451 resultados para Methane emissions modeling

em Queensland University of Technology - ePrints Archive


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It is widely recognised that defining trade-offs between greenhouse gas emissions using ‘emission equivalence’ based on global warming potentials (GWPs) referenced to carbon dioxide produces anomalous results when applied to methane. The short atmospheric lifetime of methane, compared to the timescales of CO2 uptake, leads to the greenhouse warming depending strongly on the temporal pattern of emission substitution. We argue that a more appropriate way to consider the relationship between the warming effects of methane and carbon dioxide is to define a ‘mixed metric’ that compares ongoing methane emissions (or reductions) to one-off emissions (or reductions) of carbon dioxide. Quantifying this approach, we propose that a one-off sequestration of 1 t of carbon would offset an ongoing methane emission in the range 0.90–1.05 kg CH4 per year. We present an example of how our approach would apply to rangeland cattle production, and consider the broader context of mitigation of climate change, noting the reverse trade-off would raise significant challenges in managing the risk of non-compliance. Our analysis is consistent with other approaches to addressing the criticisms of GWP-based emission equivalence, but provides a simpler and more robust approach while still achieving close equivalence of climate mitigation outcomes ranging over decadal to multi-century timescales.

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If the land sector is to make significant contributions to mitigating anthropogenic greenhouse gas (GHG) emissions in coming decades, it must do so while concurrently expanding production of food and fiber. In our view, mathematical modeling will be required to provide scientific guidance to meet this challenge. In order to be useful in GHG mitigation policy measures, models must simultaneously meet scientific, software engineering, and human capacity requirements. They can be used to understand GHG fluxes, to evaluate proposed GHG mitigation actions, and to predict and monitor the effects of specific actions; the latter applications require a change in mindset that has parallels with the shift from research modeling to decision support. We compare and contrast 6 agro-ecosystem models (FullCAM, DayCent, DNDC, APSIM, WNMM, and AgMod), chosen because they are used in Australian agriculture and forestry. Underlying structural similarities in the representations of carbon flows though plants and soils in these models are complemented by a diverse range of emphases and approaches to the subprocesses within the agro-ecosystem. None of these agro-ecosystem models handles all land sector GHG fluxes, and considerable model-based uncertainty exists for soil C fluxes and enteric methane emissions. The models also show diverse approaches to the initialisation of model simulations, software implementation, distribution, licensing, and software quality assurance; each of these will differentially affect their usefulness for policy-driven GHG mitigation prediction and monitoring. Specific requirements imposed on the use of models by Australian mitigation policy settings are discussed, and areas for further scientific development of agro-ecosystem models for use in GHG mitigation policy are proposed.

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Accurately quantifying total freshwater storage methane release to atmosphere requires the spatial–temporal measurement of both diffusive and ebullitive emissions. Existing floating chamber techniques provide localised assessment of methane flux, however, significant errors can arise when weighting and extrapolation to the entire storage, particularly when ebullition is significant. An improved technique has been developed that compliments traditional chamber based experiments to quantify the storage-scale release of methane gas to atmosphere through ebullition using the measurements from an Optical Methane Detector (OMD) and a robotic boat. This provides a conservative estimate of the methane emission rate from ebullition along with the bubble volume distribution. It also georeferences the area of ebullition activity across entire storages at short temporal scales. An assessment on Little Nerang Dam in Queensland, Australia, demonstrated whole storage methane release significantly differed spatially and throughout the day. Total methane emission estimates showed a potential 32-fold variation in whole-of-dam rates depending on the measurement and extrapolation method and time of day used. The combined chamber and OMD technique showed that 1.8–7.0% of the surface area of Little Nerang Dam is accounting for up to 97% of total methane release to atmosphere throughout the day. Additionally, over 95% of detectable ebullition occurred in depths less than 12 m during the day and 6 m at night. This difference in spatial and temporal methane release rate distribution highlights the need to monitor significant regions of, if not the entire, water storage in order to provide an accurate estimate of ebullition rates and their contribution to annual methane emissions.

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Agriculture is responsible for a significant proportion of total anthropogenic greenhouse gas emissions (perhaps 18% globally), and therefore has the potential to contribute to efforts to reduce emissions as a means of minimising the risk of dangerous climate change. The largest contributions to emissions are attributed to ruminant methane production and nitrous oxide from animal waste and fertilised soils. Further, livestock, including ruminants, are an important component of global and Australian food production and there is a growing demand for animal protein sources. At the same time as governments and the community strengthen objectives to reduce greenhouse gas emissions, there are growing concerns about global food security. This paper provides an overview of a number of options for reducing methane and nitrous oxide emissions from ruminant production systems in Australia, while maintaining productivity to contribute to both objectives. Options include strategies for feed modification, animal breeding and herd management, rumen manipulation and animal waste and fertiliser management. Using currently available strategies, some reductions in emissions can be achieved, but practical commercially available techniques for significant reductions in methane emissions, particularly from extensive livestock production systems, will require greater time and resource investment. Decreases in the levels of emissions from these ruminant systems (i.e., the amount of emissions per unit of product such as meat) have already been achieved. However, the technology has not yet been developed for eliminating production of methane from the rumen of cattle and sheep digesting the cellulose and lignin-rich grasses that make up a large part of the diet of animals grazing natural pastures, particularly in arid and semi-arid grazing lands. Nevertheless, the abatement that can be achieved will contribute significantly towards reaching greenhouse gas emissions reduction targets and research will achieve further advances.

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Water to air methane emissions from freshwater reservoirs can be dominated by sediment bubbling (ebullitive) events. Previous work to quantify methane bubbling from a number of Australian sub-tropical reservoirs has shown that this can contribute as much as 95% of total emissions. These bubbling events are controlled by a variety of different factors including water depth, surface and internal waves, wind seiching, atmospheric pressure changes and water levels changes. Key to quantifying the magnitude of this emission pathway is estimating both the bubbling rate as well as the areal extent of bubbling. Both bubbling rate and areal extent are seldom constant and require persistent monitoring over extended time periods before true estimates can be generated. In this paper we present a novel system for persistent monitoring of both bubbling rate and areal extent using multiple robotic surface chambers and adaptive sampling (grazing) algorithms to automate the quantification process. Individual chambers are self-propelled and guided and communicate between each other without the need for supervised control. They can maintain station at a sampling site for a desired incubation period and continuously monitor, record and report fluxes during the incubation. To exploit the methane sensor detection capabilities, the chamber can be automatically lowered to decrease the head-space and increase concentration. The grazing algorithms assign a hierarchical order to chambers within a preselected zone. Chambers then converge on the individual recording the highest 15 minute bubbling rate. Individuals maintain a specified distance apart from each other during each sampling period before all individuals are then required to move to different locations based on a sampling algorithm (systematic or adaptive) exploiting prior measurements. This system has been field tested on a large-scale subtropical reservoir, Little Nerang Dam, and over monthly timescales. Using this technique, localised bubbling zones on the water storage were found to produce over 50,000 mg m-2 d-1 and the areal extent ranged from 1.8 to 7% of the total reservoir area. The drivers behind these changes as well as lessons learnt from the system implementation are presented. This system exploits relatively cheap materials, sensing and computing and can be applied to a wide variety of aquatic and terrestrial systems.

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Biomass and non-food crop residues are seen as relatively low cost and abundant renewable sources capable of making a large contribution to the world’s future energy and chemicals supply. Signifi cant quantities of ethanol are currently produced from biomass via biochemical processes, but thermochemical conversion processes offer greater potential to utilize the entire biomass source to produce a range of products. This chapter will review thermochemical gasifi cation and pyrolysis methods with a focus on hydrothermal liquefaction processes. Hydrothermal liquefaction is the most energetically advantageous thermochemical biomass conversion process. If the target is to produce sustainable liquid fuels and chemicals and reduce the impact of global warming as a result of carbon dioxide, nitrous oxide, and methane emissions (i.e., protect the natural environment), the use of “green” solvents, biocatalysts and heterogeneous catalysts must be the main R&D initiatives. As the biocrude produced from hydrothermal liquefaction is a complex mixture which is relatively viscous, corrosive, and unstable to oxidation (due to the presence of water and oxygenated compounds), additional upgrading processes are required to produce suitable biofuels and chemicals.

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Accurately quantifying total greenhouse gas emissions (e.g. methane) from natural systems such as lakes, reservoirs and wetlands requires the spatial-temporal measurement of both diffusive and ebullitive (bubbling) emissions. Traditional, manual, measurement techniques provide only limited localised assessment of methane flux, often introducing significant errors when extrapolated to the whole-of-system. In this paper, we directly address these current sampling limitations and present a novel multiple robotic boat system configured to measure the spatiotemporal release of methane to atmosphere across inland waterways. The system, consisting of multiple networked Autonomous Surface Vehicles (ASVs) and capable of persistent operation, enables scientists to remotely evaluate the performance of sampling and modelling algorithms for real-world process quantification over extended periods of time. This paper provides an overview of the multi-robot sampling system including the vehicle and gas sampling unit design. Experimental results are shown demonstrating the system’s ability to autonomously navigate and implement an exploratory sampling algorithm to measure methane emissions on two inland reservoirs.

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A unique high temporal frequency dataset from an irrigated cotton-wheat rotation was used to test the agroecosystem model DayCent to simulate daily N2O emissions from sub-tropical vertisols under different irrigation intensities. DayCent was able to simulate the effect of different irrigation intensities on N2O fluxes and yield, although it tended to overestimate seasonal fluxes during the cotton season. DayCent accurately predicted soil moisture dynamics and the timing and magnitude of high fluxes associated with fertilizer additions and irrigation events. At the daily scale we found a good correlation of predicted vs. measured N2O fluxes (r2 = 0.52), confirming that DayCent can be used to test agricultural practices for mitigating N2O emission from irrigated cropping systems. A 25 year scenario analysis indicated that N2O losses from irrigated cotton-wheat rotations on black vertisols in Australia can be substantially reduced by an optimized fertilizer and irrigation management system (i.e. frequent irrigation, avoidance of excessive fertiliser application), while sustaining maximum yield potentials.

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Greenhouse gas markets, where invisible gases are traded, must seem like black boxes to most people. Farmers can make money on these markets, such as the Chicago Climate Exchange, by installing methane capture technologies in animal-based systems, no-till farming, establishing grasslands, and planting trees.

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Many corporations and individuals realize that environmental sustainability is an urgent problem to address. In this chapter, we contribute to the emerging academic discussion by proposing two innovative approaches for engaging in the development of environmentally sustainable business processes. Specifically, we describe an extended process modeling approach for capturing and documenting the dioxide emissions produced during the execution of a business process. For illustration, we apply this approach to the case of a government Shared Service provider. Second, we then introduce an analysis method for measuring the carbon dioxide emissions produced during the execution of a business process. To illustrate this approach, we apply it in the real-life case of a European airport and show how this information can be leveraged in the re-design of "green" business processes.

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Many corporations and individuals realize that environmental sustainability is an urgent problem to address. In this chapter, we contribute to the emerging academic discussion by proposing two innovative approaches for engaging in the development of environmentally sustainable business processes. Specifically, we describe an extended process modeling approach for capturing and documenting the dioxide emissions produced during the execution of a business process. For illustration, we apply this approach to the case of a governmental Shared Services provider. Second, we then introduce an analysis method for measuring the carbon dioxide emissions produced during the execution of a business process. To illustrative this approach, we apply it in the real-life case of an European airport and show how this information can be leveraged in the re-design of “green” busi-ness processes.

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Through a forest inventory in parts of the Amudarya river delta, Central Asia, we assessed the impact of ongoing forest degradation on the emissions of greenhouse gases (GHG) from soils. Interpretation of aerial photographs from 2001, combined with data on forest inventory in 1990 and field survey in 2003 provided comprehensive information about the extent and changes of the natural tugai riparian forests and tree plantations in the delta. The findings show an average annual deforestation rate of almost 1.3% and an even higher rate of land use change from tugai forests to land with only sparse tree cover. These annual rates of deforestation and forest degradation are higher than the global annual forest loss. By 2003, the tugai forest area had drastically decreased to about 60% compared to an inventory in 1990. Significant differences in soil GHG emissions between forest and agricultural land use underscore the impact of the ongoing land use change on the emission of soil-borne GHGs. The conversion of tugai forests into irrigated croplands will release 2.5 t CO2 equivalents per hectare per year due to elevated emissions of N2O and CH4. This demonstrates that the ongoing transformation of tugai forests into agricultural land-use systems did not only lead to a loss of biodiversity and of a unique ecosystem, but substantially impacts the biosphere-atmosphere exchange of GHG and soil C and N turnover processes.

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Methane (CH4) is an important greenhouse gas with a global warming potential (GWP) 25 times greater than carbon dioxide (CO2) that can be produced or consumed in soils depending on environmental conditions and other factors. Biochar application to soils has been shown to reduce CH4 emissions and to increase CH4 consumption. However, the effects of rice husk biochar (RB) have not been thoroughly investigated. Two 60-day laboratory incubation experiments were conducted to investigate the effects of amending two soil types with RB, raw mill mud (MM) and composted mill mud (CM) on soil CH4 consumption and emissions. Soil cores incubated in 1 L glass jars and gas samples were analysed for CH4 using gas chromatography. Average CH4 consumption rates varied from -0.06 to -0.68 g CH4-C( )/ha/d in sandy loam soil and -0.59 to -1.00 g CH4-C/ha/d in clay soil. Application of RB resulted in CH4 uptake of -0.52 to -0.55 g CH4-C/ha/d in sandy loam and -0.76 to -0.91 g CH4-C/ha/d in clay soil. Addition of MM showed low CH4 emissions or consumption at 60% water-filled pore space (WFPS) in both soils. However, at high water contents (>75% WFPS) the application of MM produced high rates of CH4 emissions which were significantly suppressed when RB was added. Cumulative emissions of the MM treatment produced 108.9 g CH4-C/ha at 75% WFPS and 11 459.3 g CH4-C/ha at 90% WFPS in sandy loam soil over a period of 60 days. RB can increase CH4 uptake under low soil water content (SWC) and decrease CH4 emissions under anaerobic conditions. CM expressed more potential to reduce CH4 emissions than those of MM.

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Carbon dioxide reforming of methane produces synthesis gas with a low hydrogen to carbon monoxide ratio, which is desirable for many industrial synthesis processes. This reaction also has very important environmental implications since both methane and carbon dioxide contribute to the greenhouse effect. Converting these gases into a valuable feedstock may significantly reduce the atmospheric emissions of CO2 and CH4. In this paper, we present a comprehensive review on the thermodynamics, catalyst selection and activity, reaction mechanism, and kinetics of this important reaction. Recently, research has centered on the development of catalysts and the feasible applications of this reaction in industry. Group VIII metals supported on oxides are found to be effective for this reason. However, carbon deposition causing catalyst deactivation is the major problem inhibiting the industrial application of the CO2/CH4 reaction. Ni-based catalysts impregnated on certain supports show carbon-free operation and thus attract much attention. To develop an effective catalyst for CO2 reforming of CH4 and accelerate the commercial application of the reaction, the following are identified to be the most important areas for future work: (1) selection of metal and support and studying the effect of their interaction on catalyst activity; (2) the effect of different promoter on catalyst activity; (3) the reaction mechanism and kinetics; and (4) pilot reactor performance and scale-up operation.