改善深圳河水质的补水方案及生态影响初步分析

深圳河旱季天然径流量小而污染负荷高,为了改善河流水质,在削减入河污染物的同时有必要采取补水措施。利用水质模型,计算了不同污水处理率下,分别以污水资源化再生水、珠江口海水和大鹏湾海水为补水水源时,深圳河达到基本不黑臭所需的补水量。讨论了补水方案对河流水质、盐度、水动力条件的改变及其对生态系统的影响。研究表明,引海水对河流生态系统的冲击不容忽视。而污水资源化是较优的补水方案。     

三峡库区移民贫困致因的精准识别与减贫路径的实证研究

随着我国经济发展和扶贫成效的显现,老区、山区、民族地区和移民库区等集中连片的特殊贫困区已经成为我国当前精准扶贫的主战场。由于面临生产资料匮乏、生态环境恶化和地质灾害频发等恶劣环境,库区移民贫困问题已成为新时期扶贫攻坚最难啃的"硬骨头"。因此,开展库区移民贫困致因的精准识别与减贫路径研究具有重要的现实意义。基于对库区移民贫困现状的扎根理论分析,本文提出了分析农户生计的新框架。在此基础上,本文以三峡库区26个县(区)为研究对象,随机抽取4县(区)796户移民作为样本,首先,采用灰色关联分析法和熵权法对库区移民主要致贫因子进行挖掘;接着,采用PLS-SEM模型分析影响库区移民生计状况的关键因子和关键路径。研究表明:(1)三峡库区移民贫困现象仍很严重,患病、劳动能力弱和失地是移民致贫的三大主因。三峡库区仍有175.94万人生活在贫困线以下,三大致贫原因依次是:因病致贫26.49%、因劳动能力弱致贫22.10%和失地致贫21.65%。(2)心理资本可有效促进移民其他资本效能的发挥,对生计状况存在着显著的直接效应和间接效应。(3)在影响生计状况的四类资本中,人力资本对库区移民生计状况影响最大。基于以上发现,本文提出了实现库区移民精准脱贫的政策建议:(1)国家应高度重视三峡库区移民贫困问题,大力开展精准扶贫;(2)增加心理干预措施以提高移民心理资本存量,帮助移民摆脱心理贫困;(3)开展劳动力技能培训,提高库区移民人力资本水平。     

铁路隧道弃渣的本地资源化利用

针对某大型铁路建设过程中产生大量弃渣以及建设过程中建材短缺的问题,以其典型段为例,对沿线弃渣的数量、性态等方面进行了分析,并进行了针对性规划,给出了具体的隧道弃渣利用方向和调配规划。结果表明,该段隧道产生的弃渣绝大部分都可符合相关工程的利用要求,在对典型段隧道所产生的弃渣经过合理规划后,该段弃渣的利用率理论上可达100.00%。在国内目前常规的隧道弃渣利用方式基础上,针对铁路工程,基于工程建筑材料、地方产业对隧道弃渣资源化利用进行统筹分析,提出了以隧道利用为主、其他工程利用为辅,兼顾地方产业利用的多层级隧道弃渣利用模式。本研究可为保障该大型铁路绿色环保工程提供参考。     

突发环境事件风险源识别与监控技术创新进展——（I）环境风险源识别技术与应用

环境风险防控与环境风险源管理是我国当前环境管理的重要工作之一。为了防控重大环境污染事件、实现环境风险源有序管理、科学决策,开展了重大环境污染事件风险源识别监控与管理技术的研发创新。借鉴国外环境风险源管理经验,遵循环境风险源“分类、分级、分区”管理原则,研发了环境风险源分类、识别与定量分级方法,实现了典型化工园区、特大城市及全国尺度的环境风险源分级,初步提出了全国石化化工行业重点风险企业名单。开发了环境风险源综合管理系统,以期为重点风险源监管、环境风险防控提供技术支持。     

Linking landscape development intensity within watersheds to methyl-mercury accumulation in river sediments

An indicator of the disturbance of natural systems, the landscape development intensity (LDI) index, was used to assess the potential for land-use within watersheds to influence the production/accumulation of methyl-mercury (MeHg) in river sediments. Sediment samples were collected from locations impacted by well-identified land-use types within the Mobile-Alabama River Basin in Southeastern USA. The samples were analyzed for total-Hg (THg) and MeHg concentrations and the obtained values correlated to the calculated LDI indexes of the sampled watersheds to assess the impact of prevalent land use/land cover on MeHg accumulation in sediments. The results show that unlike THg, levels of MeHg found in sediments are impacted by the LDI indexes. Overall, certain combinations of land-use types within a given watershed appear to be more conducive to MeHg accumulation than others, therefore, pointing to the possibility of targeting land-use practices as potential means for reducing MeHg accumulation in sediments, and ultimately, fish contamination.     

一株铅镉抗性菌株的分离鉴定及其生物学特性

鉴定了从黑龙江扎龙湿地土壤中筛选出的一株抗铅镉的菌株,研究了其生物学特性和部分生理生化指标。利用16SrDNA序列分析鉴定其菌属,并且研究Pb2+、Cd2+、Pb2+/Cd2+、温度、pH、盐以及抗生素对菌株生长的影响。经鉴定,该菌株为阴沟肠杆菌属(Enterobacter cloacae)。该菌株对Pb2+的去除率和吸附率分别达到了70.34%和44.39%,对Cd2+的去除率和吸附率分别达到了40.54%和25.14%。该菌株最适生长温度为25℃,最适生长pH为7.0左右。此菌株对抗生素亚胺培南最敏感。随着盐、Pb2+、Cd2+、Pb2+/Cd2+混合浓度的升高,该菌株生长受到抑制。     

Hot Spots of Perforated Forest in the Eastern United States

National assessments of forest fragmentation satisfy international biodiversity conventions, but they do not identify specific places where ecological impacts are likely. In this article, we identify geographic concentrations (hot spots) of forest located near holes in otherwise intact forest canopies (perforated forest) in the eastern United States, and we describe the proximate causes in terms of the nonforest land-cover types contained in those hot spots. Perforated forest, defined as a 0.09-ha unit of forest that is located at the center of a 7.29-ha neighborhood containing 60–99% forest with relatively low connectivity, was mapped over the eastern United States by using land-cover maps with roads superimposed. Statistically significant (P < 0.001) hot spots of high perforation rate (perforated area per unit area of forest) were then located by using a spatial scan statistic. Hot spots were widely distributed and covered 20.4% of the total area of the 10 ecological provinces examined, but 50.1% of the total hot-spot area was concentrated in only two provinces. In the central part of the study area, more than 90% of the forest edge in hot spots was attributed to anthropogenic land-cover types, whereas in the northern and southern parts it was more often associated with seminatural land cover such as herbaceous wetlands.     

生态足迹分析方法及其在国内的应用

生态足迹分析方法是90年代提出的可以定量的反映一个国家、地区、城市的可持续发展程度分析的计算模型。本文介绍了生态足迹模型的理论依据和计算方法,分析了生态足迹分析方法在我国的应用,并且指出了生态足迹分析方法的优缺点及其改进。     

Use of Microbial Community to Evaluate Performance of a Wetland System in Treating Pb/Zn Mine Drainage

The performance of a wetland system in treating lead (Pb)/zinc (Zn) mine drainage was evaluated by using the polyurethane foam unit (PFU) microbial community (method), which has been adopted by China as a standardized procedure for monitoring water quality. The wetland system consisted of four cells with three dominant plants: Typha latifolia, Phragmites australis and Paspalum distichum. Physicochemical characteristics [pH, EC, content of total suspended solid (TSS) and metals (Pb, Zn, Cd, and Cu)] and PFU microbial community in water samples had been investigated from seven sampling sites. The results indicated that the concentrations of Pb, Zn, Cd, Cu, and TSS in the mine drainage were gradually reduced from the inlet to the outlet of the wetland system and 99%, 98%, 75%, 83%, and 68% of these metals and TSS respectively, had been reduced in concentration after the drainage passed through the wetland system. A total of 105 protozoan species were identified, the number of protozoa species and the diversity index (DI) gradually increased, while the heterotrophic index (HI) gradually decreased from the inlet to the outlet of the wetland system. The results indicated that DI, HI, and total number species of protozoa could be used as biological indicators indicating the improvement of water quality.     

Synergistic Techniques for Better Understanding and Classifying the Environmental Structure of Landscapes

The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC) for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions has become the search for the best classification that optimally trades off classification complexity for class homogeneity. In this study, three techniques are investigated for their ability to find the best classification of the physical environments of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network, and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure of the landscape and to use this knowledge to select the best ELC at the required scale of analysis.