恶臭采样技术及质量保证

针对现有国标方法中的恶臭采样技术进行了更为全面的叙述。对环境和特殊情况下的采样,并提出了现实的和可行的方法,保证了采样的规范性和数据的权威性。对恶臭采样的质量保证也提出了较高的要求。     

Biological pretreatment of Yellow River water

Bio-ceramic filter(BF) and moving-bed biofilm reactor(MBBR) were used for biological pretreatment of Yellow River water in this study. The BF only had slight advantage over MBBR for TOC and ammonia removal. However, like UV254, the average removal rate of THMFP in the BF was much higher than that in the MBBR. UV254 removal did not show obvious correlation with trihalomethane formation potential(THMFP) removal. Hexachlorocyclohexane could be effectively removed in both BF and MBBR. As for diatom and cyanobateria removal the MBBR had better performance than the BF, which was contrary to the average chlorophyll-a(Chl-a) removal rate. The proposal was made in this study that biological flocculation and sedimentation of sloughed biofilm should play a more important role on algae removal in the MBBR than in the BF. The BF and MBBR could effectively remove microcystins. Moreover, MBBR could be a promising technology for biological pretreatment.     

Fe(Ⅲ,Ⅱ)/H2O2体系中Fe(Ⅲ)水解特征的对比

利用Fe Ferron逐时络合比色法对类Fenton与Fenton体系中Fe(Ⅲ )水解形态的转化规律进行了比较 .结果表明 ,水解度越高 ,两体系中Fe(Ⅲ )的水解速度也越快 ,但水解度相同时 ,与Fenton体系相比 ,类Fenton反应生成的Fe(Ⅲ )的水解速率要低 ,且Feb 所占比例也较少 .与Fenton体系一致 ,类Fenton体系中的Fe(Ⅲ )水解速率随H2 O2 浓度的增加而减缓     

天津地区表层土壤多环芳烃含量的中尺度空间结构特征

应用地统计学技术对全天津地区表层土壤中 16种优控多环芳烃含量和土壤理化参数进行了空间结构分析 .结果显示 ,各组分浓度均存在中尺度的空间自相关性 .多环芳烃浓度的空间结构存在明显的各向异性 .大气运移和土壤TOC含量可能是影响土壤多环芳烃浓度空间结构特征的重要环境因素 .     

魔芋葡甘聚糖在污水处理中的应用

该文就魔芋葡甘聚糖的发展研究状况作了概述，并探讨其与蛋白质共混胶应用于水处理的可能性。     

滇池二维分层水质模拟研究

将三维问题“二维化”的分层迭代计算方法引入滇池水质模拟中，建立了湖泊二维分层水质模型，对滇池流场和总氮浓度场分两层进行了模拟计算，计算结果表明，该模型应用于滇池是成功的。     

北武夷下汪家铜多金属矿床地质特征及成因分析

下汪家铜多金属矿床形成于燕山晚期，成矿流体主要来自岩浆期后热液，断裂和岩浆岩是两大重要的成矿条件。控矿构造为北北东向断裂。成矿流体和主要矿质均源于地球深部，以上地幔或壳幔混合带为主，与燕山晚期富碱岩浆活动密切相关。下汪家铜多金属矿床成因上的分析，对该区下一步的找矿工作具有指导意义。     

关于公路环境监理专业化问题

根据公路项目的环境管理的现状和公路施工对环境的影响，结合公路环境监理试点工作的实践，提出建立专业化的环境监理队伍，专业化的组织形式，规范化的工作方法等。     

Application of Bayesian regularized BP neural network model for analysis of aquatic ecological data-A case study of chlorophyll-a prediction in Nanzui water area of Dongting Lake

Bayesian regularized BP neural network（BRBPNN） technique was applied in the chlorophyll-α prediction of Nanzui water area in Dongting Lake. Through BP network interpolation method, the input and output samples of the network were obtained. After the selection of input variables using stepwise/multiple linear regression method in SPSS i1.0 software, the BRBPNN model was established between chlorophyll-α and environmental parameters, biological parameters. The achieved optimal network structure was 3-11-1 with the correlation coefficients and the mean square errors for the training set and the test set as 0.999 and 0.000？8426, 0.981 and 0.0216 respectively. The sum of square weights between each input neuron and the hidden layer of optimal BRBPNN models of different structures indicated that the effect of individual input parameter on chlorophyll- α declined in the order of alga amount 〉 secchi disc depth（SD） 〉 electrical conductivity （EC）. Additionally, it also demonstrated that the contributions of these three factors were the maximal for the change of chlorophyll-α concentration, total phosphorus（TP） and total nitrogen（TN） were the minimal. All the results showed that BRBPNN model was capable of automated regularization parameter selection and thus it may ensure the excellent generation ability and robustness. Thus, this study laid the foundation for the application of BRBPNN model in the analysis of aquatic ecological data（chlorophyll-α prediction） and the explanation about the effective eutrophication treatment measures for Nanzui water area in Dongting Lake.     

太阳光作用下Fenton/草酸根体系对蒽醌染料降解的试验研究

以蒽醌染料(活性艳蓝K-3R)目标污染物，在自然光源下，应用Fenton／草酸根体系的降解过程进行试验研究。结果表明，通过太阳光／Fenton／草酸根的作用，可有效地净化含染料废水。