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.     

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.     

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。     

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)     

岩溶地下河污染物运移模型对比研究

两区模型（TRM）和暂时存储模型（TSM）为两种常用的岩溶地下河（管道）污染物运移模型,为了更好表征岩溶地下河污染物运移过程,开展模型对比研究.采用两种模型拟合室内管道示踪实验穿透曲线,从概念模型框架、模型优缺点、参数校正过程和物理意义、参数敏感性等方面对比分析两种模型的异同.结果表明,OTIS软件提供TSM的数值解,而CXTFIT软件提供TRM的解析解,但两者均能通过下游不同位置的穿透曲线分段表征地下河不同阶段的污染物运移过程.两种模型的物理意义相近,均可近似描述岩溶地下河中溶质的暂时性存储现象,较好地拟合溶质运移曲线.采用TSM可校正得到暂时存储区的横截面积,但采用TRM只能获得非流动区所占的比例.两种模型中弥散系数和传质/交换系数的敏感度较低,并且弥散系数的变化对穿透曲线拖尾无显著影响.研究结果为岩溶地下河污染物运移模型的选取与应用提供了依据.     

北部湾南流江流域土地覆盖及生物多样性模拟

以北部湾独流入海河流南流江流域为研究对象,基于研究区2000年和2015年遥感数据解译的土地利用数据以及社会经济等数据,采用CLUE-S模型对未来2030年生态保护情景、自然增长情景以及粮食安全情景的土地利用格局进行了模拟预测,在此基础上采用InVEST模型对流域过去和未来不同情景的生物多样性进行了评估,探讨了流域生物多样性的生境质量和生境退化程度.结果表明：2000~2015年南流江流域建设用地、园地、水域和未利用地呈现出增加趋势,其中建设用地的增幅最大,而耕地和林地减幅最大.流域土地系统中共存在着34种土地网络转移流关系,上游存在24种,中游20种,下游28种,耕地与建设用地、耕地与林地以及林地与园地之间的转换占到流域总土地利用变化的70.74%.CLUE-S模型模拟未来土地利用的Kappa系数达到0.86,表明模型模拟未来情景的土地利用精度满足要求.2000年、2015年、2030年生态保护情景、2030年自然增长情景以及2030年粮食安全情景流域生境质量总得分和平均得分分别为866630,900357,921055,876231,865370和0.7457,0.7747,0.7925,0.7539,0.7466.2030年3种情景的中上游和下游地区生物多样性都呈现出不同程度的改善趋势,而中游地区则表现出退化趋势.     

Phosphate recovery with granular acid-activated neutralized red mud: Fixed-bed column performance and breakthrough curve modelling

Granular acid-activated neutralized red mud (AaN-RM) has been successfully prepared with good chemical stability and physical strength. However, its potential for industrial application remains unknown. Therefore, the performance of granular AaN-RM for phosphate recovery in a fixed-bed column was investigated. The results demonstrated that the phosphate adsorption performance of granular AaN-RM in a fixed-bed column was affected by various operational parameters, such as the bed depth, flow rate, initial solution pH and initial phosphate concentration. With the optimal empty-bed contact time (EBCT) of 24.27 min, the number of processed bed volumes and the phosphate adsorption capacity reached 496.95 and 84.80 mg/g, respectively. Then, the saturated fixed-bed column could be effectively regenerated with a 0.5 mol/L HCl solution. The desorption efficiency remained as high as 83.45% with a low weight loss of 3.57% in the fifth regeneration cycle. In addition, breakthrough curve modelling showed that a 5-9-1 feed-forward artificial neural network (ANN) could be effectively applied for the optimization of the fixed-bed adsorption system; the coefficient of determination (R²) and the root mean square error (RMSE) evaluated on the validation-testing data were 0.9987 and 0.0183, respectively. Therefore, granular AaN-RM fixed-bed adsorption exhibits promising potential for phosphate removal and recovery from polluted water.     

洪泽湖不同入湖河流沉积物磷形态特征及生物有效性

为揭示洪泽湖入湖河流沉积物磷形态空间差异性及影响因素,分析了洪泽湖自西北向西南7条入湖河流65个表层沉积物中不同磷（P）形态,并探讨了磷形态空间赋存特征的影响因素及环境意义.研究表明：沉积物总磷（TP）含量为488.90mg/kg~960.22mg/kg,无机磷（Pi）为主要形态,相对含量为65.81%~76.16%.西部入湖流域沉积物有机磷（Po）以非活性有机磷（NLOP）为主,汴河最高,相对含量约占Po的50.41%,生物有效态无机磷（BAP）相对含量最高,占Pi的66.84%,污染程度最高;西南和西北入湖流域Po则以中活性有机磷（MLOP）为主,Pi以钙结合态无机磷（HCl-Pi）为主.西北入湖流域由于受当地地质背景的影响,HCl-Pi所占Pi相对含量最高（43.02%）,从而减缓了磷的移动能力,污染程度最低.随着沉积物污染程度的增加,生物有效态Po含量增加,但所占Po相对含量降低;HCl-Pi含量增加,所占Pi相对含量降低,这一现象和我国其它典型地区沉积物磷形态空间分布类似.西部和西南入湖流域主要受水土流失、有机面源污染及藻类生长的影响,有机质环境较高,水交换能力弱,可被有机质降解的Po组分高于可被矿化的Po组分,大部分难降解Po组分易沉积,导致西部和西南入湖流域较高的BAP和NLOP含量,富营养化程度较高.沉积物OM是各形态磷之间相互转化的关键因素,和沉积物内源磷地球生物化学循环密切相关.洪泽湖入湖流域沉积物磷形态空间差异性主要由农业面源污染物的输入而导致内源磷负荷加剧.洪泽湖西部和西南入湖流域应重点控制农田水土流失及养殖业面源污染,建设滨岸修复带,遵循少量多次增施有机肥原则,减少农用地水土流失.健全农村养殖业废水废渣处理;划定科学养殖区;提倡铜围网箱,增加水体交换率.而对于洪泽湖西北入湖流域则应重点防止过度城镇化带来的水土流失及对生态功能保护区过高的污染负荷.     

天津市河流生态完整性评价

对河流生态健康状况进行评价,可为河流治理和生态修复提供依据.基于2018年8—9月天津市河流现场调查获取的物理、化学和生物群落指标（浮游动物、浮游植物、底栖动物、鱼类、水生大型植物、陆生植物）数据,构建包含物理完整性、化学完整性和生物完整性在内的河流IEI（index of ecological integrity,生态完整性指数）评价体系,对天津市河流生态健康状况进行评价.根据生物栖息地评分和水质状况确定参照点位,采用标准化方法筛选候选指标,应用层次分析法计算三部分指标权重,最终得出天津市河流生态健康评价结果.结果表明:①IEI评价结果显示,天津市河流生态健康状况等级为“健康”的样点占18.8%,“较好”的样点占28.1%,“一般”的样点占40.6%,“较差”的样点占6.3%,“差”的样点占6.3%,天津市河流生态健康状况整体处于“一般”水平.②相关性分析表明,ρ（NH₄+-N）和ρ（COD_Mn）超标是造成天津市水质达不到功能区标准的主要原因,同时也是影响河流生态健康的主要因素.研究显示,IEI评价法能够较为敏感地响应研究区面临的环境压力,适用于评价研究区河流生态健康.      

旅游目的地网络空间结构及其复杂性研究——野三坡旅游地案例实证

复杂性是旅游目的地网络化发展的必然趋势,是认识旅游地网络空间结构与组织特征的重要研究手段。论文以河北省野三坡旅游地为例,通过构建旅游联系强度模型,建立旅游地空间网络,并运用TOP网络空间分析以及复杂网络理论,揭示旅游地网络空间结构与组织的复杂性特征。研究发现：1）旅游地网络具有空间集聚性,形成了以核心景区为中心,由中心城镇、乡村社区和特色园区共同构成的空间集聚单元,并体现出“邻近连接”与“择优连接”的双重特性;2）旅游地网络服从幂律分布,具有无标度网络特性;3）每个节点的前三名和前五名旅游联系强度网络（Top3和Top5网络）具有较小的平均路径长度、较大的集聚系数,呈现出典型的“小世界网络”特征;4）旅游地网络是典型的异配型网络,度-度呈负相关,而网络节点的集聚系数与其度值之间存在近似的倒数关系,因此具有层次性。