product. Enhanced production efficiency due to structural change or better application of existing technologies is also generally associated with reduced emissions, and there is a trend towards increased efficiency in both developed and developing countries. New technologies may emerge to reduce emissions from livestock such as probiotics, a methane vaccine or methane inhibitors. However, increased world demand for animal products may mean that while emissions per kg of product decline, total emissions may increase.

Recycling of agricultural by-products, such as crop residues and animal manures, and production of energy crops provides opportunities for direct mitigation of GHG emissions from fossil fuel offsets. However, there are barriers in technologies and economics to using agricultural wastes, and in converting energy crops into commercial fuels. The development of innovative technologies is a critical factor in realizing the potential for biofuel production from agricultural wastes and energy crops. This mitigation option could be moved forward with government investment for the development of these technologies, and subsidies for using these forms of energy.

A number of agricultural mitigation options which have limited potential now will likely have increased potential in the long-term. Examples include better use of fertilizer through precision farming, wider use of slow and controlled release fertilizers and of nitrification inhibitors, and other practices that reduce N application (and thus N₂O emissions). Similarly, enhanced N-use efficiency is achievable as technologies such as field diagnostics, fertilizer recommendations from expert/decision support systems and fertilizer placement technologies are developed and more widely used. New fertilizers and water management systems in paddy rice are also likely in the longer term.

Possible changes to climate and atmosphere in coming decades may influence GHG emissions from agriculture, and the effectiveness of practices adopted to minimize them. For example, atmospheric CO₂ concentrations, likely to double within the next century, may affect agro-ecosystems through changes in plant growth rates, plant litter composition, drought tolerance, and nitrogen demands (e.g., Long et al., 2006 [JoC] ;( Henry et al., 2005; ) ( van Groenigen et al., 2005; ) ( Jensen and Christensen, 2004; ) ( Torbert et al., 2000; ) ( Norby et al., 2001 ) ). Similarly, atmospheric nitrogen deposition also affects crop production systems as well as changing temperature regimes, although the effect will depend on the magnitude of change and response of the crop, forage, or livestock species. For example, increasing temperatures are likely to have a positive effect on crop production in colder regions due to a longer growing season ( Smith et al., 2005b [SRC] ). In contrast, increasing temperatures could accelerate decomposition of soil organic matter, releasing stored soil carbon into the atmosphere ( Knorr et al., 2005 [JoC] ; Fang et al., 2005 [JoC, SRC] ; Smith et al. 2005b [SRC] ). Furthermore, changes in precipitation patterns could change the adaptability of crops or cropping systems selected to reduce GHG emissions. Many of these effects have high levels of uncertainty; but demonstrate that practices chosen to reduce GHG emissions may not have the same effectiveness in coming decades. Consequently, programmes to reduce emissions in the agricultural sector will need to be designed with flexibility for adaptation in response to climate change.

Overall, the outlook for GHG mitigation in agriculture suggests significant potential. Current initiatives suggest that identifying synergies between climate change policies, sustainable development, and improvement of environmental quality will likely lead the way forward to realization of mitigation potential in this sector.

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NOTE: In the Summary of Reviewer Comments,
Accepted includes only those responses that were unambiguously Accepted.
There are other categories of responses that we have not yet quantified
due to inconsistencies of usage.

Summary of Reviewer Comments - Second Order Draft

Reviewer	Total Comments	Accepted	IPCC Roles	Papers
Riedacker, Arthur	80	22	0	0
Government of Australia	60	44	0	1
Government of Germany	52	32	0	0
Government of U.S. Department of State	51	41	0	0
Muirheid, Ben	48	40	0	0
Government of Spain	23	13	0	0
Chatterjee, Anish	21	6	0	0
Government of Pakistan	20	19	0	0
Government of Sweden	19	3	0	0
Government of Norwegian Pollution Control Authority	17	16	0	0
Government of UK	14	10	0	0
Government of China Meteorological Administration	14	7	0	0
Government of Argentina	13	6	0	0
Amon, B	12	11	0	3
Machado, Pedro	11	9	0	0
Government of Switzerland	9	8	0	0
Elbersen, Berien	8	3	0	0
Viner, D	8	4	0	1
Government of European Community / European Commission	7	7	0	0
Government of New Zealand	6	3	0	0
Read, P	6	0	1	2
Latif, M	4	2	0	1
Government of Japan	4	3	0	2
Hutjes, Ronald	3	1	0	0
Yagi, K	2	2	0	2
Reisinger, Andy	2	2	0	0
IPCC	2	1	0	50
Macey, Kirsten	2	0	0	0
Shirato, Yasuhito	1	0	0	0
Government of France	1	0	0	0
Wu, Shaohong	1	1	0	0
Masui, T	1	0	0	7
Cointreau, S	1	1	0	1
Totals	523	317	1	70

Overview of Reviewer Comments - Second Order Draft

Reviewer Type	Total Comments	Accepted	% Accepted
Govt	246	165	67%
IPCC	100	68	68%
Indep	177	84	47%
Total	523	317	60%

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