Interactions between the physical soil environment and a horizontal ground coupled heat pump, for a domestic site in the UK

There is currently an increased interest of Government and Industry in the UK, as well as at the European Community level and International Agencies (i.e. Department of Energy, American International Energy Agency), to improve the performance and uptake of Ground Coupled Heat Pumps (GCHP), in order to meet the 2020 renewable energy target. A sound knowledge base is required to help inform the Government Agencies and advisory bodies; detailed site studies providing reliable data for model verification have an important role to play in this. In this study we summarise the effect of heat extraction by a horizontal ground heat exchanger (installed at 1 m depth) on the soil physical environment (between 0 and 1 m depth) for a site in the south of the UK. Our results show that the slinky influences the surrounding soil by significantly decreasing soil temperatures. Furthermore, soil moisture contents were lower for the GCHP soil profile, most likely due to temperature-gradient related soil moisture migration effects and a decreased hydraulic conductivity, the latter as a result of increased viscosity (caused by the lower temperatures for the GCHP soil profile). The effects also caused considerable differences in soil thermal properties. This is the first detailed mechanistic study conducted in the UK with the aim to understand the interactions between the soil, horizontal heat exchangers and the aboveground environment. An increased understanding of these interactions will help to achieve an optimum and sustainable use of the soil heat resources in the future. The results of this study will help to calibrate and verify a simulation model that will provide UK-wide recommendations to improve future GCHP uptake and performance, while safeguarding the soil physical resources.

Plasmodiophora brassicae in its Environment

Plasmodiophora brassicae Wor. is viewed in this article from the standpoint of a highly evolved and successful organism, well fitted for the ecological niche that it occupies. Physical, chemical, and biological components of the soil environment are discussed in relation to their effects on the survival, growth, and reproduction of this microbe. It is evident that P. brassicae is well equipped by virtue of its robust resting spores for survival through many seasonal cycles. Germination is probably triggered as a result of signals initiated by root exudates. The resultant motile zoospore moves rapidly to the root hair surface and penetration and colonization follow. The short period between germination and penetration is one of greatest vulnerability for P. brassicae. In this phase survival is affected at the very least by soil texture and structure; its moisture; pH; calcium, boron, and nitrogen content; and the presence of active microbial antagonists. These factors influence the inoculum potential (sensu Garrett, 1956) and its viability and invasive capacity. There is evidence that these effects may also influence differentially the survival of some physiologic races of P. brassicae. Considering the interaction of P. brassicae with the soil environment from the perspective of its biological fitness is an unusual approach; most authors consider only the opportunities to destroy this organism. The approach adopted here is borne of several decades spent studying P. brassicae and the respect that has been engendered for it as a biological entity. This review stops at the point of penetration, although some of the implications of the environment for successful colonization are included because they form a continuum. Interactions with the molecular and biochemical cellular environment are considered in other sections in this special edition.

Parallel implementation and one year experiments with the Danish Eulerian Model

Large scale air pollution models are powerful tools, designed to meet the increasing demand in different environmental studies. The atmosphere is the most dynamic component of the environment, where the pollutants can be moved quickly on far distnce. Therefore the air pollution modeling must be done in a large computational domain. Moreover, all relevant physical, chemical and photochemical processes must be taken into account. In such complex models operator splitting is very often applied in order to achieve sufficient accuracy as well as efficiency of the numerical solution. The Danish Eulerian Model (DEM) is one of the most advanced such models. Its space domain (4800 × 4800 km) covers Europe, most of the Mediterian and neighboring parts of Asia and the Atlantic Ocean. Efficient parallelization is crucial for the performance and practical capabilities of this huge computational model. Different splitting schemes, based on the main processes mentioned above, have been implemented and tested with respect to accuracy and performance in the new version of DEM. Some numerical results of these experiments are presented in this paper.

Post-occupancy studies of an office environment: Energy performance and occupants’ satisfaction

It is generally accepted that the physical workplace environment affects employees’ satisfaction and, consequently, their perceived productivity and well-being. This study investigated whether employee “satisfaction” variables can predict perceived productivity, well-being and enjoyment at work, and if so, to what extent. The study also explored whether limiting employees’ control over their environment could save energy without compromising employees’ satisfaction and perceived productivity. Preoccupancy and post-occupancy evaluation studies were conducted, in terms of both energy consumption and employee perceptions, to make comparisons between a company’s old and current headquarters buildings, both located in the same area of London. The results showed that employees were more satisfied with their work environment at their new HQ, in general, than with that of their previous office. Also, employees’ self-reported productivity, well-being and enjoyment at work improved after the move. It was revealed that the combination of employees’ level of satisfaction with “interior use of space” and “physical conditions” was the best predictor of their perceived productivity, while satisfaction with “indoor facilities” was not a good predictor. In terms of energy performance, although the new HQ’s energy consumption per m2 was significantly less than that of the previous building, there was still a gap between the refurbishment design target and the actual performance of the building. The findings suggest that this gap could be due to a number of factors, including an ineffective use of interior space, and occupants’ behaviour.

The relationship between diffuse spectral reflectance of the soil and its cation exchange capacity is scale-dependent

Diffuse reflectance spectroscopy (DRS) is increasingly being used to predict numerous soil physical, chemical and biochemical properties. However, soil properties and processes vary at different scales and, as a result, relationships between soil properties often depend on scale. In this paper we report on how the relationship between one such property, cation exchange capacity (CEC), and the DRS of the soil depends on spatial scale. We show this by means of a nested analysis of covariance of soils sampled on a balanced nested design in a 16 km × 16 km area in eastern England. We used principal components analysis on the DRS to obtain a reduced number of variables while retaining key variation. The first principal component accounted for 99.8% of the total variance, the second for 0.14%. Nested analysis of the variation in the CEC and the two principal components showed that the substantial variance components are at the > 2000-m scale. This is probably the result of differences in soil composition due to parent material. We then developed a model to predict CEC from the DRS and used partial least squares (PLS) regression do to so. Leave-one-out cross-validation results suggested a reasonable predictive capability (R2 = 0.71 and RMSE = 0.048 molc kg− 1). However, the results from the independent validation were not as good, with R2 = 0.27, RMSE = 0.056 molc kg− 1 and an overall correlation of 0.52. This would indicate that DRS may not be useful for predictions of CEC. When we applied the analysis of covariance between predicted and observed we found significant scale-dependent correlations at scales of 50 and 500 m (0.82 and 0.73 respectively). DRS measurements can therefore be useful to predict CEC if predictions are required, for example, at the field scale (50 m). This study illustrates that the relationship between DRS and soil properties is scale-dependent and that this scale dependency has important consequences for prediction of soil properties from DRS data

Analysis and application of ichnofabrics

Bioturbation at all scales, which tends to replace the primary fabric of a sediment by the ichnofabric (the overall fabric of a sediment that has been bioturbated), is now recognised as playing a major role in facies interpretation. The manner in which the substrate may be colonized, and the physical, chemical and ecological controls (grainsize, sedimentation rate, oxygenation, nutrition, salinity, ethology, community structure and succession), together with the several ways in which the substrate is tiered by bioturbators, are the factors and processes that determine the nature of the ichnofabric. Eleven main styles of substrate tiering are described, ranging from single, pioneer colonization to complex tiering under equilibria, their modification under environmental deterioration and amelioration, and diagenetic enhancement or obscuration. Ichnofabrics may be assessed by four attributes: primary sedimentary factors, Bioturbation Index (BI), burrow size and frequency, and ichnological diversity. Construction of tier and ichnofabric constituent diagrams aid visualization and comparison. The breaks or changes in colonization and style of tiering at key stratal surfaces accentuate the surfaces, and many reflect a major environmental shift of the trace-forming biota. due to change in hydrodynamic regime (leading to non-deposition and/or erosion and/or lithification), change in salinity regime, or subaerial exposure. The succession of gradational or abrupt changes in ichnofabric through genetically related successions, together with changes in colonization and tiering across event beds, may also be interpreted in terms of changes in environmental parameters. It is not the ichnotaxa per se that are important in discriminating between ichnofabrics, but rather the environmental conditions that determine the overall style of colonization. Fabrics composed of different ichnotaxa (and different taphonomies) but similar tier structure and ichnoguild may form in similar environments of different age or different latitude. Appreciation of colonization and tiering styles places ancient ichnofabrics on a sound processrelated basis for environmental interpretation. (C) 2002 Elsevier Science B.V. All rights reserved.

Computational complexity of weighted splitting schemes on parallel computers

In models of complicated physical-chemical processes operator splitting is very often applied in order to achieve sufficient accuracy as well as efficiency of the numerical solution. The recently rediscovered weighted splitting schemes have the great advantage of being parallelizable on operator level, which allows us to reduce the computational time if parallel computers are used. In this paper, the computational times needed for the weighted splitting methods are studied in comparison with the sequential (S) splitting and the Marchuk-Strang (MSt) splitting and are illustrated by numerical experiments performed by use of simplified versions of the Danish Eulerian model (DEM).

The power of NMR.: in two and three dimensions

Soon after its discovery in the 1950s, NMR had become an indispensable tool fr chemists. In the 1970s and 1980s, the power of the technique was extended from one dimension to two and even three dimensions, opening up exciting applkications in both chemistry and biochemistry. the success of one dimensional. high-resolution NMR stems from the unique insights that it can provide about molecular structure. The chemical shift of a nucleus gives invaluable information abut the chemical environment in which that nucleus is located, Coupling interactions between hydorgen nuclei, as revealed by characteristic splitting patterns inthe 1H-NMR spectrum, provide informaton about the loaction of one group of hydorgen atoms relative to others inthe molecule. And the nuclearf Overhauser effect (nOe) can shed light on molecular stereochemistry.

Coordination behavior of symmetrical hexadentate O2N2S2-donor Schiff bases toward zinc (II): synthesis, characterization, and crystal structure

Two series of zinc(II) complexes of two Schiff bases (H2L1 and H2L2) formulated as [Zn(HL1/HL2)]ClO4 (1a and 1b) and [Zn(L1/L2)] (2a and 2b), where H2L1 = 1,8-bis(salicylideneamino)-3,6-dithiaoctane and H2L2 = 1,9-bis(salicylideneamino)-3,7-dithianonane, have been prepared and isolated in pure form by changing the chemical environment. Elemental, spectral, and other physicochemical results characterize the complexes. A single crystal X-ray diffraction study confirms the structure of [Zn(HL1)]ClO4 (1a). In 1a, zinc(II) has a distorted octahedral environment with a ZnO2N2S2 chromophore.

Highly resolved observations of trace gases in the lowermost stratosphere and upper troposphere from the SPURT project: an overview

During SPURT (Spurenstofftransport in der Tropopausenregion, trace gas transport in the tropopause region) we performed measurements of a wide range of trace gases with different lifetimes and sink/source characteristics in the northern hemispheric upper troposphere (UT) and lowermost stratosphere (LMS). A large number of in-situ instruments were deployed on board a Learjet 35A, flying at altitudes up to 13.7 km, at times reaching to nearly 380 K potential temperature. Eight measurement campaigns (consisting of a total of 36 flights), distributed over all seasons and typically covering latitudes between 35° N and 75° N in the European longitude sector (10° W–20° E), were performed. Here we present an overview of the project, describing the instrumentation, the encountered meteorological situations during the campaigns and the data set available from SPURT. Measurements were obtained for N2O, CH4, CO, CO2, CFC12, H2, SF6, NO, NOy, O3 and H2O. We illustrate the strength of this new data set by showing mean distributions of the mixing ratios of selected trace gases, using a potential temperature-equivalent latitude coordinate system. The observations reveal that the LMS is most stratospheric in character during spring, with the highest mixing ratios of O3 and NOy and the lowest mixing ratios of N2O and SF6. The lowest mixing ratios of NOy and O3 are observed during autumn, together with the highest mixing ratios of N2O and SF6 indicating a strong tropospheric influence. For H2O, however, the maximum concentrations in the LMS are found during summer, suggesting unique (temperature- and convection-controlled) conditions for this molecule during transport across the tropopause. The SPURT data set is presently the most accurate and complete data set for many trace species in the LMS, and its main value is the simultaneous measurement of a suite of trace gases having different lifetimes and physical-chemical histories. It is thus very well suited for studies of atmospheric transport, for model validation, and for investigations of seasonal changes in the UT/LMS, as demonstrated in accompanying and elsewhere published studies.

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 DACCIWA project: dynamics-aerosol-chemistry-cloud interactions in West Africa

Massive economic and population growth, and urbanization are expected to lead to a tripling of anthropogenic emissions in southern West Africa (SWA) between 2000 and 2030. However, the impacts of this on human health, ecosystems, food security, and the regional climate are largely unknown. An integrated assessment is challenging due to (a) a superposition of regional effects with global climate change, (b) a strong dependence on the variable West African monsoon, (c) incomplete scientific understanding of interactions between emissions, clouds, radiation, precipitation, and regional circulations, and (d) a lack of observations. This article provides an overview of the DACCIWA (Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa) project. DACCIWA will conduct extensive fieldwork in SWA to collect high-quality observations, spanning the entire process chain from surface-based natural and anthropogenic emissions to impacts on health, ecosystems, and climate. Combining the resulting benchmark dataset with a wide range of modeling activities will allow (a) assessment of relevant physical, chemical, and biological processes, (b) improvement of the monitoring of climate and atmospheric composition from space, and (c) development of the next generation of weather and climate models capable of representing coupled cloud-aerosol interactions. The latter will ultimately contribute to reduce uncertainties in climate predictions. DACCIWA collaborates closely with operational centers, international programs, policy-makers, and users to actively guide sustainable future planning for West Africa. It is hoped that some of DACCIWA’s scientific findings and technical developments will be applicable to other monsoon regions.

PMIP4-CMIP6: the contribution of the Paleoclimate Modelling Intercomparison Project to CMIP6

The goal of the Palaeoclimate Modelling Intercomparison Project (PMIP) is to understand the response of the climate system to changes in different climate forcings and to feedbacks. Through comparison with observations of the environmental impacts of these climate changes, or with climate reconstructions based on physical, chemical or biological records, PMIP also addresses the issue of how well state-of-the-art models simulate climate changes. Palaeoclimate states are radically different from those of the recent past documented by the instrumental record and thus provide an out-of-sample test of the models used for future climate projections and a way to assess whether they have the correct sensitivity to forcings and feedbacks. Five distinctly different periods have been selected as focus for the core palaeoclimate experiments that are designed to contribute to the objectives of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). This manuscript describes the motivation for the choice of these periods and the design of the numerical experiments, with a focus upon their novel features compared to the experiments performed in previous phases of PMIP and CMIP as well as the benefits of common analyses of the models across multiple climate states. It also describes the information needed to document each experiment and the model outputs required for analysis and benchmarking.