88 resultados para Hubbard, Phil


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Meteorological (met) station data is used as the basis for a number of influential studies into the impacts of the variability of renewable resources. Real turbine output data is not often easy to acquire, whereas meteorological wind data, supplied at a standardised height of 10 m, is widely available. This data can be extrapolated to a standard turbine height using the wind profile power law and used to simulate the hypothetical power output of a turbine. Utilising a number of met sites in such a manner can develop a model of future wind generation output. However, the accuracy of this extrapolation is strongly dependent on the choice of the wind shear exponent alpha. This paper investigates the accuracy of the simulated generation output compared to reality using a wind farm in North Rhins, Scotland and a nearby met station in West Freugh. The results show that while a single annual average value for alpha may be selected to accurately represent the long term energy generation from a simulated wind farm, there are significant differences between simulation and reality on an hourly power generation basis, with implications for understanding the impact of variability of renewables on short timescales, particularly system balancing and the way that conventional generation may be asked to respond to a high level of variable renewable generation on the grid in the future.

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Reduced flexibility of low carbon generation could pose new challenges for future energy systems. Both demand response and distributed storage may have a role to play in supporting future system balancing. This paper reviews how these technically different, but functionally similar approaches compare and compete with one another. Household survey data is used to test the effectiveness of price signals to deliver demand responses for appliances with a high degree of agency. The underlying unit of storage for different demand response options is discussed, with particular focus on the ability to enhance demand side flexibility in the residential sector. We conclude that a broad range of options, with different modes of storage, may need to be considered, if residential demand flexibility is to be maximised.

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The variability of renewable energy is widely recognised as a challenge for integrating high levels of renewable generation into electricity systems. However, to explore its implications effectively, variability itself should first be clearly understood. This is particularly true for national electricity systems with high planned penetration of renewables and limited interconnection such as the UK. Variability cannot be considered as a distinct resource property with a single measurable parameter, but is a multi-faceted concept best described by a range of distinct characteristics. This paper identifies relevant characteristics of variability, and considers their implications for energy research. This is done through analysis of wind, solar and tidal current resources, with a primary focus on the Bristol Channel region in the UK. The relationship with electricity demand is considered, alongside the potential benefits of resource diversity. Analysis is presented in terms of persistence, distribution, frequency and correlation between supply and demand. Marked differences are seen between the behaviours of the individual resources, and these give rise to a range of different implications for system integration. Wind shows strong persistence and a useful seasonal pattern, but also a high spread in energy levels at timescales beyond one or two days. The solar resource is most closely correlated with electricity demand, but is undermined by night-time zero values and an even greater spread of monthly energy delivered than wind. In contrast, the tidal resource exhibits very low persistence, but also much greater consistency in energy values assessed across monthly time scales. Whilst this paper focuses primarily on the behaviour of resources, it is noted that discrete variability characteristics can be related to different system impacts. Persistence and predictability are relevant for system balancing, whereas statistical distribution is more relevant when exploring issues of asset utilisation and energy curtailment. Areas of further research are also identified, including the need to assess the value of predictability in relation to other characteristics.

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As wind generation increases, system impact studies rely on predictions of future generation and effective representation of wind variability. A well-established approach to investigate the impact of wind variability is to simulate generation using observations from 10 m meteorological mast-data. However, there are problems with relying purely on historical wind-speed records or generation histories: mast-data is often incomplete, not sited at a relevant wind generation sites, and recorded at the wrong altitude above ground (usually 10 m), each of which may distort the generation profile. A possible complimentary approach is to use reanalysis data, where data assimilation techniques are combined with state-of-the-art weather forecast models to produce complete gridded wind time-series over an area. Previous investigations of reanalysis datasets have placed an emphasis on comparing reanalysis to meteorological site records whereas this paper compares wind generation simulated using reanalysis data directly against historic wind generation records. Importantly, this comparison is conducted using raw reanalysis data (typical resolution ∼50 km), without relying on a computationally expensive “dynamical downscaling” for a particular target region. Although the raw reanalysis data cannot, by nature of its construction, represent the site-specific effects of sub-gridscale topography, it is nevertheless shown to be comparable to or better than the mast-based simulation in the region considered and it is therefore argued that raw reanalysis data may offer a number of significant advantages as a data source.

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Data quality is a difficult notion to define precisely, and different communities have different views and understandings of the subject. This causes confusion, a lack of harmonization of data across communities and omission of vital quality information. For some existing data infrastructures, data quality standards cannot address the problem adequately and cannot fulfil all user needs or cover all concepts of data quality. In this study, we discuss some philosophical issues on data quality. We identify actual user needs on data quality, review existing standards and specifications on data quality, and propose an integrated model for data quality in the field of Earth observation (EO). We also propose a practical mechanism for applying the integrated quality information model to a large number of datasets through metadata inheritance. While our data quality management approach is in the domain of EO, we believe that the ideas and methodologies for data quality management can be applied to wider domains and disciplines to facilitate quality-enabled scientific research.

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Insulin-like peptide 3 (INSL3), a major product of testicular Leydig cells, is also expressed by the ovary but its functional role remains poorly understood. Here, we quantified expression of INSL3 and its receptor RXFP2 in theca interna (TIC) and granulosa (GC) compartments of developing bovine antral follicles and in corpora lutea (CL). INSL3 and RXFP2 mRNA levels were much higher in TIC than GC and increased progressively during follicle maturation with INSL3 peaking in large (11-18mm) estrogen-active follicles and RXFP2 peaking in 9-10mm follicles before declining in larger (11-18mm) follicles. Expression of both INSL3 and RXFP2 in CL was much lower than in TIC. In situ hybridization and immunohistochemistry confirmed abundant expression of INSL3 mRNA and protein in TIC. These observations indicate follicular TIC rather than CL as the primary site of both INSL3 production and action, implying a predominantly auto-/paracrine role in TIC. To corroborate the above findings, we showed that in vitro exposure of TIC to a luteinizing concentration of LH greatly attenuated expression of both INSL3 and its receptor while increasing progesterone secretion and expression of STAR and CYP11A1. Moreover, in vivo, a significant cyclic variation in plasma INSL3 was observed during synchronized estrous cycles. INSL3 and estradiol-17β followed a similar pattern, both increasing after luteolysis, before falling sharply after the LH surge. Thus, theca-derived INSL3, likely from the dominant pre-ovulatory follicle, is detectable in peripheral blood of cattle and expression is down-regulated during luteinisation induced by the pre-ovulatory LH surge. Collectively, these findings underscore the likely role of INSL3 as an important intrafollicular modulator of TIC function/steroidogenesis, whilst raising doubts about its potential contribution to CL function.

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Bone morphogenetic proteins (BMP) are firmly implicated as intra-ovarian regulators of follicle development and steroidogenesis. Here we report a microarray analysis showing that treatment of cultured bovine theca cells (TC) with BMP6 significantly (>2-fold; P<0.01) up- or down-regulated expression of 445 genes. Insulin-like peptide 3 (INSL3) was the most heavily down-regulated gene (-43-fold) with CYP17A1 and other key transcripts involved in TC steroidogenesis including LHCGR, INHA, STAR, CYP11A1 and HSD3B1 also down-regulated. BMP6 also reduced expression of NR5A1 encoding steroidogenic factor-1 known to target the promoter regions of the aforementioned genes. Real-time PCR confirmed these findings and also revealed a marked reduction in expression of INSL3 receptor (RXFP2). Secretion of INSL3 protein and androstenedione were also suppressed suggesting a functional link between BMP and INSL3 pathways in controlling androgen synthesis. RNAi-mediated knockdown of INSL3 reduced INSL3 mRNA and secreted protein level (75 and 94%, respectively) and elicited a 77% reduction in CYP17A1 mRNA level and 83% reduction in androstenedione secretion. Knockdown of RXFP2 also reduced CYP17A1 mRNA level (81%) and androstenedione secretion (88%). Conversely, treatment with exogenous (human) INSL3 increased androstenedione secretion ~2-fold. The CYP17 inhibitor abiraterone abolished androgen secretion and reduced expression of both INSL3 and RXFP2. Collectively, these findings indicate a positive autoregulatory role for INSL3 signaling in maintaining thecal androgen production, and visa versa. Moreover, BMP6-induced suppression of thecal androgen synthesis may be mediated, at least in part, by reduced INSL3-RXFP2 signaling.

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Amid a worldwide increase in tree mortality, mountain pine beetles (Dendroctonus ponderosae Hopkins) have led to the death of billions of trees from Mexico to Alaska since 2000. This is predicted to have important carbon, water and energy balance feedbacks on the Earth system. Counter to current projections, we show that on a decadal scale, tree mortality causes no increase in ecosystem respiration from scales of several square metres up to an 84 km2 valley. Rather, we found comparable declines in both gross primary productivity and respiration suggesting little change in net flux, with a transitory recovery of respiration 6–7 years after mortality associated with increased incorporation of leaf litter C into soil organic matter, followed by further decline in years 8–10. The mechanism of the impact of tree mortality caused by these biotic disturbances is consistent with reduced input rather than increased output of carbon.

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In 1938, Guy Stewart Callendar was the first to demonstrate that the Earth’s land surface was warming. Callendar also suggested that the production of carbon dioxide by the combustion of fossil fuels was responsible for much of this modern change in climate. This short note marks the 75th anniversary of Callendar’s landmark study and demonstrates that his global land temperature estimates agree remarkably well with more recent analyses.

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We examine mid- to late Holocene centennial-scale climate variability in Ireland using proxy data from peatlands, lakes and a speleothem. A high degree of between-record variability is apparent in the proxy data and significant chronological uncertainties are present. However, tephra layers provide a robust tool for correlation and improve the chronological precision of the records. Although we can find no statistically significant coherence in the dataset as a whole, a selection of high-quality peatland water table reconstructions co-vary more than would be expected by chance alone. A locally weighted regression model with bootstrapping can be used to construct a ‘best-estimate’ palaeoclimatic reconstruction from these datasets. Visual comparison and cross-wavelet analysis of peatland water table compilations from Ireland and Northern Britain show that there are some periods of coherence between these records. Some terrestrial palaeoclimatic changes in Ireland appear to coincide with changes in the North Atlantic thermohaline circulation and solar activity. However, these relationships are inconsistent and may be obscured by chronological uncertainties. We conclude by suggesting an agenda for future Holocene climate research in Ireland.

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Collectively small and medium sized enterprises (SMEs) are significant energy users although many are unregulated by existing policies due to their low carbon emissions. Carbon reduction is often not a priority but smart grids may create a new opportunity. A smart grid will give electricity suppliers a picture of real-time energy flows and the opportunity for consumers to receive financial incentives for engaging in demand side management. As well as creating incentives for local carbon reduction, engaging SMEs with smart grids has potential for contributing to wider grid decarbonisation. Modelling of buildings, business activities and technology solutions is needed to identify opportunities for carbon reduction. The diversity of the SME sector complicates strategy development. SMEs are active in almost every business area and occupy the full range of property types. This paper reviews previous modelling work, exposing valuable data on floor space and energy consumption associated with different business activities. Limitations are seen with the age of this data and an inability to distinguish SME energy use. By modelling SME energy use, electrical loads are identified which could be shifted on demand, in a smart network. Initial analysis of consumption, not constrained by existing policies, identifies heating and cooling in retail and commercial offices as having potential for demand response. Hot water in hotel and catering and retail sectors may also be significant because of the energy storage potential. Areas to consider for energy efficiency schemes are also indicated.

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We use density functional theory calculations with Hubbard corrections (DFT+U) to investigate electronic aspects of the interaction between ceria surfaces and gold atoms. Our results show that Au adatoms at the (111) surface of ceria can adopt Au0, Au+ or Au� electronic configurations depending on the adsorption site. The strongest adsorption sites are on top of the surface oxygen and in a bridge position between two surface oxygen atoms, and in both cases charge transfer from the gold atom to one of the Ce cations at the surface is involved. Adsorption at other sites, including the hollow sites of the surface, and an O–Ce bridging site, is weaker and does not involve charge transfer. Adsorption at an oxygen vacancy site is very strong and involves the formation of an Au� anion. We argue that the ability of gold atoms to stabilise oxygen vacancies at the ceria surface by moving into the vacancy site and attracting the excess electrons of the defect could be responsible for the enhanced reducibility of ceria surfaces in the presence of gold. Finally, we rationalise the differences in charge transfer behaviour from site to site in terms of the electrostatic potential at the surface and the coordination of the species.

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The response of North Atlantic and European extratropical cyclones to climate change is investigated in the climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). In contrast to previous multimodel studies, a feature-tracking algorithm is here applied to separately quantify the re- sponses in the number, the wind intensity, and the precipitation intensity of extratropical cyclones. Moreover, a statistical framework is employed to formally assess the uncertainties in the multimodel projections. Under the midrange representative concentration pathway (RCP4.5) emission scenario, the December–February (DJF) response is characterized by a tripolar pattern over Europe, with an increase in the number of cyclones in central Europe and a decreased number in the Norwegian and Mediterranean Seas. The June–August (JJA) response is characterized by a reduction in the number of North Atlantic cyclones along the southern flank of the storm track. The total number of cyclones decreases in both DJF (24%) and JJA (22%). Classifying cyclones according to their intensity indicates a slight basinwide reduction in the number of cy- clones associated with strong winds, but an increase in those associated with strong precipitation. However, in DJF, a slight increase in the number and intensity of cyclones associated with strong wind speeds is found over the United Kingdom and central Europe. The results are confirmed under the high-emission RCP8.5 scenario, where the signals tend to be larger. The sources of uncertainty in these projections are discussed.

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The intention of this review is to place crop albedo biogeoengineering in the wider picture of climate manipulation. Crop biogeoengineering is considered within the context of the long-term modification of the land surface for agriculture over several thousand years. Biogeoengineering is also critiqued in relation to other geoengineering schemes in terms of mitigation power and adherence to social principles for geoengineering. Although its impact is small and regional, crop biogeoengineering could be a useful and inexpensive component of an ensemble of geoengineering schemes to provide temperature mitigation. The method should not detrimentally affect food security and there may even be positive impacts on crop productivity, although more laboratory and field research is required in this area to understand the underlying mechanisms.