951 resultados para Nitrous oxide (N2O)
Resumo:
The assimilation and regeneration of dissolved inorganic nitrogen, and the concentration of N2O, was investigated at stations located in the NW European shelf sea during June/July 2011. These observational measurements within the photic zone demonstrated the simultaneous regeneration and assimilation of NH4+, NO2- and NO3-. NH4+ was assimilated at 1.82-49.12 nmol N/L/h and regenerated at 3.46-14.60 nmol N/L/h; NO2- was assimilated at 0-2.08 nmol N/L/h and regenerated at 0.01-1.85 nmol N/L/h; NO3-was assimilated at 0.67-18.75 nmol N/L/h and regenerated at 0.05-28.97 nmol N/L/h. Observations implied that these processes were closely coupled at the regional scale and that nitrogen recycling played an important role in sustaining phytoplankton growth during the summer. The [N2O], measured in water column profiles, was 10.13 ± 1.11 nmol/L and did not strongly diverge from atmospheric equilibrium indicating that sampled marine regions were neither a strong source nor sink of N2O to the atmosphere. Multivariate analysis of data describing water column biogeochemistry and its links to N-cycling activity failed to explain the observed variance in rates of N-regeneration and N-assimilation, possibly due to the limited number of process rate observations. In the surface waters of five further stations, ocean acidification (OA) bioassay experiments were conducted to investigate the response of NH4+ oxidising and regenerating organisms to simulated OA conditions, including the implications for [N2O]. Multivariate analysis was undertaken which considered the complete bioassay data set of measured variables describing changes in N-regeneration rate, [N2O] and the biogeochemical composition of seawater. While anticipating biogeochemical differences between locations, we aimed to test the hypothesis that the underlying mechanism through which pelagic N-regeneration responded to simulated OA conditions was independent of location. Our objective was to develop a mechanistic understanding of how NH4+ regeneration, NH4+ oxidation and N2O production responded to OA. Results indicated that N-regeneration process responses to OA treatments were location specific; no mechanistic understanding of how N-regeneration processes respond to OA in the surface ocean of the NW European shelf sea could be developed.
Resumo:
Nitrous oxide emissions from a network of agricultural experiments in Europe were used to explore the relative importance of site and management controls of emissions. At each site, a selection of management interventions were compared within replicated experimental designs in plot-based experiments. Arable experiments were conducted at Beano in Italy, El Encin in Spain, Foulum in Denmark, Logarden in Sweden, Maulde in Belgium CE1, Paulinenaue in Germany, and Tulloch in the UK. Grassland experiments were conducted at Crichton, Nafferton and Peaknaze in the UK, Godollo in Hungary, Rzecin in Poland, Zarnekow in Germany and Theix in France. Nitrous oxide emissions were measured at each site over a period of at least two years using static chambers. Emissions varied widely between sites and as a result of manipulation treatments. Average site emissions (throughout the study period) varied between 0.04 and 21.21 kg N2O-N ha−1yr−1, with the largest fluxes and variability associated with the grassland sites. Total nitrogen addition was found to be the single most important deter- minant of emissions, accounting for 15 % of the variance (using linear regression) in the data from the arable sites (p<0.0001), and 77 % in the grassland sites. The annual emissions from arable sites were significantly greater than those that would be predicted by IPCC default emission fac- tors. Variability of N2O emissions within sites that occurred as a result of manipulation treatments was greater than that resulting from site-to-site and year-to-year variation, highlighting the importance of management interventions in contributing to greenhouse gas mitigation
Resumo:
The lead author, Nimai Senapati (Post doc), was funded by the European community’s Seventh Framework programme (FP2012-2015) under grant agreement no. 262060 (ExpeER). The research leading to these results has received funding principally from the ANR (ANR-11-INBS-0001), AllEnvi, CNRS-INSU. We would like to thank the National Research Infrastructure ‘Agro-écosystèmes, Cycles Biogéochimique et Biodiversité (SOERE-ACBB http://www.soere-acbb.com/fr/) for their support in field experiment. We are deeply indebted to Christophe deBerranger, Xavier Charrier for their substantial technical assistance and Patricia Laville for her valuables suggestion regarding N2O flux estimation.
Resumo:
Nitrous oxide (N2O) is primarily produced by the microbially-mediated nitrification and denitrification processes in soils. It is influenced by a suite of climate (i.e. temperature and rainfall) and soil (physical and chemical) variables, interacting soil and plant nitrogen (N) transformations (either competing or supplying substrates) as well as land management practices. It is not surprising that N2O emissions are highly variable both spatially and temporally. Computer simulation models, which can integrate all of these variables, are required for the complex task of providing quantitative determinations of N2O emissions. Numerous simulation models have been developed to predict N2O production. Each model has its own philosophy in constructing simulation components as well as performance strengths. The models range from those that attempt to comprehensively simulate all soil processes to more empirical approaches requiring minimal input data. These N2O simulation models can be classified into three categories: laboratory, field and regional/global levels. Process-based field-scale N2O simulation models, which simulate whole agroecosystems and can be used to develop N2O mitigation measures, are the most widely used. The current challenge is how to scale up the relatively more robust field-scale model to catchment, regional and national scales. This paper reviews the development history, main construction components, strengths, limitations and applications of N2O emissions models, which have been published in the literature. The three scale levels are considered and the current knowledge gaps and challenges in modelling N2O emissions from soils are discussed.
Resumo:
Irrigation is known to stimulate soil microbial carbon and nitrogen turnover and potentially the emissions of nitrous oxide (N2O) and carbon dioxide (CO2). We conducted a study to evaluate the effect of three different irrigation intensities on soil N2O and CO2 fluxes and to determine if irrigation management can be used to mitigate N2O emissions from irrigated cotton on black vertisols in South-Eastern Queensland, Australia. Fluxes were measured over the entire 2009/2010 cotton growing season with a fully automated chamber system that measured emissions on a sub-daily basis. Irrigation intensity had a significant effect on CO2 emission. More frequent irrigation stimulated soil respiration and seasonal CO2 fluxes ranged from 2.7 to 4.1 Mg-C ha−1 for the treatments with the lowest and highest irrigation frequency, respectively. N2O emission happened episodic with highest emissions when heavy rainfall or irrigation coincided with elevated soil mineral N levels and seasonal emissions ranged from 0.80 to 1.07 kg N2O-N ha−1 for the different treatments. Emission factors (EF = proportion of N fertilizer emitted as N2O) over the cotton cropping season, uncorrected for background emissions, ranged from 0.40 to 0.53 % of total N applied for the different treatments. There was no significant effect of the different irrigation treatments on soil N2O fluxes because highest emission happened in all treatments following heavy rainfall caused by a series of summer thunderstorms which overrode the effect of the irrigation treatment. However, higher irrigation intensity increased the cotton yield and therefore reduced the N2O intensity (N2O emission per lint yield) of this cropping system. Our data suggest that there is only limited scope to reduce absolute N2O emissions by different irrigation intensities in irrigated cotton systems with summer dominated rainfall. However, the significant impact of the irrigation treatments on the N2O intensity clearly shows that irrigation can easily be used to optimize the N2O intensity of such a system.
Resumo:
Nitrous oxide is a major greenhouse gas emission. The aim of this research was to develop and apply statistical models to characterize the complex spatial and temporal variation in nitrous oxide emissions from soils under different land use conditions. This is critical when developing site-specific management plans to reduce nitrous oxide emissions. These studies can improve predictions and increase our understanding of environmental factors that influence nitrous oxide emissions. They also help to identify areas for future research, which can further improve the prediction of nitrous oxide in practice.
Resumo:
Soil-based emissions of nitrous oxide (N2O), a well-known greenhouse gas, have been associated with changes in soil water-filled pore space (WFPS) and soil temperature in many previous studies. However, it is acknowledged that the environment-N2O relationship is complex and still relatively poorly unknown. In this article, we employed a Bayesian model selection approach (Reversible jump Markov chain Monte Carlo) to develop a data-informed model of the relationship between daily N2O emissions and daily WFPS and soil temperature measurements between March 2007 and February 2009 from a soil under pasture in Queensland, Australia, taking seasonal factors and time-lagged effects into account. The model indicates a very strong relationship between a hybrid seasonal structure and daily N2O emission, with the latter substantially increased in summer. Given the other variables in the model, daily soil WFPS, lagged by a week, had a negative influence on daily N2O; there was evidence of a nonlinear positive relationship between daily soil WFPS and daily N2O emission; and daily soil temperature tended to have a linear positive relationship with daily N2O emission when daily soil temperature was above a threshold of approximately 19°C. We suggest that this flexible Bayesian modeling approach could facilitate greater understanding of the shape of the covariate-N2O flux relation and detection of effect thresholds in the natural temporal variation of environmental variables on N2O emission.
Resumo:
Application of poultry litter (PL) to soil can lead to substantial nitrous oxide (N2O) emissions due to the co-application of labile carbon (C) and nitrogen (N). Slow pyrolysis of PL to produce biochar may mitigate N2O emissions from this source, whilst still providing agronomic benefits. In a corn crop on ferrosol with similarly matched available N inputs of ca. 116 kg N/ha, PL-biochar plus urea emitted significantly less N2O (1.5 kg N2O-N/ha) compared to raw PL at 4.9 kg N2O-N/ha. Urea amendment without the PL-biochar emitted 1.2 kg N2O-N/ha, and the PL-biochar alone emitted only 0.35 kg N2O-N/ha. Both PL and PL-biochar resulted in similar corn yields and total N uptake which was significantly greater than for urea alone. Using stable isotope methodology, the majority (~ 80%) of N2O emissions were shown to be from non-urea sources. Amendment with raw PL significantly increased C mineralisation and the quantity of permanganate oxidisable organic C. The low molar H/C (0.49) and O/C (0.16) ratios of the PL-biochar suggest its higher stability in soil than raw PL. The PL-biochar also had higher P and K fertiliser value than raw PL. This study suggests that PL-biochar is a valuable soil amendment with the potential to significantly reduce emissions of soil greenhouse gases compared to the raw product. Contrary to other studies, PL-biochar incorporated to 100 mm did not reduce N2O emissions from surface applied urea, which suggests that further field evaluation of biochar impacts, and methods of application of both biochar and fertiliser, are needed.
Resumo:
Nitrous oxide (N2O) is one of the greenhouse gases that can contribute to global warming. Spatial variability of N2O can lead to large uncertainties in prediction. However, previous studies have often ignored the spatial dependency to quantify the N2O - environmental factors relationships. Few researches have examined the impacts of various spatial correlation structures (e.g. independence, distance-based and neighbourhood based) on spatial prediction of N2O emissions. This study aimed to assess the impact of three spatial correlation structures on spatial predictions and calibrate the spatial prediction using Bayesian model averaging (BMA) based on replicated, irregular point-referenced data. The data were measured in 17 chambers randomly placed across a 271 m(2) field between October 2007 and September 2008 in the southeast of Australia. We used a Bayesian geostatistical model and a Bayesian spatial conditional autoregressive (CAR) model to investigate and accommodate spatial dependency, and to estimate the effects of environmental variables on N2O emissions across the study site. We compared these with a Bayesian regression model with independent errors. The three approaches resulted in different derived maps of spatial prediction of N2O emissions. We found that incorporating spatial dependency in the model not only substantially improved predictions of N2O emission from soil, but also better quantified uncertainties of soil parameters in the study. The hybrid model structure obtained by BMA improved the accuracy of spatial prediction of N2O emissions across this study region.
Resumo:
Microbial respiratory reduction of nitrous oxide (N2O) to dinitrogen (N2) via denitrification plays a key role within the global N-cycle since it is the most important process for converting reactive nitrogen back into inert molecular N2. However, due to methodological constraints, we still lack a comprehensive, quantitative understanding of denitrification rates and controlling factors across various ecosystems. We investigated N2, N2O and NO emissions from irrigated cotton fields within the Aral Sera Basin using the He/O2 atmosphere gas flow soil core technique and an incubation assay. NH4NO3 fertilizer, equivalent to 75 kg ha−1 and irrigation water, adjusting the water holding capacity to 70, 100 and 130% were applied to the incubation vessels to assess its influence on gaseous N emissions. Under soil conditions as they are naturally found after concomitant irrigation and fertilization, denitrification was the dominant process and N2 the main end product of denitrification. The mean ratios of N2/N2O emissions increased with increasing soil moisture content. N2 emissions exceeded N2O emissions by a factor of 5 ± 2 at 70% soil water holding capacity (WHC) and a factor of 55 ± 27 at 130% WHC. The mean ratios of N2O/NO emissions varied between 1.5 ± 0.4 (70% WHC) and 644 ± 108 (130% WHC). The magnitude of N2 emissions for irrigated cotton was estimated to be in the range of 24 ± 9 to 175 ± 65 kg-N ha−1season−1, while emissions of NO were only of minor importance (between 0.1 to 0.7 kg-N ha−1 season−1). The findings demonstrate that for irrigated dryland soils in the Aral Sera Basin, denitrification is a major pathway of N-loss and that substantial amounts of N-fertilizer are lost as N2 to the atmosphere for irrigated dryland soils.
Resumo:
This is the first study to investigate alternative fertilisation strategies to increase cereal production while reducing greenhouse gas emissions from the most common soil type in subtropical regions. The results of this research will contribute to define future farming practices to achieve global food security and mitigate climate change. The study established that introducing legumes in cropping systems is the most agronomically viable and environmentally sustainable fertilisation strategy. Importantly, this strategy can be widely adopted in subtropical regions since it is economically accessible, requires little know-how transfer and technology investment, and can be profitable in both low- and high-input cropping systems.