利用城市污泥堆肥及建筑弃土种植麦冬研究

将污泥堆肥产品分别与建筑弃土按0%、10%、20%、30%、40%和50%(湿重)的比例配制营养土,以麦冬为例进行180 d的栽培实验,分析了营养土对麦冬生长特性、植物体内及栽培土壤中营养学指标和重金属含量的变化规律,并通过模糊综合评价方法选择营养土较佳配制方案。实验结果表明:堆肥比例在50%时麦冬生物量增加率、新生芽数及地表部分比重为最大值,在30%时纺锤体肉质数减少率为最大值;随着营养土中堆肥比例增加,麦冬体内养分含量、重金属积累量随之增加,均在50%时达到最大值;栽培土壤养分越多损失量越多,各指残留率越低,同时全磷、全氮及K含量降低率较有效磷、碱解氮小得多,Cr降低率在5.20%～8.34%之间,Zn降低率在3.27%～17.35%之间;堆肥比例在40%以上的营养土对麦冬生长效果好,但较佳配制方案为堆肥产品占20%。     

人工神经网络和专家系统在污水生物处理系统中的应用

对近年来国内外污水生物处理系统中人工神经网络和专家系统的应用进行了简要的回顾。分析了废水生物处理工艺难于控制的原因及人工神经网络和专家系统的结构和特点。结果表明．国外智能控制发展迅速,并且应用领域遍及污水生物处理的各个方面,国内尚处于起步阶段。简要探讨了废水生物处理智能控制今后应深入研究的问题及方向。     

Source characterization of ambient fine particles at multiple sites in the Seattle area

To identify major PM_2.5 (particulate matter ≤2.5 μm in aerodynamic diameter) sources with a particular emphasis on the ship engine emissions from a major port, integrated 24 h PM_2.5 speciation data collected between 2000 and 2005 at five United State Environmental Protection Agency's Speciation Trends Network monitoring sites in Seattle, WA were analyzed. Seven to ten PM_2.5 sources were identified through the application of positive matrix factorization (PMF). Secondary particles (12–26% for secondary nitrate; 17–20% for secondary sulfate) and gasoline vehicle emissions (13–31%) made the largest contributions to the PM_2.5 mass concentrations at all of the monitoring sites except for the residential Lake Forest site, where wood smoke contributed the most PM_2.5 mass (31%). Other identified sources include diesel vehicle emissions, airborne soil, residual oil combustion, sea salt, aged sea salt, metal processing, and cement kiln. Residual oil combustion sources identified at multiple monitoring sites point clearly to the Port of Seattle suggesting ship emissions as the source of oil combustion particles. In addition, the relationship between sulfate concentrations and the oil combustion emissions indicated contributions of ship emissions to the local sulfate concentrations. The analysis of spatial variability of PM_2.5 sources shows that the spatial distributions of several PM_2.5 sources were heterogeneous within a given air shed.     

Progress in developing an ANN model for air pollution index forecast

An air pollution index (API) reporting system is introduced to selected cities of China for public communication on air quality data. Shanghai is the first city in China providing daily average API reports and forecasts. This paper describes the development of an artificial neural network (ANN) model for the API forecasting in Shanghai. It is a multiple layer perceptron (MLP) network, with meteorological forecasting data as the main input, to output the next day average API values. However, the initial version of the MLP model did not work well. To improve the model, a series of tests were conducted with respect to the training method and structure optimization. Based on the test results, the training algorithm was modified and a new model was built. The new model is now being used in Shanghai for API forecasting. Its performance is shown reasonably well in comparison with observation. The application of the old model was only weakly correlated with observation. In 1-year application, the correlation coefficients were 0.2314, 0.1022 and 0.1710 for TSP, SO₂ and NO_x, respectively. But for the new model, for over 8 months application, the correlation coefficients are raised to 0.6056, 0.6993 and 0.6300 for PM₁₀, SO₂, and NO₂. Further, the new algorithm does not rely on manpower intervention so that it is now being applied in several other Chinese cities with quite different meteorological conditions. The structure of the model and the application results are presented in this paper and also the problems to be further studied.     

Neural network forecasting of air pollutants hourly concentrations using optimised temporal averages of meteorological variables and pollutant concentrations

The new method for the forecasting hourly concentrations of air pollutants is presented in the paper. The method was developed for a site in urban residential area in city of Zagreb, Croatia, for four air pollutants (NO₂, O₃, CO and PM₁₀). Meteorological variables and concentrations of the respective pollutant were taken as predictors. A novel approach, based on families of univariate regression models, was employed in selecting the averaging intervals for input variables. For each variable and each averaging period between 1 and 97 h, a separate model was built. By inspecting values of the coefficient of correlation between measured and modelled concentrations, optimal averaging periods for each variable were selected. A new dataset for building the forecasting model was then calculated as temporal moving averages (running means) of former variables. A multi-layer perceptron type of neural networks is used as the forecasting model. Index of agreement, calculated for the entire dataset including the data for model building, ranged from 0.91 to 0.97 for the respective pollutants. As suggested by the analysis of the relative importance of the input variables, different agreements for different pollutants are likely due to different sources and production mechanisms of investigated pollutants. A comparison of the new method with more traditional method, which takes hourly averages of the forecast hour as input variables, showed similar or better performance. The model was developed for the purpose of public-health-oriented air quality forecasting, aiming to use a numerical weather forecast model for the prediction of the part of input data yet unknown at the forecasting time. It is to expect that longer term averages used as inputs in the proposed method will contribute to smaller input errors and the greater accuracy of the model.     

乡村路网对三峡库区社区水平森林结构的影响

道路作为人为扰动介质被认为是短时空尺度森林景观演化或用途转换的主要驱动力之一,体现为明显的“通道-阻隔”效应。论文以重庆市石柱县西沱镇为例,以3期遥感影像和调研数据为基础,利用ArcGIS的缓冲叠加功能,基于路网动态变化角度,从类型、林龄、起源等主要森林结构方面分析路网变化对森林结构变化的影响。结果表明：1）研究区道路数量先增加后减少,道路质量以等外公路和村级公路的改善为主。2）道路对森林景观干扰性明显。森林从类型、起源、林龄三方面在道路缓冲区内的破碎度均高于非缓冲区内的破碎度。1992—2002年及2002—2014年两个时期相比,前一时期其他灌木林、幼龄林以及萌生林大幅减少,基本表现为道路缓冲区内减少量大于非缓冲区内减少量。后一时期乔木林、中龄林以及萌生林有所增加,其他灌木林和成熟林轻微减少,其中,乔木林在道路缓冲区内增加量大于非缓冲区内增加量,中龄林及萌生林则表现为道路缓冲区内增加量弱于非缓冲区内增加量。3）道路影响域范围内,在无政策性干预条件下,道路的增加和质量的提高很大程度上导致森林景观的退化,低级路段的消失则有助于森林景观的恢复。     

“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。     

厌氧氨氧化菌富集培养过程微生物群落结构及多样性

为深入理解厌氧氨氧化菌富集培养过程微生物群落变化特征,采用ASBR反应器进行厌氧氨氧化菌富集培养,考察了不同培养时间微生物群落组成、多样性及物种网络关系.结果表明,通过逐步提高基质浓度,实现了厌氧氨氧化菌富集,NH₄⁺-N和NO₂^--N去除率分别为97.6%和95.4%,总氮去除率为84.9%.高通量测序发现,整个培养过程优势菌门(相对丰度> 5%)为变形菌门(Proteobacteria)、拟杆菌门(Bacteroidetes)、绿弯菌门(Chloroflexi)、浮霉菌门(Planctomycetes)、装甲菌门(Armatimonadetes)和放线菌门(Actinobacteria);富集培养获得的主要厌氧氨氧化菌为Candidatus Brocadia,相对丰度从1.42%增长到24.66%;培养过程,微生物群落优势菌群组成未发生变化,但相对丰度呈现显著差异(P <0.05).富集培养过程不同时间,微生物群落α多样性呈现先升高后降低的趋势,且存在显著差异(P <0.05)...     

不同土地利用方式对土壤细菌分子生态网络的影响

利用16S rDNA基因Illumina MiSeq高通量测序技术结合分子生态网络方法,测定了4种利用类型土地中的细菌群落组成,并分别构建了可视化的细菌网络.结果表明,旱田和水田土壤细菌网络的平均路径长度与模块性较小,而节点数、连接数、平均连通度和聚类系数较高;4个细菌网络均以正相关关系占优,天然林地负相关比例较高;酸杆菌门、厚壁菌门和变形菌门中的部分菌群在土壤细菌网络中起着重要的连接作用;4个细菌网络的部分关键节点所属的菌群相对丰度较低(<1%),并非本研究区域的主体细菌;旱田土壤菌群主要受TP显著影响(P<0.05);水田土壤菌群主要受黏粒、粉粒和含水量显著影响(P<0.05);天然林地和城市绿地土壤菌群主要受C/N显著影响(P<0.05).以上研究结果表明,旱田土壤细菌网络规模更大,物种间关系更加复杂,不同利用类型土地中的细菌均以协同合作关系为主,天然林地土壤细菌之间存在更强的竞争作用.水田和旱田土壤细菌对外界环境因子的扰动更加敏感,响应迅速,群落结构更易发生变化;部分细菌在网络间存在角色转化现象,低丰度菌群在构建土壤细菌网络中具有重要作用.     

我国燃煤电厂大气汞控制技术综合评估与对策探讨

采用模糊综合评价法与层次分析法或专家判定法相结合,对我国燃煤电厂非常规污染物大气汞控制技术进行了综合评估,以筛选出最佳控制技术.建立了环境、经济和技术为一级指标的三层指标体系共22个评价指标;初步筛选出洗选煤+烟气净化协同脱除技术、烟气净化协同脱除技术、烟气净化协同脱除技术+活性炭吸附技术等七项技术及技术组合并对其开展评估.结果表明:强调环境因素的层次分析法综合评估结果表明超低排放协同脱除技术+活性炭吸附技术得分最高(0.797 0),为最佳控制技术.而专家判定法与强调经济因素的层次分析法的综合评估结果一致,洗选煤+烟气净化协同脱除技术最具经济优势,是专家认可的最佳可用技术(BAT)和最佳环境实践(BEP).研究显示,我国现阶段可采用洗选煤+超低排放协同脱除技术对燃煤电厂的大气汞污染进行控制,但为达到发达国家的严格排放标准,必须采用超低排放协同脱除技术+活性炭吸附技术.