京津冀地区一次污染过程的星载地基激光雷达联合观测分析

针对2018年3月9—15日京津冀地区的一次空气重污染过程,进行了基于地基颗粒物激光雷达组网的星载-地基联合观测分析。颗粒物激光雷达观测到污染前期为局地污染累积过程,中期有明显的污染物区域传输过程,北京受太行山沿线城市污染输送影响较大。风廓线激光雷达观测结果表明:此次污染过程近地面主要为偏南风且风力较弱,冷空气到来时风向转为较强东北风,导致污染消散。微波辐射计观测到保定在污染过程中出现持续6 d的逆温层,同时在污染过程中近地面相对湿度较高,逆温层被打破后污染开始消散。在污染过程的各个阶段中,污染团的空间分布与变化特征均被很好地反映出来,可见地天联合观测对污染物的累积与输送研究有较大的意义,能对京津冀及周边地区的大气污染联防联控提供有力支持。     

基于EFDC的长江常州段污水排江浓度场数值模拟

长江感潮河段水流与污染排放引起的浓度场复杂多变,基于EFDC(Environmental Fluid Dynamic Code)模型,采用正交曲线网格拟合自然河道边界,建立了长江常州段的水动力和水质模型。采用现场同步实测资料,与计算结果比对,证明该模型在水动力和水质两个方面都与实测数据吻合较好,满足了实际工程的需要;同时由于长江水流运动较快,一阶降解动力学已经满足了化学需氧量(COD)、氨氮(NH3-N)和总磷(TP)浓度计算要求,可以不考虑它们复杂的生化反应过程。     

A hybrid model for human factor analysis in process accidents: FBN-HFACS

Human factors are the largest contributing factors to unsafe operation of the chemical process systems. Conventional methods of human factor assessment are often static, unable to deal with data and model uncertainty, and to consider independencies among failure modes. To overcome the above limitations, this paper presents a hybrid dynamic human factor model considering Human Factor Analysis and Classification System (HFACS), intuitionistic fuzzy set theory, and Bayesian network. The model is tested on accident scenarios which have occurred in a hot tapping operation of a natural gas pipeline. The results demonstrate that poor occupational safety training, failure to implement risk management principles, and ignoring reporting unsafe conditions were the factors that contributed most failures causing accident. The potential risk-based safety measures for preventing similar accidents are discussed. The application of the model confirms its robustness in estimating impact rate (degree) of human factor induced failures, consideration of the conditional dependency, and a dynamic and flexible modelling structure.     

太原汾河景区跨桥断面水体污染的时空变化模式研究

选取太原汾河景区跨桥断面8个监测点,在2012年3月—2013年10月期间对河流8项水质参数进行监测,并结合派生的水体综合污染指数及主成分分析方法分析和评价景区水污染时空变化特征。结果表明,景区水质污染变化时空差异明显,上游污染相对较小,下游污染较重;春季溶解氧和p H值变化幅度最大,夏季除总氮和氨氮外,其他各污染物均有显著变化特征,秋季则以氨氮、总氮和总磷变化最为显著。主成分分析结果显示,虽然各监测点水体污染的关键影响因子不同,但总磷是太原市河流水体污染的共同解释因子。     

Modeling of a sequencing batch reactor treating municipal wastewater using multi-layer perceptron and radial basis function artificial neural networks

A sequencing batch reactor was modeled using multi-layer perceptron and radial basis function artificial neural networks (MLPANN and RBFANN). Then, the effects of influent concentration (IC), filling time (FT), reaction time (RT), aeration intensity (AI), SRT and MLVSS concentration were examined on the effluent concentrations of TSS, TP, COD and NH₄⁺-N. The results showed that the optimal removal efficiencies would be obtained at FT of 1 h, RT of 6 h, aeration intensity of 0.88 m³/min and SRT of 30 days. In addition, COD and TSS removal efficiencies decreased and TP and NH₄⁺-N removal efficiencies did not change significantly with increases of influent concentration. The TSS, TP, COD and NH₄⁺-N removal efficiencies were 86%, 79%, 94% and 93%, respectively. The training procedures of all contaminants were highly collaborated for both RBFANN and MLPANN models. The results of training and testing data sets showed an almost perfect match between the experimental and the simulated effluent of TSS, TP, COD and NH₄⁺-N. The results indicated that with low experimental values of input data to train ANNs the MLPANN models compared to RBFANN models are more precise due to their higher coefficient of determination (R²) and lower root mean squared errors (RMSE) values.     

Evaluation of Point and Diffuse Sources of Nutrients in a River Basin on Base of Monitoring Data

The methodology of materials accounting is presented and applied to developing nutrient balance (nitrogen and phosphorus) in a river basin. The method is based on the balance principle: inputs and outputs of each nitrogen and phosphorus related sub-systems were balanced. The application of the methodology strategies was illustrated by means of a case study of the Krka river, Slovenia. Different pathways of emission to surface waters were taken into account: WWTP discharges, direct discharges, erosion/runoff and baseflow. Total annual emission into the river Krka was estimated to be 362 tonnes N/year and 73.3 tonnes P/year. The main sources of nitrogen are diffuse sources, emitted via baseflow (52%). Other important sources are effluents from WWTP, which account for 36% of total emissions. Other sources like erosion and direct discharges to surface water (animal manure, industry, households) are of lower magnitude. Erosion is main source of phosphorus emission (55% of total emission), WWTP effluents account for 37% of total emission, while other sources are less important. Besides reduction of point sources by means of wastewater collection and implementation of nutrient removal technology, managing agricultural nitrogen and phosphorus to protect water quality should become a major challenge in the Krka river basin.     

长江三峡区间数字流域水系的构建

基于全球陆地一公里基础高程GLOBE数据 ,采用Martz和Garbrecht研制的数字高程流域水系模型自动提取长江三峡万县～宜昌区间的河网水系、各子流域分水线、河网与子流域编码及河网结构拓扑关系 ,从而构成该区域的数字流域和数字水系。结果表明该模型生成的水系是可以接受的 ,与 1:10万地形图上长江三峡万县～宜昌区间的水系一致 ,这为空间分布式模型的建立提供了必备的空间信息数据。最后 ,探讨了数字流域水系在流域生态学中的应用前景 ,构建的数字水系可为中尺度以上流域水体和水生生物的资源保护与合理利用提供决策平台 ,服务于社会经济的可持续发展。     

Measuring bed shear stress along vegetated river beds using FST-hemispheres

The measurement of the bed shear stress along vegetated river beds is essential for accurately predicting the water level, velocity and solute and sediment transport fluxes in computational hydroenvironmental models. Details are given herein of an experimental and theoretical study to determine the bed boundary shear stress along vegetated river beds introducing a novel field measuring method, namely the FliessWasserStammtisch (FST)-hemispheres. Although investigations have been conducted previously for sedimentary channels using the FST-hemispheres, this preliminary study is thought to be the first time that such hemispheres have been used to investigate the bed shear stresses in vegetated channels. FST-hemispheres were first developed by Statzner and Müller [1989. Standard hemispheres as indicators of flow characteristics in lotic benthos research. Freshwater Biology 21, 445-459] to act as an integrated indicator of the gross hydrodynamic stresses present near the bed. Test and validation data were found to be at least of the same order of magnitude for the stresses predicted from literature for sedimentary channels, with this study establishing the commencement of a database of calibrated FST-hemisphere laboratory data for vegetated channel beds. In a series of experiments, depths ranging from 0.1 to 0.28m were considered, equating directly to comparable conditions in small rivers or streams. The results of this study provide a basis for enabling the FST-hemispheres to be used to evaluate the boundary shear stress for a wider range of applications in the future, including vegetated river beds.     

Biological Activity in a Heavily Organohalogen-Contaminated River Sediment (8 pp)

Background, Aims and Scope Sediments of the Spittelwasser creek are highly polluted with organic compounds and heavy metals due to the discharge of untreated waste waters from the industrial region of Bitterfeld-Wolfen, Germany over the course of more than one century. However, relatively few data have been published about the chloroorganic contamination of the sediment. This paper reports on the content of different (chloro)organic compounds with special emphasis on polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/F), and chlorobenzenes. Existing concepts for the remediation of Spittelwasser sediment include the investigation of natural attenuation processes, which largely depend on the presence of an intact microbial food web. In order to gain more insight in terms of biological activity, we analyzed the capacity of sediment microflora to degrade organic matter by measuring the activities of extracellular hydrolytic enzymes involved in the biogeochemical cycling of carbon, nitrogen, phosphorus and sulfur. Furthermore, the detection of physiologically active bacteria in the sediment, particularly of those known for their capability to reductively dehalogenate organochlorine compounds, illustrates the potential for intrinsic bioremediation processes. Methods PCDD/F and chlorobenzenes were analyzed by gas chromatography(GC)/mass spectrometry and GC/flame ionization detection, respectively. The activities of hydrolytic enzymes were determined from freshly sampled sediment layers using 4-methylumbelliferyl (MUF) or 7-amino-4-methylcoumarin-conjugated model compounds and kinetic fluorescence measurements. Physiologically active bacteria from different sediment layers were microscopically visualized by fluorescence in situ hybridization (FISH). Specific bacteria were identified by 16S rRNA gene amplification and sequencing. Results and Discussion The PCDD/F congener profile was dominated by dibenzofurans. In addition, the presence of specific tetra and pentachlorinated dibenzofurans supported the assumption that extensive magnesium production was one possible source for the high contamination. A range of other chloroorganic compounds, including several isomers of chlorobenzenes, hexachlorocyclohexane and 1,1,1-trichloro-2,2-bis (p-chloro-phenyl)ethane (DDT), was present in the sediment. Activities of extracellular hydrolytic enzymes showed a strong decrease in those sediment layers that were characterized by high contents of absorbable organic halogen (AOX), indicating disturbed organic matter decay. Interestingly, an abnormal increase of cellulolytic enzyme activities below the organochlorine-rich layers was observed, possibly caused by residual cellulose from discharges of sulfite pulping wastes. FISH revealed physiologically active bacteria in most sediment layers from the surface down to the depth of about 60 cm, including members of Desulfitobacterium (D.) and Sulfurospirillum. The presence of D. dehalogenans was confirmed by its partial 16S rRNA gene sequence. Conclusions Results of chemical sediment analyses demonstrated high loads of organochlorine compounds, particularly of PCDD/F. Several years after stopping the waste water discharge to Spittelwasser creek, this sediment remains a main source for pollution of the downstream river system by way of the ongoing mobilization of sediment during high floods. As indicated by our enzyme activity measurements, the decomposition potential for organic matter is low in organochlorine-rich sediment layers. In contrast, the comparably higher enzyme activities in less organochlorine-polluted sediment layers as well as the presence of physiologically active bacteria suggest a considerable potential for natural attenuation. Recommendations and Perspectives From our data we strongly recommend to explore the degradative capacity of sediment microorganisms and the limits for in situ activity towards specific sediment pollutants in more detail. This will give a sound basis for the integration of bioremediation approaches into general concepts to reduce the risk that permanently radiates from this highly contaminated sediment. Submission Editor: Dr. Henner Hollert (Henner.Hollert@urz.uniheidelberg.de)     

人工神经网络在预测深基坑周边地表沉降变形中的应用研究

深基坑开挖引起的周边地表变形预测是一个复杂非线性问题,引起地表沉降的影响因素很多,各因素之间呈高度的非线性关系。传统的基坑用边地表沉降变形预测方法存在着一定的局限性,其预测精度有待提高,而人工神经网络是一种多元非线性动力学系统,可以灵活方便地对多成因的复杂未知系统进行高度建模,实现全面考虑各种主要影响因素的深基坑周边地表沉降变形预测。本文介绍了误差反向传播(BP)网络模型的结构、学习过程及其算法的改进,径向基函数(RBF)网络模型的结构及其学习过程;分析了影响深基坑开挖周边土体沉降变形的主要影响因素;以25个基坑工程的地表沉降实测资料为训练样本,建立了11个输入影响因素的BP神经网络模型和RBF神经网络模型,通过对样本的学习训练过程及对5个检验样本的预测精度,说明了人工神经网络用于预测基坑周边地表沉降的可行性和准确性。