工业生态学理论在生态钢铁工业发展中的应用

根据生态工业理论和原则,指出了生态钢铁工业的基本内涵是资源、能源利用方式的转变,提出了生态钢铁工业发展的核心内容是物质、能量、水、技术、信息五大集成系统的构建。同时建立了生态钢铁工业产业链和社会功能链。济钢生态钢铁工业的实例说明,钢铁工业生态化发展是实现钢铁工业可持续发展的有效途径。     

用接触氧化+生态氧化塘工艺处理城镇污水的应用研究

通过对阿瓦提县城污水处理工程的改造项目进行分析,从而得出生物接触氧化塘技术的技术可行性论证,并通过污染源监测数据说明该氧化塘COD进口平均浓度为279.91 mg/L,出口平均浓度为73.33 mg/L。工程改造前后排口COD由205 mg/L下降为73.33 mg/L,COD浓度明显降低,COD可减少105.735 t/a,减排效果明显。     

中国生态监测存在问题及发展趋势

在生态学的基本理论基础上,探讨了生态监测的科学内涵,明确了生态监测对象就是生态系统,目标是认识反映生态系统的状态和演变趋势,为管理和决策提供科学依据。深入分析了中国生态监测存在的5个问题:生态监测缺乏统一管理,部门间任务存在交叉和重复;生态监测技术不够规范,信息整合与利用困难;生态监测网络松散,国家级生态监测网络建立缓慢;环境监测法律依据不足,法制保障力度亟待加强;生态监测能力水平普遍较低,亟待建设。最后,从国家现实需求、生态监测现状以及监测技术发展的历史规律,探讨了未来中国生态监测的总体发展趋势。     

模组箱体空间内磷酸铁锂电池热失控及其传播行为研究

为了探究储能用锂离子电池在真实应用场景下的热失控及其传播行为特征,选用86 Ah方形磷酸铁锂(LiFePO₄)电池,对其在热滥用触发方式下的热失控行为及模组箱体空间与开放空间中的传播行为规律进行了实验研究。单体实验结果表明,电池热失控产生的高温烟气会导致模组箱体内沿高度方向出现明显温度梯度,模组底部与顶部温度测点的最大温差达118.4℃。传播实验结果表明,模组箱体空间内热失控电池通过产气及喷出高温电解液向其他电池传热,在热失控电池影响下,模组箱体空间内3块电池上表面所能达到的最高温度均高于开放空间实验12℃～150℃,模组空间内热失控电池向同侧两块电池的传热量高于开放空间实验225 kJ和44.4 kJ。但箱体环境中有限的氧气供给会减缓电池在热失控时的内部放热反应进程,模组箱体空间实验中电池热失控峰值温度较开放空间实验低33℃～145℃,并且模组箱体空间实验中热失控完全传播所用时间较开放空间实验滞后213 s。研究结果对于锂离子电池模组的安全设计和热失控传播阻隔具有一定的参考价值与指导意义。     

PFOS/PFOA环境污染行为与毒性效应及机理研究进展

全氟辛烷磺酰基化合物（PFOS）和全氟辛酸（PFOA）是一类新型的持久性有机污染物（POPs）,近年来发现在环境系统中日益广泛分布,并在生物体内蓄积或发生致毒效应.本文首先从PFOS/PFOA在环境中的污染及其水平、在野生动物体内的暴露、对人体的暴露以及污染与暴露变化趋势等4个方面,分析了PFOS/PFOA最新的环境污染与生物暴露情况;从PFOS/PFOA在大气环境中的转运转化过程、在污水污泥中转运转化过程以及在生物体内的蓄积、代谢转化与降解过程等3个方面,阐述了PFOS/PFOA在环境中的迁移转化行为;还概述了最近几年在PFOS/PFOA所导致的生态效应及其可能的机理研究进展.最后,尝试性地提出了今后在PFOS/PFOA污染生态学方面的研究重点.     

新型难燃隔热保温材料——酚醛泡沫

本文介绍了一种新型难燃隔热保温材料-酚醛泡沫塑料,它具有有机泡沫保温材料低热导率的优异性能,也具有无机保温材料优异的防火性能.     

Documenting Loss of Large Trophy Fish from the Florida Keys with Historical Photographs

Abstract:  A loss of large vertebrates has occurred in aquatic and terrestrial ecosystems, but data to measure long-term population changes are sparse. Historical photographs provide visual and quantitative evidence of changes in mean individual size and species composition for groups of marine fish that have been targeted by sport fishing. I measured such trends for 13 groups of recreationally caught "trophy" reef fish with photographs taken in Key West, Florida, from 1956 to 2007. The mean fish size declined from an estimated 19.9 kg (SE 1.5) to 2.3 kg (SE 0.3), and there was a major shift in species composition. Landings from 1956 to 1960 were dominated by large groupers ( Epinephelus spp.), and other large predatory fish were commonly caught, including sharks with an average length of just <2 m. In contrast, landings in 2007 were composed of small snappers ( Lutjanus spp. and Ocyurus chrysurus ) with an average length of 34.4 cm (SE 0.62), and the average length of sharks declined by more than 50% over 50 years. Major declines in the size of fish caught were not reflected in the price of fishing trips, so customers paid the same amount for a less-valuable product. Historical photographs provide a window into a more pristine coral reef ecosystem that existed a half a century ago and lend support to current observations that unfished reef communities are able to support large numbers of large-bodied fish.     

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.     

Simulating population variation and movement within fragmented landscapes: An application to the gopher tortoise (Gopherus polyphemus)

As the human activity footprint grows, land-use decisions play an increasing role in determining the future of plant and animal species. Studies have shown that urban and agricultural development cannot only harm species populations directly through habitat destruction, but also by destroying the corridors that connect habitat patches and populations within a metapopulation. Without these pathways, populations can encounter inbreeding depression and degeneration, which can increase death rates and lower rates of reproduction. This article describes the development and application of the FRAGGLE model, a spatial system dynamics model designed to calculate connectivity indices among populations. FRAGGLE can help planners and managers identify the relative contribution of populations associated with habitat patches to future populations in those patches, taking into account the importance of interstitial land to migration success. The model is applied to the gopher tortoise (Gopherus polyphemus), a threatened species whose southeastern U.S. distribution has diminished significantly within its native range due to agricultural and urban development over the last several decades. This model is parameterized with life history and movement traits of the gopher tortoise in order to simulate population demographics and spatial distribution within an area in west-central Georgia that supports a significant tortoise population. The implications of this simulation modeling effort are demonstrated using simple landscape representations and a hypothetical on land-use management scenario. Our findings show that development resulting in even limited habitat losses (10%) may lead to significant increases in fragmentation as measured by a loss in the rate of dispersions (31%) among area subpopulations.