Alternatives to Sedum on green roofs: Can broad leaf perennial plants offer better ‘cooling service’?

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.

Whole life carbon – a building case study

There is potential to reduce both operational and embodied greenhouse gas emission from buildings. To date the focus has been on reducing the operational element, although given the urgency of carbon reductions, it may be more beneficial to consider upfront embodied carbon reductions. This paper describes a case study on the whole life carbon cycle of a warehouse building in Swindon, UK. It examines the relationship between embodied carbon (Ec) and operational carbon (Oc), the proportions of Ec from the structural and non-structural elements, carbon benchmarking of the structure, the value of ‘cradle to site’ or ‘cradle to grave’ assessments and the significance of the timing of emissions during the life of the building. The case study indicates that Ec was dominant for the building and that the structure was responsible for more than half of the Ec. Weighting of future emissions appears to be an important factor to consider. The PAS 2050 reduction factors had only a modest effect but weighting to allow for future decarbonisation of the national grid energy supply had a large effect. This suggests that future operational carbon emissions are being overestimated compared to embodied.

An effective approach for land-cover classification from airborne lidar fused with co-registered data

Airborne lidar provides accurate height information of objects on the earth and has been recognized as a reliable and accurate surveying tool in many applications. In particular, lidar data offer vital and significant features for urban land-cover classification, which is an important task in urban land-use studies. In this article, we present an effective approach in which lidar data fused with its co-registered images (i.e. aerial colour images containing red, green and blue (RGB) bands and near-infrared (NIR) images) and other derived features are used effectively for accurate urban land-cover classification. The proposed approach begins with an initial classification performed by the Dempster–Shafer theory of evidence with a specifically designed basic probability assignment function. It outputs two results, i.e. the initial classification and pseudo-training samples, which are selected automatically according to the combined probability masses. Second, a support vector machine (SVM)-based probability estimator is adopted to compute the class conditional probability (CCP) for each pixel from the pseudo-training samples. Finally, a Markov random field (MRF) model is established to combine spatial contextual information into the classification. In this stage, the initial classification result and the CCP are exploited. An efficient belief propagation (EBP) algorithm is developed to search for the global minimum-energy solution for the maximum a posteriori (MAP)-MRF framework in which three techniques are developed to speed up the standard belief propagation (BP) algorithm. Lidar and its co-registered data acquired by Toposys Falcon II are used in performance tests. The experimental results prove that fusing the height data and optical images is particularly suited for urban land-cover classification. There is no training sample needed in the proposed approach, and the computational cost is relatively low. An average classification accuracy of 93.63% is achieved.

An effective approach for selection of terrain modelling method

This letter presents an effective approach for selection of appropriate terrain modeling methods in forming a digital elevation model (DEM). This approach achieves a balance between modeling accuracy and modeling speed. A terrain complexity index is defined to represent a terrain's complexity. A support vector machine (SVM) classifies terrain surfaces into either complex or moderate based on this index associated with the terrain elevation range. The classification result recommends a terrain modeling method for a given data set in accordance with its required modeling accuracy. Sample terrain data from the lunar surface are used in constructing an experimental data set. The results have shown that the terrain complexity index properly reflects the terrain complexity, and the SVM classifier derived from both the terrain complexity index and the terrain elevation range is more effective and generic than that designed from either the terrain complexity index or the terrain elevation range only. The statistical results have shown that the average classification accuracy of SVMs is about 84.3% ± 0.9% for terrain types (complex or moderate). For various ratios of complex and moderate terrain types in a selected data set, the DEM modeling speed increases up to 19.5% with given DEM accuracy.

Time valued life cycle greenhouse gas emissions from buildings

The UK has adopted legally binding carbon reduction targets of 34% by 2020 and 80% by 2050 (measured against the 1990 baseline). Buildings are estimated to be responsible for more than 50% of greenhouse gas (GHG) emissions in the UK. These consist of both operational, produced during use, and embodied, produced during manufacture of materials and components, and during construction, refurbishments and demolition. A brief assessment suggests that it is unlikely that UK emission reduction targets can be met without substantial reductions in both Oc and Ec. Oc occurs over the lifetime of a building whereas the bulk of Ec occurs at the start of a building’s life. A time value for emissions could influence the decision making process when it comes to comparing mitigation measures which have benefits that occur at different times. An example might be the choice between building construction using low Ec construction materials versus building construction using high Ec construction materials but with lower Oc, although the use of high Ec materials does not necessarily imply a lower Oc. Particular time related issues examined here are: the urgency of the need to achieve large emissions reductions during the next 10 to 20 years; the earlier effective action is taken, the less costly it will be; future reduction in carbon intensity of energy supply; the carbon cycle and relationship between the release of GHG’s and their subsequent concentrations in the atmosphere. An equation is proposed, which weights emissions according to when they occur during the building life cycle, and which effectively increases Ec as a proportion of the total, suggesting that reducing Ec is likely to be more beneficial, in terms of climate change, for most new buildings. Thus, giving higher priority to Ec reductions is likely to result in a bigger positive impact on climate change and mitigation costs.

The neuropsychology of male adults with High-Functioning Autism or Asperger Syndrome

Autism Spectrum Disorder (ASD) is diagnosed on the basis of behavioral symptoms, but cognitive abilities may also be useful in characterizing individuals with ASD. One hundred seventy-eight high-functioning male adults, half with ASD and half without, completed tasks assessing IQ, a broad range of cognitive skills, and autistic and comorbid symptomatology. The aims of the study were, first, to determine whether significant differences existed between cases and controls on cognitive tasks, and whether cognitive profiles, derived using a multivariate classification method with data from multiple cognitive tasks, could distinguish between the two groups. Second, to establish whether cognitive skill level was correlated with degree of autistic symptom severity, and third, whether cognitive skill level was correlated with degree of comorbid psychopathology. Fourth, cognitive characteristics of individuals with Asperger Syndrome (AS) and high-functioning autism (HFA) were compared. After controlling for IQ, ASD and control groups scored significantly differently on tasks of social cognition, motor performance, and executive function (P's < 0.05). To investigate cognitive profiles, 12 variables were entered into a support vector machine (SVM), which achieved good classification accuracy (81%) at a level significantly better than chance (P < 0.0001). After correcting for multiple correlations, there were no significant associations between cognitive performance and severity of either autistic or comorbid symptomatology. There were no significant differences between AS and HFA groups on the cognitive tasks. Cognitive classification models could be a useful aid to the diagnostic process when used in conjunction with other data sources-including clinical history.

The AeroCom evaluation and intercomparison of organic aerosol in global models

This paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry transport models (CTMs) and general circulation models (GCMs) have participated in this intercomparison, in the framework of AeroCom phase II. The simulation of OA varies greatly between models in terms of the magnitude of primary emissions, secondary OA (SOA) formation, the number of OA species used (2 to 62), the complexity of OA parameterizations (gas-particle partitioning, chemical aging, multiphase chemistry, aerosol microphysics), and the OA physical, chemical and optical properties. The diversity of the global OA simulation results has increased since earlier AeroCom experiments, mainly due to the increasing complexity of the SOA parameterization in models, and the implementation of new, highly uncertain, OA sources. Diversity of over one order of magnitude exists in the modeled vertical distribution of OA concentrations that deserves a dedicated future study. Furthermore, although the OA / OC ratio depends on OA sources and atmospheric processing, and is important for model evaluation against OA and OC observations, it is resolved only by a few global models. The median global primary OA (POA) source strength is 56 Tg a−1 (range 34–144 Tg a−1) and the median SOA source strength (natural and anthropogenic) is 19 Tg a−1 (range 13–121 Tg a−1). Among the models that take into account the semi-volatile SOA nature, the median source is calculated to be 51 Tg a−1 (range 16–121 Tg a−1), much larger than the median value of the models that calculate SOA in a more simplistic way (19 Tg a−1; range 13–20 Tg a−1, with one model at 37 Tg a−1). The median atmospheric burden of OA is 1.4 Tg (24 models in the range of 0.6–2.0 Tg and 4 between 2.0 and 3.8 Tg), with a median OA lifetime of 5.4 days (range 3.8–9.6 days). In models that reported both OA and sulfate burdens, the median value of the OA/sulfate burden ratio is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9 models higher than 1. For 26 models that reported OA deposition fluxes, the median wet removal is 70 Tg a−1 (range 28–209 Tg a−1), which is on average 85% of the total OA deposition. Fine aerosol organic carbon (OC) and OA observations from continuous monitoring networks and individual field campaigns have been used for model evaluation. At urban locations, the model–observation comparison indicates missing knowledge on anthropogenic OA sources, both strength and seasonality. The combined model–measurements analysis suggests the existence of increased OA levels during summer due to biogenic SOA formation over large areas of the USA that can be of the same order of magnitude as the POA, even at urban locations, and contribute to the measured urban seasonal pattern. Global models are able to simulate the high secondary character of OA observed in the atmosphere as a result of SOA formation and POA aging, although the amount of OA present in the atmosphere remains largely underestimated, with a mean normalized bias (MNB) equal to −0.62 (−0.51) based on the comparison against OC (OA) urban data of all models at the surface, −0.15 (+0.51) when compared with remote measurements, and −0.30 for marine locations with OC data. The mean temporal correlations across all stations are low when compared with OC (OA) measurements: 0.47 (0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for marine stations with OC data. The combination of high (negative) MNB and higher correlation at urban stations when compared with the low MNB and lower correlation at remote sites suggests that knowledge about the processes that govern aerosol processing, transport and removal, on top of their sources, is important at the remote stations. There is no clear change in model skill with increasing model complexity with regard to OC or OA mass concentration. However, the complexity is needed in models in order to distinguish between anthropogenic and natural OA as needed for climate mitigation, and to calculate the impact of OA on climate accurately.

The Devil’s Daughters and a question of translation between Occitan and Anglo-Norman French: ‘De las .vii. filhas del diable’ (British Library Add. MS 17920).

The evidence for vernacular-to-vernacular translation is hard to demonstrate in medieval Romance languages. This article analyses a hypothesis published a century ago that there is an identifiable Anglo-Norman source for an Occitan prose text. Both texts spring from a Latin exemplum in which the seven capital vices are personified as the Devil's daughters, married off to seven social categories (the clergy, knights, peasants, etc.). Although the hypothesis is disproved, it remains that the dialogue between Anglo-Norman French and Occitan has been overlooked, and deserves further exploration.

Application of complex extreme learning machine to multiclass classification problems with high dimensionality: a THz spectra classification problem

We extend extreme learning machine (ELM) classifiers to complex Reproducing Kernel Hilbert Spaces (RKHS) where the input/output variables as well as the optimization variables are complex-valued. A new family of classifiers, called complex-valued ELM (CELM) suitable for complex-valued multiple-input–multiple-output processing is introduced. In the proposed method, the associated Lagrangian is computed using induced RKHS kernels, adopting a Wirtinger calculus approach formulated as a constrained optimization problem similarly to the conventional ELM classifier formulation. When training the CELM, the Karush–Khun–Tuker (KKT) theorem is used to solve the dual optimization problem that consists of satisfying simultaneously smallest training error as well as smallest norm of output weights criteria. The proposed formulation also addresses aspects of quaternary classification within a Clifford algebra context. For 2D complex-valued inputs, user-defined complex-coupled hyper-planes divide the classifier input space into four partitions. For 3D complex-valued inputs, the formulation generates three pairs of complex-coupled hyper-planes through orthogonal projections. The six hyper-planes then divide the 3D space into eight partitions. It is shown that the CELM problem formulation is equivalent to solving six real-valued ELM tasks, which are induced by projecting the chosen complex kernel across the different user-defined coordinate planes. A classification example of powdered samples on the basis of their terahertz spectral signatures is used to demonstrate the advantages of the CELM classifiers compared to their SVM counterparts. The proposed classifiers retain the advantages of their ELM counterparts, in that they can perform multiclass classification with lower computational complexity than SVM classifiers. Furthermore, because of their ability to perform classification tasks fast, the proposed formulations are of interest to real-time applications.

Climate responses to anthropogenic emissions of short-lived climate pollutants

Policies to control air quality focus on mitigating emissions of aerosols and their precursors, and other short-lived climate pollutants (SLCPs). On a local scale, these policies will have beneficial impacts on health and crop yields, by reducing particulate matter (PM) and surface ozone concentrations; however, the climate impacts of reducing emissions of SLCPs are less straightforward to predict. In this paper we consider a set of idealised, extreme mitigation strategies, in which the total anthropogenic emissions of individual SLCP emissions species are removed. This provides an upper bound on the potential climate impacts of such air quality strategies. We focus on evaluating the climate responses to changes in anthropogenic emissions of aerosol precursor species: black carbon (BC), organic carbon (OC) and sulphur dioxide (SO2). We perform climate integrations with four fully coupled atmosphere-ocean global climate models (AOGCMs), and examine the effects on global and regional climate of removing the total land-based anthropogenic emissions of each of the three aerosol precursor species. We find that the SO2 emissions reductions lead to the strongest response, with all three models showing an increase in surface temperature focussed in the northern hemisphere high latitudes, and a corresponding increase in global mean precipitation and run-off. Changes in precipitation and run-off patterns are driven mostly by a northward shift in the ITCZ, consistent with the hemispherically asymmetric warming pattern driven by the emissions changes. The BC and OC emissions reductions give a much weaker forcing signal, and there is some disagreement between models in the sign of the climate responses to these perturbations. These differences between models are due largely to natural variability in sea-ice extent, circulation patterns and cloud changes. This large natural variability component to the signal when the ocean circulation and sea-ice are free-running means that the BC and OC mitigation measures do not necessarily lead to a discernible climate response.

The forms of bioavailability of phosphorus in integrated vertical flow constructed wetland with earthworms and different substrates

A sequential extraction method was utilized to analyze seven forms of P in an integrated vertical-flow constructed wetland (IVFCW) containing earthworms and different substrates. The aluminum-bound P (Al-P) content was found to be lower, and the occluded P (Oc-P) content was higher in the IVFCW. The addition of earthworms into the influent chamber of IVFCW increased the exchange P (Ex-P), iron-bound P (Fe-P), calcium bound P (Ca-P), Oc-P, detritus-bound (De-P) and organic P (Org-P) content in the influent chamber, and also enhanced P content uptake by wetland plants. A significantly positive correlation between P content of above-ground wetland plants and the Ex-P, Fe-P, Oc-P and Org-P content in the rhizosphere was found (P < 0.05), which indicated that the Ex-P, Fe-P, Oc-P and Org-P could be bio-available P. The Ex-P, Fe-P, De-P, Oc-P and Ca-P content of the influent chamber was higher where the substrate contained a mixture of Qing sand and river sand rather than only river sand. Also the IVFCW with earthworms and both Qing sand and river sand had a higher removal efficiency of P, which was related to higher P content uptake by wetland plants and P retained in IVFCW. These findings suggest that addition of earthworms in IVFCW increases the bioavailable P content, resulting in enhanced P content uptake by wetland plants.

Impact of Interbasin Exchange on the Atlantic Overturning Circulation

The ther mohaline exchange between the Atlantic and the Souther n Ocean is analyzed, using a dataset based on WOCE hydrographic data. It is shown that the salt and heat transports brought about by the South Atlantic subtropical gyre play an essential role in the Atlantic heat and salt budgets. It is found that on average the exported North Atlantic Deep W ater (NADW) is fresher than the retur n flows (basically composed of ther mocline and inter mediate water), indicating that the overtur ning circulation (OC) exports freshwater from the Atlantic. The sensitivity of the OC to interbasin fluxes of heat and salt is studied in a 2 D model, representing the Atlantic between 60 8 N and 30 8 S. The model is forced by mixed boundar y conditions at the sur face, and by realistic fluxes of heat and salt at its 30 8 S boundar y. The model circulation tur ns out to be ver y sensitive to net buoyancy fluxes through the sur face. Both net sur face cooling and net sur face saltening are sources of potential energy and impact positively on the circulation strength. The vertical distributions of the lateral fluxes tend to stabilize the stratification, and, as they extract potential energy from the system, tend to weaken the flow . These results imply that a change in the composition of the NADW retur n transports, whether by a change in the ratio ther mocline/inter mediate water , o r by a change in their ther mohaline characteristics, might influence the Atlantic OC considerably . It is also shown that the circulation is much more sensitive to changes in the shape of the lateral buoyancy flux than to changes in the shape of the sur face buoyancy flux, as the latter does not explicitly impact on the potential energy of the system. It is concluded that interocean fluxes of heat and salt are important for the strength and operation of the Atlantic ther mohaline circulation, and should be correctly represented in models that are used for climate sensitivity studies.

Climatology, storm morphologies, and environments of tornadoes in the British Isles: 1980–2012

A climatology is developed for tornadoes during 1980–2012 in the British Isles, defined in this article as England, Scotland, Wales, Northern Ireland, Republic of Ireland, Channel Islands, and the Isle of Man. The climatology includes parent storm type, interannual variability, annual and diurnal cycles, intensities, oc- currence of outbreaks (defined as three or more tornadoes in the same day), geographic distribution, and environmental conditions derived from proximity soundings of tornadoes. Tornado reports are from the Tornado and Storm Research Organization (TORRO). Over the 33 years, there were a mean of 34.3 tor- nadoes and 19.5 tornado days (number of days in which at least one tornado occurred) annually. Tornadoes and tornado outbreaks were most commonly produced from linear storms, defined as radar signatures at least 75 km long and approximately 3 times as long as wide. Most (78%) tornadoes occurred in England. The probability of a tornado within 10 km of a point was highest in the south, southeast, and west of England. On average, there were 2.5 tornado outbreaks every year. Where intensity was known, 95% of tornadoes were classified as F0 or F1 with the remainder classified as F2. There were no tornadoes rated F3 or greater during this time period. Tornadoes occurred throughout the year with a maximum from May through October. Finally, tornadoes tended to occur in low-CAPE, high-shear environments. Tornadoes in the British Isles were difficult to predict using only sounding-derived parameters because there were no clear thresholds between null, tornadic, outbreak, and significant tornado cases.

Reconstructing paleosalinity from δ18O: coupled model simulations of the Last Glacial Maximum, Last Interglacial and Late Holocene

Reconstructions of salinity are used to diagnose changes in the hydrological cycle and ocean circulation. A widely used method of determining past salinity uses oxygen isotope (δOw) residuals after the extraction of the global ice volume and temperature components. This method relies on a constant relationship between δOw and salinity throughout time. Here we use the isotope-enabled fully coupled General Circulation Model (GCM) HadCM3 to test the application of spatially and time-independent relationships in the reconstruction of past ocean salinity. Simulations of the Late Holocene (LH), Last Glacial Maximum (LGM), and Last Interglacial (LIG) climates are performed and benchmarked against existing compilations of stable oxygen isotopes in carbonates (δOc), which primarily reflect δOw and temperature. We find that HadCM3 produces an accurate representation of the surface ocean δOc distribution for the LH and LGM. Our simulations show considerable variability in spatial and temporal δOw-salinity relationships. Spatial gradients are generally shallower but within ∼50% of the actual simulated LH to LGM and LH to LIG temporal gradients and temporal gradients calculated from multi-decadal variability are generally shallower than both spatial and actual simulated gradients. The largest sources of uncertainty in salinity reconstructions are found to be caused by changes in regional freshwater budgets, ocean circulation, and sea ice regimes. These can cause errors in salinity estimates exceeding 4 psu. Our results suggest that paleosalinity reconstructions in the South Atlantic, Indian and Tropical Pacific Oceans should be most robust, since these regions exhibit relatively constant δOw-salinity relationships across spatial and temporal scales. Largest uncertainties will affect North Atlantic and high latitude paleosalinity reconstructions. Finally, the results show that it is difficult to generate reliable salinity estimates for regions of dynamic oceanography, such as the North Atlantic, without additional constraints.