990 resultados para Fine-Particle Emissions


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Four established mature tree species (Aesculus hippocastanum L., Betula pendula Roth., Primus avium L. and Quercus rohur L.) commonly planted in UK urban landscapes were subjected to soil injections of the carbohydrate sucrose at 25, 50 and 70g per litre of water. Fine root dry weight was recorded at month 5 following soil injections. Soil injections of sucrose significantly increased fine root dry weight compared to controls, however; growth responses were influenced by species and the concentration of sucrose applied. Results indicate soil injections of sucrose ≥ 50g litre of water may be able to improve root growth of established mature trees. Such a response is desirable as root damage following construction is a frequent problem encountered by established trees growing in UK towns and cities.

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The ECMWF operational grid point model (with a resolution of 1.875° of latitude and longitude) and its limited area version (with a resolution of !0.47° of latitude and longitude) with boundary values from the global model have been used to study the simulation of the typhoon Tip. The fine-mesh model was capable of simulating the main structural features of the typhoon and predicting a fall in central pressure of 60 mb in 3 days. The structure of the forecast typhoon, with a warm core (maximum potential temperature anomaly 17 K). intense swirling wind (maximum 55 m s-1 at 850 mb) and spiralling precipitation patterns is characteristic of a tropical cyclone. Comparison with the lower resolution forecast shows that the horizontal resolution is a determining factor in predicting not only the structure and intensity but even the movement of these vortices. However, an accurate and refined initial analysis is considered to be a prerequisite for a correct forecast of this phenomenon.

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[1] We have implemented a process-based isoprene emission model in the HadGEM2 Earth-system model with coupled atmospheric chemistry in order to examine the feedback between isoprene emission and climate. Isoprene emissions and their impact on atmospheric chemistry and climate are estimated for preindustrial (1860–1869), present-day (2000–2009), and future (2100–2109) climate conditions. The estimate of 460 TgC/yr for present-day global total isoprene emission is consistent with previous estimates. Preindustrial isoprene emissions are estimated to be 26% higher than present-day. Future isoprene emissions using the RCP8.5 scenario are similar to present-day because increased emissions resulting from climate warming are countered by CO2 inhibition of isoprene emissions. The impact of biogenic isoprene emissions on the global O3 burden and CH4 lifetime is small but locally significant, and the impact of changes in isoprene emissions on atmospheric chemistry depends strongly on the state of climate and chemistry.

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Approximately 1–2% of net primary production by land plants is re-emitted to the atmosphere as isoprene and monoterpenes. These emissions play major roles in atmospheric chemistry and air pollution–climate interactions. Phenomenological models have been developed to predict their emission rates, but limited understanding of the function and regulation of these emissions has led to large uncertainties in model projections of air quality and greenhouse gas concentrations. We synthesize recent advances in diverse fields, from cell physiology to atmospheric remote sensing, and use this information to propose a simple conceptual model of volatile isoprenoid emission based on regulation of metabolism in the chloroplast. This may provide a robust foundation for scaling up emissions from the cellular to the global scale.

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We investigate the role of the anthropogenic heat flux on the urban heat island of London. To do this, the time-varying anthropogenic heat flux is added to an urban surface-energy balance parametrization, the Met Office–Reading Urban Surface Exchange Scheme (MORUSES), implemented in a 1 km resolution version of the UK Met Office Unified Model. The anthropogenic heat flux is derived from energy-demand data for London and is specified on the model's 1 km grid; it includes variations on diurnal and seasonal time-scales. We contrast a spring case with a winter case, to illustrate the effects of the larger anthropogenic heat flux in winter and the different roles played by thermodynamics in the different seasons. The surface-energy balance channels the anthropogenic heat into heating the urban surface, which warms slowly because of the large heat capacity of the urban surface. About one third of this additional warming goes into increasing the outgoing long-wave radiation and only about two thirds goes into increasing the sensible heat flux that warms the atmosphere. The anthropogenic heat flux has a larger effect on screen-level temperatures in the winter case, partly because the anthropogenic flux is larger then and partly because the boundary layer is shallower in winter. For the specific winter case studied here, the anthropogenic heat flux maintains a well-mixed boundary layer through the whole night over London, whereas the surrounding rural boundary layer becomes strongly stably stratified. This finding is likely to have important implications for air quality in winter. On the whole, inclusion of the anthropogenic heat flux improves the comparison between model simulations and measurements of screen-level temperature slightly and indicates that the anthropogenic heat flux is beginning to be an important factor in the London urban heat island.

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Forests are a store of carbon and an eco-system that continually removes carbon dioxide from the atmosphere. If they are sustainably managed, the carbon store can be maintained at a constant level, while the trees removed and converted to timber products can form an additional long term carbon store. The total carbon store in the forest and associated ‘wood chain’ therefore increases over time, given appropriate management. This increasing carbon store can be further enhanced with afforestation. The UK’s forest area has increased continually since the early 1900s, although the rate of increase has declined since its peak in the late 1980s, and it is a similar picture in the rest of Europe. The increased sustainable use of timber in construction is a key market incentive for afforestation, which can make a significant contribution to reducing carbon emissions. The case study presented in this paper demonstrates the carbon benefits of a Cross Laminated Timber (CLT) solution for a multi-storey residential building in comparison with a more conventional reinforced concrete solution. The embodied carbon of the building up to completion of construction is considered, together with the stored carbon during the life of the building and the impact of different end of life scenarios. The results of the study show that the total stored carbon in the CLT structural frame is 1215tCO2 (30tCO2 per housing unit). The choice of treatment at end of life has a significant effect on the whole life embodied carbon of the CLT frame, which ranges from -1017 tCO2e for re-use to +153tCO2e for incinerate without energy recovery. All end of life scenarios considered result in lower total CO2e emissions for the CLT frame building compared with the reinforced concrete frame solution.

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Hybrid multiprocessor architectures which combine re-configurable computing and multiprocessors on a chip are being proposed to transcend the performance of standard multi-core parallel systems. Both fine-grained and coarse-grained parallel algorithm implementations are feasible in such hybrid frameworks. A compositional strategy for designing fine-grained multi-phase regular processor arrays to target hybrid architectures is presented in this paper. The method is based on deriving component designs using classical regular array techniques and composing the components into a unified global design. Effective designs with phase-changes and data routing at run-time are characteristics of these designs. In order to describe the data transfer between phases, the concept of communication domain is introduced so that the producer–consumer relationship arising from multi-phase computation can be treated in a unified way as a data routing phase. This technique is applied to derive new designs of multi-phase regular arrays with different dataflow between phases of computation.

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Both the EU’s Renewable Energy Directive (RED) and Article 7a of its Fuel Quality Directive (FQD) seek to reduce greenhouse gas (GHG) emissions from transport fuels. The RED mandates a 10% share of renewable energy in transport fuels by 2020, whilst the FQD requires a 6% reduction in GHG emissions (from a 2010 base) by the same date. In practice, it will mainly be biofuels that economic operators will use to meet these requirements, but the different approaches can lead to either the RED, or the FQD, acting as the binding constraint. A common set of environmental sustainability criteria apply to biofuels under both the RED and the FQD. In particular, biofuels have to demonstrate a 35% (later increasing to 50/60%) saving in life-cycle GHG emissions. This could be problematic in the World Trade Organization (WTO), as a non-compliant biofuel with a 34% emissions saving would probably be judged to be ‘like’ a compliant biofuel. A more economically rational way to reduce GHG emissions, and one that might attract greater public support, would be for the RED to reward emission reductions along the lines of the FQD. Moreover, this modification would probably make the provisions more acceptable in the WTO, as there would be a clearer link between policy measures and the objective of reductions in GHG emissions; and the combination of the revised RED and the FQD would lessen the commercial incentive to import biofuels with modest GHG emission savings, and thus reduce the risk of trade tension.

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We have incorporated a semi-mechanistic isoprene emission module into the JULES land-surface scheme, as a first step towards a modelling tool that can be applied for studies of vegetation – atmospheric chemistry interactions, including chemistry-climate feedbacks. Here, we evaluate the coupled model against local above-canopy isoprene emission flux measurements from six flux tower sites as well as satellite-derived estimates of isoprene emission over tropical South America and east and south Asia. The model simulates diurnal variability well: correlation coefficients are significant (at the 95 % level) for all flux tower sites. The model reproduces day-to-day variability with significant correlations (at the 95 % confidence level) at four of the six flux tower sites. At the UMBS site, a complete set of seasonal observations is available for two years (2000 and 2002). The model reproduces the seasonal pattern of emission during 2002, but does less well in the year 2000. The model overestimates observed emissions at all sites, which is partially because it does not include isoprene loss through the canopy. Comparison with the satellite-derived isoprene-emission estimates suggests that the model simulates the main spatial patterns, seasonal and inter-annual variability over tropical regions. The model yields a global annual isoprene emission of 535 ± 9 TgC yr−1 during the 1990s, 78 % of which from forested areas.

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A novel two-stage construction algorithm for linear-in-the-parameters classifier is proposed, aiming at noisy two-class classification problems. The purpose of the first stage is to produce a prefiltered signal that is used as the desired output for the second stage to construct a sparse linear-in-the-parameters classifier. For the first stage learning of generating the prefiltered signal, a two-level algorithm is introduced to maximise the model's generalisation capability, in which an elastic net model identification algorithm using singular value decomposition is employed at the lower level while the two regularisation parameters are selected by maximising the Bayesian evidence using a particle swarm optimization algorithm. Analysis is provided to demonstrate how “Occam's razor” is embodied in this approach. The second stage of sparse classifier construction is based on an orthogonal forward regression with the D-optimality algorithm. Extensive experimental results demonstrate that the proposed approach is effective and yields competitive results for noisy data sets.

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The anthropogenic heat emissions generated by human activities in London are analysed in detail for 2005–2008 and considered in context of long-term past and future trends (1970–2025). Emissions from buildings, road traffic and human metabolism are finely resolved in space (30 min) and time (200 × 200 m2). Software to compute and visualize the results is provided. The annual mean anthropogenic heat flux for Greater London is 10.9 W m−2 for 2005–2008, with the highest peaks in the central activities zone (CAZ) associated with extensive service industry activities. Towards the outskirts of the city, emissions from the domestic sector and road traffic dominate. Anthropogenic heat is mostly emitted as sensible heat, with a latent heat fraction of 7.3% and a heat-to-wastewater fraction of 12%; the implications related to the use of evaporative cooling towers are briefly addressed. Projections indicate a further increase of heat emissions within the CAZ in the next two decades related to further intensification of activities within this area.