A bunch of tiny individuals—Individual-based modeling for microbes

The individual-based (aka agent-based) approach is now well established in ecological modeling. Traditionally, most applications have been to organisms at higher trophic levels, where the importance of population heterogeneity (intra-population variability), complete life cycles and behavior adapted to internal and external conditions has been recognized for some time. However, advances in molecular biology and biochemistry have brought about an increase in the application of individual-based modeling (IBM) to microbes as well. This literature review summarizes 46 IBM papers for bacteria in wastewater treatment plants, phytoplankton in ocean and inland waters, bacteria in biofilms, bacteria in food and other environs, and “digital organisms” and “domesticated computer viruses” in silico. The use of IBM in these applications was motivated by population heterogeneity (45%), emergence (24%), absence of a continuum (5%), and other unknown reasons (26%). In general, the challenges and concepts of IBM modeling for microbes and higher trophic levels are similar. However, there are differences in the microbe population dynamics and their environment that create somewhat different challenges, which have led to somewhat different modeling concepts. Several topics are discussed, including producing, maintaining and changing population heterogeneity (different life histories, internal variability, positive feedback, inter-generation memory), dealing with very large numbers of individuals (different up-scaling methods, including representative space vs. super-individual, number vs. biomass based, discrete vs. continuous kinetics, various agent accounting methods), handling space, simulating interactions with the extracellular environment (hybrid Eulerian–Lagrangian approach), modeling agent–agent interaction (self-shading, predation, shoving) and passive transport (random walk with spatially variable diffusivity, well-mixed reactors). Overall, the literature indicates that the application of IBM to microbes is developing into a mature field. However, several challenges remain, including simulating various types of agent–agent interactions (formation and function of colonies or filaments, sexual reproduction) and even smaller individuals (viruses, genes). Further increases in intracellular detail and complexity in microbe IBMs may be considered the combination of systems biology and systems ecology, or the new field of systems bioecology.     

A Bayesian hierarchical framework for calibrating aquatic biogeochemical models

Model practitioners increasingly place emphasis on rigorous quantitative error analysis in aquatic biogeochemical models and the existing initiatives range from the development of alternative metrics for goodness of fit, to data assimilation into operational models, to parameter estimation techniques. However, the treatment of error in many of these efforts is arguably selective and/or ad hoc. A Bayesian hierarchical framework enables the development of robust probabilistic analysis of error and uncertainty in model predictions by explicitly accommodating measurement error, parameter uncertainty, and model structure imperfection. This paper presents a Bayesian hierarchical formulation for simultaneously calibrating aquatic biogeochemical models at multiple systems (or sites of the same system) with differences in their trophic conditions, prior precisions of model parameters, available information, measurement error or inter-annual variability. Our statistical formulation also explicitly considers the uncertainty in model inputs (model parameters, initial conditions), the analytical/sampling error associated with the field data, and the discrepancy between model structure and the natural system dynamics (e.g., missing key ecological processes, erroneous formulations, misspecified forcing functions). The comparison between observations and posterior predictive monthly distributions indicates that the plankton models calibrated under the Bayesian hierarchical scheme provided accurate system representations for all the scenarios examined. Our results also suggest that the Bayesian hierarchical approach allows overcoming problems of insufficient local data by “borrowing strength” from well-studied sites and this feature will be highly relevant to conservation practices of regions with a high number of freshwater resources for which complete data could never be practically collected. Finally, we discuss the prospect of extending this framework to spatially explicit biogeochemical models (e.g., more effectively connect inshore with offshore areas) along with the benefits for environmental management, such as the optimization of the sampling design of monitoring programs and the alignment with the policy practice of adaptive management.     

Gas-phase and aerosol chemistry interactions in South Europe and the Mediterranean region

The atmospheric chemical composition is affected by the interaction mechanisms among gases and particulate matter through a wide range of chemical reactions that can occur with the aid of particulate matter (e.g. particles act as reacting or absorbing surfaces) or be influenced by the presence of particulate matter in the atmosphere (photochemical reactions). Physical and chemical processes are also bonded in an interactive way that often leads to the influence of the radiation budget, cloud physics and the warming or cooling of the lower atmospheric levels. The Euro-Mediterranean region is a key-sensitive area due to the unique climatic and air quality characteristics associated with the regional climatic patterns, geomorphology (land and water contrast) and coexistence of pollutants from different origin. Focusing on this region, the gas-aerosol interactions are studied using state-of-the-art atmospheric and chemical transport modeling tools following the necessary development in the chemical transport model CAMx. Sensitivity and large-scale simulations have shown significant responses of the modeling system to the inclusion of natural species emissions, the direct shading effect of dust particles on photochemical processes and the formation of new types of aerosols through heterogeneous uptake of gases on dust particles. Including such interactions in the chemical transport model often led to the improvement of the model performance compared with available measurements in the region.     

超临界流体萃取固体物料动力学模型的研究进展(英文)

文章总结与讨论了超临界流体萃取固体物料的动力学模型。这些动力学模型包括经验模型,基于热传递类推的模型以及基于微分质量平衡的模型。所有这些都有助于实现过程的数学模拟放大,有助于投资前的经济预算,有效减小投资风险,也可作为超临界流体萃取过程的研究手段,减少实验探索的工作量。     

Modeling of BP Texas City refinery incident

This paper presents detailed modeling results of the BP Texas City refinery incident. Three different approaches and explosion modeling tools were used to study the event. The results predicted by all three approaches are similar and all approaches identified a hazard potential comparable to what was witnessed on March 23, 2005. This confirms that quantitative risk assessment (QRA) has the ability to model a realistic scenario, and is therefore useful in safety measure design and emergency preparedness decision making to improve overall safety performance. Had QRA been conducted during a management of change (MOC) decision-making process, personnel trailers likely would not have been sited in such close proximity to the process units. The resulting severe consequences would then not have occurred. This work also aims to emphasize the importance of QRA in process safety management.

The paper presents the authors’ perception of the sequence of events involved in the incident based on the published literature available at the time of writing. It also assesses potential consequences for the perceived sequence of events using a variety of consequence assessment tools. In doing so, the analysis illustrates how this incident could have been prevented in spite of many operational difficulties. The observations and commentary presented in this paper are intended solely for the purpose of process safety enhancement on the basis of the lessons learned. BP has published its own detailed report; the incident is also the subject of a recent investigation by the US Chemical Safety and Hazard Investigation Board, with the CSB's final report being available at http://www.csb.gov/index.cfm?folder=completed_investigations&page=info&INV_ID=52 (as of April 2007).     

基于GIS的电力工程勘察信息系统设计研究

从分析电力行业工程勘察信息管理与利用现状入手,提出了基于地理信息系统GIS(以下简称GIS)的工程勘察设计一体化的设想,设计了工程勘察信息化集成应用系统的逻辑模型,阐述了系统所采用的组件式GIS和数据融合等关键技术,最后结合具体的工程实例,详细介绍了具有系统分析决策功能的任意工程地质剖面图的绘制和三维实体地层模型的构建...     

Predicted effects of prescribed burning and harvesting on forest recovery and sustainability in southwest Georgia, USA

A model-based analysis of the effect of prescribed burning and forest thinning or clear-cutting on stand recovery and sustainability was conducted at Fort Benning, GA, in the southeastern USA. Two experiments were performed with the model. In the first experiment, forest recovery from degraded soils was predicted for 100 years with or without prescribed burning. In the second experiment simulations began with 100 years of predicted stand growth, then forest sustainability was predicted for an additional 100 years under different combinations of prescribed burning and forest harvesting. Three levels of fire intensity (low, medium, and high), that corresponded to 17%, 33%, and 50% consumption of the forest floor C stock by fire, were evaluated at 1-, 2-, and 3-year fire return intervals. Relative to the control (no fire), prescribed burning with a 2- or 3-year return interval caused only a small reduction in predicted steady state soil C stocks (< or =25%) and had no effect on steady state tree wood biomass, regardless of fire intensity. Annual high intensity burns did adversely impact forest recovery and sustainability (after harvesting) on less sandy soils, but not on more sandy soils that had greater N availability. Higher intensity and frequency of ground fires increased the chance that tree biomass would not return to pre-harvest levels. Soil N limitation was indicated as the cause of unsustainable forests when prescribed burns were too frequent or too intense to permit stand recovery.     

Effect of Long Retention Time in the Settler on Phosphorus Removal from Communal Wastewater (4 pp)

- Goals. The objective of the paper is to illustrate the solution of a chronic problem occurring in a wastewater treatment facility with a capacity of 12,000 inhabitant equivalent. A drastic phosphorus concentration increase (two or three times higher than the Hungarian limit of 1 mg/l) was observed in the wastewater treatment facility for a long time (12–24 h) with changing time periods indicating malfunctioning in the operation of the facility. Methods Computer-aided simulation technique was used to develop a solution for the treatment of the problem using a software developed by the Department of Environmental and Chemical Engineering, University of Veszprém, Hungary. Results and Discussion The simulation studies show that if the nightly inflow is less than 200 m3/h at least for two hours, the system doesn't then receive enough fresh nutrients which can cause a deficiency in the nutrient uptake of the PAOs in the anaerobic zones. This can result in the fact that the PAOs accumulate less phosphorus into the aerobic zones. Conclusion Long retention time (10 h) is the reason for the problem, namely – under special conditions – the phosphorus in the sludge of the settling tank of the wastewater treatment plant. The problem was caused by phosphorus dissolution from the sludge of the settling tank during the undesirably long retention time.     

煤粉锅炉SCR脱硝系统的设计与优化

以某新建460t/h煤粉炉的SCR脱硝项目为例,基于CFD软件完成几何建模、网格划分、数值计算等模拟工作,分析SCR脱硝系统的速度分布、NH3浓度分布、烟气入射角及压损情况。结果显示:最终的导流板布置方案能达到比较理想的流场分布,脱硝系统满足各项性能指标要求。     

Modeling flooding extent from Hurricane Floyd in the coastal plains of North Carolina

Abstract

In this article two modeling approaches were developed based on the use of US Geological Survey digital elevation model (DEM) data. These models were utilized to delineate the extent of flooding induced by precipitation from Hurricane Floyd in a portion of Pitt County, North Carolina. The patterns of flood extent derived from the two models were compared to the extent of flooding indicated on a digital aerial photograph taken two days after peak flood levels had been reached. In addition, floodplain boundaries based on Federal Emergency Management Agency Q3 maps were compared to the extent of flooding on the aerial photo. Actual emergency response operations undertaken through the Pitt County Emergency Operations Center during the flood event are described, and are used to provide a context for evaluating the potential utility of these models. The flood extents produced by the modeling methods performed well at representing the actual extent of the flooding.