The Lagrangian particle dispersion model FLEXPART was originally designed for calculating long-range and mesoscale dispersion of air pollutants from point sources, such that occurring after an accident in a nuclear power plant. In the meantime, FLEXPART has evolved into a comprehensive tool for atmospheric transport modeling and analysis at different scales. A need for further multiscale modeling and analysis has encouraged new developments in FLEXPART. In this paper, we present a FLEXPART version that works with the Weather Research and Forecasting (WRF) mesoscale meteorological model. We explain how to run this new model and present special options and features that differ from those of the preceding versions. For instance, a novel turbulence scheme for the convective boundary layer has been included that considers both the skewness of turbulence in the vertical velocity as well as the vertical gradient in the air density. To our knowledge, FLEXPART is the first model for which such a scheme has been developed. On a more technical level, FLEXPART-WRF now offers effective parallelization, and details on computational performance are presented here. FLEXPART-WRF output can either be in binary or Network Common Data Form (NetCDF) format, both of which have efficient data compression. In addition, test case data and the source code are provided to the reader as a Supplement. This material and future developments will be accessible at http://www.flexpart.eu.Peer ReviewedPostprint (published version
The Lagrangian particle dispersion model FLEX-PART in its original version in the mid-1990s was designed for calculating the long-range and mesoscale dispersion of hazardous substances from point sources, such as those released after an accident in a nuclear power plant. Over the past decades, the model has evolved into a comprehensive tool for multi-scale atmospheric transport modeling and analysis and has attracted a global user community. Its application fields have been extended to a large range of atmospheric gases and aerosols, e.g., greenhouse gases, short-lived climate forcers like black carbon and volcanic ash, and it has also been used to study the atmospheric branch of the water cycle. Given suitable meteorological input data, it can be used for scales from dozens of meters to global. In particular, inverse modeling based on source-receptor relationships from FLEXPART has become widely used. In this paper, we present FLEXPART version 10.4, which works with meteorological input data from the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) and data from the United States National Cen-ters of Environmental Prediction (NCEP) Global Forecast System (GFS). Since the last publication of a detailed FLEX-PART description (version 6.2), the model has been improved in different aspects such as performance, physicochemical parameterizations, input/output formats, and available preprocessing and post-processing software. The model code has also been parallelized using the Message Passing Interface (MPI). We demonstrate that the model scales well up to using 256 processors, with a parallel efficiency greater than 75 % for up to 64 processes on multiple nodes in runs with very large numbers of particles. The deviation from 100 % efficiency is almost entirely due to the remaining nonparallelized parts of the code, suggesting large potential for further speedup. A new turbulence scheme for the convective boundary layer has been developed that considers the skewness in the vertical velocity distribution (updrafts and downdrafts) and vertical gradients in air density. FLEXPART is the only model available considering both effects, making it highly accurate for small-scale applications, e.g., to quantify dispersion in the vicinity of a point source. The wet deposi-Published by Copernicus Publications on behalf of the European Geosciences Union. 4956 I. Pisso et al.: FLEXPART version 10.4tion scheme for aerosols has been completely rewritten and a new, more detailed gravitational settling parameterization for aerosols has also been implemented. FLEXPART has had the option of running backward in time from atmospheric concentrations at receptor locations for many years, but this has now been extended to also work for deposition values and may become useful, for instance, for the interpretation of ice core measurements. To our knowledge, to date FLEX-PART is the only model with that capability. Furthermore, the temporal variation and temperature dependence of chemical reactions with ...
Abstract. The Lagrangian particle dispersion model FLEXPART was in its original version in the mid-1990s designed for calculating the long-range and mesoscale dispersion of hazardous substances from point sources, such as released after an accident in a nuclear power plant. Over the past decades, the model has evolved into a comprehensive tool for multi-scale atmospheric transport modelling and analysis and has attracted a global user community. Its application fields have been extended to a large range of atmospheric gases and aerosols, e.g. greenhouse gases, short-lived climate forcers like black carbon, or volcanic emissions, and it has also been used to study the atmospheric branch of the water cycle. Given suitable meteorological input data, it can be used for scales from dozens of meters to the global scale. In particular, inverse modelling based on source-receptor relationships from FLEXPART has become widely used. In this paper, we present FLEXPART version 10.3, which works with meteorological input data from the European Centre for Medium-Range Weather Forecasts' (ECMWF) Integrated Forecast System (IFS), and data from the United States' National Centers of Environmental Prediction (NCEP) Global Forecast System (GFS). Since the last publication of a detailed FLEXPART description (version 6.2), the model has been improved in different aspects such as performance, physico-chemical parametrizations, input/output formats and available pre- and post-processing software. The model code has also been parallelized using the Message Passing Interface (MPI). We demonstrate that the model scales well up to using 256 processors, with a parallel efficiency greater than 75 % for up to 64 processes on multiple nodes. The deviation from 100 % efficiency is almost entirely due to remaining non-parallelized parts of the code, suggesting large potential for further speed-up. A new turbulence scheme for the convective boundary layer has been developed that considers the skewness in the vertical velocity distribution (updrafts and downdrafts) and vertical gradients in air density. FLEXPART is the only model available considering both effects, making it highly accurate for small-scale applications, e.g. to quantify dispersion in the vicinity of a point source. The wet deposition scheme for aerosols has been completely rewritten and a new, more detailed gravitational settling parameterization for aerosols has also been implemented. FLEXPART has had the option for running backward in time from atmospheric concentrations at receptor locations since many years, but this has now been extended to work also for deposition values and may become useful, for instance, for the interpretation of ice core measurements. To our knowledge, to date FLEXPART is the only model with that capability. Furthermore, temporal variation and temperature dependence of chemical reactions with the OH radical have been included, allowing more accurate simulations for species with intermediate lifetimes against the reaction with OH, such as ethane. Finally, user settings can now be specified in a more flexible namelist format, and output files can be produced in NetCDF format instead of FLEXPART's customary binary format. In this paper, we describe these new developments. Moreover, we present some tools for the preparation of the meteorological input data and for processing of FLEXPART output data and briefly report on alternative FLEXPART versions.
Perfused rat hearts show a markedly increased binding of phosphofructokinase and fructose-bisphosphate aldolase as a consequence of ischaemia, but little change in binding of pyruvate kinase, lactate dehydrogenase or glyceraldehyde-3-phosphate dehydrogenase. After 10 min ischaemia over one quarter of the phosphofructokinase and three quarters of the aldolase are bound. The effect of anoxia is less well marked in its influence on binding with only aldolase showing a significant increase in binding. These results suggest that one factor involved in the increased binding during ischaemia is the fall in p H of the heart. Binding studies with isolated myofibrils confirm that the affinity and stoichiometry of aldolase binding are considerably increased as the pH is lowered over a range comparable to that which occurs in ischaemic heart. The low level of binding of glyceraldehyde-3-phosphate dehydrogenase in perfused rat hearts correlates with the relatively low affinity of this enzyme for binding to rat or rabbit cardiac myofibrils. There are species differences in the enzyme binding response to ischaemia. Sheep hearts show rapid and large increases in the binding of glyceraldehyde-3-phosphate dehydrogenase in addition to changes in aldolase and phosphofructokinase binding. The greater binding of glyceraldehyde-3-phosphate dehydrogenase reflects the greater affinity of sheep cardiac myofibrils. It is suggested that the altered metabolic demands of ischaemia are satisfied by changes in glycolytic enzyme organisation as the enzymes shift from the soluble to the particulate phase of cardiac muscle.Pette and co-workers first demonstrated an association between glycolytic enzymes and the I-band of cardiac muscle [I] and this localisation was shown to be general [l -31 for striated muscle. F-actin, the main structural protein of the I-band, was shown to bind phosphofructokinase, fructose-bisphosphate aldolase, glyceraldehyde-3-phosphate dehydrogenase, pyruvate kinase, lactate dehydrogenase and a number of other glycolytic enzymes 14-61. Subsequently we have shown that the accessory I-band proteins, tropomyosin and troponin, are also sites for enzyme binding and that this binding can be observed at physiologically relevant ionic strengths [7 -121.It has been suggested [5, 71 that a reversible interaction of glycolytic enzymes with structural proteins could constitute an effective mechanism for metabolic control as the kinetic parameters of some enzymes are known to alter on binding. If such mechanisms are operative, then the degree of enzyme association with structural components might be expected to vary depending on the metabolic state of the muscle. Earlier reports [13,14] from these laboratories have shown that in both ovine and bovine skeletal muscle there is an appreciable binding of a range of glycolytic enzymes notably phosphofructokinase, aldolase and glyceraldehyde-3-phosphate dehydrogenase and this binding is markedly increased upon electrical stimulation. In the live animal the increased binding is rapidly rev...
The extent of binding of glycolytic enzymes to the particulate fraction of homogenates was measured in bovine psoas muscle before and after electrical stimulation. In association with an accelerated glycolytic rate on stimulation, there was a significant increase in the binding of certain glycolytic enzymes, the most notable of which were phosphofructokinase, aldolase, glyceraldehyde 3-phosphate dehydrogenase and pyruvate kinase. From the known association of glycolytic enzymes with the I-band of muscle it is proposed that electrical stimulation of anaerobic muscle increases enzyme binding to actin filaments. Calculations of the extent of enzyme binding suggest that significant amounts of enzyme protein, particularly aldolase and glyceraldehyde 3-phosphate dehydrogenase, are associated with the actin filaments. The results also imply that kinetic parameters derived from considerations of the enzyme activity in the soluble state may not have direct application to the situation in the muscle fibre, particularly during accelerated glycolysis.
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