稻田甲烷排放模型研究——模型及其修正

在过去十多年内 ,关于稻田甲烷排放的模拟已经进行了不少有益的探索并且开发出了数个有关的模型。模型的成功研制是准确定量估计不同区域范围内稻田甲烷排放的前提。以往大部分模型由于模拟精度不高 ,或者是其要求太多的输入参数 ,因而限制了它在大尺度范围内的广泛应用。在一个比较成熟的模型基础上 ,进行了必要的修正与扩充。增加了稻田甲烷通过气泡方式排放的模拟模块 ,并修正了原模型中关于土壤氧化还原电位变化的模拟 ,使之能适应于多种稻田水管理方式。新修正的模型 (CH4 MOD)不仅保留了原模型输入参数较少和易于获得的优点 ,而且能适应多种水稻耕作方式 ,这为进一步利用模型技术准确估计大尺度区域稻田甲烷排放提供了一种新的科学方法     

稻田甲烷排放模型研究——模型灵敏度分析

模型方法对区域稻田甲烷排放估计的不确定性主要源于模型参数在区域范围内的误差,这种误差导致的估计不确定性由模型灵敏度决定.采用一种动力学分析与统计分析相结合的方法对稻田甲烷模型CH4MOD进行了参数灵敏度分析,结果表明,稻田水管理方式的灵敏度最高,灵敏度指数为O.64,其次为稻田土壤的砂粒含量参数,灵敏度指数0.50,灵敏度最低的参数是水稻移栽期地上生物量.以模型灵敏度指数为基础,建立了模型估计值不确定性与模型参数区域化误差间的数量关系,利用这一量化关系得出我国2000年稻田甲烷排放的不确定性范围为3.09～10.61Tg.此外,模型灵敏度参数的大小也反映了模型要素对稻田甲烷排放影响的大小,因而分析的结果对于采取合理措施减少稻田甲烷排放具有指导意义.     

稻田甲烷排放模型研究——模型的验证

模型的有效性检验是模型应用于估计区域尺度稻田甲烷排放量的基本前提 ,尤其是针对多种不同的土壤、气候以及农业管理方式等可能影响稻田甲烷排放的环境条件下的模型检验。利用覆盖全国主要水稻产区的 94个甲烷排放观测案例对稻田甲烷排放模型 (CH4 MOD)进行了验证。这些观测区域分布范围北至北京 (4 0°30′N,116°2 5′E) ,南至广州 (2 3°0 8′N,113°2 0′E) ,东起杭州 (30°19′N,12 0°12′E) ,西到四川的土主 (2 9°4 0′N,10 3°5 0′E)。既有双季稻 ,也有单季稻 ,稻田灌溉及施肥方式也多种多样 ,对我国水稻生产具有较广泛的代表性。观测获得的稻田甲烷排放季节总量从 3.1kg C/hm2到 76 1.7kg C/hm2 ,平均值为199.4 (± 187.3) kg C/hm2 ;相应的模拟值分别为 13.9、82 4 .3和 2 2 4 .6 (± 187.0 ) kg C/hm2。模拟值与实测值的线性相关系数(r2 )为 0 .84 (n=94 ,p<0 .0 0 1)。CH4 MOD模型能够通过较少的输入参数有效地模拟我国主要农作方式下的稻田甲烷排放     

水稻植株对稻田甲烷排放的影响

稻田CH4排放是稻田土壤中CH4产生、氧化和传输不同过程的净效应,水稻植株强烈影响稻田CH4的产生、氧化和传输过程,是导致稻田CH4排放季节性变化规律的一个重要因素,本文综述了水稻植株对稻田CH4排放过程的不同影响,水稻植株根系分泌物和脱落物作为产甲烷前体促进稻田土壤中CH4的产生,在水稻生长后期,植株根系分泌物和脱落物被认为是稻田土壤甲烷产生的主要基质,是导致这一时期稻田CH4高排放通量的主要原因;水稻植株根系泌氧在根际环境形成一个微氧区域氧化稻田甲烷,整个水稻生长季稻田土壤中产生的CH4大约36％～90％在植株根际环境中被氧化;约80％甚至更多的稻田CH4通过水稻植株的通气组织进入大气圈,植株对稻田CH4的传输具有十分重要的意义。     

稻田秸秆还田:土壤固碳与甲烷增排

基于我国农田土壤有机质长期定位试验和稻田甲烷排放试验成果,将全国稻田划分为单季区和双季区.根据土壤有机质试验数据,分析了秸秆还田在我国两个稻田区的单季稻田、水旱轮作稻田和双季稻田的固碳潜力.同时根据我国稻田甲烷排放试验数据,采用取平均排放系数的方法,估算了我国稻田在无秸秆还田情况下的甲烷排放总量;结合IPCC推荐的方法和参数,估算了我国稻田秸秆还田后甲烷排放总量及增排甲烷的全球增温潜势.结果表明:在中国稻田推广秸秆还田的固碳潜力为10.48TgC.a-1,对减缓全球变暖的贡献为38.43TgCO2-eqv.a-1;但秸秆还田后稻田甲烷排放将从无秸秆还田的5.796Tg.a-1增加到9.114Tg.a-1;秸秆还田引起甲烷增排3.318Tg.a-1,其全球增温潜势达82.95TgCO2-eqv.a-1,为土壤固碳减排潜力的2.158倍.可见,推广秸秆还田后,中国稻田增排甲烷的温室效应会大幅抵消土壤固碳的减排效益,是一项重要的温室气体泄漏.     

微生物生物量C、土壤呼吸的季节性变化与黑土稻田甲烷排放

对黑土水稻田一个生长季中土壤微生物生物量C、土壤呼吸和甲烷排放通量进行了监测。结果表明,在水稻生长初期,长效尿素能显著抑制微生物生物量C和土壤呼吸(P<0．05),间歇灌溉措施对二者几乎没有影响,间歇灌溉能减少稻田甲烷的排放,平均排放量比对照减少了32．5％,长效尿素的施用稻田使甲烷的排放略有增加,施用长效尿素的处理,微生物生物量C与甲烷排放量之间呈显著正相关关系。     

夜间增温对稻田甲烷排放的影响及其高光谱估算

昼夜不对称增温是全球气候变化的主要特征之一,有关夜间增温对稻田甲烷(CH_4)排放影响的报道尚不多见。通过田间模拟试验,研究了被动式夜间增温下水稻田CH_4排放及高光谱的特征,并用高光谱数据对稻田甲烷排放进行定量模拟。田间试验设夜间增温(NW)和对照处理(CK),夜间增温即在整个水稻生育期的夜间(19:00—6:00)用铝箔反射膜覆盖水稻冠层。结果表明,夜间增温显著促进水稻拔节期和抽穗期-灌浆期CH_4排放。水稻冠层近红外光谱反射率表现为,在分蘖期和拔节期时,NWCK;而在抽穗-灌浆期和成熟期时,CKNW。水稻冠层光谱反射率、一阶导数光谱及光谱特征值均与CH_4排放通量显著相关,相关系数最大可达0.8(P0.01),其中以"蓝边面积"(SD_b)构成的二次多项式模型模拟精度和检验精度综合最佳,决定系数R~2分别为0.70和0.72。研究结果对稻田CH_4排放通量遥感监测的可行性提供了理论依据和技术支持。     

猪粪与沼气渣对双季稻田甲烷排放的影响

随着环境温度的升高,稻田甲烷排放通量增加。早稻期间甲烷排放通量随着水稻生育期的增加而逐步加快,而晚稻甲烷排放主要集中在水稻生长的前中期,而且排放量很高。一天中甲烷排放具有很强的周期性,在6：00～8：00时,甲烷排放通量进入谷底,14：00时甲烷排放通量达到峰值。稻田甲烷排放通量与土壤5cm处的温度及土壤水溶解甲烷含量具有较高的相关性。猪粪和沼气渣的施用分别提高稻田甲烷排放量22．14％和4．40％。在早稻期间,施用猪粪和沼气渣分别提高土壤水溶解甲烷含量40．3％和11．9％,而晚稻期间仅分别提高23．9％和5．04％。     

基于主成分分析水稻植株CH4排放估算模型

估算稻田甲烷（CH4）排放量是开展稻田甲烷排放研究的重要内容之一．通过观测南方红黄壤稻田不同水稻品种甲烷排放通量,测定了16个早稻、20个晚稻品种的植株节间组织的数量特征．选取株高、茎秆长度、茎秆维管束面积／茎壁横切面积、茎壁横切面积／节间横切面积、叶鞘横切面积／节间横切面积、气腔面积／茎壁横切面积、维管束总面积／茎壁横切面积等相关因子进行了主成分分析,建立基于水稻植株的CHa排放估算模型,早、晚稻估算模型相关系数分别为0．827、0．853．同时构造了综合评价函数,得出了水稻品种CH4排放综合分值,与实测结果相比较,吻合度较高．利用估算模型进行模拟,比较模拟值与实测值,相对误差较小,证明模型具有有效性和可行性,为估算水稻CH4排放提供参考依据,为评价水稻品种CH4排放高低提供经验参考．     

中国地区稻田CH4和生物质燃烧CO排放对对流层氧化性的影响

利用稻田甲烷排放模型估计中国地区稻田CH4排放,得到排放总量为9.26Tg,排放有明显的季节和空间变化。运用中尺度气象模式MM5以及光化学模式CALGRID,研究上述稻田CH4排放以及Streets等估计的生物质燃烧CO排放对对流层化学的影响。结果表明,这些排放对对流层低层CH4、CO、OH、HO2、O3浓度均有影响。稻田CH4排放在主要水稻种植区附近使得CH4浓度明显增加、最大增量达到66.97μg.m-3。由于大气中存在活性更强的VOC和CO,稻田CH4排放对自由基和O3全国平均浓度的影响不大,使O3增加0.24%、使HO2增加0.4%、使OH减小0.06%。生物质燃烧CO排放使主要排放区附近CO浓度增加大于60μg.m-3,使OH全国平均浓度减小2.2%,使HO2和O3浓度分别增加2.8%和0.9%。生物质燃烧CO排放对中国地区近地面O3浓度影响强于稻田CH4排放。两者的综合影响使得全国对流层低层O3浓度平均增加1.2%,局部地区最大增加量达4.12μg.m-3。上述自然源排放的影响有明显的空间变化,与下垫面类型有关;还有强烈的季节变化,通常夏季影响最为显著。     

Estimates of methane emissions from Chinese rice paddies by linking a model to GIS database

Methane is one of the principal greenhouse gases. Irrigated rice paddies are recognized as contributing to atmospheric methane concentration. Methane emissions from rice paddies are among the most uncertain estimates in rice-growing countries. Efforts have been made over the last decade to estimate CH₄ emissions from Chinese rice paddies via the model method. However, these estimates are very vague due to different models and upscaling methods. A reduction in these uncertainties may be achieved by coupling field-scale models with regional databases. The objective of this article is to develop a methodology of coupling a CH₄ emission model with regional databases by which CH₄ emissions from Chinese rice paddies can then be estimated. CH4MOD, a model for simulating CH₄ emissions from rice paddies with minimal input by using commonly available parameters, is of great potential in terms of upscaling as it has provided a realistic estimate of the observed results from various soils, climates and agricultural practices. By linking spatial databases to CH4MOD, CH₄ emissions from Chinese rice paddies in the 2000 rice-growing season were simulated on a day-by-day basis. The spatial databases were created by GIS with a spatial resolution of 10km×10km, including soil sand percentage, amounts of crop straw and roots from the previous season and farm manure, the water management pattern, dates of rice transplanting and harvesting, acreage of rice planted, rice grain yield and daily air temperature. ARCGIS software was used to meet all GIS needs, including data access, projection definition, overlaying of different vector layers, creation of grids (a raster format of ARCGIS software) by converting vector data, and the data conversion between grids and ASCII formats. Methane emissions from rice paddies in mainland China in the 2000 rice-growing season were estimated to be 6.02 Tg (1 Tg = 10⁹ kg). Of the total, approximately 49% (2.93Tg) is emitted during the single rice-growing season, and 27% (1.63Tg) and 24% (1.46Tg) are from the early and late rice-growing seasons respectively. It was concluded that regional CH4 emissions from rice paddies could be estimated by coupling CH4MOD with regional databases with a high spatial resolution. A further effort should be made to improve the quality of the spatial databases, especially in terms of the amount of added organic matter and the water regime. It is also necessary to evaluate the uncertainties of the present estimates in order to improve the overall accuracy.     

Estimates of methane emissions from Chinese rice paddies by linking a model to GIS database

Methane is one of the principal greenhouse gases. Irrigated rice paddies are recognized as contributing to atmospheric methane concentration. Methane emissions from rice paddies are among the most uncertain estimates in rice-growing countries. Efforts have been made over the last decade to estimate CH₄ emissions from Chinese rice paddies via the model method. However, these estimates are very vague due to different models and upscaling methods. A reduction in these uncertainties may be achieved by coupling field-scale models with regional databases. The objective of this article is to develop a methodology of coupling a CH₄ emission model with regional databases by which CH₄ emissions from Chinese rice paddies can then be estimated. CH4MOD, a model for simulating CH₄ emissions from rice paddies with minimal input by using commonly available parameters, is of great potential in terms of upscaling as it has provided a realistic estimate of the observed results from various soils, climates and agricultural practices. By linking spatial databases to CH4MOD, CH₄ emissions from Chinese rice paddies in the 2000 rice-growing season were simulated on a day-by-day basis. The spatial databases were created by GIS with a spatial resolution of 10km10km, including soil sand percentage, amounts of crop straw and roots from the previous season and farm manure, the water management pattern, dates of rice transplanting and harvesting, acreage of rice planted, rice grain yield and daily air temperature. ARCGIS software was used to meet all GIS needs, including data access, projection definition, overlaying of different vector layers, creation of grids (a raster format of ARCGIS software) by converting vector data, and the data conversion between grids and ASCII formats. Methane emissions from rice paddies in mainland China in the 2000 rice-growing season were estimated to be 6.02 Tg (1 Tg = 10⁹ kg). Of the total, approximately 49% (2.93Tg) is emitted during the single rice-growing season, and 27% (1.63Tg) and 24% (1.46Tg) are from the early and late rice-growing seasons respectively. It was concluded that regional CH4 emissions from rice paddies could be estimated by coupling CH4MOD with regional databases with a high spatial resolution. A further effort should be made to improve the quality of the spatial databases, especially in terms of the amount of added organic matter and the water regime. It is also necessary to evaluate the uncertainties of the present estimates in order to improve the overall accuracy.     

Characterizing spatiotemporal dynamics of methane emissions from rice paddies in Northeast China from 1990 to 2010

Background

Rice paddies have been identified as major methane (CH₄) source induced by human activities. As a major rice production region in Northern China, the rice paddies in the Three-Rivers Plain (TRP) have experienced large changes in spatial distribution over the recent 20 years (from 1990 to 2010). Consequently, accurate estimation and characterization of spatiotemporal patterns of CH₄ emissions from rice paddies has become an pressing issue for assessing the environmental impacts of agroecosystems, and further making GHG mitigation strategies at regional or global levels.

Methodology/Principal Findings

Integrating remote sensing mapping with a process-based biogeochemistry model, Denitrification and Decomposition (DNDC), was utilized to quantify the regional CH₄ emissions from the entire rice paddies in study region. Based on site validation and sensitivity tests, geographic information system (GIS) databases with the spatially differentiated input information were constructed to drive DNDC upscaling for its regional simulations. Results showed that (1) The large change in total methane emission that occurred in 2000 and 2010 compared to 1990 is distributed to the explosive growth in amounts of rice planted; (2) the spatial variations in CH₄ fluxes in this study are mainly attributed to the most sensitive factor soil properties, i.e., soil clay fraction and soil organic carbon (SOC) content, and (3) the warming climate could enhance CH₄ emission in the cool paddies.

Conclusions/Significance

The study concluded that the introduction of remote sensing analysis into the DNDC upscaling has a great capability in timely quantifying the methane emissions from cool paddies with fast land use and cover changes. And also, it confirmed that the northern wetland agroecosystems made great contributions to global greenhouse gas inventory.     

Methane emissions from rice paddies natural wetlands,lakes in China: synthesis new estimate

Sources of methane (CH₄) become highly variable for countries undergoing a heightened period of development due to both human activity and climate change. An urgent need therefore exists to budget key sources of CH₄, such as wetlands (rice paddies and natural wetlands) and lakes (including reservoirs and ponds), which are sensitive to these changes. For this study, references in relation to CH₄ emissions from rice paddies, natural wetlands, and lakes in China were first reviewed and then reestimated based on the review itself. Total emissions from the three CH₄ sources were 11.25 Tg CH₄ yr^?1 (ranging from 7.98 to 15.16 Tg CH₄ yr^?1). Among the emissions, 8.11 Tg CH₄ yr^?1 (ranging from 5.20 to 11.36 Tg CH₄ yr^?1) derived from rice paddies, 2.69 Tg CH₄ yr^?1 (ranging from 2.46 to 3.20 Tg CH₄ yr^?1) from natural wetlands, and 0.46 Tg CH₄ yr^?1 (ranging from 0.33 to 0.59 Tg CH₄ yr^?1) from lakes (including reservoirs and ponds). Plentiful water and warm conditions, as well as its large rice paddy area make rice paddies in southeastern China the greatest overall source of CH₄, accounting for approximately 55% of total paddy emissions. Natural wetland estimates were slightly higher than the other estimates owing to the higher CH₄ emissions recorded within Qinghai‐Tibetan Plateau peatlands. Total CH₄ emissions from lakes were estimated for the first time by this study, with three quarters from the littoral zone and one quarter from lake surfaces. Rice paddies, natural wetlands, and lakes are not constant sources of CH₄, but decreasing ones influenced by anthropogenic activity and climate change. A new progress‐based model used in conjunction with more observations through model‐data fusion approach could help obtain better estimates and insights with regard to CH₄ emissions deriving from wetlands and lakes in China.     

冬季水分管理和水稻覆膜栽培对川中丘陵地区冬水田CH4排放的影响

采用静态箱-气相色谱法观测冬季水分管理和水稻覆膜栽培对川中丘陵地区冬水田全年的CH_4排放通量。试验设置持续淹水(CF)、冬季直接落干+稻季淹水(TF)与冬季覆膜落干+稻季覆膜(PM)3个处理。结果表明,冬季休闲期,CF、TF和PM处理CH_4排放分别为16.1、1.4 g/m~2和2.7 g/m~2;水稻生长期,CF、TF和PM处理CH_4排放分别为57.7、27.7 g/m~2和13.5 g/m~2。相较于CF处理,TF与PM处理分别减少其全年CH_4排放60.6%和78.0%。TF与PM处理水稻生长期CH_4排放峰值分别较CF处理低33.0%和56.1%。休闲期,TF、PM处理厢面与厢沟区域CH_4排放与土壤温度显著正相关(P0.05),与土壤氧化还原电位(土壤Eh)显著负相关(P0.05),而CF处理CH_4排放仅与土壤温度显著正相关(P0.05)。水稻生长期,CF处理CH_4排放与土壤温度显著正相关(P0.05),与土壤Eh显著负相关(P0.05),TF处理CH_4排放仅与土壤Eh显著负相关(P0.05),PM处理厢沟CH_4排放与土壤Eh显著正相关(P0.05)。各处理水稻生长期土壤可溶性有机碳含量(DOC)与微生物生物量碳含量(MBC)显著高于休闲期(P0.05)。研究结果为进一步研究冬水田全年CH_4排放规律及寻求有效的减排措施提供数据支撑和科学依据。     

Model estimates of methane emission from irrigated rice cultivation of China

A model developed by the authors ( Huang et al. 1998 ) was further validated against field measurements from various regions of the world and calibrated to estimate methane emission from irrigated rice cultivation of China. On the basis of available information on rice cultivated area, growth duration, grain yield, soil texture and temperature, methane emission from Chinese rice paddies was estimated for 28 rice cultivated provinces in mainland. The calculated daily methane emission rates, on a provincial scale, ranged from 0.15 to 0.86 g m^–2 with an average of 0.32 g m^–2. Five of the top six locations with higher daily methane emissions are located at a latitude between 28° and 31° N. A total amount of 9.66 Tg (1 Tg = 10¹² g) CH₄ per year, ranging from 7.19 to 13.62, was estimated to be released from Chinese rice paddy soils. Of the total, 45% is emitted from the single-rice growing season, and 19% and 36% are from the early-rice and the late-rice growing seasons, respectively. Approximately 70% of the total is emitted in the region located at latitude between 25° and 32° N. The emissions from rice fields in Sichuan and Hunan Province were calculated to be 2.85 Tg y^–1, accounting for ≈ 30% of the total. Comparisons of the estimated and the observed emission rates show that the estimates were, in general, close to the measurements at most locations.     

控释氮肥对抗除草剂转基因水稻田土壤甲烷排放的影响

采用温室盆栽和静态箱-气相色谱法,研究了控释氮肥对抗除草剂转基因水稻和亲本常规水稻稻田土壤甲烷(CH4)排放的影响。供试土壤为潴育型水稻土,氮肥种类为尿素和控释氮肥。结果表明,与对照(尿素)相比,控释氮肥提高了水稻分蘖数、株高、生物量及产量。水稻品种对CH4季节性排放规律没有明显影响,CH4排放通量基本表现为,自水稻移栽后逐渐升高,移栽后62—92 d出现峰值,而后逐渐降低至水稻收获。与对照相比,控释氮肥可显著降低CH4排放通量和全生育期累积排放量。抗除草剂转基因水稻稻田土壤CH4排放通量和累积排放量均显著低于亲本常规水稻。研究认为,一次性基施控释氮肥和种植抗除草剂转基因水稻对有效减缓稻田甲烷排放具有重要意义。     

Agronomic aspects of wetland rice cultivation and associated methane emissions

Wetland rice cultivation is one of the major sources of atmospheric methane (CH₄). Global rice production may increase by 65% between 1990 and 2025, causing an increase of methane emissions from a 92 Tg CH₄ y^–1 now to 131 Tg in 2025.Methane production depends strongly on the ratio oxidizing: reducing capacity of the soil. It can be influenced by e.g. addition of sulphate, which inhibits methanogenesis. The type and application mode of mineral fertilizers may also affect methane emissions. Addition of organic matter in the form of compost or straw causes an increase of methane emissions, but methane production is lower for materials with a low C/N ratio.High percolation rates in wetland rice soils and occasional drying up of the soil during the cultivation period depresses methane release. Water management practices aimed at reducing emissions are only feasible during specific periods in the rice growing season in flat lowland irrigated areas with high security of water availability and good control of the water supply. Intermittent drying of soils may not be possible on terraced rice lands.Assuming a 10 to 30% reduction in emission rates per unit harvested area, the global emission may amount to 93 Tg CH₄ y^– in 2025. A reduction of global emissions seems very difficult. To develop techniques for reducing CH₄ emissions from wetland rice fields, research is required concerning interactions between soil chemical and physical properties, and soil, water and crop management and methanogenesis. Such techniques should not adversely affect rice yields.     

Effects of soil water content and rice straw incorporation in the fallow season on CH4 emissions during fallow and the following rice-cropping seasons

Methane (CH₄) emissions from paddy fields are believed to contribute to the greenhouse effect. Yet, in the literature, only a few reports are available on the effects of soil moisture regime and straw application in the non-rice-growing season separately on CH₄ emissions during the rice-growing season. The objective of this study was to investigate CH₄ emissions during the winter fallow and the following rice-growing season as affected by soil moisture regime and rice straw application during the fallow season. The experiment was designed to have 10 treatments, that is, five soil water contents (18%, 38%, 59%, and 79% of soil water-holding capacity [SWHC] and flooding; hereafter, W18, W38, W59, W79, and W100) and two rice straw application rates (0.91 and 4.55 g kg^-1 dry soil; hereafter, Sl and Sh) during the fallow season. Both W100 and W79 showed obvious CH₄ emissions during the fallow season, contributing 5.3% and 5.9% (Sl) and 34.8% and 27.8% (Sh), respectively, to their gross CH₄ emissions, which increased significantly with the rising soil water content in the fallow season, except for W18. Rice straw application significantly affected gross CH₄ emissions, but its effect was strongly influenced by soil moisture. The CH₄ emissions per unit weight of rice straw applied of W38 and W59 were 9% and 16%, respectively, as much as that of W100. The findings demonstrate that keeping the soil water content in the range of 38–59% SWHC in the fallow season is important for a reduction in CH₄ emissions.