Global estimations of the inventory and mitigation potential of methane emissions from rice cultivation conducted using the 2006 Intergovernmental Panel on Climate Change Guidelines

Yan, Xiaoyuan; Akiyama, Hiroko; Yagi, Kazuyuki; Akimoto, Hajime

doi:10.1029/2008gb003299

Cited by 373 publications

(298 citation statements)

References 41 publications

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“…For both AW expansion scenarios, we assume that the percentages of rain-fed and irrigated systems are the same as in the RW, and that drainage practices and organic amendments are the same in each scenario. These values are derived following the methods and sources used by Yan et al (14,(51)(52)(53) (30).…”

Section: Methodsmentioning

confidence: 99%

“…As with total cropland, we calculate the amount of land that would be needed to meet RW production values with 1961 yields. We follow the methodology outlined by Yan (14,51) to calculate methane emissions from rice cultivation and GHGs from the burning of rice straw. For both AW expansion scenarios, we assume that the percentages of rain-fed and irrigated systems are the same as in the RW, and that drainage practices and organic amendments are the same in each scenario.…”

Section: Methodsmentioning

confidence: 99%

“…In particular, it has been estimated that modified rice drainage and straw incorporation practices could reduce global CH 4 emissions from rice cultivation by up to 30% (14). Precision agriculture and nutrient budgeting can facilitate more efficient use of fertilizers and thus reduce emissions associated with excess application (6).…”

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confidence: 99%

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Greenhouse gas mitigation by agricultural intensification

Burney

Davis

Lobell

2010

Proc. Natl. Acad. Sci. U.S.A.

914

474

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As efforts to mitigate climate change increase, there is a need to identify cost-effective ways to avoid emissions of greenhouse gases (GHGs). Agriculture is rightly recognized as a source of considerable emissions, with concomitant opportunities for mitigation. Although future agricultural productivity is critical, as it will shape emissions from conversion of native landscapes to food and biofuel crops, investment in agricultural research is rarely mentioned as a mitigation strategy. Here we estimate the net effect on GHG emissions of historical agricultural intensification between 1961 and 2005. We find that while emissions from factors such as fertilizer production and application have increased, the net effect of higher yields has avoided emissions of up to 161 gigatons of carbon (GtC) (590 GtCO 2 e) since 1961. We estimate that each dollar invested in agricultural yields has resulted in 68 fewer kgC (249 kgCO 2 e) emissions relative to 1961 technology ($14.74/tC, or ∼$4/tCO 2 e), avoiding 3.6 GtC (13.1 GtCO 2 e) per year. Our analysis indicates that investment in yield improvements compares favorably with other commonly proposed mitigation strategies. Further yield improvements should therefore be prominent among efforts to reduce future GHG emissions.agriculture | greenhouse gas emissions | land use change | climate change mitigation | carbon price

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Greenhouse gas mitigation by agricultural intensification

Burney

Davis

Lobell

2010

Proc. Natl. Acad. Sci. U.S.A.

914

474

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“…The geographical distribution of the emissions is assessed by global (USEPA, 2006(USEPA, , 2012EDGARv4.2FT2010, 2013 and regional Chen et al, 2013;Chen and Prinn, 2006;Yan et al, 2009;Castelán-Ortega et al, 2014; inventories or by land surface models (Spahni et al, 2011;Zhang and Chen, 2014;Ren et al, 2011;Tian et al, 2010Tian et al, , 2011Li et al, 2005;Pathak et al, 2005). The emissions show a seasonal cycle, peaking in the summer months in the extratropics associated with the monsoon and land management.…”

Section: Rice Cultivationmentioning

confidence: 99%

“…the use of urea and organic fertilizers), soil temperature, soil type (texture and aggregated size), rice variety and cultivation practices (e.g. tillage, seeding, and weeding practices) (USEPA, 2011(USEPA, , 2016Kai et al, 2011;Yan et al, 2009;Conrad et al, 2000). For instance, methane emissions from rice paddies increase with organic amendments (Cai et al, 1997) but can be mitigated by applying other types of fertilizers (mineral, composts, biogas residues, wet seeding) (Wassmann et al, 2000).…”

Section: Rice Cultivationmentioning

confidence: 99%

The global methane budget 2000–2012

Saunois

Bousquet

Poulter

et al. 2016

Earth Syst. Sci. Data

934

733

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Abstract. The global methane (CH 4 ) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH 4 over the past decade. Emissions and concentrations of CH 4 are continuing to increase, making CH 4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH 4 sources that overlap geographically, and from the destruction of CH 4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (∼ biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). . Top-down inversions consistently infer lower emissions in China (∼ 58 Tg CH 4 yr −1 , range 51-72, −14 %) and higher emissions in Africa (86 Tg CH 4 yr −1 , range 73-108, +19 %) than bottom-up values used as prior estimates. Overall, uncertainties for anthropogenic emissions appear smaller than those from natural sources, and the uncertainties on source categories appear larger for top-down inversions than for bottom-up inventories and models.The most important source of uncertainty on the methane budget is attributable to emissions from wetland and other inland waters. We show that the wetland extent could contribute 30-40 % on the estimated range for wetland emissions. Other priorities for improving the methane budget include the following: (i) the development of process-based models for inland-water emissions, (ii) the intensification of methane observations at local scale (flux measurements) to constrain bottom-up land surface models, and at regional scale (surface networks and satellites) to constrain top-down inversions, (iii) improvements in the estimation of atmospheric loss by OH, and (iv) improvements of the transport models integrated in top-down inversions.

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Methane emissions in East Asia for 2000–2011 estimated using an atmospheric Bayesian inversion

et al. 2015

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We present methane (CH 4 ) emissions for East Asia from a Bayesian inversion of CH 4 mole fraction and stable isotope (δ 13 C-CH 4 ) measurements. Emissions were estimated at monthly resolution from 2000 to 2011. A posteriori, the total emission for East Asia increased from 43 ± 4 to 59 ± 4 Tg yr À1 between 2000 and 2011, owing largely to the increase in emissions from China, from 39 ± 4 to 54 ± 4 Tg yr À1 , while emissions in other East Asian countries remained relatively stable. For China, South Korea, and Japan, the total emissions were smaller than the prior estimates (i.e., Emission Database for Global Atmospheric Research 4.2 FT2010 for anthropogenic emissions) by an average of 29%, 20%, and 23%, respectively. For Mongolia, Taiwan, and North Korea, the total emission was less than 2 Tg yr À1 and was not significantly different from the prior. The largest reductions in emissions, compared to the prior, occurred in summer in regions important for rice agriculture suggesting that this source is overestimated in the prior. Furthermore, an analysis of the isotope data suggests that the prior underestimates emissions from landfills and ruminant animals for winter 2010 to spring 2011 (no data available for other times). The inversion also found a lower average emission trend for China, 1.2 Tg yr À1 compared to 2.8 Tg yr À1 in the prior. This trend was not constant, however, and increased significantly after 2005, up to 2.0 Tg yr À1 . Overall, the changes in emissions from China explain up to 40% of the increase in global emissions in the 2000s.

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Global estimations of the inventory and mitigation potential of methane emissions from rice cultivation conducted using the 2006 Intergovernmental Panel on Climate Change Guidelines

Cited by 373 publications

References 41 publications

Greenhouse gas mitigation by agricultural intensification

Greenhouse gas mitigation by agricultural intensification

The global methane budget 2000–2012

Methane emissions in East Asia for 2000–2011 estimated using an atmospheric Bayesian inversion

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