建筑物影响下大气污染物扩散数值模拟方法的比较

利用计算流体力学软件Fluent6.3.26提供的大涡模式和国标推荐的AERMOD模式分别对方形建筑物影响下的大气污染物扩散进行了模拟,通过与风洞实验结果的比较,对各模式的模拟能力进行了评价.结果表明,大涡模式对污染物散布特征的模拟与风洞实验结果基本一致,对建筑物顶部、空腔区和尾流区等区域污染物浓度分布的模拟效果均处于可接受水平;AERMOD模式模拟结果与风洞试验结果偏离较远,尤其是对空腔区污染物散布的模拟能力较差,误差较大.与大涡模式Y/H =0平面流场模拟结果对比(H为建筑物高度),AERMOD模式对风场的假设未能客观地反映建筑物附近气流变化的基本特征,是误差的主要来源之一,建议结合大涡模式订正,提高模拟结果的准确性.     

土壤湿度和浇水对紫色土土/气界面汞释放通量的影响

以重庆市的主要耕作土壤——紫色土为研究对象,用动力通量箱与RA-915＋汞分析仪联用技术,通过室内模拟实验研究土壤湿度和浇水对紫色土土/气界面汞交换通量的影响.结果表明,加入外源硝酸汞的土壤汞交换通量大于加入硝酸亚汞的土壤汞交换通量,对照土壤的汞释放通量最小.随着土壤含水量的增加,土/气界面汞交换通量有增加的趋势,在土...     

Simulating the potential for ecological restoration of dryland forests in Mexico under different disturbance regimes

Examining the potential for ecological restoration is important in areas where anthropogenic disturbance has degraded forest landscapes. However, the conditions under which restoration of degraded tropical dry forests (TDF) might be achieved in practice have not been determined in detail. In this study, we used LANDIS-II, a spatially explicit model of forest dynamics, to assess the potential for passive restoration of TDF through natural regeneration. The model was applied to two Mexican landscapes under six different disturbance regimes, focusing on the impact of fire and cattle grazing on forest cover, structure and composition. Model results identified two main findings. First, tropical dry forests are more resilient to anthropogenic disturbance than expected. Results suggested that under both a scenario of small, infrequent fires and a scenario of large, frequent fires, forest area can increase relatively rapidly. However, forest structure and composition differed markedly between these scenarios. After 400 years, the landscape becomes increasingly occupied by relatively shade-tolerant species under small, infrequent fires, but only species with both relatively high shade tolerance and high fire tolerance can thrive under conditions with large, frequent fires. Second, we demonstrated that different forms of disturbance can interact in unexpected ways. Our projections revealed that when grazing acts in combination with fire, forest cover, structure and composition vary dramatically depending on the frequency and extent of the fires. Results indicated that grazing and fire have a synergistic effect causing a reduction in forest cover greater than the sum of their individual effects. This suggests that passive landscape-scale restoration of TDF is achievable in both Mexican study areas only if grazing is reduced, and fires are carefully managed to reduce their frequency and intensity.     

A simple individual model for simulating weight gain dynamics in response to intake rate and daily behavior

It is often necessary to estimate the weight that an individual may be capable of gaining depending on its degree of activity. A simple individual-based model was developed for studying the dynamics of weight in terms of daily behavior and ingestion rate. It was based on the balance between the individual's energy intake and the cost of its daily activities. Costs depend on the weight of the individual and the photoperiod, as well as on the time spent on each activity. Different combinations of ingestion rate, individual's weight, photoperiod length, and time assigned to different activities were used for simulating the weight dynamics, taking the species Rhea americana as a study case. Estimations of energetic costs of the activities were obtained from specialized literature. Using different photoperiods and individual behaviors, the model yields field metabolic rate (FMR) values in agreement with those obtained from direct measurements for other omnivorous bird species.     

Combining state and transition models with dynamic Bayesian networks

Bashari et al. (2009) propose combining state and transition models (STMs) with Bayesian networks for decision support tools where the focus is on modelling the system dynamics. There is already an extension of Bayesian networks - so-called dynamic Bayesian networks (DBNs) - for explicitly modelling systems that change over time, that has also been applied in ecological modelling. In this paper we propose a combination of STMs and DBNs that overcome some of the limitations of Bashari et al.’s approach including providing an explicit representation of the next state, while retaining its advantages, such an the explicit representation of transitions. We then show that the new model can be applied iteratively to predict into the future consistently with different time frames. We use Bashari et al.’s rangeland management problem as an illustrative case study. We present a comparative complexity analysis of the different approaches, based on the structure inherent in the problem being modelled. This analysis showed that any models that explicitly represent all the transitions only remain tractable when there are natural constraints in the domain. Thus we recommend modellers should analyse these aspects of their problem before deciding whether to use the framework.     

Identifying key species in ecosystems with stochastic sensitivity analysis

The development of approaches to estimate the vulnerability of biological communities and ecosystems to extirpations and reductions of species is a central challenge of conservation biology. One key aim of this challenge is to develop quantitative approaches to estimate and rank interaction strengths and keystoneness of species and functional groups, i.e. to quantify the relative importance of species. Network analysis can be a powerful tool for this because certain structural aspects of ecological networks are good indicators of the mechanisms that maintain co-evolved, biotic interactions. A static view of ecological networks would lead us to focus research on highly-central species in food webs (topological key players in ecosystems). There are a variety of centrality indices, developed for several types of ecological networks (e.g. for weighted and un-weighted webs). However, truly understanding extinction and its community-wide effects requires the use of dynamic models. Deterministic dynamic models are feasible when population sizes are sufficiently large to minimize noise in the overall system. In models with small population sizes, stochasticity can be modelled explicitly. We present a stochastic simulation-based ecosystem model for identification of “dynamic key species” in situations where stochastic models are appropriate. To demonstrate this approach, we simulated ecosystem dynamics and performed sensitivity analysis using data from the Prince William Sound, Alaska ecosystem model. We then compare these results to those of purely topological analyses and deterministic dynamic (Ecosim) studies. We present the relationships between various topological and dynamic indices and discuss their biological relevance. The trophic group with the largest effect on others is nearshore demersals, the species mostly sensitive to others is halibut, and the group of both considerable effect on and sensitivity to others is juvenile herring. The most important trophic groups in our dynamical simulations appear to have intermediate trophic levels.     

Modelling llama population development under environmental and market constraints in the Bolivian highlands

Changes in the size of animal populations over time are mainly determined by demographic and environmental factors. Livestock population dynamics are additionally influenced by harvesting decisions taken by herders. In Bolivia, not much is known about current llama husbandry and the main influencing factors determining population sizes. We collected data on demography, environmental factors and market values affecting the current and future llama population in three different regions in Bolivia. We generated a population model and assessed the future development of the llama population including environmental factors (rangeland carrying capacity, disturbance phenomena), herd structure and dynamics, and economic market demands. We calibrated and validated the llama model on the basis of 20-year data sets of the regions of Oruro, Potosi and La Paz, respectively. Model calibration by means of the Gauss-Marquardt-Levenberg algorithm yielded a model efficiency of 0.94. For model validation, however, the simulation slightly overestimated the observed llama population yielding model efficiencies of 0.91 and 0.87 for Potosi and La Paz, respectively. Model outcomes were most sensitive to death and birth rates of juveniles and death rate of females compared to environmental or other demographic factors. Population trajectories approached an overall carrying capacity for Oruro, Potosi and La Paz of 8.8 × 10⁵, 9.1 × 10⁵, and 9.0 × 10⁵ llama individuals after 100 years of simulation. Hence, detailed monitoring of demographic, environmental, and economic factors can improve predictions of llama population development over time. Further management should focus on improving birth rates and lowering female mortality through providing supplemental food and shelters against the harsh environmental conditions of the Andean highlands.     

Equivalence of the realized input and output oriented indirect effects metrics in Ecological Network Analysis

A new understanding of the consequences of how ecosystem elements are interconnected is emerging from the development and application of Ecological Network Analysis. The relative importance of indirect effects is central to this understanding, and the ratio of indirect flow to direct flow (I/D) is one indicator of their importance. Two methods have been proposed for calculating this indicator. The unit approach shows what would happen if each system member had a unit input or output, while the realized technique determines the ratio using the observed system inputs or outputs. When using the unit method, the input oriented and output oriented ratios can be different, potentially leading to conflicting results. However, we show that the input and output oriented I/D ratios are identical using the realized method when the system is at steady state. This work is a step in the maturation of Ecological Network Analysis that will let it be more readily testable empirically and ultimately more useful for environmental assessment and management.     

A system dynamics model for evaluating the alternative of type in construction and demolition waste recycling center - The case of Chongqing, China

This paper presents a system dynamics computer model to evaluate alternative type of recycling center under different policy and economy environments through comparison on the economic feasibility of recycling centers and ratio of savings to costs in C&D waste management. A case study for the City of Chongqing, China is selected. Simulated results show three key factors can contribute to the economic feasibility of recycling and the ratio of savings to costs in C&D waste management: (a) profit; (b) unit recycling cost; (c) extra revenue from location advantage (It was assumed that the mobile centers can attain extra revenue from the location advantage compared with fixed recycling centers). The sensitive analysis and comparison on ratios between public and private sector indicate that to achieve the optimum ratio of savings to costs, design of recycling centers and selection of governmental instruments are determined by the priority list: (1) low extra revenue from location advantage; (2) low profit; (3) low unit recycling cost. Meanwhile, the fluctuation of the three factors must be prior to achieve economic feasibility of corresponding recycling centers.     

针对C3H8／空气扩散火焰的PCA简化机理构筑

C3H8是液化石油气（LPG）的主要成分,其火焰结构的数值预测对于消防等相关行业具有重要意义。单步或总包反应过于简单,不能描述碳氢燃料的氧化机制,而耦合燃料详细机理的燃烧模拟计算量大,且描述反应的数学系统具有极强的“刚性”,限制了反应机理的实际应用,而去除冗余反应和组分的简化机理具有描述燃烧的全面性优点,且降低了数学系统的“刚性”,因此耦合简化机理的火焰结构数值预测具有优势。本文采用基于矩阵分析的主成分（PCA）分析技术,分析研究了wang等发展的469步C3H8详细反应动力学机理,获得了组分的重要性排序,基于此分别构筑了320步和214步两个简化机理,针对典型扩散火焰的计算,表明建立的两个简化机理具有较高的模拟可靠性,同时也提供了一种框架简化机理的构筑方法。