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。     

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.     

城市给水管网优化设计研究

研究了几种典型的城市给水管网优化设计数学模型,并给出了求解方法,指出在给水管网系统的优化设计中进一步完善广义简约(GRG)算法的必要性.     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability     

Effects of bed materials on the performance of an anaerobic sequencing batch biofilm reactor treating domestic sewage

The objective of this study was to determine the best performance of an anaerobic sequencing batch biofilm reactor (AnSBBR) based on the use of four different bed materials as support for biomass immobilization. The bed materials utilized were polyurethane foam (PU), vegetal carbon (VC), synthetic pumice (SP), and recycled low-density polyethylene (PE). The AnSBBR, with a total volume of 7.2L, was operated in 8-h batch cycles over 10 months, and fed with domestic sewage with an average influent chemical oxygen demand (COD) of 358+/-110mg/L. The average effluent COD values were 121+/-31, 208+/-54, 233+/-52, and 227+/-51mg/L, for PU, VC, SP, and PE, respectively. A modified first-order kinetic model was adjusted to temporal profiles of COD during a batch cycle, and the apparent kinetic constants were 0.52+/-0.05, 0.37+/-0.05, 0.80+/-0.04, and 0.30+/-0.02h(-1) for PU, VC, SP, and PE, respectively. Specific substrate utilization rates of 1.08, 0.11, and 0.86mg COD/mgVS day were obtained for PU, VC, and PE, respectively. Although SP yielded the highest kinetic coefficient, PU was considered the best support, since SP presented loss of chemical constituents during the reactor's operational phase. In addition, findings on the microbial community were associated with the reactor's performance data. Although PE did not show a satisfactory performance, an interesting microbial diversity was found on its surface. Based on the morphology and denaturing gradient gel electrophoresis (DGGE) results, PE showed the best capacity for promoting the attachment of methanogenic organisms, and is therefore a material that merits further analysis. PU was considered the most suitable material showing the best performance in terms of efficiency of solids and COD removal.     

The Role of Foreign Direct Investment in Urban Environmental Management: Some Evidence from Hanoi, Vietnam

In recent years flows of foreign direct investment (FDI) to developing countries have rapidly been increasing. It is now an important contributor to the national economy and urban growth in scores of developing countries. Rapid urbanization in these countries is leading to many problems in the cities. Existing urban infrastructure and municipal services have been unable to cope with the increased demand arising from growing population and rapid economic growth. Consequently, the environment in these cities has deteriorated alarmingly. This paper assesses the role of FDI in urban environmental management (UEM) by analyzing the linkages between them for Hanoi City in Vietnam. The paper's analysis and findings are presented under three main themes: one, FDI, employment and income; two, FDI and environmental degradation; and three, potential of utilizing FDI for the provision of urban environmental infrastructure and services (UEI&S) in order to improve the urban environment. Both primary and secondary source data have been used. Policy implications of the research findings are drawn from the perspective of sustainable development.     

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。     

我国南方冰雪灾害的特征与城市救灾对策研究

在对2008年初中国南方所发生的冰雪灾害的损失、影响和成因进行分析的基础上,指出该次灾害具有受灾范围的全面性、灾害过程的发展性和救灾行动的艰难性等特征,阐明冰雪灾害在城市会造成停电停水、交通瘫痪和通讯中断等严重灾情,进而引发断油断粮、物价飞涨和人心恐慌等综合性灾害。通过冰雪灾害对城市救灾行动的总结,指出冰雪灾害给城市政府的深刻启示在于城市规模的急速扩张必须同时加强防灾救灾的软硬件建设,并提出城市必须采取持久开展防灾救灾知识宜传教育、大力加强防灾救灾基础设施建设、科学制订各类灾害的专业性应急预案和努力构建协同联动救灾机制等对策,有效提升城市应对灾害的能力,减少灾害造成的损失。     

城市燃气管道事故应急抢修方案的决策分析

通过对近年来的城市燃气管道事故抢险统计数据的分析与研究,管道事故抢险方案的选择存在着很大的主观性和片面性.为了克服应急抢修方案的种种局限,笔者应用模糊综合评判方法建立了城市燃气管道事故应急抢修方案评价选择模型;考虑可靠性、抢修时间、事故损失、抢险费用、社会影响及政治影响等6类影响因素来评判抢修方案的优劣,可以科学合理地选择最佳的管道事故应急抢修方案,达到经济合理、快速可靠的目的;实例验证,评判模型对城市燃气管道事故抢险具有重要的现实意义和参考价值.