弹性滑移支座力学性能的试验研究

介绍了弹性滑移支座的原理、构造和特点;通过对其在不同工况下的性能试验,研究了竖向荷载、位移幅值以及加载频率对弹性滑移支座力学性能的影响,并给出了试验值与理论计算值之间的对比。研究结果表明:弹性滑移支座具有良好的工作性能,滞回曲线饱满,耗能能力强;竖向荷载和加载频率对弹性滑移支座的力学性能有一定的影响,而位移幅值对其影响较小;弹性滑移支座的恢复力模型,可以用考虑速度的指数摩擦力模型来描述,并且模拟得较为准确。     

张北地震序列的尾波Qc值研究

采用尾波单次散射模型,选取张北地震序列70条波形记录,计算了张北地区t=58.88s时的尾波QC值:QC(f)=132.6±20f0.96±0.14。研究中发现,随流逝时间的增加QC逐渐增大,当流逝时间>120s时,出现逆转,QC迅速减小。文中采用频率域方法计算QC值,尾波功率谱计算自t>2ts开始,选用垂直向波形记录,取时间窗长为5.12s,步长2.56s向前滑动,每个时间窗两端5%的数据与余弦函数相乘,然后做FFT变换,分别计算9个中心频点各时间窗的能量密度谱,尾波流逝时间取各时间窗的中心点。当信号的能量密度<4倍的背景噪声能量密度时,尾波能量密度取值结束。求得能量密度谱后,线性拟合可求得不同流逝时间各频点的QC值。     

用于污水再生利用的生物活性炭床的有机物降解特性

以微生物增殖动力学的基本方程-莫诺方程为出发点,通过氮同位素分析比较了具有同源性微生物的生物陶粒滤床和生物活性炭床的有机物生物降解规律,建立了生物活性炭床的有机物生物降解动力学方程,提出在污水再生利用过程中生物活性炭床符合高基质有机物降解动力学模型,即有机物降解呈一级反应动力学方程。以此方程为基础,分析计算了生物活性炭床沿炭床深度的吸附性能,结果表明,在生物活性炭床中,随生物功能的减弱,生物活性炭床对有机物的吸附能力逐渐加强。     

城市大气质量模式研究进展

本文通过对大气质量模式发展历史的回顾,及其发展趋势的讨论,认为城市大气质量预报模式的建立与发展主要受以下三个动态因素的支配：（１）政府环境管理目标;（２）科学进步;（３）计算机及信息处理和通讯技术。结合三要素就建立我国城市空气质量预报系统框架进行了讨论。     

粘性泥石流运动模型的实验研究

粘性泥石流运动模型的研究因受实验条件的限制,还很不完善。国内外学者应用较多的５种模型都有一定的适用性,但也都存在不同的缺陷。本文应用粘性泥石流土样中的细颗粒和粗颗粒进行流变实验,不仅得到了粗颗粒在浆体中的沉降特性和泥石流体的流变特性,还研究了粘性泥石流运动模型及其参数。所提模型能很好地反映泥石流体的流变特性,较现有的５种模型能更好地描述粘性泥石流。     

Molecular composition of recycled organic wastes,as determined by solid-state 13C NMR and elemental analyses

Using solid state ¹³C NMR data and elemental composition in a molecular mixing model, we estimated the molecular components of the organic matter in 16 recycled organic (RO) wastes representative of the major materials generated in the Sydney basin area. Close correspondence was found between the measured NMR signal intensities and those predicted by the model for all RO wastes except for poultry manure char. Molecular nature of the organic matter differed widely between the RO wastes. As a proportion of organic C, carbohydrate C ranged from 0.07 to 0.63, protein C from <0.01 to 0.66, lignin C from <0.01 to 0.31, aliphatic C from 0.09 to 0.73, carbonyl C from 0.02 to 0.23, and char C from 0 to 0.45. This method is considered preferable to techniques involving imprecise extraction methods for RO wastes. Molecular composition data has great potential as a predictor of RO waste soil carbon and nutrient outcomes.     

Implications of different population model structures for management of threatened plants

Population viability analysis (PVA) is a reliable tool for ranking management options for a range of species despite parameter uncertainty. No one has yet investigated whether this holds true for model uncertainty for species with complex life histories and for responses to multiple threats. We tested whether a range of model structures yielded similar rankings of management and threat scenarios for 2 plant species with complex postfire responses. We examined 2 contrasting species from different plant functional types: an obligate seeding shrub and a facultative resprouting shrub. We exposed each to altered fire regimes and an additional, species‐specific threat. Long‐term demographic data sets were used to construct an individual‐based model (IBM), a complex stage‐based model, and a simple matrix model that subsumes all life stages into 2 or 3 stages. Agreement across models was good under some scenarios and poor under others. Results from the simple and complex matrix models were more similar to each other than to the IBM. Results were robust across models when dominant threats are considered but were less so for smaller effects. Robustness also broke down as the scenarios deviated from baseline conditions, likely the result of a number of factors related to the complexity of the species’ life history and how it was represented in a model. Although PVA can be an invaluable tool for integrating data and understanding species’ responses to threats and management strategies, this is best achieved in the context of decision support for adaptive management alongside multiple lines of evidence and expert critique of model construction and output.     

基于优化模型的抚仙湖营养物标准技术经济评估方法

在对美国水质标准经济分析研究的基础上,结合我国环境管理的实际情况,构建湖泊营养物标准的技术经济评估框架。计算标准建议值条件下的湖泊营养物容量及入量湖,得到削减量。通过不确定性优化模型对削减量进行分配,核算湖泊富营养化控制成本,并假设标准执行后,对流域经济造成的影响进行评估。将该方法应用于抚仙湖营养物标准的技术经济评估系统,结果表明,通过优化模型对削减量进行分配的削减成本较原规划低,通过构建的技术经济评估框架对该成本进行评估,标准执行后,对流域经济影响适中。     

Using empirical models of species colonization under multiple threatening processes to identify complementary threat‐mitigation strategies

Approaches to prioritize conservation actions are gaining popularity. However, limited empirical evidence exists on which species might benefit most from threat mitigation and on what combination of threats, if mitigated simultaneously, would result in the best outcomes for biodiversity. We devised a way to prioritize threat mitigation at a regional scale with empirical evidence based on predicted changes to population dynamics—information that is lacking in most threat‐management prioritization frameworks that rely on expert elicitation. We used dynamic occupancy models to investigate the effects of multiple threats (tree cover, grazing, and presence of an hyperaggressive competitor, the Noisy Miner (Manorina melanocephala) on bird‐population dynamics in an endangered woodland community in southeastern Australia. The 3 threatening processes had different effects on different species. We used predicted patch‐colonization probabilities to estimate the benefit to each species of removing one or more threats. We then determined the complementary set of threat‐mitigation strategies that maximized colonization of all species while ensuring that redundant actions with little benefit were avoided. The single action that resulted in the highest colonization was increasing tree cover, which increased patch colonization by 5% and 11% on average across all species and for declining species, respectively. Combining Noisy Miner control with increasing tree cover increased species colonization by 10% and 19% on average for all species and for declining species respectively, and was a higher priority than changing grazing regimes. Guidance for prioritizing threat mitigation is critical in the face of cumulative threatening processes. By incorporating population dynamics in prioritization of threat management, our approach helps ensure funding is not wasted on ineffective management programs that target the wrong threats or species.     

The Value of Using Feasibility Models in Systematic Conservation Planning to Predict Landholder Management Uptake

Understanding the social dimensions of conservation opportunity is crucial for conservation planning in multiple‐use landscapes. However, factors that influence the feasibility of implementing conservation actions, such as the history of landscape management, and landholders’ willingness to engage are often difficult or time consuming to quantify and rarely incorporated into planning. We examined how conservation agencies could reduce costs of acquiring such data by developing predictive models of management feasibility parameterized with social and biophysical factors likely to influence landholders’ decisions to engage in management. To test the utility of our best‐supported model, we developed 4 alternative investment scenarios based on different input data for conservation planning: social data only; biological data only; potential conservation opportunity derived from modeled feasibility that incurs no social data collection costs; and existing conservation opportunity derived from feasibility data that incurred collection costs. Using spatially explicit information on biodiversity values, feasibility, and management costs, we prioritized locations in southwest Australia to control an invasive predator that is detrimental to both agriculture and natural ecosystems: the red fox (Vulpes vulpes). When social data collection costs were moderate to high, the most cost‐effective investment scenario resulted from a predictive model of feasibility. Combining empirical feasibility data with biological data was more cost‐effective for prioritizing management when social data collection costs were low (<4% of the total budget). Calls for more data to inform conservation planning should take into account the costs and benefits of collecting and using social data to ensure that limited funding for conservation is spent in the most cost‐efficient and effective manner.