959 resultados para close range photogrammetry
Resumo:
Green roof plants alter the microclimate of building roofs and may improve roof insulation. They act by providing cooling by shading, but also through transpiration of water through their stomata. However, leaf surfaces can become warmer when plants close the stomata and decrease water loss in response to drying substrate (typically associated with green roofs during summers), also reducing transpirational cooling. By using a range of contrasting plant types (Sedum mix – an industry green roof ‘standard’, Stachys byzantina, Bergenia cordifolia and Hedera hibernica) we tested the hypothesis that plants differ in their ‘cooling potential’. We firstly examined how leaf morphology influenced leaf temperature and how drying substrate altered that response. Secondly, we investigated the relationship between leaf surface temperatures and the air temperatures immediately above the canopies (i.e. potential to provide aerial cooling). Finally we measured how the plant type influenced the substrate temperature below the canopy (i.e. potential for building cooling). In our experiments Stachys outperformed the other species in terms of leaf surface cooling (even in drying substrate, e.g. 5 oC cooler compared with Sedum), substrate cooling beneath its canopy (up to 12 oC) and even - during short intervals over hottest still periods - the air above the canopy (up to 1 oC, when soil moisture was not limited). We suggest that the choice of plant species on green roofs should not be entirely dictated by what survives on the shallow substrates of extensive systems, but consideration should be given to supporting those species providing the greatest eco-system service potential.
Resumo:
The aim of this study was to investigate the antimicrobial properties of fifteen selected strains belonging to the Lactobacillus, Bifidobacterium, Lactococcus, Streptococcus and Bacillus genera against Gram-positive and Gram-negative pathogenic bacteria. In vitro antibacterial activity was initially investigated by an agar spot method. Results from the agar spot test showed that most of the selected strains were able to produce active compounds on solid media with antagonistic properties against Salmonella Typhimurium, Escherichia coli, Enterococcus faecalis, Staphylococcus aureus and Clostridium difficile. These results were also confirmed when cell-free culture supernatants (CFCS) from the putative probiotics were used in an agar well diffusion assay. Neutralization of the culture supernatants with alkali reduced the antagonistic effects. These experiments are able to confirm the capacity of potential probiotics to inhibit selected pathogens. One of the main inhibitory mechanisms may result from the production of organic acids from glucose fermentation and consequent lowering of culture pH. This observation was confirmed when the profile of organic acids was analysed demonstrating that lactic and acetic acid were the principal end products of probiotic metabolism. Furthermore, the assessment of the haemolytic activity and the susceptibility of the strains to the most commonly used antimicrobials, considered as basic safety aspects, were also studied. The observed antimicrobial activity was mainly genus-specific, additionally significant differences could be observed among species.
Resumo:
Predictability is considered in the context of the seamless weather-climate prediction problem, and the notion is developed that there can be predictive power on all time-scales. On all scales there are phenomena that occur as well as longer time-scales and external conditions that should combine to give some predictability. To what extent this theoretical predictability may actually be realised and, further, to what extent it may be useful is not clear. However the potential should provide a stimulus to, and high profile for, our science and its application for many years.
Resumo:
The primary objective was to determine fatty acid composition of skinless chicken breast and leg meat portions and chicken burgers and nuggets from the economy price range, standard price range (both conventional intensive rearing) and the organic range from four leading supermarkets. Few significant differences in the SFA, MUFA and PUFA composition of breast and leg meat portions were found among price ranges, and supermarket had no effect. No significant differences in fatty acid concentrations of economy and standard chicken burgers were found, whereas economy chicken nuggets had higher C16:1, C18:1 cis, C18:1 trans and C18:3 n-3 concentrations than had standard ones. Overall, processed chicken products had much higher fat contents and SFA than had whole meat. Long chain n-3 fatty acids had considerably lower concentrations in processed products than in whole meat. Overall there was no evidence that organic chicken breast or leg meat had a more favourable fatty acid composition than had meat from conventionally reared birds.
Resumo:
Particulate matter generated during the cooking process has been identified as one of the major problems of indoor air quality and indoor environmental health. Reliable assessment of exposure to cooking-generated particles requires accurate information of emission characteristics especially the size distribution. This study characterizes the volume/mass-based size distribution of the fume particles at the oil-heating stage for the typical Chinese-style cooking in a laboratory kitchen. A laser-diffraction size analyzer is applied to measure the volume frequency of fume particles ranged from 0.1 to 10 μm, which contribute to most mass proportion in PM2.5 and PM10. Measurements show that particle emissions have little dependence on the types of vegetable oil used but have a close relationship with the heating temperature. It is found that volume frequency of fume particles in the range of 1.0–4.0 μm accounts for nearly 100% of PM0.1–10 with the mode diameter 2.7 μm, median diameter 2.6 μm, Sauter mean diameter 3.0 μm, DeBroukere mean diameter 3.2 μm, and distribution span 0.48. Such information on emission characteristics obtained in this study can be possibly used to improve the assessment of indoor air quality due to PM0.1–10 in the kitchen and residential flat.
Resumo:
Melting of the Greenland Ice Sheet (GrIS) is accelerating and will contribute significantly to global sea level rise during the 21st century. Instrumental data on GrIS melting only cover the last few decades, and proxy data extending our knowledge into the past are vital for validating models predicting the influence of ongoing climate change. We investigated a potential meltwater proxy in Godthåbsfjord (West Greenland), where glacier meltwater causes seasonal excursions with lower oxygen isotope water (δ18Ow) values and salinity. The blue mussel (Mytilus edulis) potentially records these variations, because it precipitates its shell calcite in oxygen isotopic equilibrium with ambient seawater. As M. edulis shells are known to occur in raised shorelines and archaeological shell middens from previous Holocene warm periods, this species may be ideal in reconstructing past meltwater dynamics. We investigate its potential as a palaeo-meltwater proxy. First, we confirmed that M. edulis shell calcite oxygen isotope (δ18Oc) values are in equilibrium with ambient water and generally reflect meltwater conditions. Subsequently we investigated if this species recorded the full range of δ18Ow values occurring during the years 2007 to 2010. Results show that δ18Ow values were not recorded at very low salinities (< ~ 19), because the mussels appear to cease growing. This implies that Mytilus edulis δ18Oc values are suitable in reconstructing past meltwater amounts in most cases, but care has to be taken that shells are collected not too close to a glacier, but rather in the mid-region or mouth of the fjord. The focus of future research will expand on the geographical and temporal range of the shell measurements by sampling mussels in other fjords in Greenland along a south–north gradient, and by sampling shells from raised shorelines and archaeological shell middens from prehistoric settlements in Greenland.
Resumo:
Phylogenetic analysis of nrDNA ITS and trnL (UAA) 5′ exon-trnF (GAA) chloroplast DNA sequences from 17 species ofPelargonium sect.Peristera, together with nine putative outgroups, suggests paraphyly for the section and a close relationship between the highly disjunct South African and Australian species of sect.Peristera. Representatives fromPelargonium sectt.Reniformia, Ligularia s. l. andIsopetalum (the St. Helena endemicP. cotyledonis) appear to be nested within thePeristera clade. The close relationship between the South African and AustralianPeristera is interpreted as being caused by long-range dispersal to Australia, probably as recent as the late Pliocene.
Resumo:
We use a soil carbon (C) model (RothC), driven by a range of climate models for a range of climate scenarios to examine the impacts of future climate on global soil organic carbon (SOC) stocks. The results suggest an overall global increase in SOC stocks by 2100 under all scenarios, but with a different extent of increase among the climate model and emissions scenarios. The impacts of projected land use changes are also simulated, but have relatively minor impacts at the global scale. Whether soils gain or lose SOC depends upon the balance between C inputs and decomposition. Changes in net primary production (NPP) change C inputs to the soil, whilst decomposition usually increases under warmer temperatures, but can also be slowed by decreased soil moisture. Underlying the global trend of increasing SOC under future climate is a complex pattern of regional SOC change. SOC losses are projected to occur in northern latitudes where higher SOC decomposition rates due to higher temperatures are not balanced by increased NPP, whereas in tropical regions, NPP increases override losses due to higher SOC decomposition. The spatial heterogeneity in the response of SOC to changing climate shows how delicately balanced the competing gain and loss processes are, with subtle changes in temperature, moisture, soil type and land use, interacting to determine whether SOC increases or decreases in the future. Our results suggest that we should stop looking for a single answer regarding whether SOC stocks will increase or decrease under future climate, since there is no single answer. Instead, we should focus on improving our prediction of the factors that determine the size and direction of change, and the land management practices that can be implemented to protect and enhance SOC stocks.
Resumo:
At the end of the 20th century, we can look back on a spectacular development of numerical weather prediction, which has, practically uninterrupted, been going on since the middle of the century. High-resolution predictions for more than a week ahead for any part of the globe are now routinely produced and anyone with an Internet connection can access many of these forecasts for anywhere in the world. Extended predictions for several seasons ahead are also being done — the latest El Niño event in 1997/1998 is an example of such a successful prediction. The great achievement is due to a number of factors including the progress in computational technology and the establishment of global observing systems, combined with a systematic research program with an overall strategy towards building comprehensive prediction systems for climate and weather. In this article, I will discuss the different evolutionary steps in this development and the way new scientific ideas have contributed to efficiently explore the computing power and in using observations from new types of observing systems. Weather prediction is not an exact science due to unavoidable errors in initial data and in the models. To quantify the reliability of a forecast is therefore essential and probably more so the longer the forecasts are. Ensemble prediction is thus a new and important concept in weather and climate prediction, which I believe will become a routine aspect of weather prediction in the future. The limit between weather and climate prediction is becoming more and more diffuse and in the final part of this article I will outline the way I think development may proceed in the future.
Resumo:
Total ozone trends are typically studied using linear regression models that assume a first-order autoregression of the residuals [so-called AR(1) models]. We consider total ozone time series over 60°S–60°N from 1979 to 2005 and show that most latitude bands exhibit long-range correlated (LRC) behavior, meaning that ozone autocorrelation functions decay by a power law rather than exponentially as in AR(1). At such latitudes the uncertainties of total ozone trends are greater than those obtained from AR(1) models and the expected time required to detect ozone recovery correspondingly longer. We find no evidence of LRC behavior in southern middle-and high-subpolar latitudes (45°–60°S), where the long-term ozone decline attributable to anthropogenic chlorine is the greatest. We thus confirm an earlier prediction based on an AR(1) analysis that this region (especially the highest latitudes, and especially the South Atlantic) is the optimal location for the detection of ozone recovery, with a statistically significant ozone increase attributable to chlorine likely to be detectable by the end of the next decade. In northern middle and high latitudes, on the other hand, there is clear evidence of LRC behavior. This increases the uncertainties on the long-term trend attributable to anthropogenic chlorine by about a factor of 1.5 and lengthens the expected time to detect ozone recovery by a similar amount (from ∼2030 to ∼2045). If the long-term changes in ozone are instead fit by a piecewise-linear trend rather than by stratospheric chlorine loading, then the strong decrease of northern middle- and high-latitude ozone during the first half of the 1990s and its subsequent increase in the second half of the 1990s projects more strongly on the trend and makes a smaller contribution to the noise. This both increases the trend and weakens the LRC behavior at these latitudes, to the extent that ozone recovery (according to this model, and in the sense of a statistically significant ozone increase) is already on the verge of being detected. The implications of this rather controversial interpretation are discussed.
Resumo:
Long-range global climate forecasts were made by use of a model for predicting a tropical Pacific sea-surface temperature (SST) in tandem with an atmospheric general circulation model. The SST is predicted first at long lead times into the future. These ocean forecasts are then used to force the atmospheric model and so produce climate forecasts at lead times of the SST forecasts. Prediction of seven large climatic events of the 1970s to 1990s by this technique are in good agreement with observations over many regions of the globe.