inated by N2 with smaller quantities of CH4 (Sharpe et al. 2002). A portion of CH4 emitted to the atmosphere can be sequestered by aerobic soils. Thus, land application of manure could significantly decrease the net quantity of CH4 emitted to the atmosphere compared to stockpiling or long-term storage of manure. Manure applied to pasture land did not appear to impact CH4 emission (Chad-wick et al. 2000). On the other hand, net uptake of CH4 under corn from mold-board plowed soils amended with manure was reduced relative to soils without manure.
c. Animal management: Livestock sources of CH4 are predominantly enteric (i.e. from the breath of ruminants and flatus of monogastric animals) as a result of feed digestion. Globally, enteric production of CH4 was estimated at ~80Tg.yr-1, which was 20-25% of the observed increase in atmospheric CH4 concentration (Lassey 2007). Methane emission can be reduced by feeding more concentrates, normally replacing fodder (Beauchemin and McGinn 2005). Although concentrates might increase daily CH4 emission, emissions per kg feed intake and per kg product are reduced due to better efficiency. Other practices that can reduce CH4 emissions include: (a) adding oils to the diet, (b) improving pasture quality and (c) optimizing protein intake. While dietary supplements in the form of ionophores, halogenated compounds, propionate precursors have been tested, their efficacy is doubtful and their overall environmental impact is also under cloud.
d. Consumption of CH4 by soil: Soils have the potential to consume CH4 by the activities of methanotrophic bacteria which constitute the only known net biological sink for atmospheric CH4 and terrestrial emissions. Methanotrophic bacteria are able to oxidize CH4 for energy purposes or for building up of microbial biomass (Hanson and Hanson 1996). Methane uptake is controlled by the interplay of biotic and abiotic factors providing proximate limitation on CH4 oxidation. Methane oxidation in the rice fields is assumed to consume about one-third of the CH4 production (Bosse and Frenzel 1997), although values as high as 90% have also been reported (Schutz et al. 1989). There is an evidence that agricultural practices have adverse effects on the CH4-oxidizing ability of soils (Arif et al. 1996; Kessavalou et al. 1998; Hutsch 2001). Cultivation appears to decrease net CH4 consumption, as CH4 oxidation potentials of cultivated soils are less than in grasslands (Mosier et al. 1996; Kessavalou et al. 1998). Nitrogen fertilization has also been identified among other factors as an important contributor to this effect. In many cases, NH4 is the most detrimental form of N for CH4 oxidation (Bronson and Mosier 1994). In a long-term fertilization experiment, CH4 consumption was significantly lowered after application of mineral N. On the contrary, stimulation of CH4 oxidation by NH4-based fertilizers in soil and around rice roots has also been reported - both in microcosm (Bodelier et al. 2000) and under field conditions (Kruger and Frenzel 2003). It was suggested that elevated CH4/NH4+ ratio in the rooted soil greatly reduces the inhibitory effect of NH4+ (Cai and Mosier 2000). Methane oxidation in an alluvial soil planted to rice under a long-term fertilization experiment was stimulated following the application of mineral fertilizers or compost, indicating nutrient limitation as one of the factors affecting the process (Nayak et al. 2007). Combined application of compost and mineral fertilizer, however, inhibited CH4 oxidation probably due to N immobilization by the added compost.
Nitrous oxide is emitted from agricultural soils by soil microbial processes of nitrification (aerobic transformation of ammonium to nitrate) and denitrification (anaerobic transformation of nitrate to N2 gas (Sahrawat and Keeney 1986; Monteny et al. 2006). The main cause of increases in agricultural N2O emission to the atmosphere is the application of N fertilizers and animal manure management. The major factors controlling soil nitrification-denitrification are soil pH, texture, organic C supply, crop residue management, temperature, soil N content, soil aeration and water status and certain agri-chemicals (Sahrawat and Keeney 1986).
a. Animal manure management: Animal manures can release significant amount of N2O during storage, but their magnitude varies. Preliminary evidences suggest that covering manure heaps can reduce N2O emissions (Chadwick 2005). For most animals worldwide, especially the grazing ones, there is limited scope for manure management, as excretion happens in the field. However, emissions from manure may be curtailed to a limited extent by altering the feeding practices (Kulling et al. 2003), but these mechanisms and the system-wise influence have not been widely explored.
Rotz (2004) outlined several management options to reduce N loss from animal manure management. Management should focus on improving N-use efficiency of animals to reduce N excretion, retaining N contained in manure until it is applied to land and applying the appropriate amount of manure in a timely manner to enhance crop uptake. Nitrous oxide emission from livestock faeces deposited on pasture is dependent on rainfall, quantity and frequency of N-inputs from stocking rate and soil organic C level (Saggar et al. 2007).
b. N2 O emission management from agricultural fields: In general, N2O emission increases with increased N-inputs (Gregorich et al. 2005). The proportion of applied N emitted as N2O has been estimated at 1.25% (IPCC 1997). Both fertilized and unfertilized soils emit N2O. While fertilizer-N is a source of N2O in case of fertilized soils, mineralization of soil organic-N contributes to the production of N2O from unfertilized soils (Aulakh et al. 2000b). The scope of different management practices mitigating N2O emission from croplands and their field potential is listed in Table 15.5. McSwiney and Robertson (2005) reported that N2O fluxes were low to moderate until the N-input exceeded crop needs, after which the flux nearly doubles, suggesting that prudent management of N-inputs can be an effective strategy to minimize N2O emitted from croplands. Emission of N2O after application of anhydrous ammonia was 2-4 times higher than surface applying urea, ammonium nitrate or broadcasting urea (Venterea et al. 2005).
Table 15.5 List of practices to improve fertilizer and manure N-use efficiency in agriculture and expected reduction of N2O emissions assuming global application of mitigation practices (Mosier et al. 1998)_
Estimated decrease in N2O emissions Field
Practice followed (Tg.yr-1) potential
1. Match N supply with crop demand 0.24 ~50%
• Use soil/plant testing to determine fertilizer N needs
• Minimize fallow period to limit mineral N accumulation
• Optimize split application schemes
• Match N application to reduce production goals in region of crop over-production
• Integrate animal and crop production systems in terms of manure reuse in plant production
• Maintain plant residue N on the production site
3. Use advanced fertilization techniques 0.15 ~50%
• Controlled release fertilizers
• Place fertilizers below the soil surface
• Foliar application of fertilizers
• Use nitrification inhibitors
• Match fertilizer type to seasonal precipitation
4. Optimize tillage, irrigation and drainage 0.15 ~40%
Fertilizing with ammonium fertilizers, like urea, increased the potential for ammonia emission (Harrison and Webb 2001), but under anaerobic flooded soil, it could minimize gaseous N emissions via denitrification (Aulakh 1989). N2O emission from field crops is strongly related to the moisture status of the soil. Drying conditions affect nitrification favour low N2O production, but when aerobic periods are followed by irrigation/flooding, large N2O fluxes are observed. The N2O emissions often increase with increasing aeration (decreasing water-filled pore space) during drainage of anaerobic rice soils. Cai et al. (1997) found a very small N2O flux when the rice paddy plots were flooded, but it peaked at the beginning of the disappearance of floodwater, suggesting a trade-off between CH4 and N2O emissions. Substantial N2O emission can occur during freeze-thaw events (Gregorich et al. 2005). Even though the soil temperatures may be near 0°C, the emission of N2O is due to microbial activity (Chang and Hao 2001) and the production of N2O exceeds its reduction to gaseous N2 at low temperature, thus contributing to N2O emission during spring-thaw events (Holtan-Hartwig et al. 2002).
Assessing the impact of agriculture on global climate change requires converting emission data to GWP. Cole et al. (1997) estimated that agriculture has the potential to reduce radiative forcing from 1.2 to 3.3PgCO2-Ceq. yr-1. It was estimated that about 32% could be from reduced CO2 emissions, 42% from C offsets through biofuel production on 15% of the existing croplands, 16% from reduced CH4 emissions and 10% from reduced emission of N2O.
A full-cost accounting of the effects of agriculture on greenhouse gas emissions is necessary to quantify the relative importance of all mitigation options. Such an analysis shows nitrogen fertilizer, agricultural liming, fuel use, N2O emissions and CH4 fluxes to have additional significant potential for mitigation (Robertson and Grace 2004). Net GWP calculations should take into consideration the sum of net GHG emission after deducting the biological consumption and chemical decay, biomass production and ideally net changes in soil organic carbon (SOC). Lal (2007) estimated that SOC sequestration potentially could offset ~15% of the global CO2 emission. There are potential trade-offs between SOC sequestration and GHG emission, as conservation tillage enhanced N2O emission. Mosier et al. (2005) reported that SOC storage relative to total emission determined whether a site would provide a net increase or decease in GWP. Their comparisons included GWP from farm operations (planting, harvesting and applying pesticides), fertilizer, liming, irrigation, N2O, CH4 and change in surface SOC (0-5 or 0-7.5 cm).
Calculating net GWP appears simple, sum the GHG emission from all sources (soil, energy use etc.) and deduct the sum of total GHG consumption (C sequestration, methane consumption etc.). However, such measurements are fraught with high spatial and temporal variability. Mosier et al. (2006) compared two methods of estimating net GWP, one based on SOC change (0-7.5 cm) and the other based on soil respiration. The two calculation methods resulted in highly different estimates of GWP, both qualitative and quantitative. It is thus important that while reporting GWP, assumptions and calculations are carefully and clearly delineated.
Recent study has shown that there is a significant economic potential for GHG mitigation in agriculture, with total potentials of 1900-2100, 2400-2600 and 3100-3300Mt CO2 yr-1 at carbon prices of 0-20, 0-50 and 0-100 US $ per ton CO2-eq., respectively (Smith et al. 2007). About 70% of this potential arises from developing countries with a further 10% from countries with economies in transition (Trines et al. 2006). Despite such significant economic potential, there are several barriers that could prevent the implementation of these measures. Many of these barriers are particularly prevalent in developing countries and include economic, risk-related, political, logistical and education as well as societal barriers.
a. Economic barriers include the cost of land, competition for land, continued economic penury, lack of existing capacity, low price of carbon, population growth, transaction costs and monitoring costs.
b. Risk related barriers include the delay on returns from investment, issues of stability (particularly of C sinks) and issues related to leakage and natural variation in C sink strength.
c. Political barriers include unclear policies on land use planning and the lack of clarity in carbon/GHG accounting rules and overall a lack of political will.
d. Logisitical barriers include scattered nature of land holdings and conflict of interest among landowners, accessibility to large areas and biological suitability of the land areas for GHG farming.
e. The educational and societal barriers include newer legislations governing the sector, stakeholders' perception and the persistence of traditional practices.
Maximizing the productivity of existing agricultural land and applying best management practices would help to reduce greenhouse gas emissions (Smith et al. 2008). Ideally, agricultural mitigation measures need to be considered within a broader framework of sustainable development. Policies to encourage sustainable development will make agricultural mitigation in developing countries more achievable. The barriers to implementation of mitigation actions in developing countries need to be overcome, if we are to realize even a proportion of the 70% of global agricultural climate mitigation potential that is available in these countries.
Although GHG emission derived from soil has been researched for several decades, there are still geographic regions and agricultural systems that have not been well characterized. There is an urgent need to estimate GWP across a wide range of agricultural systems. Ideally, a standard or benchmark method to calculate GWP should be established. Methodology to improve the accuracy of determining changes in SOC and GHG emissions would reduce the uncertainty of estimating GWP. Similarly, farmers' participation appears indispensable for technology transfer of any kind, including management changes aimed at sustainable production systems. It is essential to initiate dialogue with the farmers and other stakeholders about GHG concerns and the agricultural practices that would help in mitigating the menace, through various routes:
(i) Improving the understanding of farmers' perceptions and decision making to classify different target groups for specific mitigation strategies.
(ii) Conducting research on farmers' fields or community areas (instead of research stations) as a 'reality check' for suggested improvements.
(iii) Developing alternative management options in close collaboration with farmers preferably derived from indigenous knowledge on sustainable management practices.
(iv) Focusing on farm households rather than individual production systems and evaluating the economic benefit to the farmer, e.g. affordability versus profitability.
(v) Packaging scientific knowledge in practical and user-friendly forms through easy decision-support tools.
(vi) Establishing continuous feed-back on mitigation strategies over longer time spans, e.g. farmers' perception on water pricing may vary according to weather events.
(vii) Educating farmers and rural communities by knowledge initiatives. 15.7 Conclusion
There are significant opportunities for mitigation of GHG in agriculture, however, there are large uncertainties and it is difficult to assess the effectiveness of GHG mitigation measures under the changing environmental conditions. Many recent studies have shown that actual levels of GHG mitigation are far below the technological potential for these measures. However, several barriers, mostly economical, and lack of political will, act as deterrent to achieve this technological potential. The estimated biophysical potential of approximately 5500-6000 Mt CO2 yr-1 would not be realized due to these constraints. With appropriate policies - education and policy initiatives, it may be possible for agriculture to make a significant contribution to climate mitigation by 2030.
Many agricultural mitigation options have both co-benefits (in terms of improved efficiency, reduced cost and environmental benefits) and trade-offs. Many agricultural GHG mitigation options could be implemented immediately without any further technological development, while a few options are still undergoing technological validation. It is important that policy planners understand the issue of climate change vis-a-vis GHG mitigation measures or potential opportunities and get motivated to act and analyze the costs and benefits of mitigation actions. The long-term outlook for GHG mitigation in agriculture suggests that there is a significant potential, but many uncertainties, both price and non-price related, will determine the level of implementation.
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