“十二五”地表水国家环境监测网络吉林省水环境国控监测点位布设的构想

根据国家环境质量监测网络,对“十二五”地表水环境质量监测断面调整工作要求,吉林省在辖区内所有水环境质量监测断面及采样点基础上,完成了松花江流域和辽河流域国控监测断面的优化调整工作。在此过程中,如何从国家尺度上,既能充分反映吉林省水环境质量状况,又能满足国家对地表水环境管理需求进行了深入思考。本文以吉林省为例,在确定国控监测断面及采样点的布设中．提出了自己的构想和建议。     

主成分分析法在水环境质量评价中的应用进展

对研究水质的一种多元统计方法——主成分分析法做了详细介绍,并对主成分分析法在河流、地下水、矿区、湖泊水质评价中的应用进行了综述,简要分析了主成分分析法在水环境质量评价中尚有不足之处。     

黑岱沟露天矿排土场不同植被配置土壤水分研究——土壤水分垂直动态研究

文章通过黑岱沟露天煤矿排土场不同植被配置土壤水分垂直动态研究,阐述了不同植被配置类型对土壤水分的影响。结果显示：9种植被配置类型的土壤台水量随土层深度的增加而减小,但变化幅度有差异;原生植被处的土壤水分利用层厚度大于人工植被。     

耐冷菌在低温下处理污水的研究进展

低温污水的生物处理一直是水处理领域的难点和热点,由于耐冷菌对温度的适应范围较宽,且在低温下仍然保持较高的代谢活性,因此在污水处理和污染环境生物修复领域中的应用逐渐受到重视。本文介绍了耐冷菌在环境中的分布、主要种类以及适冷机理,概述了耐冷菌在工业废水和生活污水处理中的主要研究进展。指出应进一步开发环境中耐冷菌菌种资源,揭示耐冷菌的冷适应特性和功能表达之间的关系,加强耐冷菌在水体修复与净化领域的理论和应用研究,从而为我国北方尤其是东北地区的水环境保护提供行之有效的新途径。     

污水处理厂产泥量与进水水质关系的研究

为研究阜阳污水处理厂近几年来污泥产量与进水水质之间的关系,对自2007年1月份以来的产泥量与进水水质的基础数据进行了整理．并通过建立各个数据之间的相互关系图表来分析产泥量与进水水质之间的关系。     

聚硅酸对不同形态铝沉积行为的影响

针对给水管网中残余铝沉积和再溶解现象可能引起的水质问题,研究了聚硅酸对不同水解聚合形态铝沉积、再溶解的影响,并以石英微晶天平为表征手段,初步探讨了聚硅酸对不同形态铝沉积、再溶解过程影响的机理.结果表明,聚硅酸能显著改变不同水解聚合形态铝的沉积、再溶解行为.聚硅酸可与3种水解聚合形态的铝迅速结合而生成可沉积产物,但产物性质不同.以单体形态为主的Al_0与聚硅酸的反应产物性质较稳定,部分以溶解态存在,部分以非溶解态(可沉积态)存在;尽管铝的两种聚合形态Al_(13)和Al_(30)与聚硅酸反应也生成了部分可沉积产物,但随着时间的推移,这些产物又逐渐向溶解态转化.铝硅比对Al_0体系中铝的沉积溶解行为影响较小,而对Al_(13)和Al_(30)影响较大,且在0.2∶20(以Al和SiO_2计的质量比)时,沉积态铝的溶解速率最快.     

富营养化水体中黑水团的吸收及反射特性分析

对黑水团水体光学特性进行研究,是利用遥感技术监测和评估黑水团事件的前提.针对2015年7月在太湖发生的黑水团现象,采集了太湖黑水团区(区域一)、蓝藻水华区(区域二)、清水区(区域三)共36个水样,对这3个区域的水体遥感反射率以及吸收特性进行对比分析.结果表明:1区域一水体的总颗粒物、色素颗粒物和非色素颗粒物吸收系数比区域二、区域三高出1~2倍,在400~500 nm之间,区域一CDOM吸收系数相比另外两个区域的水体高出2倍左右.导致黑水团区域水体具有很低的遥感反射率,被人眼感知时呈现为黑色;2黑水团区域水体M值低于滇池、巢湖和太湖的M值变化范围,说明黑水团中CDOM的腐殖酸含量较高.此外,叶绿素a浓度与CDOM在350 nm处吸收系数之间具有很好的相关性,表明蓝藻的降解可能是黑水团中CDOM的一个主要来源;3在380 nm之后,黑水团区域的水体总吸收以色素颗粒物占主导,但在短波350~380 nm处,CDOM对总吸收的贡献率高于色素颗粒物和非色素颗粒物.     

Efficacy of two chemical coagulants and three different filtration media on removal of Aspergillus flavus from surface water

Aquatic fungi are common in various aqueous environments and play potentially crucial roles in nutrient and carbon cycling as well as interacting with other organisms. Species of Aspergillus are the most common fungi that occur in water. The present study was undertaken to elucidate the efficacy of two coagulants, aluminum sulfate and ferric chloride, used at different concentrations to treat drinking water, in removing Aspergillusflavus, as well as testing three different filtration media： sand, activated carbon, and ceramic granules, for their removal of fungi from water. The results revealed that both coagulants were effective in removing fungi and decreasing the turbidity of drinking water, and turbidity decreased with increasing coagulant concentration. Also, at the highest concentration of the coagulants, A. flavus was decreased by 99.6% in the treated water. Among ceramic granules, activated carbon, and sand used as media for water filtration, the sand and activated carbon filters were more effective in removing A.flavus than ceramic granules while simultaneously decreasing the turbidity levels in the test water samples. Post-treatment total organic carbon （TOC） and total nitrogen （TN） concentrations in the experimental water did not decrease; on the contrary, TN concentrations increased with the increasing dosage of coagulants. The filtration process had no effect in reducing TOC and TN in tested water.     

Biostability in distribution systems in one city in southern China：Characteristics, modeling and control strategy

This study investigated the bacterial regrowth in drinking water distribution systems receiving finished water from an advanced drinking water treatment plant in one city in southem China. Thirteen nodes in two water supply zones with different aged pipelines were selected to monitor water temperature, dissolved oxygen （DO）, chloramine residual, assimilable organic carbon （AOC）, and heterotrophic plate counts （HPC）. Regression and principal component analyses indicated that HPC had a strong correlation with chloramine residual. Based on Chick-Watson＇s Law and the Monod equation, biostability curves under different conditions were developed to achieve the goal of HPC 100 CFU/mL. The biostability curves could interpret the scenario under various AOC concentrations and predict the required chloramine residual concentration under the condition of high AOC level. The simulation was also carded out to predict the scenario with a stricter HPC goal （≤50 CFU/mL） and determine the required chloramine residual. The biological regrowth control strategy was assessed using biostability curve analysis. The results indicated that maintaining high chloramine residual concentration was the most practical way to achieve the goal of HPC ≤ 100 CFU/mL. Biostability curves could be a very useful tool for biostability control in distribution systems. This work could provide some new insights towards biostability control in real distribution systems.     

Evaluation of accuracy of linear regression models in predicting urban stormwater discharge characteristics

Stormwater runoff has been identified as a source of pollution for the environment, especially for receiving waters. In order to quantify and manage the impacts of stormwater runoff on the environment, predictive models and mathematical models have been developed. Predictive tools such as regression models have been widely used to predict stormwater discharge characteristics. Storm event characteristics, such as antecedent dry days （ADD）, have been related to response variables, such as pollutant loads and concentrations. However it has been a controversial issue among many studies to consider ADD as an important variable in predicting stormwater discharge characteristics. In this study, we examined the accuracy of general linear regression models in predicting discharge characteristics of roadway runoff. A total of 17 storm events were monitored in two highway segments, located in Gwangju, Korea. Data from the monitoring were used to calibrate United States Environmental Protection Agency＇s Storm Water Management Model （SWMM）. The calibrated SWMM was simulated for 55 storm events, and the results of total suspended solid （TSS） discharge loads and event mean concentrations （EMC） were extracted. From these data, linear regression models were developed. R2 and p-values of the regression of ADD for both TSS loads and EMCs were investigated. Results showed that pollutant loads were better predicted than pollutant EMC in the multiple regression models. Regression may not provide the true effect of site-specific characteristics, due to uncertainty in the data.