气相抽提去除红壤中挥发性有机污染物的去污机理探讨

通过探讨土壤气相抽提去除红壤中挥发性有机污染物的去污机理,建立了一维稳态条件下污染物在土壤多孔介质中传质的总微分方程,分别求出了平衡模型和动力学模型的解析解和数值解,并用实验结果对平衡模型和动力学模型进行了模拟和验证.实验结果和模型模拟结果表明理论模型与实验结果吻合良好,平衡模型和动力学模型在描述污染物在土柱通风过程中的传质时,分别适用于不同的阶段.在通风初期平衡模型能够很好地描述实验结果,而随着时间的推移,平衡模型的预测曲线逐渐偏离数据点,到了通风中后期,只有动力学模型才能够较好地描述和预测实验结果.     

A heuristic approach to predicting water beetle diversity in temporary and fluctuating waters

An understanding of the causal mechanisms and processes that shape macroinvertebrate communities at a local scale has important implications for the management and conservation of freshwater biodiversity. Here we compare the performance of linear and non-linear statistics to explore diversity-environment relationships using data from 76 temporary and fluctuating ponds in two regions of southern England. We focus on aquatic beetle assemblages, which have been shown to be excellent surrogates of wider freshwater macroinvertebrate diversity. Ponds in the region contained a rich coleopteran fauna, totaling 68 species, which provided an excellent model system with which to compare the performance of two non-linear procedures (artificial neural networks—ANNs and generalised additive models—GAMs) and one more traditional linear approach (Multiple linear regression—MLR) to modelling diversity-environment relationships. Of all approaches employed, the best fit was obtained using an ANN model with only four input variables (conductivity, turbidity, magnesium concentration and depth). This model accounted for 82% of the observed variability in Shannon diversity index across ponds. In contrast, the best GAM and MLR models only explained 50% and 14% of this variation, respectively. Contribution profile analysis of conductivity, turbidity, magnesium concentration and depth, obtained from the best fit ANN through a hierarchical cluster analysis, allowed the identification of direct and proxy effects in relation to the environmental variables measured in this study. In each case, distinct clusters of ponds were identified in contribution profile analysis, suggesting that ponds across the two regions fall into a number of discrete groups, whose beetle faunas respond in subtly yet significantly different ways to key environmental variables. Aquatic coleopteran diversity in ponds in the two regions appears to be driven at a local scale by changes in relatively few physicochemical gradients, which are related to diversity in a clearly non-linear manner.     

Application of a temperature-dependent von Bertalanffy growth model to bullhead (Cottus gobio)

The most studied and commonly applied model of fish growth is the von Bertalanffy model. However, this model does not take water temperature into account, which is one of the most important environmental factors affecting the life cycle of fish, as many physiological processes that determine growth, e.g. metabolic rate and oxygen supply, are directly influenced by temperature. In the present study we propose a version of the von Bertalanffy growth model that includes mean annual water temperatures by correlating the growth coefficient, k, explicitly and the asymptotic length, L_∞, implicitly to water temperature. All relationships include parameters with an obvious biological relevance that makes them easier to identify. The model is used to fit growth data of bullhead (Cottus gobio) at different locations in the Bez River network (Drme, France). We show that temperature explains much of the growth variability at the different sampling sites of the network.     

Multiple structural modifications to dendritic ecological networks produce simple responses

Structural modifications to landscapes affect the ability of organisms to access different habitat patches. There exist, however, very few general methods by which to relate modifications to expectations of effects, and even fewer that enable understanding of how multiple modifications may interact. In the absence of any guiding principles, ecologists have assumed that interactions will result in complex landscape-scale effects. One way of understanding such effects is through rendering a landscape as a graph or network, among the simplest of which are dendritic networks typified by stream systems. Yet even for stream networks, there are no known general principles concerning the nature of interactions between multiple modifications. We developed a model to describe the ability of fish to access and use different habitat patches within dendritic networks. We used mathematical and numerical analyses of the model to investigate how the habitat value of a network is affected by changes in connectivity and habitat quality, and then to examine interactions between multiple modifications. Rather than showing complex interactions, our analytic and simulation-based results show that the combined effect of multiple modifications approximately equals the sum of individually predicted effects. Dendritic networks thus appear to respond far more simply to multiple modifications than has previously been assumed. These results have implications for stream management planning, and offer a firm foundation from which to better understand population processes within dendritic networks.     

基于人工神经网络法的绿色建筑评价

以实际建筑物为例,介绍了用层次分析法建立绿色建筑评价模型的过程,并分别用层次分析法和人工神经网络法对实际建筑物进行了评价。评价结果显示,人工神经网络法与层次分析法相对误差不到0.5%,表明人工神经网络法作为一种客观科学的评价方法,应用于绿色建筑的评价,能有效降低主观因素带来的影响,会使结果更具有客观性。     

平原河网地区滨岸带外来植物入侵现状及影响研究——以上海青浦区为例

河流滨岸带作为一种典型的开放系统,在受到外界干扰的条件下极易被外来植物所入侵并受到严重影响。以上海青浦区为例,通过对河流滨岸带生态系统入侵植物分布及现状调查,以及对两种入侵植物：白花三叶草（Trifolium repens）和加拿大一枝黄花（Solidago canadensis）群落的物种多样性及其土壤特性的实证研究,探讨外来植物入侵对河流滨岸带生态系统造成的影响。结果表明：目前该地区河流滨岸带外来入侵植物共有14科24种,其科、种数分别占到该生态系统所有植物的48．3％与26．1％。入侵植物白花三叶草与加拿大一枝黄花在春、秋两季均显著降低了河流滨岸带植物群落的物种多样性。此外,两种人侵植物也对当地河流滨岸及土壤特性造成了不同程度的影响,其中对土壤含水量、pH值的影响最为显著。该研究填补了平原河网地区河流滨岸带生态系统外来植物入侵研究的空白,有助于今后开展对该生态系统的评价、恢复及管理工作。     

珠江三角洲水位演变分析

全球气候变暖导致的海平面加速上升已是不争的事实,其长期累积的结果将给沿海地区造成巨大威胁。利用层次聚类分析法、灰关联法、相关分析法等重点分析了海平面上升对珠江三角洲水位的影响。结果显示：海平面上升对珠江三角洲代表站的年平均水位和年最低水位的影响大于对年最高水位的影响;海平面上升对马口站和三水站水位的影响小于河床下切和径流的影响;海平面上升对珠江河口区水位的影响由三角洲深处向口门区有增强趋势。掌握海平面上升对水位的影响规律,对于河口地区的防灾减灾和水资源的合理开发利用具有重要的指导意义。     

Development of pretreatment protocol for DNA extraction from biofilm attached to biologic activated carbon (BAC) granules

The biologic activated carbon (BAC) process is widely used in drinking water treatments. A comprehensive molecular analysis of the microbial community structure provides very helpful data to improve the reactor performance. However, the bottleneck of deoxyribonucleic acid (DNA) extraction from BAC attached biofilm has to be solved since the conventional procedure was unsuccessful due to firm biomass attachment and adsorption capacity of the BAC granules. In this study, five pretreatments were compared, and adding skim milk followed by ultrasonic vibration was proven to be the optimal choice. This protocol was further tested using the vertical BAC samples from the full-scale biofilter of Pinghu Water Plant. The results showed the DNA yielded a range of 40 μg·g^-1 BAC (dry weight) to over 100 μg·g^-1 BAC (dry weight), which were consistent with the biomass distribution. All results suggested that the final protocol could produce qualified genomic DNA as a template from the BAC filter for downstream molecular biology researches.     

扬州市河网大型底栖动物群落结构及其生境特征研究

构建适用于城市大型底栖动物的生境适宜性模型,探究大型底栖动物与生境因子间的响应关系,对城市河流生态系统恢复具有重要指示意义.本文以长江下游北岸扬州市城市河网为研究对象,基于丰水期（2018年8月）和枯水期（2019年1月）的大型底栖动物调查数据,利用典范对应分析与相关性分析筛选城市河网生态健康的关键生境因子,采用GAM模型拟合关键生境因子与大型底栖动物优势种的关系,构建城市大型底栖动物生境特征研究模型.结果表明,本次调查共获得大型底栖动物48个物种,隶属3门6纲13目20科40属,其中,水生昆虫为优势类群,霍甫水丝蚓（Limnodrilus hoffmeisteri）为研究区域优势种.影响优势种霍甫水丝蚓的主要生境因子为溶解氧（DO）、COD_Mn、NH₃-N、电导率（Cond）,当霍甫水丝蚓生境适宜度为1.0时,水体中NH₃-N含量界限值为0.554 mg·L^-1,COD_Mn界限值为2.23 mg·L^-1,DO界限值为7.87 mg·L^-1,Cond界限值为272.5 S·m^-1.GAM模型能识别城市水环境关键问题,有效解释城市大型底栖动物与生境因子间的响应关系,可为城市河网水生态修复提供参考依据.     

Quantitative risk analysis of urban natural gas pipeline networks using geographical information systems

This paper presents a novel quantitative risk analysis process for urban natural gas pipeline networks using geographical information systems (GIS). The process incorporates an assessment of failure rates of integrated pipeline networks, a quantitative analysis model of accident consequences, and assessments of individual and societal risks. Firstly, the failure rates of the pipeline network are calculated using empirical formulas influenced by parameters such as external interference, corrosion, construction defects, and ground movements. Secondly, the impacts of accidents due to gas leakage, diffusion, fires, and explosions are analyzed by calculating the area influenced by poisoning, burns, and deaths. Lastly, based on the previous analyses, individual risks and social risks are calculated. The application of GIS technology helps strengthen the quantitative risk analysis (QRA) model and allows construction of a QRA system for urban gas pipeline networks that can aid pipeline management staff in demarcating high risk areas requiring more frequent inspections.