Sensitivity of predicted bioaerosol exposure from open windrow composting facilities to ADMS dispersion model parameters

Bioaerosols are released in elevated quantities from composting facilities and are associated with negative health effects, although dose-response relationships are not well understood, and require improved exposure classification. Dispersion modelling has great potential to improve exposure classification, but has not yet been extensively used or validated in this context. We present a sensitivity analysis of the ADMS dispersion model specific to input parameter ranges relevant to bioaerosol emissions from open windrow composting. This analysis provides an aid for model calibration by prioritising parameter adjustment and targeting independent parameter estimation. Results showed that predicted exposure was most sensitive to the wet and dry deposition modules and the majority of parameters relating to emission source characteristics, including pollutant emission velocity, source geometry and source height. This research improves understanding of the accuracy of model input data required to provide more reliable exposure predictions

The importance of understanding computer analyses in civil engineering

Sophisticated computer modelling systems are widely used in civil engineering analysis. This paper takes examples from structural engineering, environmental engineering, flood management and geotechnical engineering to illustrate the need for civil engineers to be competent in the use of computer tools. An understanding of a model's scientific basis, appropriateness, numerical limitations, validation, verification and propagation of uncertainty is required before applying its results. A review of education and training is also suggested to ensure engineers are competent at using computer modelling systems, particularly in the context of risk management. 1. Introductio

Effectiveness of 3D Geoelectrical Resistivity Imaging using Parallel 2D Profiles

Acquisition geometry for 3D geoelectrical resistivity imaging in which apparent resistivity data of a set of parallel 2D profiles are collated to 3D dataset was evaluated. A set of parallel 2D apparent resistivity data was generated over two model structures. The models, horst and trough, simulate the geological environment of a weathered profile and refuse dump site in a crystalline basement complex respectively. The apparent resistivity data were generated for Wenner–alpha, Wenner–beta, Wenner–Schlumberger, dipole–dipole, pole–dipole and pole–pole arrays with minimum electrode separation, a (a = 2, 4, 5 and 10 m) and inter-line spacing, L (L = a, 2a, 2.5a, 4a, 5a and 10a). The 2D apparent resistivity data for each of the arrays were collated to 3D dataset and inverted using a full 3D inversion code. The 3D imaging capability and resolution of the arrays for the set of parallel 2D profiles are presented. Grid orientation effects are observed in the inversion images produced. Inter-line spacing of not greater than four times the minimum electrode separation gives reasonable inverse models. The resolution of the inverse models can be greatly improved if the 3D dataset is built by collating sets of orthogonal 2D profile

Abiotic controls on macroscale variations of humid tropical forest height

Spatial variation of tropical forest tree height is a key indicator of ecological processes associated with forest growth and carbon dynamics. Here we examine the macroscale variations of tree height of humid tropical forests across three continents and quantify the climate and edaphic controls on these variations. Forest tree heights are systematically sampled across global humid tropical forests with more than 2.5 million measurements from Geoscience Laser Altimeter System (GLAS) satellite observations (2004–2008). We used top canopy height (TCH) of GLAS footprints to grid the statistical mean and variance and the 90 percentile height of samples at 0.5 degrees to capture the regional variability of average and large trees globally. We used the spatial regression method (spatial eigenvector mapping-SEVM) to evaluate the contributions of climate, soil and topography in explaining and predicting the regional variations of forest height. Statistical models suggest that climate, soil, topography, and spatial contextual information together can explain more than 60% of the observed forest height variation, while climate and soil jointly explain 30% of the height variations. Soil basics, including physical compositions such as clay and sand contents, chemical properties such as PH values and cation-exchange capacity, as well as biological variables such as the depth of organic matter, all present independent but statistically significant relationships to forest height across three continents. We found significant relations between the precipitation and tree height with shorter trees on the average in areas of higher annual water stress, and large trees occurring in areas with low stress and higher annual precipitation but with significant differences across the continents. Our results confirm other landscape and regional studies by showing that soil fertility, topography and climate may jointly control a significant variation of forest height and influencing patterns of aboveground biomass stocks and dynamics. Other factors such as biotic and disturbance regimes, not included in this study, may have less influence on regional variations but strongly mediate landscape and small-scale forest structure and dynamics.The research was funded by Gabon National Park (ANPN) under the contract of 011-ANPN/2012/SE-LJTW at UCLA. We thank IIASA, FAO, USGS, NASA, Worldclim science teams for making their data available. (011-ANPN/2012/SE-LJTW - Gabon National Park (ANPN) at UCLA

Developing Guidelines for Two-Dimensional Model Review and Acceptance

Two independent modelers ran two hydraulic models, SRH-2D and HEC-RAS 2D. The models were applied to the Lakina River (MP 44 McCarthy Road) and to Quartz Creek (MP 0.7 Quartz Creek Road), which approximately represent straight and bend flow conditions, respectively. We compared the results, including water depth, depth averaged velocity, and bed shear stress, from the two models for both modelers. We found that the extent and density of survey data were insufficient for Quartz Creek. Neither model was calibrated due to the lack of basic field data (i.e., discharge, water surface elevation, and sediment characteristics). Consequently, we were unable to draw any conclusion about the accuracy of the models. Concerning the time step and the equations used (simplified or full) to solve the momentum equation in the HEC-RAS 2D model, we found that the minimum time step allowed by the model must be used if the diffusion wave equation is used in the simulations. A greater time step can be used if the full momentum equation is used in the simulations. We developed a set of guidelines for reviewing model results, and developed and provided a two-day training workshop on the two models for ADOT&PF hydraulic engineers