遥感技术在水生态环境管理的应用与前景

随着遥感数据源的不断丰富,遥感技术不断提高,可以解决越来越多的水环境问题。指出了当前水生态环境管理方面的主要需求,结合目前遥感技术的发展,对国内外的水环境遥感研究进展进行综述。以湖泊富营养化监测与评估、核电站温排水遥感监测及城市黑臭水体遥感监测为案例,具体阐述遥感在水环境管理中的应用方法及成效。未来水生态环境管理发展趋势将以水污染防治为主向水污染防治和水生态修复与保护并重发展。基于此趋势,提出遥感在水生态修复的应用潜力,利于更多地方部门积极有效应用遥感技术,解决水生态环境问题。     

阳宗海沉积物中磷的稳定性

絮凝剂(Fe Cl3)治理阳宗海砷污染的过程中,水体中的磷被大量沉积进入底泥,弄清其是否会在环境条件变化后发生反溶形成二次污染对湖泊富营养化防治具有重要意义。通过模拟实验模拟泥-水界面p H变化、物理扰动和微生物活动的变化,旨在分析这些环境因子变化对沉积物中磷溶出的影响。结果表明,阳宗海水体在目前这种磷浓度下,底泥的磷会随时间的增加而溶出再次造成水体磷污染,当暴露在清洁水条件下时磷的释放率会增加;这种由于絮凝剂吸附沉淀到湖底的磷,在上覆水p H增加0.5时底泥磷解吸附释放速率增加;每年秋季湖泊上下层水的交换活动会造成水体磷浓度的季节性升高,形成不可忽视的磷内源。而夏季水温分层导致湖泊底部厌氧,使厌氧微生物活性增强,这将进一步促进底泥中磷的释放。     

How will Ocean Acidification Affect Baltic Sea Ecosystems? An Assessment of Plausible Impacts on Key Functional Groups

Increasing partial pressure of atmospheric CO₂ is causing ocean pH to fall—a process known as ‘ocean acidification’. Scenario modeling suggests that ocean acidification in the Baltic Sea may cause a ≤3 times increase in acidity (reduction of 0.2–0.4 pH units) by the year 2100. The responses of most Baltic Sea organisms to ocean acidification are poorly understood. Available data suggest that most species and ecologically important groups in the Baltic Sea food web (phytoplankton, zooplankton, macrozoobenthos, cod and sprat) will be robust to the expected changes in pH. These conclusions come from (mostly) single-species and single-factor studies. Determining the emergent effects of ocean acidification on the ecosystem from such studies is problematic, yet very few studies have used multiple stressors and/or multiple trophic levels. There is an urgent need for more data from Baltic Sea populations, particularly from environmentally diverse regions and from controlled mesocosm experiments. In the absence of such information it is difficult to envision the likely effects of future ocean acidification on Baltic Sea species and ecosystems.     

河流型硅藻水华研究进展

通过对硅藻水华发生机制相关文献的研究分析,对硅藻水华发生机制做了一般性探讨,并重点关注了河流型水华的发生机制的独特点。河流水华种类主要为中心硅藻纲,静水生态系统水华种类除中心硅藻纲还包括部分羽纹硅藻纲种类。河流水华硅藻种类对营养盐浓度、温度和光照等环境因子具有一定的适应范围。与静水生态系统相比,河流硅藻水华受气象和水文等物理指标的影响更为明显。河流硅藻水华中常具有时滞现象,其中由气象和水文因素引起的时滞现象最为明显。目前河流硅藻水华的防治仍然以上游水库下泄稀释为主,但是这种方法会造成一定的水资源浪费。河流水华硅藻的生理属性、硅藻水华对生态系统的影响、节水与抑制水华的统筹以及其他控制水华的方法都是未来河流硅藻水华研究的重点。     

多源信息融合技术在内陆湖库水华预警中的研究进展与展望

面对水体富营养化愈来愈严重,水华爆发越来越频繁的严峻形式;为减少水华发生频率及由此造成的损失,开展水华预警已成当务之急。水华爆发是水体中营养盐的累积、气候条件与水力条件等众多因素非线性共同作用的产物;为此,有必要在众多水华影响因素的动态监测信息的融合基础上,寻求水华爆发与这些影响因素间的影射关系,这就需要信息融合技术。通过归纳总结多源信息融合技术在内陆湖库水华预警中应用的研究进展,结合目前我国水华预警的具体需求,提出建立基于多源信息融合技术的水华预警决策支持系统的研究前景与初步设想。信息融合技术为水华预警提供了一个良好的平台,它将与水华相关的不同信息源（水文、气象、水环境质量与环境遥感）所提供的局部不完整的观测信息加以集成与互补,消除多源信息之间存在的冗余和矛盾,形成对水华爆发环境相对完整的感知与描述;从而提高水华预警与应急响应决策的效率,提高预警信息的时间与空间分辨率,扩展信息的时空监测范围。     

Observations of Atmospheric Nitrogen and Phosphorus Deposition During the Period of Algal Bloom Formation in Northern Lake Taihu,China

Cyanobacterial blooms in Lake Taihu occurred at the end of April 2007 and had crucial impacts on the livelihood of millions of people living there. Excessive nutrients may promote bloom formation. Atmospheric nitrogen (N) and phosphorus (P) deposition appears to play an important role in algal bloom formation. Bulk deposition and rain water samples were collected respectively from May 1 to November 30, 2007, the period of optimal algal growth, to measure the bulk atmospheric deposition rate, wet deposition rate, and dry deposition rate for total nitrogen (TN; i.e., all species of nitrogen), and total phosphorus (TP; i.e., all species of phosphorus), in northern Lake Taihu, China. The trends of the bulk atmospheric deposition rate for TN and the wet deposition rate for TN showed double peaks during the observation period and distinct influence with plum rains and typhoons. Meanwhile, monthly bulk atmospheric deposition rates for TP showed little influence of annual precipitation. However, excessive rain may lead to high atmospheric N and P deposition rates. In bulk deposition samples, the average percentage of total dissolved nitrogen accounting for TN was 91.2% and changed little with time. However, the average percentage of total dissolved phosphorus accounting for TP was 65.6% and changed substantially with time. Annual bulk atmospheric deposition rates of TN and TP during 2007 in Lake Taihu were estimated to be 2,976 and 84 kg km⁻² a⁻¹, respectively. The results showed decreases of 34.4% and 78.7%, respectively, compared to 2002–2003. Annual bulk deposition load of TN for Lake Taihu was estimated at 6,958 t a⁻¹ in 2007 including 4,642 t a⁻¹ of wet deposition, lower than the values obtained in 2002–2003. This may be due to measures taken to save energy and emission control regulations in the Yangtze River Delta. Nevertheless, high atmospheric N and P deposition loads helped support cyanobacterial blooms in northern Lake Taihu during summer and autumn, the period of favorable algal growth.     

基于人工免疫原理的事故预防研究

介绍生物免疫识别模式,分析事故预防过程的实质是抑制潜在危险转化成事故的控制过程,分析比较事故预防与生物免疫识别模式在作用、生存环境、动作触发源等的共性,构建了基于免疫识别模式的事故预防系统并建立了事故预防数学模型;定义事故预防系统的识别率、失效率、误判率并给出了数学表达式,指出监测生产系统各环节状态信息是否符合系统的安全要求就是识别潜在危险的过程,是事故预防的关键,基于人工免疫原理的事故预防数学模型具有较强的健壮性、自适应性和动态防护性等特点。     

虹膜识别在肉类食品安全追溯系统中的应用及关键技术研究

为了提高大型动物肉类食品的安全性,在研究肉类食品供应链的安全管理的基础上,将大型动物的虹膜识别技术引入食品供应链管理中,构建基于虹膜识别的大型动物肉类食品安全可追溯系统,达到肉类食品安全信息查询及出现安全问题后的个体溯源的目的。借鉴人眼虹膜识别的相关技术,以牛眼为例对大型动物虹膜识别的相关算法和虹膜定位等关键技术进行研究,运用改进的Sobel算子对图像进行边缘检测;引入二次B样条曲线算法实现了牛眼虹膜的精确定位;分析牛虹膜纹理特征的分布特点,实现了虹膜特征区域的提取及归一化处理。研究成果对大型动物的虹膜识别研究和肉类食品供应链安全管理具有一定的参考意义。     

模式识别在火灾调查中的汽油分类问题的应用研究

在火灾调查中,检测汽油成分并对其进行正确分类尤为重要.运用GC-MS对90#和93#两种普通汽油的共50个样本进行检测,所得的GC-MS原始数据通过PCA方法进行处理,以提取有用信息,避免冗余变量进入后续计算.在此基础上应用KNN方法对这两种汽油助燃剂进行分类.结果表明, KNN方法对这两种汽油的分类准确率达到100%,且当初始数据未经标准化预处理时也能达到同样准确的分类效果.研究表明:将模式识别方法正确地运用到助燃剂鉴定和分类工作中有助于火灾调查.     

水动力条件下蓝藻水华生消的模拟实验研究与探讨

蓝藻水华是当今世界共同面临的重大水污染问题之一。通过室内模拟实验,在温度、光照、初始pH值和营养盐等基本条件相同的前提下模拟水流流速分别为10cm/s、20cm/s、30cm/s、40cm/s时铜绿微囊藻(Microcystis aeruginosa)水华的产生与消亡过程,在10～40cm/s流速区间里藻类生长周期随流速增大而变长,藻类最大现存量在40cm/s流速下最大,在10cm/s流速下最小,流速为30cm/s时藻类比增率最大,较适合藻类生存,在整个水华暴发过程中水体氮磷营养浓度呈下降趋势,水体的pH、DO和Ec变化不大。