Development and verification of a screening model for surface spreading of petroleum

Overflows and leakage from aboveground storage tanks and pipelines carrying crude oil and petroleum products occur frequently. The spilled hydrocarbons pose environmental threats by contaminating the surrounding soil and the underlying ground water. Predicting the fate and transport of these chemicals is required for environmental risk assessment and for remedial measure design. The present paper discusses the formulation and application of the Oil Surface Flow Screening Model (OILSFSM) for predicting the surface flow of oil by taking into account infiltration and evaporation. Surface flow is simulated using a semi-analytical model based on the lubrication theory approximation of viscous flow. Infiltration is simulated using a version of the Green and Ampt infiltration model, which is modified to account for oil properties. Evaporation of volatile compounds is simulated using a compositional model that accounts for the changes in the fraction of each compound in the spilled oil. The coupling between surface flow, infiltration and evaporation is achieved by incorporating the infiltration and evaporation fluxes into the global continuity equation of the spilled oil. The model was verified against numerical models for infiltration and analytical models for surface flow. The verification study demonstrates the applicability of the model.     

Assessment of contribution of SO2 and NO2 from different sources in Jamshedpur region, India

Contribution of pollution from different types of sources in Jamshedpur, the steel city of India, has been estimated in winter 1993 using two approaches in order to delineate and prioritize air quality management strategies for the development of region in an environmental friendly manner. The first approach mainly aims at preparation of a comprehensive emission inventory and estimation of spatial distribution of pollution loads in terms of SO₂ and NO₂ from different types of industrial, domestic and vehicular sources in the region. The results indicate that industrial sources account for 77% and 68% of the total emissions of SO₂ and NO₂, respectively, in the region, whereas vehicular emissions contributed to about 28% of the total NO₂ emissions. In the second approach, contribution of these sources to ambient air quality levels to which the people are exposed to, was assessed through air pollution dispersion modelling. Ambient concentration levels of SO₂ and NO₂ have been predicted in winter season using the ISCST3 model. The analysis indicates that emissions from industrial sources are responsible for more than 50% of the total SO₂ and NO₂ concentration levels. Vehicular activities contributed to about 40% of NO₂ pollution and domestic fuel combustion contributed to about 38% of SO₂ pollution. Predicted 24-h concentrations were compared with measured concentrations at 11 ambient air monitoring stations and good agreement was noted between the two values. In-depth zone-wise analysis of the above indicates that for effective air quality management, industrial source emissions should be given highest priority, followed by vehicular and domestic sources in Jamshedpur region.     

Review and comparison of methods to study the contribution of variables in artificial neural network models

Convinced by the predictive quality of artificial neural network (ANN) models in ecology, we have turned our interests to their explanatory capacities. Seven methods which can give the relative contribution and/or the contribution profile of the input factors were compared: (i) the ‘PaD’ (for Partial Derivatives) method consists in a calculation of the partial derivatives of the output according to the input variables; (ii) the ‘Weights’ method is a computation using the connection weights; (iii) the ‘Perturb’ method corresponds to a perturbation of the input variables; (iv) the ‘Profile’ method is a successive variation of one input variable while the others are kept constant at a fixed value; (v) the ‘classical stepwise’ method is an observation of the change in the error value when an adding (forward) or an elimination (backward) step of the input variables is operated; (vi) ‘Improved stepwise a’ uses the same principle as the classical stepwise, but the elimination of the input occurs when the network is trained, the connection weights corresponding to the input variable studied is also eliminated; (vii) ‘Improved stepwise b’ involves the network being trained and fixed step by step, one input variable at its mean value to note the consequences on the error. The data tested in this study concerns the prediction of the density of brown trout spawning redds using habitat characteristics. The PaD method was found to be the most useful as it gave the most complete results, followed by the Profile method that gave the contribution profile of the input variables. The Perturb method allowed a good classification of the input parameters as well as the Weights method that has been simplified but these two methods lack stability. Next came the two improved stepwise methods (a and b) that both gave exactly the same result but the contributions were not sufficiently expressed. Finally, the classical stepwise methods gave the poorest results.     

A Minimal Model of Adiabatic Isotherms Surfacing in Very Shallow Waters

Based on a phenomenology that is rather frequent in the Gulf of Trieste (Northern Adriatic Sea), we analytically model the short time evolution of the temperature field inside a shallow layer of coastal water induced by a sudden offshore wind. In particular, we reproduce in a very simple way the unsteady surfacing of the isotherms forced by the marine current circulating in a vertical plane perpendicular to the coastline. The model is in agreement with the observations of a significant event recorded on 25 June, 2002 in the Gulf of Trieste.     

Modelling the responses of the Lagoon of Venice ecosystem to variations in physical forcings

A Finite Element Ecological Model for the Lagoon of Venice (VELFEEM) has been used to test the responses of the Lagoon of Venice ecosystem to variations in physical conditions.The model is obtained by coupling a finite element hydrodynamic model, that computes the velocity fields of water, an energetic model to compute the water temperature fields, and an ecological model that simulates the dynamic of phytoplankton, zooplankton, nutrients (ammonia, nitrate and phosphate) organic detritus (organic nitrogen, organic phosphorous and CBOD) and dissolved oxygen.The transport model is a two-dimensional barotropic finite element model which allows for a better resolution of the lagoon morphology.The ecological model has been developed by starting from the ecological module EUTRO of WASP (Water Analysis Simulation System released by US EPA), and by adapting it to the peculiarity of the Lagoon of Venice.A reference condition has been identified by running a 1-year simulation under climatologic condition. Then, the sensitivity to physical forcing (tide and wind) and to the input of macronutrients has been investigated, by comparing model predictions of spatial and temporal evolution of major state variables and of an aggregate index of Water Quality Trophic Index (TRIX).     

Environmental Impact of Undular Tidal Bores in Tropical Rivers

A tidal bore impacts significantly on the estuarine ecosystem, although little is known on the flow field, mixing and sediment motion beneath tidal bores. In the absence of detailed systematic field measurements, a quasi-steady flow analogy was applied to investigate undular tidal bores with inflow Froude numbers between 1.25 and 1.6. Experimental results indicated that rapid flow redistributions occur beneath the free-surface undulations, with significant variations in bed shear stress between wave crests and troughs. Dynamic similarity was used to predict detailed flow characteristics of undular tidal bores. The effects of periodic loading on river sediments, scour of river bed and flow mixing behind the bore are discussed. A better understanding of these processes will contribute to better management practices in tidal bore affected rivers, including the Styx and Daly rivers in tropical Australia.     

森林-水资源系统的理论分析

本文认为,应当从森林-水资源系统出发研究森林与水资源的关系。并提出了一个分析森林-水资源系统产流过程的仿真模拟方法,得出在一定条件下,有森林植被的地方可能会比无森林植被的地方产生更多的能够为人类所利用的水资源的结论;进一步提出了构成最佳水资源生成系统的四项条件。作者分析了森林对降雨的影响,认为二次降雨和水平降雨对水资源量的直接影响很小;由于森林是大气的特殊下垫面具有软边界和强烈的物质能量变换的特点,加之森林蒸散的水汽和释放的凝结核等因素,可能会影响大气垂直降雨的空间分布,或提高产生降雨的可能性,从而使有林地区有增雨效果。最后对森林-水资源的研究方法提出了几点建议。     

水中COD测量不确定度的评定

建立了用重铬酸钾法测定水中COD测定的不确定度数学模型,用“鱼刺图“方法排列出每种可能作为来源的影响因素,并从标准溶液制备、样品滴定、水样移取等方面分析了COD监测结果的不确定度,计算了各不确定度分量值并给出了扩展不确定度,从中得出在标准滴定溶液制备过程中,重铬酸钾溶液的制备是最具权重的分量,其中标准物质质量的不确定度又是最大的分量,提高天平的精度对COD的不确定度会有明显改善.     

Mesoscale meteorological modelling for Hong Kong-application of the MC2 model

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Modelling of dust lifting process behind propagating shock wave

Dust dispersion from a layer is a complicated problem, which has not been completely solved yet, especially if an Eulerian–Eulerian approach has to be used to model the two-phase dusty flow. In previous investigation, a phenomenological model of the dust dispersion process from a layer was developed, but the evaluation of the model revealed some weaknesses. In the current paper, the model of the dust dispersion process was presented and three improvements of the model were studied: Saffman force, Magnus force and particles collisions. The implementation of Magnus and Saffman forces into the code did not improve the numerical results and it was shown that it had very little influence on the dust lifting process, in case the phenomenological model of the layer is used. Some explanations were proposed in the paper. Besides, an empirical model of particles collisions was also added to the code and its influence on the results was studied. It was shown that the particles collisions model improved the obtained results, but further modifications are to be studied in the future.