Updating research works on GHG emission from Paddy Rice in China Institute of Environment and Sustainable Development in Agriculture,Chinese Academy of Agricultural Sciences IEDA, CAAS Updating research works on GHG emission from Paddy Rice in China Xiaobo Qin, Yu’e Li, Yunfan Wan, Bin Wang, Jianling Li Sept 2, 2017 Hi, I m. from. Its my pleasure to give this brief report on Mitigation of …,

In this talk In this talk Governmental emission reduction policy Projects stock taking Research updates There are three items in this talk

Mitigation policy Stock-take Ministry of Agriculture, 2015: “One control” To control the total amount of agricultural water use, to set the red lines of both the total amount and the use of coefficient. Alternative：drip irrigation, sprinkler irrigation, mid-season-drainage, wet irrigation Water saving irrigation Flooding

Mitigation policy Stock-take “Two reduction” Reduce the total application of chemical fertilizers, pesticides, by 2020, to achieve zero increase in the fertilizer and pesticide application. Alternative：organic fertilizer Demonstration of organic fertilizer

Mitigation policy Stock-take “Three basic” for the problems of livestock and poultry treatment, plastic film recycling and straw residue, take the relevant measures, through the use of resources to fundamentally solve these problems Alternatives: Biochar based fertilizer Composting Film degradation

Projects Stock take Stock-take “Thirteenth five plan”: national and provincial policy Low carbon development and coping with climate change NDRC: 2014: “National Response to Climate Change Planning (2014-2020)” MOST: 2017: “Response to climate change science and technology innovation special plan” MEP: “National Ecological Protection”: ecological civilization and food security For projects stock take about greenhouse gas mitigation, you know, now, it’s the period of “thirteenth five plan”,

Projects Stock take Stock-take “Thirteenth five plan”: key research and development plan, MOST Mitigation and adaptation to global change and sustainable transformation research (2016-2020) Optimization path research to achieve the 2030 carbon emission peak target Research on climate and environmental effects of black carbon and mitigation strategies Study on Key Technologies of Quantification and Verification of Non-CO2 Greenhouse Gas Emission and Emission Reduction in the industrious of crop planting and breeding Accounting research of greenhouse gas and air pollutant emissions Besides the national policy, there are many projects proposed by Ministry of science and technology.the first one aims to synergy of mitigation and adaptation, the second one emphasize the emission peak target,

Research update Our field monitor distributed in Hubei and Guangdong province, both of the two locations are the major double rice plantation region of China.

1、Influence of biochcar application on greenhouse gas emissions and its microbial effects in a double rice cropping system

Objectives Elucidate the long-term effects of biochar application on yield-scaled GHG emissions in a rice paddy cropping system Investigate the potential microbial mechanisms involved Consequently, the purpose of our study is to firstly …, and then …

Biochar and fertilization design Ttreatments Base fertilization Tillering fertilization Jointing fertilization Booting fertilization N P2O5 K2O Biochar Straw N (Urea) K2O (KCL) CK 72.00 135.00   34.50 55.20 45.00 36.00 BC1 5000 BC2 10000 BC3 20000 RS 132.36 2400 19.38 24.60 RI Abide by a local survey, we designed the fertilization strategy. For the biochar application, we set three different rate as 5t, 10t and 20t per hectare. we also had two rice residue treatments regular one (rs) and inoculated one (ri), all the six practices were set to the same Nitrogen rate.

（Qin et al., 2016） 4.61% 25.7% 29.14% Yield and GHG effects Biochar application significantly reduced methane and gross greenhouse gases emission, simultaneously, slightly promoted rice grain yield, thus inhibited yield-scaled greenhouse effect Rice yield: biochar amendment slightly increased the rice grain yield (4.61%) relative to the control, with the greatest increase in yield occurring in the BC3 treatment (7.47%), followed by BC2 (3.56%), and BC1 (2.82%) GHG emissions: 25.7% of gross GHG emission was reduced by biocar. BC3 (20 t ha −1 ) showed the greatest reduction in CH4 and gross GHG emissions, but we found no relationship between reduction in GHG emissions and increasing levels of biochar application GHGI: BC1, BC2, and BC3 treatments caused reductions of 24.21%, 23.2%, and 40.02%, respectively, in YSGEs compared with the control CK

PCA So, what reason caused these yield and ghg effects by biochar application? Above all, we conducted the PCA to see the relationship among field practices, environmental factors and microbial gene abundance. PCA of the T-RFs (bp) for each gene in the various treatments in 2012 was conducted, based on the T-RFLP analysis (Fig. 2). For the pmoA genes, totally 7 bp ranges of T-RFs were recognized, and 5 of these had strong loadings with the 3 biochar treatments, while the RS and RI treatments just dominated the two ranges of T-RFs. This indicates that the abundance of methanotrophs was stimulated by biochar treat- ment, particularly at the highest application rate (BC3). for the methanogen 16S rDNA genes, totally 11 ranges of T-RFs were screened, and there was no clear correlation of their loadings with dif- ferent treatments. For example, treatments RI and BC3 had similar load- ings, and RS, the control, and BC2 also had similar loadings, with treatment BC1 dominating the distribution of 4 T-RFs. Evidently, Biochar amendment stimulated the activity and abundance of methanotrophs rather than methanogens, consequently, CH4 emissions were reduced in the biochar treatments

Gene abundance and biodiversity Biochar amendment increased the abundance of methnotrophic microbes, decreased the ratio of “16S rDNA/pmoA” The biodiversity indices of the pmoA gene were significant greater than 16S rDNA, increased the ratio of “BC/other treatments” of pmoA 39.77% Furthermore, gene abundance and biodiversity analysis told us more. The rice paddy soil still was dominated by anaerobic archaea,so the 16S rDNA gene copy number was 100-fold greater than pmoA gene. While biochar amendment increased the abundance of methnotrophic microbes. On average, the copy numbers for the 16S rDNA gene in the BC1, BC2, and BC3 treatments were greater than that for the pomA gene by factors of 95.61, 94.11, and 105.76, respectively, which was 41.55%, 42.47%, and 35.34% less than that of the control, even obvious, the average value of this ratio of biochar was just 30.06% of the two rice straw return treatments biodiversity indices for the two kinds of microorganisms showed different patterns with biochar amendment. Relative to the other treatments, under the BC treatments the mean biodiversity indices for the pomA gene (%) were significant higher than those for the 16S rDNA gene, indicating that biochar addition increased the biodiversity of methanotrophic microbes rather than methanogenic archaea the relative percent of biodiversity index of BC (average of 3 biochar treatments) to CK, RS and RI for the 16S rDNA and pmoA, respectively. Note: H presents the Shannon-Wiener index; S is the Simpson index and J denotes the Pielou homogeneity index. (Qin et al., 2016)

Highlights Biochar amendment significantly decreased CH4 and gross GHG emissions Biochar application stimulated biodivesity and abundance of methanotrophic microbes, thus decreased the ratio of “16S rDNA/pmoA” Biochar addition increased soil aeration by reducing bulk density, thus decreased the soil methanogenisis and enhanced methane oxidation potential The highest biochar rate (20 t ha-1) promoted the greatest reduction in GHG emissions and highest improvement in rice yield Our results suggested that, rather than the direct return rice straw to rice paddy fields to make full use of the enormous straw resources from rice production in China, the use of straw-derived biochar may offer the potential to reduce GHG emissions, simultaneously improving rice productivity and contributing to the abatement of global warming.

2、Responses of yield, CH4 and N2O emission to elevated temperature and CO2 in a double rice cropping system

Objectives A modified OTC device was used to simulate the climate change scenarios with 60ppm CO2 and/or 2℃ temperature elevation, and a static chamber-gas chromatography (GC) method was employed to monitor CH4 and N2O fluxes. Investigate the individual and combined impacts of elevated CO2 and temperature on CH4 and N2O emissions Identify seasonal differences in responses to elevated CO2 and temperature Evaluate the effects on yield-scaled emission

Treatments： UC, paddy field without OTC covering, representing ambient atmospheric temperature and CO2 CK, OTC with the same temperature and CO2 to the ambient environment, as the control group CT, OTC with 2℃ temperature elevation and ambient CO2 CC, OTC with 60 ppm CO2 elevation and ambient temperature CTC, OTC with 2℃ temperature and 60ppm CO2 elevation simultaneously A two-factor experiment design was adopted in a randomized block. Twelve OTCs were arranged in three rows in the rice planting area (25 m × 20 m) at equal spacing.

Pictures of the actual set-up. Static chamber method was used to sample the gas in the right picture.

Treatment Emissions (kg ha-1) in 2013 Early rice Late rice CH4 CK 87.1b 78.3b CT 116.3ab 102.4a CC 104.3ab 109.6a CTC 124.0a 112.1a UC 94.5ab 77.0b N2O 1.44b 3.59b 1.29b 3.37b 3.31a 8.53a 1.57b 4.65b 1.41b 3.12b CH4 fluxes were of direct relevance to water conditions in the rice field. Flux peaks occurred after flooding and rapidly declined during mid-season drainage. N2O fluxes varied sharply in response to mid-season drainage, fertilization and precipitation. Elevated atmospheric temperature and/or [CO2] had no obvious impact on the seasonal pattern of fluxes, but increased the peak values significantly. Seasonal variations of water depth and daily precipitation (a-1), CH4 fluxes (a-2), N2O fluxes (a-3) in 2013

Treatment Emissions (kg ha-1) in 2014 Early rice Late rice CH4 CK 68.1b 67.8b CT 71.0b 92.2a CC 101.4a 103.5a CTC 86.9ab 104.9a UC 67.9b 59.9b N2O 1.04c 1.46b 1.64bc 1.43b 2.5a 2.95a 2.13ab 3.11a 1.16c 1.47b Seasonal variations of water depth and daily precipitation (b-1), CH4 fluxes (b-2), N2O fluxes (b-3) in 2014

Total emissions (CO2 eq =34RCH4+298RN2O , calculated by GWP on a 100 year horizon) were in the rank order of CC > CTC > CT > CK ≈ UC Elevated temperature and/or [CO2] caused more greenhouse gas emissions from rice paddy during the two-year experiment.

Averaging across the four growing seasons ： CH4 emissions were increased by 42.1% under CTC, by 38.7% under CC, and by 26.8% under CT N2O emissions were increased by 129% under CC Total emissions were increased by 55.5% under CTC, by 44.1% under CC, and by 22.5% under CT

GHGI increased with temperature and CO2 elevation, this suggests that more CH4 and N2O emissions will be generated to produce a unit mass of rice under global warming. As demand for rice production increases, the GHG emissions from rice paddies may increase further in a future warming climate

Highlights CH4 emission further increased when elevated temperature and [CO2] were combined. Warming weakened the enhancement on N2O emission by elevated [CO2]. The impact of warming on yield was different between early rice and late rice. GHGI increased significantly with temperature and [CO2] elevation.

3、Effect of the combination of modified nitrogen management and water saving irrigation on rice production and GHG emissions from a double rice cropping system

Organic Carbon Content/g·kg-1 Location: Jingzhou Agrometeorological Station, Jianghan Plain, Central China (30°21'N, 112°09'E) Time: April 30rd to October 24th, 2016 Cropping system: double rice Jing Zhou Soil is hydragric paddy soil after years of rice cultivation, texture is medium loam, with the following basic characteristics (0-20cm depth): Field experiments were conducted at Jingzhou, Hubei province. And the cropping system dominated by double rice. Year pH Bulk Density/g·cm-1 Organic Carbon Content/g·kg-1 Total N/g·kg-1 Available P/mg·kg-1 Available K/mg·kg-1 2016 7.8 1.40 15.9 1.09 9.7 56.3

Treatments： U+CI: Urea with conventional irrigation (CK) U+SWD: Urea with shallow depth and wetting-drying irrigation CRU+SWD: Polymer-coated controlled release urea (N≥42%, release period 90d) with SWD irrigation NU+HQ+SWD: N-Sever (N≥46%) plus hydroquinone with SWD irrigation CRU+CI: CRU with conventional irrigation EM+U+SWD: Urea plus effective microorganism with SWD irrigation A single factor randomized complete block design with three replications of each treatment in plots of 6 m × 4.5 m.

N fertilization scheme (kg N ha-1) Treat Base fertilizer 1st top-dressing 2nd top-dressing Early rice (Liangyou 287) U+CI 90 30 45 U+SWD CRU+SWD 120 NU+HQ+SWD CRU+CI EM+U+SWD Late rice (Xiangfengyou 9) 60 The fertilizers were applied three times in each growing season. Phosphate and potassium fertilizers were applied as conventional requirement

Water regime during different rice growing stages Irrigation Limits for irrigation Re-greening Tillering Mid-season drainage Booting Heading Milk maturity Yellow maturity CI Lower limit before irrigation 40 mm 20 mm Drying 10 mm Upper limit after irrigation 60 mm 50 mm 30 mm SWD 0.75 θs 0.60 θs 5 mm 0.70 θs 15 mm Here we can see the water regime during different rice growth stages in CI and SWD irrigation. One of the biggest differences between these irrigations is that AWD is conducted in the tillering and milk maturity stage.

The static chamber-gas chromatography (GC) method was applied An automatic sampling system was used during the rice growing season Manual sampling was undertaken during the winter fallow and land preparation period An automatic sampling system was used during the rice growing season. GWP =25RCH4+298RN2O （kg CO2 eq ha-1）, 100a GHGI= GWP / yield （kg CO2 eq kg-1 grain yield）

The automated monitor and analysis system Single chip microcomputer Temperature sensor Air fan Agilent 7890A There are the instruments in the field and the laboratory for GHG measurement. 0.7 m × 0.7 m × 1.5 m A pump was used to control the chamber closing and opening Gas samples were injected into the prepared vacuum vials by the switching of another pump

CH4 fluxes CH4 fluxes changed with the water drainage events. Most of CH4 flux peaks appeared before mid-season drainage N2O emissions were primarily induced by water drainage and fertilization. The biggest N2O flux peak appeared in the U+SWD treatment N20 fluxes

U+SWD show remarkable CH4 reduction compared to U+CI, and the modified nitrogen fertilizer with SWD irrigation further reduced CH4 emissions. CRU+CI also reduced CH4 emission compared to U+CI. CRU+CI reduced N2O emission compared to U+CI. Compared with U+CI, U+SWD increased cumulative N2O emissions. The type of nitrogen fertilizer had a significant effect on N2O emissions. Compared with U+SWD, N2O emissions were reduced under CRU+SWD and NU+HQ+SWD and EM+U+SWD. Similar with the CH4 emissions, U+SWD and CRU+CI show remarkable the total GHG emissions reduction compared to U+CI, and the modified nitrogen fertilizer with SWD irrigation further reduced the total GHG emissions .

No yield loss occurred under the application of U+SWD No yield loss occurred under the application of U+SWD. When SWD irrigation was combined with application of CRU or NU+HQ or EM+U, the yields of these treatments increased to some extent. CRU+SWD and NU+HQ+SWD showed greater potential in increasing yield. Compared to U+CI, other treatments reduced GHGI.

Highlights The combination of modified nitrogen management and water saving irrigation or conventional irrigation is a win-win strategy for food security and environmental sustainability. The impact of warming on yield was different between early rice and late rice Lower GWP were observed under the SWD water saving irrigation Controlled release urea or urease inhibitor, nitrification inhibitor or EM plus urea in combination with SWD irrigation could be used to decrease the overall effect on greenhouse gas while simultaneously increasing yields. Controlled release urea also have the same function in decreasing GHGI under the conventional irrigation, to replace conventional urea in rice paddies in China

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