981 resultados para Greenhouse gas fluxes


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Atmospheric concentrations of the three important greenhouse gases (GHGs) CO2, CH4 and N2O are mediated by processes in the terrestrial biosphere that are sensitive to climate and CO2. This leads to feedbacks between climate and land and has contributed to the sharp rise in atmospheric GHG concentrations since pre-industrial times. Here, we apply a process-based model to reproduce the historical atmospheric N2O and CH4 budgets within their uncertainties and apply future scenarios for climate, land-use change and reactive nitrogen (Nr) inputs to investigate future GHG emissions and their feedbacks with climate in a consistent and comprehensive framework1. Results suggest that in a business-as-usual scenario, terrestrial N2O and CH4 emissions increase by 80 and 45%, respectively, and the land becomes a net source of C by AD 2100. N2O and CH4 feedbacks imply an additional warming of 0.4–0.5 °C by AD 2300; on top of 0.8–1.0 °C caused by terrestrial carbon cycle and Albedo feedbacks. The land biosphere represents an increasingly positive feedback to anthropogenic climate change and amplifies equilibrium climate sensitivity by 22–27%. Strong mitigation limits the increase of terrestrial GHG emissions and prevents the land biosphere from acting as an increasingly strong amplifier to anthropogenic climate change.

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Carbon (C) and nitrogen (N) process-based models are important tools for estimating and reporting greenhouse gas emissions and changes in soil C stocks. There is a need for continuous evaluation, development and adaptation of these models to improve scientific understanding, national inventories and assessment of mitigation options across the world. To date, much of the information needed to describe different processes like transpiration, photosynthesis, plant growth and maintenance, above and below ground carbon dynamics, decomposition and nitrogen mineralization. In ecosystem models remains inaccessible to the wider community, being stored within model computer source code, or held internally by modelling teams. Here we describe the Global Research Alliance Modelling Platform (GRAMP), a web-based modelling platform to link researchers with appropriate datasets, models and training material. It will provide access to model source code and an interactive platform for researchers to form a consensus on existing methods, and to synthesize new ideas, which will help to advance progress in this area. The platform will eventually support a variety of models, but to trial the platform and test the architecture and functionality, it was piloted with variants of the DNDC model. The intention is to form a worldwide collaborative network (a virtual laboratory) via an interactive website with access to models and best practice guidelines; appropriate datasets for testing, calibrating and evaluating models; on-line tutorials and links to modelling and data provider research groups, and their associated publications. A graphical user interface has been designed to view the model development tree and access all of the above functions.

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Pig’s slurry is a key source of greenhouse gases (GHG). In Spain, GHG emissions (CH4+ N2O) from pig slurry (storage and land application) accounted in 2011 for 18.4% of total GHG emissions (in CO2- equivalent) of the agriculture sector according to the National Inventory Report (NIR). Slurry composition can be modified through diet manipulation. The aim of this work was to evaluate the effect of different fibre types in fattening pigs’ diets on GHG emissions from pig slurry storage and field application.

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Funded by Energy Technologies Institute EPSRC-Supergen. Grant Number: EP/M013200/1

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This work was supported by a Grant from the Welsh Government (Glastir Monitoring and Evaluation Project—GMEP).

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Equity is of fundamental concern in the quest for international cooperation to stabilize greenhouse gas concentrations by the reduction of emissions. By modeling the carbon cycle, we estimate the global CO2 emissions that would be required to stabilize the atmospheric concentration of CO2 at levels ranging from 450 to 1,000 ppm. These are compared, on both an absolute and a per-capita basis, to scenarios for emissions from the developed and developing worlds generated by socio-economic models under the assumption that actions to mitigate greenhouse gas emissions are not taken. Need and equity have provided strong arguments for developing countries to request that the developed world takes the lead in controlling its emissions, while permitting the developing countries in the meantime to use primarily fossil fuels for their development. Even with major and early control of CO2 emissions by the developed world, limiting concentration to 450 ppm implies that the developing world also would need to control its emissions within decades, given that we expect developing world emissions would otherwise double over this time. Scenarios leading to CO2 concentrations of 550 ppm exhibit a reduction of the developed world's per-capita emission by about 50% over the next 50 years. Even for the higher stabilization levels considered, the developing world would not be able to use fossil fuels for their development in the manner that the developed world has used them.

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Climate change is becoming more visible in the political arena. Electric generating companies will likely be impacted by future regulation of climate change related emissions. Even though few climate related programs are mandatory, electric generating companies should begin to implement greenhouse gas management systems. This report includes a review of issues facing the electric generating industry, an examination of current emission management programs, and recommendations for an effective greenhouse gas management framework. An effective greenhouse gas management program allows a company to continually improve their impact on climate change by reducing emissions using the plan, do, check, act process. To ease the reporting burden, companies should apply de minimis exemptions to sources that produce less than 5% of emissions.

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