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1.
An open dynamic chamber system was used to measure the soil CO2 efflux intensively and continuously throughout a growing season in a mature spruce forest (Picea abies) in Southern Germany. The resulting data set contained a large amount of temporally highly resolved information on the variation in soil CO2 efflux together with environmental variables. Based on this background, the dependencies of the soil CO2 efflux rate on the controlling environmental factors were analysed in-depth. Of the abiotic factors, soil temperature alone explained 72% of the variation in the efflux rate, and including soil water content (SWC) as an additional variable increased the explained variance to about 83%. Between April and December, average rates ranged from 0.43 to 5.15 μmol CO2 m−2 s−1 (in November and July, respectively) with diurnal variations of up to 50% throughout the experiment. The variability in wind speed above the forest floor influenced the CO2 efflux rates for measuring locations with a litter layer of relatively low bulk density (and hence relatively high proportions of pore spaces). For the temporal integration of flux rates for time scales of hours to days, however, wind velocities were of no effect, reflecting the fact that wind forcing acts on the transport, but not the production of CO2 in the soil. The variation in both the magnitude of the basal respiration rate and the temperature sensitivity throughout the growing season was only moderate (coefficient of variation of 15 and 25%, respectively). Soil water limitation of the CO2 production in the soil could be best explained by a reduction in the temperature-insensitive basal respiration rate, with no discernible effect on the temperature sensitivity. Using a soil CO2 efflux model with soil temperature and SWC as driving variables, it was possible to calculate the annual soil CO2 efflux for four consecutive years for which meteorological data were available. These simulations indicate an average efflux sum of 560 g C m−2 yr−1 (SE=22 g C m−2 yr−1). An alternative model derived from the same data but using temperature alone as a driver over-estimated the annual flux sum by about 7% and showed less inter-annual variability. Given a likely shift in precipitation patterns alongside temperature changes under projected global change scenarios, these results demonstrate the necessity to include soil moisture in models that calculate the evolution of CO2 from temperate forest soils.  相似文献   

2.
Estimates of long-term landscape-scale N2O emissions for greenhouse gas inventories are complicated by large temporal and spatial variability. Much of this variability is likely caused by topographic effects on surface and subsurface water flows. We hypothesized that this variability could be explained as degassing events during anaerobic soil conditions and during transitions from anaerobic to aerobic soil conditions as controlled by precipitation and subsequent water redistribution in complex landscapes. We simulated degassing events in the ecosystem model ecosys run in three-dimensional mode to simulate a fertilized agricultural field with topographic variation derived from a digital terrain map. N2O emissions modelled from two areas within the field that had received 15.5 and 9.9 g N m−2 as urea in May 1998 were compared with those measured by micrometeorological flux towers during June and July 1998. Modelled N2O emissions during 1998 accounted for 2.3 and 2.0% of urea N applied at 15.5 and 9.9 g N m−2, respectively. Degassing events in the model coincided with a key N2O emission event measured in the field during several days after a rainfall in mid-June. During this event, modelled and measured surface fluxes rose rapidly to exceed 1 mg N m−2 h−1 for 2-3 d before declining. Emissions modelled concurrently at different topographic positions within the landscape during the emission event had coefficients of variation that varied over time between 30 and 180%. Much of the spatial variability in modelled emissions was attributed to temporal differences in the progression of emission events at different landscape positions caused by lateral water movement. The magnitude of temporal and spatial variability in N2O emissions suggests that aggregation of flux measurements to regional scales should be based upon sub-daily measurements at representative landscape positions, rather than upon less frequent measurements at individual sites as currently done. The use of three-dimensional ecosystem models with input from digital terrain maps may provide a means for such aggregation to be conducted.  相似文献   

3.
The importance of constraining the global budget of nitrous oxide (N2O) has been well established. The current global estimate of the contribution of N2O to total anthropogenic greenhouse gas emissions from agriculture is about 69%. Considerable progress has been made over the past few years in developing tools for quantifying the emissions from agricultural sources, at the local and field scale (i.e., chamber and tower-based measurements) as well as at the landscape and regional levels (i.e., aircraft-based measurement and modelling). However, aggregating these emissions over space and time remains a challenge because of the high degree of temporal and spatial variability. Emissions of N2O in temperate climate are largely event driven, e.g., in Eastern Canada, large emissions are observed right after snowmelt. The average emissions during the snowmelt period vary considerably, reflecting the influence of many controlling factors. Cumulative emissions reported here range from 0.05 kg N2O-N ha−1 in Western Canada to 1.26 kg N2O-N ha−1 in Eastern Canada, values that reflect differences in climatic zones and fertilizer management practices. This paper describes the tools for refining the global N2O budget and provides examples of measurements at various scales. Tower-based and aircraft measurement platforms provide good data for quantifying the variability associated with the measurements. Chamber-based methods lack the temporal and spatial resolution required to follow the event driven nature of N2O fluxes but provide valuable information for evaluating management practices. The model DeNitrification and DeComposition is an example of a technique to estimate N2O emissions when no data is available.  相似文献   

4.
为揭示亚热带森林土壤N2O排放对林分类型和氮添加的响应特征,选取位于福建省三明市的中亚热带米槠次生林、杉木人工林和马尾松人工林土壤为研究对象,分别设置无氮添加(N0 mg/kg)、低氮添加(N10 mg/kg)、中氮添加(N25 mg/kg)和高氮添加(N50 mg/kg)4个氮添加水平,进行微宇宙培养试验,测定土壤N2O排放。结果表明：与无氮添加处理相比,氮添加整体上降低3种林分土壤pH,增加土壤NH4+-N和NO3--N含量。无氮添加处理中杉木人工林和马尾松人工林土壤N2O累积排放量分别为9.67和9.62 mg/kg,显著高于米槠次生林土壤N2O累积排放量6.81 mg/kg。低氮添加处理中杉木人工林和马尾松人工林土壤N2O累积排放量显著高于米槠次生林。但在中氮和高氮添加处理中,3种林分土壤N2O累积排放量均无显著性差异。不同氮添加处理均促进3种林分土壤N  相似文献   

5.
Since N2O emissions cannot be measured easily at large scales, global emission estimates inevitably involve problems with scaling. To date, up-scaling processes depend highly on the models and database. Because of the limitation in resolution of the databases, which provide input parameters to drive the model's regional simulations, the uncertainties generated from the up-scaling processes must be quantified. In this paper, the uncertainties in up-scaling N2O emissions from the field scale (∼1 km2) to 1°×1° scale (∼10,000 km2) were quantified in a case study from the Xilin River basin of Inner Mongolia, China. A revised process-based DNDC model was applied in the study for quantifying N2O fluxes with a high-resolution (1 km2) soil database constructed with remote sensing data and GIS technique. The results showed that the uncertainties coming from spatial scaling effect is 63.6%, and from the partitioning of sensitive model parameter (SOC) is 86.4%. We found that inclusion of spatial heterogeneity of soil factors resulted in lower regional N2O emission estimates. Utilization of the spatial structural information based on soil type was more effective for reducing the spatial scaling effect in comparison with the variability information calculated from Monte Carlo method.  相似文献   

6.
Croplands are an important source of atmospheric methane (CH4) and nitrous oxide (N2O), both potent greenhouse gases. Reduction of cropland CH4 and N2O emissions is expected to mitigate climate change. However, large uncertainty remains in the assessment and prediction of these emissions, which prevents us from establishing appropriate mitigation options and strategies. The uncertainty is attributed mainly to the high spatiotemporal variability in emissions (e.g., emission spikes of N2O). Understanding and quantifying how hotspots of CH4 and N2O production in soil and then hot moments of their emissions occur would help reduce the uncertainty. This review focuses on soil–plant systems, particularly the rhizosphere, as possible hotspots of production and consumption of CH4 and N2O. It is well known that the rhizosphere controls CH4 emission strongly, though each process of production and consumption remains to be quantified. On the other hand, surprisingly little attention has been paid to N2O, besides the fact that plant roots strongly control nitrification and denitrification. We review the current knowledge of cropland CH4 and N2O emissions, and conclude that soil–plant interactions strongly affect cropland emissions of both gases, in which functions of plant roots affecting biogeochemical factors (e.g., availability of oxygen, labile organic carbon and inorganic nitrogen) in the rhizosphere and phenological changes are particularly important. In relation to the status of current knowledge, we discuss future research needed.  相似文献   

7.
农业土壤中的氧化亚氮排放: 为减排综述时空变化   总被引：3，自引：0，他引：3  
This short review deals with soils as an important source of the greenhouse gas N2O. The production and consumption of N2O in soils mainly involve biotic processes: the anaerobic process of denitrification and the aerobic process of nitrification. The factors that significantly influence agricultural N2O emissions mainly concern the agricultural practices (N application rate, crop type, fertilizer type) and soil conditions (soil moisture, soil organic C content, soil pH and texture). Large variability of N2O fluxes is known to occur both at different spatial and temporal scales. Currently new techniques could help to improve the capture of the spatial variability. Continuous measurement systems with automatic chambers could also help to capture temporal variability and consequently to improve quantification of N2O emissions by soils. Some attempts for mitigating soil N2O emissions, either by modifying agricultural practices or by managing soil microbial functioning taking into account the origin of the soil N2O emission variability, are reviewed.  相似文献   

8.
Abstract

Both nitrogen (N) deposition and biochar can affect the emissions of nitrous oxide (N2O), carbon dioxide (CO2) and ammonia (NH3) from different soils. Here, we have established a simulated wet N deposition experiment to investigate the effects of N deposition and biochar addition on N2O and CO2 emissions and NH3 volatilization from agricultural and forest soils. Repacked soil columns were subjected to six N deposition events over a 1-year period. N was applied at rates of 0 (N0), 60 (N60), and 120 (N120) kg Nh a?1 yr?1 without or with biochar (0 and 30 t ha?1 yr?1). For agricultural soil, adding N increased cumulative N2O emissions by 29.8% and 99.1% (p < 0.05) from the N60 and N120 treatments, respectively as compared to without N treatments, and N120 emitted 53.4% more (p < 0.05) N2O than the N60 treatment; NH3 volatilization increased by 33.6% and 91.9% (p < 0.05) from the N60 and N120 treatments, respectively, as compared to without N treatments, and N120 emitted 43.6% more (p < 0.05) NH3 than N60; cumulative CO2 emissions were not influenced by N addition. For forest soil, adding N significantly increased cumulative N2O emissions by 141.2% (p < 0.05) and 323.0% (p < 0.05) from N60 and N120 treatments, respectively, as compared to without N treatments, and N120 emitted 75.4% more (p < 0.05) N2O than N60; NH3 volatilization increased by 39.0% (p < 0.05) and 56.1% (p < 0.05) from the N60 and N120 treatments, respectively, as compared to without N treatments, and there was no obvious difference between N120 and N60 treatments; cumulative CO2 emissions were not influenced by N addition. Biochar amendment significantly (p < 0.05) decreased cumulative N2O emissions by 20.2% and 25.5% from agricultural and forest soils, respectively, and increased CO2 emissions slightly by 7.2% and NH3 volatilization obviously by 21.0% in the agricultural soil, while significantly decreasing CO2 emissions by 31.5% and NH3 volatilization by 22.5% in the forest soil. These results suggest that N deposition would strengthen N2O and NH3 emissions and have no effect on CO2 emissions in both soils, and treatments receiving the higher N rate at N120 emitted obviously more N2O and NH3 than the lower rate at N60. Under the simulated N deposition circumstances, biochar incorporation suppressed N2O emissions in both soils, and produced contrasting effects on CO2 and NH3 emissions, being enhanced in the agricultural soil while suppressed in the forest soil.  相似文献   

9.
N2O是重要的温室气体,了解福建省农业生态系统N2O排放情况及其年代变化规律,对于寻找减排的技术路线与对策,进而实现全国的控制目标有重要意义。本研究基于福建省农业活动水平数据,采用区域氮素循环模型IAP-N方法,估算1991—2010年福建省农业生态系统氧化亚氮(N2O)的排放量(以纯氮量计)并分析其排放特征。结果表明:(1)1991—2010年福建省农业生态系统N2O排放总量(包括农田直接、间接排放,田间秸秆燃烧排放,粪便管理系统排放)呈先增加后降低趋势,从1991年的23 675.3 t·a–1增加到2006年的32 610.4t·a–1,之后降低至30 810.7 t·a–1(2010年)。1991—1995年、1996—2000年、2001—2005年、2006—2010年农业生态系统年平均N2O排放量分别为26 170.7 t·a–1、29 870.0 t·a–1、32 085.8 t·a–1、31 287.6 t·a–1。各类型排放量大小依次为:农田直接(66.2%)-粪便管理系统(20.7%)-农田间接(12.9%)-田间秸秆燃烧(0.2%)。(2)1991—2010年,农田N2O直接排放量呈先增加后降低趋势,从1991年的15 108 t·a–1增加到2006年的21 547 t·a–1,之后下降到2010年的20 594 t·a–1。4个时期年平均N2O直接排放量分别为17 073.0 t·a–1、19 976.8 t·a–1、21 183.4 t·a–1、20 778.6 t·a–1。农田旱作(包括蔬菜地、非蔬菜旱地、水旱轮作的旱季)N2O排放占农田N2O直接排放量的83.0%~90.7%,是农田直接排放的关键源。(3)1991—2010年间,福建省粪便管理系统N2O排放量保持在5 213.2~6 988.0 t·a–1,变化较稳定。粪便管理系统N2O排放的关键源为猪,占粪便管理系统N2O排放量的57.4%~67.9%。(4)2010年,农业生态系统N2O排放高值区主要分布在漳州市、南平市、泉州市和宁德市,其N2O排放量均在4 000 t·a–1以上,占全省总排放量的61.7%,应优先考虑削减这些地区的N2O排放。研究结果为决策者合理利用肥料,制定福建省农业生态系统温室气体减排措施提供科学依据。  相似文献   

10.
The chemometric calibration of near‐infrared Fourier‐transform Raman (NIR‐FT/Raman) spectroscopy was investigated for the purpose of providing a rigorous spectroscopic technique to analyze rice flour for protein and apparent amylose content. Ninety rice samples from a 1996 collection of short, medium, and long grain rice grown in four states of the United States, as well as Taiwan, Korea, and Australia were investigated. Milled rice flour samples were scanned in rotating cups with a 1,064 nm (NIR) excitation laser using 500 mW of power. Raman scatter was collected using a liquid N2 cooled Ge detector over the Raman shift range of 175–3,600 cm‐1. The spectral data was preprocessed using baseline correction with and without derivatives or with derivatives alone and normalization. Nearly equivalent results were obtained using all of the preprocessing methods with partial least squares (PLS) models. However, models using baseline correction and normalization of the entire spectrum, without derivatives, showed slightly better performance based on the criteria of highest r2 and the lowest SEP with low bias. Calibration samples (n = 57) and validation samples (n = 33) were chosen to have similar respective distributions for protein and apparent amylose. The best model for protein was obtained using six factors giving r2 = 0.992, SEP = 0.138%, and bias = ‐0.009%. The best model for apparent amylose was obtained using eight factors giving r2 = 0.985, SEP = 1.05%, and bias = ‐0.006%.  相似文献   

11.
Nitrous oxide (N2O) emissions from the soil surface of five different forest types in Thailand were measured using the closed chamber method. Soil samples were also taken to study the N2O production pathways. The monthly average emissions (±SD, n?=?12) of N2O from dry evergreen forest (DEF), hill evergreen forest (HEF), moist evergreen forest (MEF), mixed deciduous forest (MDF) and acacia reforestation (ARF) were 13.0?±?8.2, 5.7?±?7.1, 1.2?±?12.1, 7.3?±?8.5 and 16.7?±?9.2?µg N m?2 h?1, respectively. Large seasonal variations in fluxes were observed. Emission was relatively higher during the wet season than during the dry season, indicating that soil moisture and denitrification were probably the main controlling factors. Net N2O uptake was also observed occasionally. Laboratory studies were conducted to further investigate the influence of moisture and the N2O production pathways. Production rates at 30% water holding capacity (WHC) were 3.9?±?0.2, 0.5?±?0.06 and 0.87?±?0.01?ng N2O-nitrogen (N) g-dw?1day?1 in DEF, HEF and MEF respectively. At 60% WHC, N2O production rates in DEF, HEF and MEF soils increased by factors of 68, 9 and 502, respectively. Denitrification was found to be the main N2O production pathway in these soils except in MEF.  相似文献   

12.
Hierarchical Bayesian (HB) methods are useful tools for modeling multifaceted, nonlinear phenomena such as those encountered in ecology, and have been increasingly applied in environmental sciences, e.g., to estimate soil gas flux from different soil textures or sites. We have developed a model of soil carbon dioxide (CO2) flux based on soil temperature (T, 5 cm depth) and water-filled pore space (WFPS, 5 cm depth) using HB theory. The HB model was calibrated using a dataset of CO2 flux measured from bare soils belonging to four texture classes in 14 upland field sites in a watershed in central Hokkaido, Japan, in the nonsnow-cover season from 2003 to 2011. The numerical software HYDRUS-1D was used to simulate daily WFPS, and the estimated values were significantly correlated with the measured WFPS (R2 = 0.68, P < 0.001). Compared to a nonhierarchical Bayesian model (Bayesian pooled model), the CO2 predictions with the HB model more accurately represented texture-specific observations. The simulation–observation fit of the CO2 flux model was R2 = 0.64 (P < 0.001). More than 90% of the observed daily data were within the 95% confidence interval. The HB model exhibited high uncertainty for high CO2 flux values. The HB model calibration revealed differing sensitivity of CO2 flux to T and WFPS in different soil texture classes. CO2 flux increased with an increase in T, and it increased to a lesser degree with a finer texture, possibly because the clay and silt facilitated soil aggregation, thus reducing temperature fluctuations. WFPS values between 0.48 and 0.64 resulted in optimal conditions for CO2 flux. The minimum WFPS value increased with an increase in clay content (P < 0.05). Although only a small number of soil types were studied in only one season in this study, the HB model may provide a method for predicting how the effects of soil temperature and moisture on CO2 flux change with texture, and soil texture could be regarded as an upscaling factor in future research on regional extrapolation.  相似文献   

13.
In boreal forests, canopy-scale emissions of biogenic volatile organic compounds (BVOCs) are rather well characterised, but knowledge of ecosystem-scale BVOC emissions is still inadequate. We used adsorbent tubes to measure BVOCs from a boreal Scots pine (Pinus sylvestris L.) forest floor in southern Finland and analysed the compounds with a gas chromatograph-mass spectrometer. The most abundant compound group was the monoterpenes (averaging 5.04 μg m−2 h−1), in which α-pinene, Δ3-carene and camphene contributed over 90% of the emissions. Emissions of other terpenoids (isoprene and sesquiterpenes) were low (averaging 0.05 and 0.04 μg m−2 h−1, respectively). BVOC emissions from the forest floor varied seasonally, peaking in early summer and autumn, with most of the compounds following similar patterns. The emission pattern was sustained throughout the measurement period, suggesting that the main sources of the emissions remained more or less stable. We compared the BVOC fluxes with environmental parameters such as temperature, precipitation and PAR, and with fluxes of other trace gases (CO2, CH4, N2O), as well as with ground vegetation photosynthesis and with litter input. Several of these parameters were correlated with the presence of BVOCs. The sources of soil BVOC emissions are very poorly understood, but our results suggest, that changes in litter quantity and quality, soil microbial activity and the physiological stages of plants are linked with changes in BVOC fluxes.  相似文献   

14.
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15.
The potential impact of climate change on forest distribution in Sri Lanka was evaluated. The Holdridge Life Zone Classification was used along with current climate and climate change scenarios derived from two general circulation models, the Geophysical Fluid Dynamics Laboratory model and the Canadian Climate Centre Model, at a 0.5° × 0.5° resolution. Current and future distributions of life zones were mapped with a Geographic Information System. These maps were then used to calculate the extent of the impact areas for the climate change scenarios. The current distribution pattern of forest vegetation includes tropical very dry forest (6%), tropical dry forest (56%), and tropical wet forest (38%). Results obtained using the Geophysical Fluid Dynamics Laboratory model show an increase in tropical dry forest (8%) and decrease in tropical wet forest (2%). The Canadian Climate Centre Model scenario predicted an increase in tropical very dry forest (5%) and tropical dry forest (7%), and a decrease in tropical wet forest (11 %). Both models predicted a northward shift of tropical wet forest into areas currently occupied by tropical dry forest. The application of general circulation models such as the Geophysical Fluid Dynamics Laboratory model and the Canadian Climate Centre Model, as well as the Holdridge Life Zone Classification, to estimate the effect of climate change on Sri Lankan forests in this paper indicates that these methods are suitable as a tool for such investigations in Sri Lanka.  相似文献   

16.
Abstract

Nitrous oxide (N2O) emissions were measured monthly over 1 year in three ecosystems on tropical peatland of Sarawak, Malaysia, using a closed-chamber technique. The three ecosystems investigated were mixed peat swamp forest, sago (Metroxylon sagu) and oil palm (Elaeis guineensis) plantations. The highest annual N2O emissions were observed in the sago ecosystem with a production rate of 3.3 kg N ha?1 year?1, followed by the oil palm ecosystem at 1.2 kg N ha?1 year?1 and the forest ecosystem at 0.7 kg N ha?1 year?1. The N2O emissions ranged from –3.4 to 19.7 µg N m?2 h?1 for the forest ecosystem, from 1.0 to 176.3 µg N m?2 h?1 for the sago ecosystem and from 0.9 to 58.4 µg N m?2 h?1 for the oil palm ecosystem. Multiple regression analysis showed that N2O production in each ecosystem was regulated by different variables. The key factors influencing N2O emissions in the forest ecosystem were the water table and the NH+ 4 concentration at 25–50 cm, soil temperature at 5 cm and nitrate concentration at 0–25 cm in the sago ecosystem, and water-filled pore space, soil temperature at 5 cm and NH+ 4 concentrations at 0–25 cm in the oil palm ecosystem. R2 values for the above regression equations were 0.57, 0.63 and 0.48 for forest, sago and oil palm, respectively. The results suggest that the conversion of tropical peat swamp forest to agricultural crops, which causes substantial changes to the environment and soil properties, will significantly affect the exchange of N2O between the tropical peatland and the atmosphere. Thus, the estimation of net N2O production from tropical peatland for the global N2O budget should take into consideration ecosystem type.  相似文献   

17.
基于DNDC模型的东北地区春玉米农田固碳减排措施研究   总被引：6，自引：1，他引：5  
春玉米是我国东北地区主要粮食作物,但由于连年耕作和氮肥的高投入,春玉米农田也可能成为重要的温室气体排放源。因此,通过优化田间管理措施在保证作物产量的同时实现固碳减排,对于春玉米种植系统的可持续发展具有重要意义。过程模型（Denitrification Decomposition, DNDC）是评估固碳减排措施的有效工具,本研究在对DNDC模型进行验证的基础上,应用模型研究不同施氮和秸秆还田措施对东北地区春玉米农田固碳和氧化亚氮（N2O）排放的长期综合影响。模型验证结果表明,DNDC模拟的不同处理下土壤呼吸季节总量、 N2O排放季节总量和春玉米产量与田间观测结果较一致;同时模型也能较好地模拟不同处理下土壤呼吸和N2O排放季节变化动态。这表明DNDC模型能较理想地模拟不同施氮和秸秆还田措施对春玉米农田土壤呼吸、 N2O排放和作物产量的影响。利用模型综合分析不同管理情景对产量和土壤固碳减排的长期影响,结果表明: 1）与当地农民习惯施肥相比,优化施氮措施不会明显影响作物产量,能减少N2O排放,且对土壤固碳影响很小,因而能降低温室气体净排放,但净排放降低幅度有限（8%~13%）; 2）在优化施氮措施的同时秸秆还田能在保障供试农田春玉米产量的同时大幅度减少春玉米种植系统温室气体净排放,甚至可能将供试农田由温室气体排放源转变为温室气体吸收汇。本研究结果可为优化管理措施实现春玉米种植系统固碳减排提供科学依据。  相似文献   

18.
Understanding the greenhouse gas(GHG)emission from rice paddy fields is essential to come up with appropriate countermeasure in response to global warming.However,GHG emissions from paddy fields in South Korea are not well characterized.The objectives of this study were to estimate the carbon dioxide(CO2)and methane(CH4)emissions from rice paddy fields in South Korea,under the Representative Concentration Pathway 8.5(RCP-8.5)climate change scenario using the DNDC(i.e.,DeNitrification-DeComposition)model at 1-km2resolution.The performance of the model was verified with field data collected using a closed chamber,which supports the application of the model to South Korea.Both the model predictions and field measurements showed that most(>95%)GHG emissions occur in the cropping period,between April and October.As a baseline(assuming no climate change),the national sums of the CO2and CH4emissions for the 2020 s and 2090 s were estimated to be 5.8×106and 6.0×106t CO2-equivalents(CO2-eq)year-1for CO2and 6.4×106and 6.6×106t CO2-eq year-1for CH4,respectively,indicating no significant changes over 80 years.Under RCP-8.5,in the 2090 s,CH4emissions were predicted to increase by 10.7×106and 14.9×106t CO2-eq year-1,for a 10-or 30-cm tillage depth,respectively.However,the CO2emissions gradually decreased with rising temperatures,due to reduced root respiration.Deep tillage increased the emissions of both GHGs,with a more pronounced effect for CH4than CO2.Intermittent drainage in the middle of the cropping season can attenuate the CH4emissions from paddy fields.The findings of this work will aid in developing nationwide policies on agricultural land management in the face of climate change.  相似文献   

19.
Artificial urine, an aqueous solution of various nitrogenous compounds and salts, is routinely used in soil incubation studies on nitrous oxide (N2O) emissions and related nitrogen (N) and pH dynamics. There is, however, no consensus on artificial urine composition, and a wide variety of compositions are used. The aim of this study was to test which artificial urine composition is adequate for simulating N2O fluxes, respiration, soil mineral N and pH dynamics of real cattle urine in both short- and long-term incubation studies. Urine solutions of differing compositions were applied to a sandy soil and incubated for 65 days, and results of measurements on N2O fluxes and soil mineral N were analyzed over the first 5 days as well as over the whole incubation period. Results from two real cattle urines with known nitrogenous composition (R1 and R2) were compared with three artificial urine types: (i) urea+glycine (AG), (ii) urea+hippuric acid (AH) and (iii) an artificial urine identical to the nitrogenous composition of real urine R1 (AR). During the first 5 days, only cumulative N2O emissions for AG deviated significantly (P=0.02) from the N2O emissions for real urines, with 0.4% of applied N emitted compared with 0.0% and 0.1% for R1 and R2, respectively. Respiration from R1 was significantly (P<0.001) higher than from R2 and all artificial urines. Over the whole incubation period, no significant differences could be detected for N2O emissions or respiration with urine type. From all artificial urine types, AH yielded N2O emissions closest to those from real urine. AG deviated most from real urine, both in short- and long-term incubations. Over the whole period, soil NH4+ was higher for all artificial urines (P<0.001) and pH-KCl was lower for AG and AR (P=0.004) than for the real urines. AH was not significantly different from real urine R2 with respect to all measured properties except soil NH4+. We conclude that only AG did not adequately simulate N2O emissions, and that glycine is therefore not an appropriate substitution for hippuric acid in artificial urine. For future studies using artificial urine we recommend therefore a mixture containing at least urea and hippuric acid as sources of N. As no artificial urine composition resembled real urine with respect to all measured variables, even when nitrogenous composition was identical (AR), we recommend the use of real urines whenever possible.  相似文献   

20.
Abstract

Nitrous oxide (N2O) contributes to global climate change, and its emission from soil–crop systems depend on soil, environmental, and anthropogenic factors. Thus, we evaluated the variability of N2O emissions measured by microchambers (cross section: 184 cm2) from a groundnut–fallow–maize–fallow cropping system of the humid tropics. The crops received inorganic nitrogen (N) plus crop residues (NC), inorganic N alone as ammonium sulfate (RN), and half of the inorganic N along with crop residues and chicken manure (N1/2CM), amounting for the crop rotation to 322, 180, and 400 kg N ha?1 yr?1, respectively. The N2O fluxes during the groundnut–maize crop rotation were log‐normally distributed, and the frequency distributions were positively skewed. Daytime changes in N2O fluxes were inconsistent, and the 50% of total N2O emission during the 12 h measurement periods was attained earlier under maize (～11∶00 h) than groundnut covers (～13∶00 h). Spatial variability in each treatment with eight gas chambers was large but smaller during the cropping periods than the fallow, indicating masking efficiency of crop covers for the soil heterogeneity that was accelerated presumably by antecedent climatic variables. The temporal variability of N2O emissions was also large (coefficients of variation, CV, ranged from 60 to 81%), involving both input differences between treatments and measurement periods. As such, the relative deviation from the annual mean of total N2O emission was high during the period after a large N application with a maximum of +480%, due to addition of chicken manure. The seasonal contribution of summer and monsoon to N2O emissions was insignificant. However, intensive rainfall negatively (?0.65**) and the amount of added N from either source positively (0.83***) correlated with the integrated N2O emissions, and those were exponential. Results suggest that around noon (12∶00 h) gas collection could represent well the daily N2O fluxes, increasing the number or size of the gas chambers could minimize the large variability, and mainly the rainfall and N inputs regulated its emissions in the humid tropics of Malaysia.  相似文献   

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