七星河湿地氨氧化古菌多样性和丰度及其与环境因子的相关性分析

以典型东北寒温带沼泽湿地——七星河湿地中芦苇和小叶樟植被下不同深度土壤中氨氧化古菌(Ammonia-Oxidizing Archaea,AOA)为研究对象,以编码氨氧化作用关键酶——氨单加氧酶(AMO)的amo A基因为分子标记,通过构建克隆文库和生物信息学方法分析数据,考察了不同植被环境中AOA多样性和丰度的垂直分布规律,及其与环境因子的相关性.研究结果表明,小叶樟植被土壤中AOA amo A基因多样性显著高于芦苇植被土壤中amo A基因多样性,芦苇植被土壤中AOA amo A基因多样性在深度为40~60 cm土层中最高,AOA多样性与NH+4-N、NO-3-N含量呈正相关;小叶樟植被土壤中AOA amo A基因多样性在深度为20~40 cm土层中最高,AOA多样性与NH+4-N、NO-3-N含量呈正相关.芦苇植被土壤中AOA丰度最低值出现于0~20 cm土层中,到20~40 cm土层中出现最高值,随着深度增加AOA丰度下降,AOA丰度则与NO-2-N含量呈正相关.小叶樟植被土壤中AOA丰度变化趋势与芦苇不同,最高值出现于0~20 cm土层中,随着土层深度增加AOA丰度下降,到40~60 cm出现最低值,AOA丰度与NO-2-N、TOC含量呈正相关.两种植被土壤中AOA丰度均在60~90 cm处有升高趋势.芦苇植被土壤中AOA丰度约是小叶樟植被土壤中AOA丰度的1.49倍.以上结果为湿地AOA生态功能及分布模式的研究提供基础数据,对全球氮循环的研究提供补充.     

寒区典型湿地浮游植物功能群季节变化及其与环境因子关系

安邦河湿地是一个典型的寒区湿地,本文运用功能群的方法对其浮游植物季节变化进行研究,并运用多元分析方法分析其与环境因子的关系.安邦河湿地共有浮游植物种8门104种,划分为14个功能群,分别是C、D、E、F、H1、J、Lo、M、MP、N、P、SN、X1和Y.其中重要功能群是C、D、E、J、Lo、N、P和Y.浮游植物的功能群组成季节变化明显,春季以功能群E和Lo生物量所占比例最大,分别为27.45%和20.49%;夏季以功能群D、J、P占优,为28.59%、18.53%和19.47%;秋季以功能群J、P为主,占39.65%和13.34%.可见,安邦河湿地浮游植物功能群的季节变化呈现为E+Lo→D+J+P→J+P的特点,反映了水环境特征:春季低水温低营养盐、夏季高水温高营养盐且水体混浊、秋季水温和营养盐均较高.运用冗余分析(RDA)分析浮游植物功能群与环境因子之间的关系,结果显示水温(WT)、无机氮(DIN)和溶解性磷酸盐(SRP)是安邦河湿地浮游植物功能群季节变化的主要环境因子.     

不同退耕年限下菜子湖湿地土壤铁形态变化

选取菜子湖区不同退耕年限(3、5、7、9、11、21 a)湿地为研究对象,以仍耕作油菜地和原始湿地为参照,分别采用王水消解法和Tessier连续提取法,分析了退耕还湖后湿地土壤全铁和铁的赋存形态特征,探讨退耕还湖后湿地土壤铁组分特征变化规律.结果表明:研究区土壤铁各形态含量大小顺序为:残渣态(RES-Fe:17.09~30.84 g·kg-1)铁锰氧化态(RED-Fe:3.66~4.48 g·kg-1)有机结合态(OM-Fe:0.87~3.09g·kg-1)碳酸盐结合态(CARB-Fe:0.01~0.37 g·kg-1)可交换态(EXC-Fe:0.01~0.15 g·kg-1).占全铁均小于1.5%的EXC-Fe和CARB-Fe均在退耕3 a和5 a期间含量快速升高,而后降低再升高,最低值出现在退耕11 a;RED-Fe在退耕3~9 a比较稳定,随后缓慢增加;而OM-Fe随退耕年限增加整体上呈增加趋势;占土壤铁形态总量73.91%~85.42%的RES-Fe在退耕3a时含量下降,在3~9 a间呈现逐渐增加的趋势,9~21 a又逐渐下降;研究区全铁(Tot-Fe)平均含量在18.50~38.41 g·kg-1之间,变化趋势与RES-Fe基本一致.讨论结果表明退耕还湖后水文条件和植被状况的改变导致了土壤环境发生变化,从而不仅影响退耕后湿地土壤全铁含量变化,也影响土壤铁形态组分特征,进而影响土壤铁的有效性.     

农村生态环境中生活污水治理问题剖析研究--以重庆市江津区为例

对江津区2009年－2013年农村生活污水处理设施调查分析结果表明,目前江津区农村建设的生活污水处理设施采用的技术主要有生物技术、生态技术和生物生态组合技术三种类型。结合江津区农村的特点,分析了农村生活污水处理设施建设及运管方面存在的问题,并提出解决措施与建议。农村生活污水处理设施建设和运管费等是一项长期的投入,特别是在后期的运行过程中应加强管理,建立有效的运营管理机制,保证正常运行,才能达到预期的处理效果,有效改善农村生活环境。     

利用水资源环境创建城市生态湿地景观的研究

针对利用水资源环境创建城市生态湿地景观的研究,介绍了南京湿地目前存在的问题,主要包括有湿地水质需要改善、湿地生物多样性受到威胁和湿地科研有待加强,探讨了新济洲国家湿地公园的建设,包括新济洲国家湿地公园定位体现地域特色、新济洲湿地建设思路,介绍了新济洲水资源协调利用,主要包括,建立水资源可持续利用机制、合理控制湿地污水排放、开展湿地治理,提升湿地水质,提出了新济洲国家湿地公园建设内容,并进行了对新济洲国家湿地公园建设效益分析.     

An integrated EDIB model for probabilistic risk analysis of natural gas pipeline leakage accidents

Natural gas pipeline construction is developing rapidly worldwide to meet the needs of international and domestic energy transportation. Meanwhile, leakage accidents occur to natural gas pipelines frequently due to mechanical failure, personal operation errors, etc., and induce huge economic property loss, environmental damages, and even casualties. However, few models have been developed to describe the evolution process of natural gas pipeline leakage accidents (NGPLA) and assess their corresponding consequences and influencing factors quantitatively. Therefore, this study aims to propose a comprehensive risk analysis model, named EDIB (ET-DEMATEL-ISM-BN) model, which can be employed to analyze the accident evolution process of NGPLA and conduct probabilistic risk assessments of NGPLA with the consideration of multiple influencing factors. In the proposed integrated model, event tree analysis (ET) is employed to analyze the evolution process of NGPLA before the influencing factors of accident evolution can be identified with the help of accident reports. Then, the combination of DEMATEL (Decision-making Trial and Evaluation Laboratory) and ISM (Interpretative Structural Modeling) is used to determine the relationship among accident evolution events of NGPLA and obtain a hierarchical network, which can be employed to support the construction of a Bayesian network (BN) model. The prior conditional probabilities of the BN model were determined based on the data analysis of 773 accident reports or expert judgment with the help of the Dempster-Shafer evidence theory. Finally, the developed BN model was used to conduct accident evolution scenario analysis and influencing factor sensitivity analysis with respect to secondary accidents (fire, vapor cloud explosion, and asphyxia or poisoning). The results show that ignition is the most critical influencing factor leading to secondary accidents. The occurrence time and occurrence location of NGPLA mainly affect the efficiency of emergency response and further influence the accident consequence. Meanwhile, the weight ranking of economic loss, environmental influence, and casualties on social influence is determined with respect to NGPLAs.     

A data-driven narratives skeleton pattern recognition from accident reports dataset for human-and-organizational-factors analysis

Accidents in the process industry involve several interacting factors, including human and organizational factors (HOFs). A long-standing obstacle to HOFs analysis is lack of data. Accident reports are an essential data source to learn from the past and contain HOFs-related data, but they are usually unstructured text in a not standardized format. Some studies have explored the extraction of information automatically from accident reports based on Natural Language Processing (NLP) techniques. However, they were not dedicated to HOFs. Risk communication is considered an essential pillar in safety and risk science. This research develops a HOFs-focused risk communication framework based on the NLP techniques that can support risk assessment and mitigation. The proposed approach automatically extracts the target groups oriented “Who, When, Where, Why” (4Ws) information from accident reports.This framework was applied to explore the eMARS database. The results show that the “4Ws” skeleton of narratives has appreciated performance in pattern recognition and holistic information analysis. The graphical representation interfaces are designed to display the features of HOFs-related accidents, which can better be communicated to the sharp-end operators and decision-makers.     

Integrating long-term stewardship goals into the remediation process: natural resource damages and the Department of Energy

The United States and other developed countries are faced with restoring and managing degraded ecosystems. Evaluations of the degradation of ecological resources can be used for determining ecological risk, making remediation or restoration decisions, aiding stakeholders with future land use decisions, and assessing natural resource damages. Department of Energy (DOE) lands provide a useful case study for examining degradation of ecological resources in light of past or present land uses and natural resource damage assessment (NRDA). We suggest that past site history should be incorporated into the cleanup and restoration phase to reduce the ultimate NRDA costs, and hasten resource recovery. The lands that DOE purchased over 50 years ago ranged from relatively undisturbed to heavily impacted farmland, and the impact that occurred from DOE occupation varies from regeneration of natural ecosystems (benefits) to increased exposure to several stressors (negative effects). During the time of the DOE releases, other changes occurred on the lands, including recovery from the disturbance effects of farming, grazing, and residential occupation, and the cessation of human disturbance. Thus, the injury to natural resources that occurred as a result of chemical and radiological releases occurred on top of recovery of already degraded systems. Both spatial (size and dispersion of patch types) and temporal (past/present/future land use and ecological condition) components are critical aspects of resource evaluation, restoration, and NRDA. For many DOE sites, integrating natural resource restoration with remediation to reduce or eliminate the need for NRDA could be a win-win situation for both responsible parties and natural resource trustees by eliminating costly NRDAs by both sides, and by restoring natural resources to a level that satisfies the trustees, while being cost-effective for the responsible parties. It requires integration of remediation, restoration, and end-state planning to a greater degree than is currently done at most DOE sites.     

高盐废水人工湿地处理中耐盐植物的筛选

天津塘沽作为滨海新区核心区,是目前天津发展最快的地区之一。由于本区盐碱土壤等自然条件,污水中盐分含量较高,制约了废水的回用。本文通过模拟人工湿地实验,比较了芦苇（Phragmites australis）、盐地碱篷（Suaeda salsa）、碱蒿（Artemisia anethifo原lia）、黄花鸢尾（Iris wilsonii）、盐角草（Salicornia europaea）和大米草（Spartina anglica）等耐盐植物对轻污染水体中高浓度氯离子的去除能力,筛选出去除能力较强的植物,并确定植物对盐分去除率达到最大时的生态系统条件。结果表明,适合人工湿地的耐盐碱植物对氯离子的去除效果依次为：芦苇＆gt;盐地碱篷＆gt;碱蒿＆gt;黄花鸢尾＆gt;盐角草＆gt;大米草,停留时间一般在第4d时可达到平衡。该研究为利用人工湿地处理高盐废水提供了科学依据。