Air pollution modelling using a graphics processing unit with CUDA

The Graphics Processing Unit (GPU) is a powerful tool for parallel computing. In the past years the performance and capabilities of GPUs have increased, and the Compute Unified Device Architecture (CUDA) - a parallel computing architecture - has been developed by NVIDIA to utilize this performance in general purpose computations. Here we show for the first time a possible application of GPU for environmental studies serving as a basement for decision making strategies. A stochastic Lagrangian particle model has been developed on CUDA to estimate the transport and the transformation of the radionuclides from a single point source during an accidental release. Our results show that parallel implementation achieves typical acceleration values in the order of 80-120 times compared to CPU using a single-threaded implementation on a 2.33 GHz desktop computer. Only very small differences have been found between the results obtained from GPU and CPU simulations, which are comparable with the effect of stochastic transport phenomena in atmosphere. The relatively high speedup with no additional costs to maintain this parallel architecture could result in a wide usage of GPU for diversified environmental applications in the near future.Comment: 5 figure

Space life sciences: A status report

The scientific research and supporting technology development conducted in the Space Life Sciences Program is described. Accomplishments of the past year are highlighted. Plans for future activities are outlined. Some specific areas of study include the following: Crew health and safety; What happens to humans in space; Gravity, life, and space; Sustenance in space; Life and planet Earth; Life in the Universe; Promoting good science and good will; Building a future for the space life sciences; and Benefits of space life sciences research

Eulerian and modified Lagrangian approaches to multi-dimensional condensation and collection

Turbulence is argued to play a crucial role in cloud droplet growth. The combined problem of turbulence and cloud droplet growth is numerically challenging. Here, an Eulerian scheme based on the Smoluchowski equation is compared with two Lagrangian superparticle (or su- perdroplet) schemes in the presence of condensation and collection. The growth processes are studied either separately or in combination using either two-dimensional turbulence, a steady flow, or just gravitational acceleration without gas flow. Good agreement between the differ- ent schemes for the time evolution of the size spectra is observed in the presence of gravity or turbulence. Higher moments of the size spectra are found to be a useful tool to characterize the growth of the largest drops through collection. Remarkably, the tails of the size spectra are reasonably well described by a gamma distribution in cases with gravity or turbulence. The Lagrangian schemes are generally found to be superior over the Eulerian one in terms of computational performance. However, it is shown that the use of interpolation schemes such as the cloud-in-cell algorithm is detrimental in connection with superparticle or superdroplet approaches. Furthermore, the use of symmetric over asymmetric collection schemes is shown to reduce the amount of scatter in the results.Comment: 36 pages, 17 figure

Hydrology

In this book, an attempt is made to highlight the recent advances in Hydrology. The several topics examined in this book form the underpinnings of larger-scale considerations, including but not limited to topics such as large-scale hydrologic processes and the evolving field of Critical Zone Hydrology. Computational modeling, data collection, and visualization are additional subjects, among others, examined in the set of topics presented

The Brazilian Developments on the Regional Atmospheric Modeling System (BRAMS 5.2): An Integrated Environmental Model Tuned for Tropical Areas

We present a new version of the Brazilian developments on the Regional Atmospheric Modeling System where different previous versions for weather, chemistry and carbon cycle were unified in a single integrated software system. The new version also has a new set of state-of-the-art physical parameterizations and greater computational parallel and memory usage efficiency. Together with the description of the main features are examples of the quality of the transport scheme for scalars, radiative fluxes on surface and model simulation of rainfall systems over South America in different spatial resolutions using a scale-aware convective parameterization. Besides, the simulation of the diurnal cycle of the convection and carbon dioxide concentration over the Amazon Basin, as well as carbon dioxide fluxes from biogenic processes over a large portion of South America are shown. Atmospheric chemistry examples present model performance in simulating near-surface carbon monoxide and ozone in Amazon Basin and Rio de Janeiro megacity. For tracer transport and dispersion, it is demonstrated the model capabilities to simulate the volcanic ash 3-d redistribution associated with the eruption of a Chilean volcano. Then, the gain of computational efficiency is described with some details. BRAMS has been applied for research and operational forecasting mainly in South America. Model results from the operational weather forecast of BRAMS on 5 km grid spacing in the Center for Weather Forecasting and Climate Studies, INPE/Brazil, since 2013 are used to quantify the model skill of near surface variables and rainfall. The scores show the reliability of BRAMS for the tropical and subtropical areas of South America. Requirements for keeping this modeling system competitive regarding on its functionalities and skills are discussed. At last, we highlight the relevant contribution of this work on the building up of a South American community of model developers

Particulate Matter Dispersion Modeling in Agricultural Applications: Investigation of a Transient Open Source Solver

Agriculture is a major emitter of particulate matter (PM), which causes health problems and can act as a carrier of the pathogen material that spreads diseases. The aim of this study was to investigate an open-source solver that simulates the transport and dispersion of PM for typical agricultural applications. We investigated a coupled Eulerian–Lagrangian solver within the open source software package OpenFOAM. The continuous phase was solved using transient large eddy simulations, where four different subgrid-scale turbulence models and an inflow turbulence generator were tested. The discrete phase was simulated using two different Lagrangian solvers. For the validation case of a turbulent flow of a street canyon, the flowfield could be recaptured very well, with errors of around 5% for the non-equilibrium turbulence models (WALE and dynamicKeq) in the main regions. The inflow turbulence generator could create a stable and accurate boundary layer for the mean vertical velocity and vertical profile of the turbulent Reynolds stresses R11. The validation of the Lagrangian solver showed mixed results, with partly good agreements (simulation results within the measurement uncertainty), and partly high deviations of up to 80% for the concentration of particles. The higher deviations were attributed to an insufficient turbulence regime of the used validation case, which was an experimental chamber. For the simulation case of PM dispersion from manure application on a field, the solver could capture the influence of features such as size and density on the dispersion. The investigated solver is especially useful for further investigations into time-dependent processes in the near-source area of PM sources