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.     

Effects of Coastal Lighting on Foraging Behaviorof Beach Mice

Abstract:  Introduction of artificial light into wildlife habitat represents a rapidly expanding form of human encroachment, particularly in coastal systems. Light pollution alters the behavior of sea turtles during nesting; therefore, long-wavelength lights—low-pressure sodium vapor and bug lights—that minimize impacts on turtles are required for beach lighting in Florida (U.S.A.). We investigated the effects of these two kinds of lights on the foraging behavior of Santa Rosa beach mice (  Peromyscus polionotus leucocephalus ). We compared patch use and giving-up densities of mice for experimental food patches established along a gradient of artificial light in the field. Mice exploited fewer food patches near both types of artificial light than in areas with little light and harvested fewer seeds within patches near bug lights. Our results show that artificial light affects the behavior of terrestrial species in coastal areas and that light pollution deserves greater consideration in conservation planning.     

Stability of a Coal Waste Artificial Reef

The feasibility of using U.K. coal-fired power station waste materials for artificial reef production is being examined. in June, 1989, an experimental artificial reef was constructed in Poole Bay, off the central south coast of the U.K., using three different mixtures of pulverised fuel ash (PFA), flue gas desulphurisation (FGD) gypsum and slurry, stabilized with cement and formed into blocks. Fifty tonnes of 40 × 20 × 20 cm blocks were formed into eight conical reef units replicating three different PFA/gypsum mixtures and one concrete control. the reef structure is 10m below chart datum on a flat sandy sea-bed.

Combustion of coal concentrates the heavy metal content in the resultant ash. the purpose of stabilization of the ash as blocks is twofold: to immobilize heavy metals (or other components) and to provide hard substratum for the attachment of organisms. to examine the effectiveness of this stabilization and hence the environmental compatibility of the block materials, heavy metal (Cd, Cr, Cu, Pb, Mn, Ni, Zn) content of the blocks has been monitored routinely over two years, to determine leaching rates. Sectional profiles indicate partial replacement of calcium content by magnesium. Associated with this there has also been some redistribution of heavy metals. Only in the case of cadmium has there been a detectable loss from the surface of blocks. Chromium and manganese concentrations appear to have increased. the metal content of the reef epibiota (including ascidians, Ascidia mentula; hydroids, Halecium spp.; bryozoans, Bugula spp. and red algae) growing on the ash blocks has been compared to that of epibiota attached to the concrete controls and surrounding sea-bed. to date no evidence of excess bioaccumulation of metals has been detected.

The physical integrity of the ash reef blocks has been maintained. There is evidence that the blocks are increasing in compressive strength.

An indication of the fishery enhancement potential of the experimental structure is given by the presence of eight commercially fished species (crustaceans and molluscs) including lobsters (Homarus gammarus).     

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。     

2018年春节期间京津冀地区污染过程分析

为了解2018年春节期间京津冀地区空气污染情况,利用近地面污染物浓度数据、激光雷达组网观测数据,结合WRF气象要素、颗粒物输送通量和HYSPLIT气团轨迹综合分析污染过程.结果表明,春节期间出现3次污染过程.春节前一次污染过程,各站点PM_2.5浓度均未超过200μg/m³;除夕夜,廊坊站点PM_2.5峰值浓度达到504μg/m³,是清洁天气的26倍;年初二~初五,各站点PM_2.5始终高于120μg/m³,且污染主要聚集在500m高度以下,北京地区存在高空传输,800m处最大输送通量达939μg/（m³·s）,此次重污染过程为一次典型的区域累积和传输过程.京津冀地区处于严格管控状态时,燃放烟花爆竹期间PM_2.5峰值浓度可达无燃放时PM_2.5峰值的3.2倍.为防止春节期间重污染现象的发生,需对静稳天气下燃放烟花炮竹采取预防对策.     

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.     

武当山夏季颗粒物数浓度谱分布特征及气团来源影响研究

为研究大气边界层中上层大气颗粒物的数浓度谱分布特征及气团来源的影响,于2018年6月利用3080型SMPS粒径谱仪对武当山14.6~660 nm颗粒物数浓度谱进行观测,分析和探讨了其数浓度谱分布及日变化特征,并结合后向轨迹、潜在源贡献因子法（PSCF）与浓度权重轨迹分析法（CWT）探讨对武当山颗粒物数浓度影响较大的外源输送路径和贡献源区.结果表明:①武当山大气颗粒物主要以爱根模态为主,平均数浓度为2 500个/cm3,积聚模态、核膜态平均数浓度分别为2 265、359个/cm3,3种模态数浓度分别占总数浓度的48.79%、44.21%、7.01%.②在新粒子生成日,核膜态数浓度于10:00开始上升,11:00—17:00的核膜态数浓度相对较高,约2 000个/cm3.新粒子生成日ρ（SO₂）与ρ（O₃）的日变化趋势均与核模态数浓度较为相似,表明SO₂和O₃参与光化学反应后的产物（硫酸及有机物）有利于新粒子的生成与增长.新粒子生成日风速、温度均大于非新粒子生成日,但相对湿度较低.③在东部及局地气团影响下大气颗粒物主要以积聚模态为主,数浓度分别为2 311和2 596个/cm3;核模态、爱根模态数浓度在受西北气团影响时最大,数浓度分别为806和3 078个/cm3.④潜在源区分析表明,影响武当山积聚模态数浓度的主要源区为十堰市本地及襄阳市,二者贡献值在840个/cm3以上.研究显示,武当山颗粒物主要以爱根模态为主,颗粒物数浓度日变化主要受大气边界层发展及山谷风的影响,较高的ρ（SO₂）与ρ（O₃）以及高温、低湿及较大的风速均有利于新粒子的生成,周边城市的区域性传输对武当山颗粒物的影响较大.      

厦门市冬季PM2.5污染情境识别及其与气象条件的关系

为研究厦门市冬季不同PM_2.5污染情境与气象条件和气团轨迹路径特征的关系,结合PM_2.5观测数据,使用AGAGE（Advanced Global Atmospheric Gases Experiment）统计方法识别2014—2018年冬季厦门市PM_2.5观测值、基线值和污染值情境,通过气象数据统计和气团后向轨迹聚类对不同PM_2.5污染情境下气象条件和气团轨迹路径特征进行探究.结果表明:①厦门市冬季不同PM_2.5污染情境下,ρ（PM_2.5）及PM_2.5污染值情境时长占比均呈波动中下降的趋势,具体表现为冬季PM_2.5观测值、污染值和基线值情境下,ρ（PM_2.5）平均值分别从2014年的42.2、90.7、16.4 μg/m3降至2018年的26.3、56.9、8.8 μg/m3,冬季PM_2.5污染值情境时长占比从2014年的10.2%降至2018年的3.0%.②冬季PM_2.5污染值情境下气象要素呈低风速、低气压、高温度、高相对湿度的特征.③冬季到达厦门市的气团轨迹路径中,局地路径由于大气条件稳定易累积形成PM_2.5污染;偏北路径和西北路径易从临近省份携带污染物输入导致PM_2.5污染,属于重要的外源污染输入路径;沿海路径和偏西路径均属于清洁路径,但沿海路径易在福建省北部与偏北路径重合形成污染输入,加强了偏北路径的污染物输送能力.研究显示,近年来厦门市冬季PM_2.5污染有明显减弱趋势,但不利的气象条件和外来污染输入仍会造成PM_2.5污染的发生.      

人工智能技术对长江流域水污染治理的思考

随着经济的快速发展和城市化进程的不断加速,促使水污染严重的长江流域需从污染物去除过程的建模与优化、污水处理过程的优化控制、水污染监测系统的构建开展水污染治理研究.传统的水污染处理技术存在污染物去除效率预测精度较低、污水优化控制成本较高、水污染监测滞后效应严重的问题.人工智能技术能够有效克服上述问题,因此通过梳理国内外学者利用人工智能技术在污水污染物去除过程的建模与优化、污水处理过程的优化控制及水污染监测系统的构建等方面的研究成果,为全面加强长江流域水污染治理能力提供科学可靠的技术指导.结果表明:①利用人工神经网络技术（径向基神经网络、多层前馈网络-人工神经网络、多层感知器神经网络）对污水污染物去除过程进行建模与优化,为精确预测长江流域重金属（Cr、Cu）、营养盐（TN、TP）、持久性有机污染物〔PBDEs（多溴二苯醚）、HCH（六氯环己烷）〕的去除率提供重要参考价值.②采用污水处理的自动控制技术与人工智能技术（递归神经网络、支持向量机、模糊神经网络等）构建污水智能控制系统,为长江流域实现高效节能的污水优化控制提供重要的技术指导.③利用在线监测仪器和人工智能技术（小波神经网络、多元线性回归-人工神经网络、叠层去噪自动编码器等）建立水污染智能监测系统,为解决长江流域水污染监测响应滞后问题提供有力的技术支持.因此,人工智能技术对长江流域提高污水污染物去除率,降低污水优化控制成本,提升水污染监测时效性具有重要的推广价值.