Mitigation Options for Methane and Nitrous Oxide from Agricultural Soil

Downloaded by UCSF LIB CKM RSCS MGMT on November 24, 2014 | http://pubs.acs.org Publication Date (Web): October 11, 2011 | doi: 10.1021/bk-2011-1072.ch010

Chapter 10

Mitigation Options for Methane and Nitrous Oxide from Agricultural Soil: From Field Measurement to Evaluation of Overall Effectiveness Hiroko Akiyama,* Yoshitaka Uchida, and Akinori Yamamoto National Institute for Agro-Environmental Sciences, 3-1-3 Kannondai, Tsukuba 305-8604, Japan *E-mail: [email protected]

This chapter describes field measurement techniques and mitigation options for methane (CH4) and nitrous oxide (N2O). Of the currently available technologies, the most potent and feasible options for mitigating CH4 from paddy rice fields are mid-season drainage and off-season rice straw application (i.e., rice straw from a previous season is incorporated into the soil long before cultivation) and the use of nitrification inhibitors to mitigate N2O emission from agricultural fields. Mid-season drainage and rice straw management were estimated to reduce global CH4 emission by 16% each. If both of these mitigation options were adopted, the global CH4 emission from rice paddies would be reduced by 30%. According to meta-analysis of field data, nitrification inhibitors significantly reduced N2O emission from agricultural fields (mean effect: –38%) compared with that of conventional fertilizers.

Introduction Agriculture is an important source of anthropogenic methane (CH4) and nitrous oxide (N2O). Rice cultivation is a major source of CH4, which is a greenhouse gas. Yan et al. (1) estimated global CH4 emission from rice paddy fields in 2000 as 25.6 Tg year–1, which accounts for about 4% of global CH4 emission. N2O is a greenhouse gas, and is involved in the destruction of © 2011 American Chemical Society In Understanding Greenhouse Gas Emissions from Agricultural Management; Guo, L., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2011.


stratospheric ozone. Agriculture is the largest single source of global N2O. The agricultural sector is estimated to emit 2.8 Tg N year–1 from soil and livestock, which accounts for 16% of global N2O emission (42% of global anthropogenic N2O emission) (2). Recent advances in measurement techniques have led to significant improvements in the estimation of CH4 and N2O emission from agricultural fields. These advances are also expected to allow more accurate evaluations of existing mitigation options and to enhance the development of new mitigation technologies. Mitigation options for CH4 and N2O from agricultural soil have been intensively studied, primarily in field experiments. For example, 85 field measurements of the effectiveness of nitrification inhibitors on N2O have been reported (3). Such field studies are useful for evaluating the effectiveness of mitigation options within local environments and for investigating the mechanisms of those mitigation options. However, CH4 and N2O fluxes and the effectiveness of mitigation options vary widely depending on environmental factors such as soil type and climate. Therefore, the overall effectiveness of mitigation options cannot be evaluated by a single field experiment. Statistical models and meta-analyses can combine the results of numerous field studies, and these statistical methods are useful for evaluating the overall effectiveness of mitigation options. This chapter describes techniques for measuring CH4 and N2O fluxes and options for mitigating CH4 and N2O, focusing particularly on recent developments in the evaluation of the overall effectiveness of those mitigation options.

Estimating CH4 and N2O Fluxes from Agricultural Field Field Measurement Techniques for CH4 and N2O Fluxes There are two methods for measuring CH4 and N2O fluxes from soil: the use of closed chambers and micrometeorological techniques (4). In the closed chamber method, CH4 and N2O fluxes are determined by enclosing the atmosphere above soil and measuring the changes in headspace gas concentrations over time. This method is useful for comparisons between adjacent treatments and allows processbased studies. Rochette and Eriksen-Hamel (5) assessed chamber designs and techniques and made suggestions for obtaining more accurate flux measurements. Greenhouse gas fluxes from soils, and particularly those of N2O, generally show large spatial and temporal variability. Therefore, to develop reasonable estimates of annual emission, it is important to monitor these fluxes from many chambers frequently over long periods. Because the manual chamber techniques are simple and inexpensive, it has become a widely used method. However, it is also laborintensive and time-consuming. Consequently, flux measurements reported in the literatures have been typically obtained at intervals of 3 to 7 days over a period of several months (6). Automated chamber techniques reduce labor costs and achieve frequent and long-term sampling (these are described in the following section).

166 In Understanding Greenhouse Gas Emissions from Agricultural Management; Guo, L., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2011.


Micrometeorological (eddy covariance) techniques involve measurements of CH4 and N2O concentrations in the atmosphere at two or more points above the soil surface, in combination with meteorological measurements (e.g., wind speed, wind direction, and air temperature). These methods are suitable for measuring gas flux from a large area and are widely used to measure CO2 fluxes from forests and agricultural fields. Although the eddy covariance technique has been used to measure CH4 fluxes from a paddy rice field (7) and N2O flux from a pasture (8), most studies of CH4 and N2O fluxes use chamber methods. One disadvantage of micrometeorological techniques is that they are less reliable at low wind speed and high atmospheric stability. In addition, because eddy covariance methods require large homogenous field sites, it is difficult to use them to evaluate mitigation options, which requires comparison among different treatments in adjacent field plots. Owing to these disadvantages, micrometeorological techniques are not discussed any further here.

Automated Chamber Techniques Automated chamber techniques were developed for frequent and long-term monitoring of gas fluxes, which is difficult with manual chamber methods. Since Schütz et al. (9) reported the use of an on-line connected automated sampling–analytical system (hereafter, an on-line monitoring system) for monitoring CH4 fluxes from a rice field, various on-line systems for monitoring CH4 and N2O fluxes from soils have been developed (Figure 1) (10–15). These systems typically consist of automated chambers, a gas sampling system, and analytical systems such as a gas chromatograph or a photoacoustic infrared trace gas analyzer. Although on-line monitoring systems allow frequent and long-term flux measurement, one disadvantage is their large size. The monitoring systems can be difficult to transport between sites once they have been set up, and the analytical systems usually must be maintained at constant temperature. Because these systems also require frequent maintenance, field sites are usually limited to those near a research station that can provide appropriate maintenance facilities. An alternative approach is the use of off-line monitoring systems, which are based on a gas sampling system with automated chambers. In such systems, the gas samples are transferred to a laboratory for analysis. Such systems greatly reduce the labor cost compared to that of manual chamber methods. In addition, the systems are much less expensive and smaller than typical on-line monitoring systems. Off-line monitoring systems are easier to transport between sites for subsequent experiments, and they can be set up in remote areas. Such systems using specially made aluminum gas tubes (16) or copper sample loops (17) as the sample gas containers were reported. Akiyama et al. (18) developed a simple and robust automated sampling system that uses common glass vials as the sample gas containers (Figure 2). Their system was further modified to control three chambers with one sampling unit and is commercially available in Japan. In 2010, more than 20 of these systems were in operation in Japan.



Figure 1. Example of an on-line connected automated sampling–analytical system. The system uses six auto-chambers. For N2O and nitric oxide flux measurements, the lid of each chamber is closed to isolate the air inside from the atmosphere, and the air inside is drawn into the analysis system through a 10-m-long Teflon tube. GC-ECD: gas chromatograph equipped with electron capture detector. (Reproduced with permission from reference (10). Copyright 2000 Elsevier B.V.)

Mitigation Options for CH4 Emission from Paddy Rice Fields CH4 is produced by the activity of CH4-producing archaea (methanogens) as one of the terminal products in the anaerobic food web in rice paddy soils (19, 20). Methanogens are strict anaerobes that require highly reducing conditions. Part of the produced CH4 is consumed by CH4-oxidizing bacteria (methanotrophs). The emission pathway of CH4 accumulated in flooded paddy soils is as follows: diffusion into the flood water, loss through ebullition, and transport through the aerenchyma system of rice plants. In temperate rice fields, more than 90% of CH4 is emitted via the plants (21). In tropical rice fields, however, the contribution of ebullition may be larger than in temperate regions (22). The possible strategies for 168 In Understanding Greenhouse Gas Emissions from Agricultural Management; Guo, L., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2011.


mitigating CH4 emission from rice cultivation include controlling the production, oxidation, or transport processes.

Yagi et al. (19) and Minamikawa et al. (23) assessed strategies for reducing CH4 emission from paddy rice and reported various mitigation options, such as water management (mid-season drainage, short flooding period, and increased percolation), organic matter management (composting and off-season rice straw application), soil amendments (oxidants, soil dressing), no or minimum tillage, rotation, and the use of particular rice varieties. Among these, mid-season drainage and off-season rice straw application are the two most intensively studied technologies and therefore the most potent and feasible mitigation options.

Water Management Because CH4 production occurs strictly under reducing conditions, water management greatly affects CH4 emission from paddy rice fields. Mid-season drainage is a traditional management practice in which irrigated rice paddies are drained for 7-10 days during the growing season. Mid-season drainage is practiced in Japan, China, and other monsoon Asian countries to enhance grain yield, whereas continuous flooding of rice paddies is common in Vietnam (1). According to intensive field measurements across five countries (24), mid-season drainage reduces CH4 emission by 7% to 80% compared to continuous flooding. Another traditional water management practice of intermittent irrigation is also practiced in Japan, China, India and other Asian countries. In intermittent irrigation, drainage and irrigation repeated with few days cycle during the growing season. Studies have shown this practice to be effective for reducing CH4 emission (25–30), although fewer studies have examined intermittent irrigation as compared to mid-season drainage. Lu et al. (31) reported that mid-season drainage reduced CH4 emission by 44% compared to continuous flooding, and intermittent irrigation reduced CH4 emission by 30% as compared with mid-season drainage. Yagi et al. (32) reported that a high percolation rate of irrigation water greatly reduced CH4 emission, although there are not many reports related to this mitigation option. Yan et al. (33) developed a statistical model using more than 1000 seasonal measurements from more than 100 sites. On the basis of their results, the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (34) adopted a 40% CH4 reduction rate for a single mid-season drainage and 48% for drainage on multiple occasions, compared to continuous flooding (Figure 3). It should be noted that good irrigation systems are required to practice mid-season drainage or intermittent irrigation. In many parts of tropical Asia, rice fields are rain-fed, so they are naturally flooded during the monsoonal rainy season, making fully controlled drainage often impossible. For paddy fields in which irrigation water can be controlled, mid-season drainage would be one of most effective and costeffective mitigation options.



Figure 2. Schematic diagram of the automated gas sampling system (Japan patent pending 2008-011540). (Reproduced with permission from reference (18). Copyright 2009 John Wiley and Sons, Inc.)

Organic Matter Management

Rice straw, green manure and animal manure are widely applied in rice cultivation. This added organic matter acts as an electron donor and a substrate for CH4 production. According to a statistical model developed by Yan et al. (33), the impact of organic amendments on CH4 emission depends on the type and amount of material applied (Figure 4). When rice straw is applied during the off-season—that is, rice straw from a previous season is incorporated into the soil long before cultivation so that it decomposes under aerobic conditions—CH4 emission is greatly reduced compared to application just before the cultivation. However, this practice is not universally applicable. For example, in double rice crop areas such as southern China, late rice is planted immediately after the early rice harvest, which necessitates that the rice straw be applied just before the growing season.



Figure 3. Relative CH4 fluxes for different water regimes in the rice growing season, shown as relative fluxes (with flux from continuously flooded fields = 1), according to the statistical model of Yan et al. (33). Mean and 95% confidence intervals are shown. No confidence intervals are shown for deep water, because limited data were available. (Adapted with permission from reference (33). Copyright 2005 John Wiley and Sons, Inc.)

Figure 4. Simulated effects of different organic amendments on CH4 emission from rice fields, assuming flux without any organic amendment to be 1. Note that straw is in dry weight but others are in fresh weight. FYM: farmyard manure; GM: green manure; Straw_on_season: rice straw applied just before planting; Straw_off_season: rice straw applied and incorporated long before planting. (Reproduced with permission from reference (33). Copyright 2005 John Wiley and Sons, Inc.) 171 In Understanding Greenhouse Gas Emissions from Agricultural Management; Guo, L., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2011.

The application of composted rice straw is more effective at reducing CH4 emission than the use of non-composted straw (Figure 4). This practice, however, involves additional labor to transport material from and back to the field. If no straw is applied to the field, CH4 emission is greatly reduced. In this case, however, rice straw is likely to be burned, which causes severe air pollution. Therefore, burning straw is prohibited in many places.


Other Options

Aside from reports on mid-season drainage and off-season straw application, there is little information available regarding other options for mitigating CH4. The use of soil amendments, such as iron-containing materials, has been reported to be effective at reducing CH4 emission by soil incubation or pot experiments (35–37) and field experiments (38–40). Although there are some reports that no-till is effective at reducing CH4 emission (41, 42), Ishibashi et al. (43) found that the mitigation effect of no-till declined over time and became ineffective after 4 to 7 years. Results of CH4 emission reduction by planting certain rice varieties are conflicting, and Wassmann et al. (44) concluded that the varietyspecific differences are small compared to the effects of other factors, and that they vary between seasons and are too elusive for accurate classification of varieties with respect to their CH4 mitigation potential. Shiratori et al. (45) reported that tile drainage was effective at reducing CH4 emission by oxidizing soil during the fallow season.

The Mitigation Potential of Global CH4 Emission from Paddy Fields Yan et al. (1) investigated the global CH4 mitigation potential of mid-season drainage and off-season rice straw application. They estimated that if all of the continuously flooded rice fields were drained at least once during the growing season, CH4 emission would be reduced by 4.1 Tg year-1, which is equal to a 16% reduction of global CH4 emission from paddy fields. They estimated that off-season rice straw application (>30 days before cultivation) would result in a global reduction in CH4 emission of 4.1 Tg year-1. If both of these mitigation options were adopted, the global CH4 emission from rice paddies could be reduced by 7.6 Tg year-1, which is equal to a 30% reduction of global CH4 emission from paddy rice fields. Draining continuously flooded rice fields may lead to an increase in N2O emission. However, Akiyama et al. (46) analyzed N2O emission from paddy fields and concluded that the increase of global warming potential (GWP) resulting from the N2O increase due to mid-season drainage is much smaller than the reduction in GWP that would result from the CH4 reduction associated with draining the fields.


Mitigation Options for N2O Emission from Agricultural Fields The application of nitrogen to soils as chemical or organic fertilizer stimulates N2O production mainly via the biochemical processes of nitrification (under aerobic conditions) and denitrification (anaerobic conditions) (47). Nitrifier denitrification and the non-biochemical process of chemodenitrification are also involved in the production of N2O in soil, although the contributions of these processes are unclear (47).


Optimizing Fertilizer Application Rate The basic strategy for mitigating N2O emission is optimizing nitrogen use efficiency (48), although this strategy has not been assessed quantitatively. Recently, Mosier et al. (49) introduced the concept of Greenhouse Gas Intensity, which is GWP divided by crop yield. By linking grain yield with greenhouse gas emission, it becomes possible to maximize yield in an environmentally sound manner by using appropriate levels of fertilizer-nitrogen input (49). Van Groenigen et al. (50) further developed this concept and conducted a meta-analysis of 147 field data from 19 studies. They found that optimizing fertilizer-nitrogen use efficiency under median rates of nitrogen input, rather than minimizing nitrogen application rates, resulted in minimum yield-scaled N2O emission (i.e., N2O emission in relation to aboveground nitrogen uptake) for non-leguminous arable crops. Yield-scaled N2O emission was smallest (8.4 g N2O-N kg−1 N uptake) at application rates of approximately 180–190 kg N ha−1 and increased sharply above that (e.g., 26.8 g N2O-N kg−1 N uptake at 301 kg N ha−1). If the aboveground nitrogen surplus was equal to or less than zero, yield-scaled N2O emission remained stable and relatively small. At a nitrogen surplus of 90 kg N ha−1, yield-scaled emission increased threefold. It is notable that minimum input of nitrogen fertilizer, which is generally considered to minimize N2O emission, did not result in minimum N2O emission when crop yield was taken into account. The strategies that reduce N2O emission while maximizing nitrogen use efficiency will also reduce the environmental impacts caused by nitrogen fertilizer, such as nitrogen leaching and subsequent water pollution and ammonia volatilization. Use of Enhanced-Efficiency Fertilizers Enhanced-efficiency fertilizers, such as those containing nitrification and urease inhibitors and polymer-coated fertilizers, have been developed to increase the efficiency of fertilizer use by crops. Nitrification inhibitors are compounds that delay the oxidation of NH4+ by depressing the activities of nitrifiers in the soil, whereas urease inhibitors are compounds that delay the hydrolysis of urea. Polymer-coated fertilizers have a slower rate of nutrient release than conventional fertilizers. These types of enhanced-efficiency fertilizers have been studied intensively, and the findings indicate that they can be effective in increasing nitrogen use efficiency and have other benefits such as reducing labor and fuel costs (51) and decreasing nitrogen leaching (52). These technologies have not 173 In Understanding Greenhouse Gas Emissions from Agricultural Management; Guo, L., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2011.


been used widely thus far, however, because a yield increase is rarely observed despite the additional costs (53, 54). Although many field studies have tested the effectiveness of enhancedefficiency fertilizers on N2O emission, the effectiveness of each option varies across sites depending on environmental factors and field management practices. Akiyama et al. (3) evaluated the overall effectiveness of enhanced-efficiency fertilizers on N2O emission by a meta-analysis of field experiment data (113 datasets from 35 studies). The results showed that nitrification inhibitors significantly reduced N2O emission (mean effect: –38%, Figure 5) compared with conventional fertilizers. Polymer-coated fertilizers also significantly reduced N2O emission (–35%), whereas urease inhibitors were not effective at reducing N2O. Nitrification inhibitors and polymer-coated fertilizers also significantly reduced nitric oxide emission (–46% and –40%, respectively). The effectiveness of nitrification inhibitors was relatively consistent across the various types of inhibitors and land uses. However, the effect of polymer-coated fertilizers showed contrasting results across soil and land-use types: they were significantly effective when used on imperfectly drained Gleysol grassland (–77%), but were ineffective when used on well-drained Andosol upland fields. Because the available data for polymer-coated fertilizers were dominated by certain regions and soil types, additional data are needed to evaluate their effectiveness more reliably. Among nitrification inhibitors, dicyandiamide (DCD) has been the most widely tested. According to a meta-analysis of field experiments (3), DCD significantly reduces N2O emission (mean effect: –30%) compared to conventional fertilizers. In contrast, a much larger effect of DCD (–61% to –76%) was reported based on soil column experiments (55–58). The reason for this discrepancy between field and laboratory experiments is that soil incubation or soil column experiments are often conducted under optimal conditions for DCD to inhibit nitrification (4).

Other Options Bouwman et al. (59) estimated that replacing synthetic nitrogen fertilizer with animal manure nitrogen would result in a 33% reduction of global nitrogen fertilizer use and an 11% reduction of N2O emission. In contrast, replacing synthetic nitrogen fertilizer with biological nitrogen fixation would lead to a N2O increase at the global scale (59). Many studies have suggested that no-till and reduced tillage can decrease agriculture’s contribution to greenhouse gas emission through carbon sequestration (60). However, conclusions on the effect of these practices on greenhouse gas budgets are complicated by the inconsistent effects of no-till and reduced tillage on N2O emission (60, 61). Rochette (61) summarized available data from field studies and concluded that no-till generally increased N2O emission in poorly aerated soils but had a neutral effect in soils with good and medium aeration. Six et al. (60) summarized field experiment data from humid and dry temperate climates and concluded that mitigation of GWP by the adoption of no-till is variable and complex. 174 In Understanding Greenhouse Gas Emissions from Agricultural Management; Guo, L., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2011.


Figure 5. The effect of nitrification inhibitors (NIs) on N2O emission, shown as relative emission (N2O emission from conventional fertilizer = 1), by a meta-analysis of field experiments. Mean effect and 95% confidence intervals are shown. Numerals indicate number of observations. (Note that the sum of observations for each type of NI does not match the number of observations for all NIs because one dataset that tested 2-amino-4-chloro-6-methyl pyrimidine is included in the all NIs category.) All NIs: integrated effect of all types of NI; DCD: dicyandiamide; DMPP: 3,4-dimethyl pyrazole phosphate; Ca-carbide: encapsulated and coated calcium carbide; Neem: various products such as neem oil–coated urea, neem-coated urea, nimin-coated urea, and urea with neem cake from the Indian neem tree (Azadirachta indica). (Reproduced with permission from reference (3). Copyright 2010 John Wiley and Sons, Inc.)

Conclusions Recent advances in measurement techniques, such as the use of automated chambers, have made significant improvements in the estimation of CH4 and N2O emission from agricultural fields. These advances are also expected to allow more accurate evaluation of existing mitigation options and the development of new mitigation technologies. Of the currently available mitigation technologies, the most potent and feasible mitigation options are mid-season drainage and off-season rice straw application for CH4 from paddy rice fields and nitrification inhibitors for N2O from agricultural fields. Mid-season drainage and rice straw management is estimated to reduce global CH4 emission by 16% each. If both of these mitigation options were adopted, the global CH4 emission from rice paddies could be reduced by 30%. According to meta-analysis of field data, nitrification inhibitors significantly reduce N2O emission from agricultural fields (mean effect: –38%) compared with that of conventional fertilizers. Optimizing fertilizer-nitrogen use efficiency under median rates of nitrogen input would minimize yield-scaled N2O 175 In Understanding Greenhouse Gas Emissions from Agricultural Management; Guo, L., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2011.

emission. The strategies that reduce N2O emission while maximizing nitrogen use efficiency will also reduce the environmental impacts caused by nitrogen fertilizer, such as nitrogen leaching and subsequent water pollution and ammonia volatilization.

References


1. 2.

3. 4. 5. 6. 7.

8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18.

Yan, X.; Akiyama, H.; Yagi, K.; Akimoto, H. Global Biogeochem. Cycles 2009, 23. doi.10.1029/2008GB003299. Denman, K. L.; Brasseur, G.; Chidthaisong, A.; Ciais, P.; Cox, P. M.; Dickinson, R. E.; Hauglustaine, D.; Heinze, C.; Holland, E.; Jacob, D.; Lohmann, U.; Ramachandran, S.; da Silva Dias, P. L.; Wofsy S. C.; Zhang, X. In Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change; Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., Miller, H. L., Eds.; Cambridge University Press: Cambridge, U.K., 2007; pp 500–587. Akiyama, H.; Yan, X.; Yagi, K. Global Change Biol. 2010, 16, 1837–1846. de Klein, C. A. M.; van der Weerden T. J.; Eckard R. J. In Nitrous Oxide and Climate Change; Smith, K., Ed.; Earthscan: London, 2010; pp 107–142. Rochette, P.; Eriksen-Hamel, N. S. Soil Sci. Soc. Am. J. 2008, 72 (2), 331–342. Bouwman, A. F.; Boumans, L. J. M.; Batjes N. H. Global Biogeochem. Cycles 2002, 16(4), GB1058, doi:10.1029/2001GB001811. Miyata, A.; Iwata, T.; Nagai, H.; Yamada, T.; Yoshikoshi, H.; Mano, M.; Ono, K.; Han, G. H.; Harazono, Y.; Ohtaki, E.; Baten, M. A.; Inohara, S.; Takimoto, T.; Saito, M. Phyton-Ann. Rei Bot. 2005, 45 (4), 89–97. Phillips, F. A.; Leuning, R.; Baigenta, R.; Kelly, K. B.; Denmead, O. T. Agric. For. Meteorol. 2007, 143 (1–2), 92–105. Schütz, H.; Holzapfelpschorn, A.; Conrad, R.; Rennenberg, H.; Seiler, W. J. Geophys. Res. Atmos. 1989, 94 (D13), 16405–16416. Akiyama, H.; Tsuruta, H.; Watanabe, T. Chemosphere: Global Change Sci. 2000, 2 (3–4), 313–320. Ambus, P.; Robertson, G. P. Soil Sci. Soci. Am. J. 1998, 62 (2), 394–400. Loftfield, N. S.; Brumme, R.; Beese, F. Soil Sci. Soc. Am. J. 1992, 56 (4), 1147–1150. Nishimura, S.; Sudo, S.; Akiyama, H.; Yonemura, S.; Yagi, K.; Tsuruta, H. Soil Sci. Plant Nutr. 2005, 51 (4), 557–564. Thornton, F. C.; Valente, R. J. Soil Sci. Soc. Am. J. 1996, 60 (4), 1127–1133. Yamulki, S.; Jarvis, S. C. J. Geophys. Res. Atmos. 1999, 104 (D5), 5463–5469. Scott, A.; Crichton, I.; Ball, B. C. J. Environ. Qual. 1999, 28 (5), 1637–1643. Smith, K. A.; Dobbie, K. E. Global Change Biol. 2001, 7 (8), 933–945. Akiyama, H.; Hayakawa, A.; Sudo, S.; Yonemura, S.; Tanonaka, T.; Yagi, K. Soil Sci. Plant Nutr. 2009, 55 (3), 435–440. 176

In Understanding Greenhouse Gas Emissions from Agricultural Management; Guo, L., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2011.


19. Yagi, K.; Tsuruta, H.; Minami, K. Nutri. Cycling Agroecosyst. 1997, 49 (1–3), 213–220. 20. Conen, F.; Smith, K. A.; Yagi, K. In Methane and Climate Change; Reay, D., Smith, P., van Amstel, A., Eds.; Earthscan: London, 2010; pp 115–135. 21. Schutz, H.; Seiler, W.; Conrad, R. Biogeochemistry 1989, 7 (1), 33–53. 22. Vandergon, H.; Neue, H. U. Global Biogeochem. Cycles 1995, 9 (1), 11–22. 23. Minamikawa, K.; Sakai, N.; Yagi, K. Microbes Environ. 2006, 21 (3), 135–147. 24. Wassmann, R.; Lantin, R. S.; Neue, H. U.; Buendia, L. V.; Corton, T. M.; Lu, Y. Nutr. Cycling Agroecosyst. 2000, 58 (1–3), 23–36. 25. Adhya, T. K.; Bharati, K.; Mohanty, S. R.; Ramakrishnan, B.; Rao, V. R.; Sethunathan, N.; Wassmann, R. Nutr. Cyclying Agroecosyst. 2000, 58 (1–3), 95–105. 26. Jain, M. C.; Kumar, S.; Wassmann, R.; Mitra, S.; Singh, S. D.; Singh, J. P.; Singh, R.; Yadav, A. K.; Gupta, S. Nutr. Cyclying Agroecosyst. 2000, 58 (1–3), 75–83. 27. Yang, S. S.; Chang, H. L. Biol. Fertil. Soils 2001, 33 (2), 157–165. 28. Pathak, H.; Prasad, S.; Bhatia, A.; Singh, S.; Kumar, S.; Singh, J.; Jain, M. C. Agric., Ecosyst. Environ. 2003, 97 (1–3), 309–316. 29. Yue, J.; Shi, Y.; Liang, W.; Wu, J.; Wang, C. R.; Huang, G. H. Nutr. Cycling Agroecosyst. 2005, 73 (2–3), 293–301. 30. Jiao, Z. H.; Hou, A. X.; Shi, Y.; Huang, G. H.; Wang, Y. H.; Chen, X. Commun. Soil Sci. Plant Anal. 2006, 37 (13–14), 1889–1903. 31. Lu, W. F.; Chen, W.; Duan, B. W.; Guo, W. M.; Lu, Y.; Lantin, R. S.; Wassmann, R.; Neue, H. U. Nutr. Cycling Agroecosyst. 2000, 58 (1–3), 65–73. 32. Yagi, K.; Minami, K.; Ogawa, Y. Plant Soil 1998, 198 (2), 193–200. 33. Yan, X. Y.; Yagi, K.; Akiyama, H.; Akimoto, H. Global Change Biol. 2005, 11 (7), 1131–1141. 34. IPCC, 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4 Agriculture, Forestry and Other Land Use; Institute for Global Environmental Strategies (IGES): Hayama, Japan, 2006. 35. Furukawa, Y.; Inubushi, K. Soil Sci. Plant Nutr. 2004, 50 (7), 1029–1036. 36. Qu, D.; Ratering, S.; Schnell, S. Bull. Environ. Contam. Toxicol. 2004, 72 (6), 1172–1181. 37. Ali, M. A.; Lee, C. H.; Kim, S. Y.; Kim, P. J. Waste Manage. 2009, 29 (10), 2759–2764. 38. Jackel, U.; Russo, S.; Schnell, S. Soil Biol. Biochem. 2005, 37 (11), 2150–2154. 39. Mukherjee, R.; Barua, A.; Sarkar, U.; De, B. K.; Mandal, A. K. Int. J. Greenhouse Gas Control 2009, 3 (5), 664–672. 40. Ali, M. A.; Lee, C. H.; Lee, Y. B.; Kim, P. J. Agric., Ecosyst. Environ. 2009, 132 (1–2), 16–22. 41. Chareonsilp, N.; Buddhaboon, C.; Promnart, P.; Wassmann, R.; Lantin, R. S. Nutri. Cycl. Agroecosys. 2000, 58 (1–3), 121–130. 42. Ahmad, S.; Li, C. F.; Dai, G. Z.; Zhan, M.; Wang, J. P.; Pan, S. G.; Cao, C. G. Soil Tillage Res. 2009, 106 (1), 54–61. 177 In Understanding Greenhouse Gas Emissions from Agricultural Management; Guo, L., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2011.


43. Ishibashi, E.; Akai, N.; Ohya, M.; Ishii, T.; Tsuruta H. Japanese Soil Sic. Plant Nutri. 2001, 72, 542–549 (In Japanese with English abstract). 44. Wassmann, R.; Aulakh, M. S.; Lantin, R. S.; Rennenberg, H.; Aduna, J. B. Nutri. Cycling Agroecosyst. 2002, 64 (1–2), 111–124. 45. Shiratori, Y.; Watanabe, H; Furukawa, Y.; Tsuruta, H; Inubushi, K. Soil Sci. Plant Nutr. 2007, 53 (4), 387–400. 46. Akiyama, H.; Yagi K.; Yan X. Y. Global Biogeochem. Cycles 2005, 19(1), GB1005, doi:10.1029/2004GB002378. 47. Baggs E. M.; Philippot, L. In Nitrous Oxide and Climate Change; Smith, K. A., Ed.; Earthscan: London, U.K.; pp 4–35. 48. Saggar, S.; Tate, K. R.; Giltrap, D. L.; Singh, J. Plant Soil 2008, 309 (1–2), 25–42. 49. Mosier, A. R.; Halvorson, A. D.; Reule, C. A.; Liu, X. J. J. J. Environ. Qual. 2006, 35 (4), 1584–1598. 50. van Groenigen, J. W.; Velthof, G. L.; Oenema, O.; Van Groenigen, K. J.; van Kessel, C. European J. Soil Sci. 2010, 61 (6), 903–913. 51. Grant, C. IFA International Workshop on Enhanced-Efficiency Fertilizers, Frankfurt, Germany, 2005, URL http://www.fertilizer.org/ifa/Home-Page/ LIBRARY/Conference-proceedings/Agriculture-Conferences/2005-IFAAgriculture-Workshop. 52. Bolan, N. S.; Saggar, S.; Luo, J. F.; Bhandral, R.; Singh, J. Adv. Agron. 2004, 84, 37–120. 53. Frye, W. IFA International Workshop on Enhanced-Efficiency Fertilizers, Frankfurt, Germany, 2005, URL http://www.fertilizer.org/ifa/Home-Page/ LIBRARY/Conference-proceedings/Agriculture-Conferences/2005-IFAAgriculture-Workshop. 54. Guertal, E. A. HortTechnology 2009, 19 (1), 16–19. 55. Di, H.; Cameron, K.; Sherlock, R.; Shen, J. P.; He, J. Z.; Winefield, C. J. Soils Sediments 2010, 10 (5), 943–954. 56. Di, H. J.; Cameron, K. C. Soil Use Management 2003, 19 (4), 284–290. 57. Di, H. J.; Cameron, K. C. Biol. Fertil. Soils 2006, 42 (6), 472–480. 58. Di, H. J.; Cameron, K. C.; Sherlock, R. R. Soil Use Manage. 2007, 23 (1), 1–9. 59. Bouwman, A. F.; Stehfest, E.; van Kessel, C. In Nitrous oxide and Climate Change; Smith, K. A., Ed.; Earthscan: London, 2010; pp 85–106. 60. Six, J.; Ogle, S. M.; Breidt, F. J.; Conant, R. T.; Mosier, A. R.; Paustian, K. Global Change Biol. 2004, 10 (2), 155–160. 61. Rochette, P. Soil Tillage Res. 2008, 101 (1–2), 97–100.


Mitigation Options for Methane and Nitrous Oxide from Agricultural Soil

Recommend Documents