Cytenamide trifluoroacetic acid solvate

Cytenamide forms a 1:1 solvate with trifluoroacetic acid (systematic name: 5H-dibenzo[a, d] cycloheptatriene-5-carboxamide trifluoroacetic acid solvate), C16H13NO center dot C2HF3O2. The compound crystallizes with one molecule of cytenamide and one of trifluoroacetic acid in the asymmetric unit; these are linked by O-H center dot center dot center dot O and N-H center dot center dot center dot O hydrogen bonds to form an R-2(2)(8) motif. The trifluoromethyl group of the solvent molecule displays rotational disorder over two sites, with site-occupancy factors of 0.964 (4) and 0.036 (4).

Carbamazepine trifluoroacetic acid solvate

Carbamazepine forms a 1:1 solvate with trifluoroacetic acid (systematic name: 5H-dibenzo[b,f] azepine-5-carboxamide trifluoroacetic acid solvate), C(15)H(12)N(2)O center dot C(2)HF(3)O(2). The compound crystallizes with one molecule of carbamazepine and one of trifluoroacetic acid in the asymmetric unit to form an R(2)(2)(8) motif. The solvent molecule is disordered over two sites, with site-occupancy factors 0.53 (1) and 0.47 (1).

Estimating soil water fluxes from soil water records obtained using dielectric sensors

Accurate estimation of the soil water balance (SWB) is important for a number of applications (e.g. environmental, meteorological, agronomical and hydrological). The objective of this study was to develop and test techniques for the estimation of soil water fluxes and SWB components (particularly infiltration, evaporation and drainage below the root zone) from soil water records. The work presented here is based on profile soil moisture data measured using dielectric methods, at 30-min resolution, at an experimental site with different vegetation covers (barley, sunflower and bare soil). Estimates of infiltration were derived by assuming that observed gains in the soil profile water content during rainfall were due to infiltration. Inaccuracies related to diurnal fluctuations present in the dielectric-based soil water records are resolved by filtering the data with adequate threshold values. Inconsistencies caused by the redistribution of water after rain events were corrected by allowing for a redistribution period before computing water gains. Estimates of evaporation and drainage were derived from water losses above and below the deepest zero flux plane (ZFP), respectively. The evaporation estimates for the sunflower field were compared to evaporation data obtained with an eddy covariance (EC) system located elsewhere in the field. The EC estimate of total evaporation for the growing season was about 25% larger than that derived from the soil water records. This was consistent with differences in crop growth (based on direct measurements of biomass, and field mapping of vegetation using laser altimetry) between the EC footprint and the area of the field used for soil moisture monitoring. Copyright (c) 2007 John Wiley & Sons, Ltd.

Estimating uncertainty in terrestrial critical loads and their exceedances at four sites in the UK

Critical loads are the basis for policies controlling emissions of acidic substances in Europe and elsewhere. They are assessed by several elaborate and ingenious models, each of which requires many parameters, and have to be applied on a spatially-distributed basis. Often the values of the input parameters are poorly known, calling into question the validity of the calculated critical loads. This paper attempts to quantify the uncertainty in the critical loads due to this "parameter uncertainty", using examples from the UK. Models used for calculating critical loads for deposition of acidity and nitrogen in forest and heathland ecosystems were tested at four contrasting sites. Uncertainty was assessed by Monte Carlo methods. Each input parameter or variable was assigned a value, range and distribution in an objective a fashion as possible. Each model was run 5000 times at each site using parameters sampled from these input distributions. Output distributions of various critical load parameters were calculated. The results were surprising. Confidence limits of the calculated critical loads were typically considerably narrower than those of most of the input parameters. This may be due to a "compensation of errors" mechanism. The range of possible critical load values at a given site is however rather wide, and the tails of the distributions are typically long. The deposition reductions required for a high level of confidence that the critical load is not exceeded are thus likely to be large. The implication for pollutant regulation is that requiring a high probability of non-exceedance is likely to carry high costs. The relative contribution of the input variables to critical load uncertainty varied from site to site: any input variable could be important, and thus it was not possible to identify variables as likely targets for research into narrowing uncertainties. Sites where a number of good measurements of input parameters were available had lower uncertainties, so use of in situ measurement could be a valuable way of reducing critical load uncertainty at particularly valuable or disputed sites. From a restricted number of samples, uncertainties in heathland critical loads appear comparable to those of coniferous forest, and nutrient nitrogen critical loads to those of acidity. It was important to include correlations between input variables in the Monte Carlo analysis, but choice of statistical distribution type was of lesser importance. Overall, the analysis provided objective support for the continued use of critical loads in policy development. (c) 2007 Elsevier B.V. All rights reserved.

Estimating surface net solar radiation by use of Landsat-5 TM and digital elevation models

The ground surface net solar radiation is the energy that drives physical and chemical processes at the ground surface. In this paper, multi-spectral data from the Landsat-5 TM, topographic data from a gridded digital elevation model, field measurements, and the atmosphere model LOWTRAN 7 are used to estimate surface net solar radiation over the FIFE site. Firstly an improved method is presented and used for calculating total surface incoming radiation. Then, surface albedo is integrated from surface reflectance factors derived from remotely sensed data from Landsat-5 TM. Finally, surface net solar radiation is calculated by subtracting surface upwelling radiation from the total surface incoming radiation.

Estimating relationships between air mass origin and chemical composition

Observations of a chemical at a point in the atmosphere typically show sudden transitions between episodes of high and low concentration. Often these are associated with a rapid change in the origin of air arriving at the site. Lagrangian chemical models riding along trajectories can reproduce such transitions, but small timing errors from trajectory phase errors dramatically reduce the correlation between modeled concentrations and observations. Here the origin averaging technique is introduced to obtain maps of average concentration as a function of air mass origin for the East Atlantic Summer Experiment 1996 (EASE96, a ground-based chemistry campaign). These maps are used to construct origin averaged time series which enable comparison between a chemistry model and observations with phase errors factored out. The amount of the observed signal explained by trajectory changes can be quantified, as can the systematic model errors as a function of air mass origin. The Cambridge Tropospheric Trajectory model of Chemistry and Transport (CiTTyCAT) can account for over 70% of the observed ozone signal variance during EASE96 when phase errors are side-stepped by origin averaging. The dramatic increase in correlation (from 23% without averaging) cannot be achieved by time averaging. The success of the model is attributed to the strong relationship between changes in ozone along trajectories and their origin and its ability to simulate those changes. The model performs less well for longer-lived chemical constituents because the initial conditions 5 days before arrival are insufficiently well known.

Estimating the potential yield of small wind turbines in urban areas: a case study for Greater London, UK

To optimise the placement of small wind turbines in urban areas a detailed understanding of the spatial variability of the wind resource is required. At present, due to a lack of observations, the NOABL wind speed database is frequently used to estimate the wind resource at a potential site. However, recent work has shown that this tends to overestimate the wind speed in urban areas. This paper suggests a method for adjusting the predictions of the NOABL in urban areas by considering the impact of the underlying surface on a neighbourhood scale. In which, the nature of the surface is characterised on a 1 km2 resolution using an urban morphology database. The model was then used to estimate the variability of the annual mean wind speed across Greater London at a height typical of current small wind turbine installations. Initial validation of the results suggests that the predicted wind speeds are considerably more accurate than the NOABL values. The derived wind map therefore currently provides the best opportunity to identify the neighbourhoods in Greater London at which small wind turbines yield their highest energy production. The model does not consider street scale processes, however previously derived scaling factors can be applied to relate the neighbourhood wind speed to a value at a specific rooftop site. The results showed that the wind speed predicted across London is relatively low, exceeding 4 ms-1 at only 27% of the neighbourhoods in the city. Of these sites less than 10% are within 10 km of the city centre, with the majority over 20 km from the city centre. Consequently, it is predicted that small wind turbines tend to perform better towards the outskirts of the city, therefore for cities which fit the Burgess concentric ring model, such as Greater London, ‘distance from city centre’ is a useful parameter for siting small wind turbines. However, there are a number of neighbourhoods close to the city centre at which the wind speed is relatively high and these sites can only been identified with a detailed representation of the urban surface, such as that developed in this study.

The curious case of the camelthorn: competition, coexistence and nest-site limitation in a multispecies mutualism

Myrmecophyte plants house ants in domatia in exchange for protection from herbivores. Ant-myrmecophyte mutualisms exhibit two general patterns due to competition between ants for plant occupancy: i) domatia nest-sites are a limiting resource and ii) each individual plant hosts one ant species at a time. However, individual camelthorn trees (Vachellia erioloba) typically host two to four ant species simultaneously, often coexisting in adjacent domatia on the same branch. Such fine-grain spatial coexistence brings into question the conventional wisdom on ant-myrmecophyte mutualisms. Camelthorn ants appear not to be nest-site limited, despite low abundance of suitable domatia, and have random distributions of nest-sites within and across trees. These patterns suggest a lack of competition between ants for domatia and contrast strongly with other ant-myrmecophyte systems. Comparison of this unusual case with others suggests that spatial scale is crucial to coexistence or competitive exclusion involving multiple ant species. Furthermore, coexistence may be facilitated when co-occurring ant species diverge strongly on at least one niche axis. Our conclusions provide recommendations for future ant-myrmecophyte research, particularly in utilising multispecies systems to further our understanding of mutualism biology.

A multi-instrument comparison of integrated water vapour measurements at a high latitude site

We compare measurements of integrated water vapour (IWV) over a subarctic site (Kiruna, Northern Sweden) from five different sensors and retrieval methods: Radiosondes, Global Positioning System (GPS), ground-based Fourier-transform infrared (FTIR) spectrometer, ground-based microwave radiometer, and satellite-based microwave radiometer (AMSU-B). Additionally, we compare also to ERA-Interim model reanalysis data. GPS-based IWV data have the highest temporal coverage and resolution and are chosen as reference data set. All datasets agree reasonably well, but the ground-based microwave instrument only if the data are cloud-filtered. We also address two issues that are general for such intercomparison studies, the impact of different lower altitude limits for the IWV integration, and the impact of representativeness error. We develop methods for correcting for the former, and estimating the random error contribution of the latter. A literature survey reveals that reported systematic differences between different techniques are study-dependent and show no overall consistent pattern. Further improving the absolute accuracy of IWV measurements and providing climate-quality time series therefore remain challenging problems.