Fault-dynamic modelling of a phthalic anhydride reactor

A new methodology, fault-dynamic modelling, has been developed for analysis of potentially hazardous situations in the process industries. Traditional fault-tree analysis is used to determine the combinations of component failure that can lead to a particular process upset condition. Realistic dynamic modelling is then used to calculate the time available for corrective action once the upset has started. The method is applied to a phthalic anhydride reactor. The results of the analysis identify three process upsets that can lead to catastrophic failure in 2–5 min if left uncorrected. Other process upsets lead to safe conditions.     

Estimation of Cumulative Frequency Distribution for Carbon Monoxide Concentration from Wind-Speed Data, in Buenos Aires (Argentina)

In this article we apply and test a methodology to estimate cumulative frequency distribution for air pollutant concentration from wind-speed data. We use the inverse relationship after Simpson et al. (Atmospheric Environment, 19, 75–82, 1985) between the opposing percentile values in the statistical distributions for air pollutant concentrations and wind-speed data. This relationship is valid, irrespective of the statistical distributions of both variables, if an inverse relationship between them is also applicable. The available data are five years of 8-h average carbon monoxide concentration and 8-h mean wind-speed, observed in Buenos Aires (Argentina). The performance of the obtained empirical expressions in estimating cumulative frequency distributions for 8-h CO is statistically evaluated. The results show that it is possible to obtain an acceptable cumulative frequency distribution for 8-h CO concentration at the site if the cumulative frequency distribution for wind-speed is known. Q–Q plots show a good agreement between estimated and observed values. From our data, the mean relative error of the estimations was found to be as much as 8.0%.     

Temporal and Spatial Relationships Between Watershed Land Use and Salt Marsh Disturbance in a Pacific Estuary

Historical and recent remote sensing data can be used to address temporal and spatial relationships between upland land cover and downstream vegetation response at the watershed scale. This is demonstrated for sub-watersheds draining into Elkhorn Slough, California, where salt marsh habitat has diminished because of the formation of sediment fans that support woody riparian vegetation. Multiple regression models were used to examine which land cover variables and physical properties of the watershed most influenced sediment fan size within 23 sub-watersheds (1.4 ha to 200 ha). Model explanatory power increased (adjusted R(2) = 0.94 vs. 0.75) among large sub-watersheds (>10 ha) and historical watershed variables, such as average farmland slope, flowpath slope, and flowpath distance between farmland and marsh, were significant. It was also possible to explain the increase in riparian vegetation by historical watershed variables for the larger sub-watersheds. Sub-watershed area is the overriding physical characteristic influencing the extent of sedimentation in a salt marsh, while percent cover of agricultural land use is the most influential land cover variable. The results also reveal that salt marsh recovery depends on relative cover of different land use classes in the watershed, with greater chances of recovery associated with less intensive agriculture. This research reveals a potential delay between watershed impacts and wetland response that can be best revealed when conducting multi-temporal analyses on larger watersheds.     

Synergistic Techniques for Better Understanding and Classifying the Environmental Structure of Landscapes

The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC) for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions has become the search for the best classification that optimally trades off classification complexity for class homogeneity. In this study, three techniques are investigated for their ability to find the best classification of the physical environments of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network, and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure of the landscape and to use this knowledge to select the best ELC at the required scale of analysis.     

垃圾填埋场地下水污染修复技术优选研究

结合国内外地下水污染场地的修复经验,综合考虑当地社会经济条件、地下水脆弱性、污染物特征等因素,采用层次分析法建立了修复技术优化指标体系;在此基础上运用多准则决策分析模型(MCDA)进行地下水污染修复技术优选排序,构建垃圾填埋场地下水污染修复技术筛选模型;并以湖北省某简易垃圾填埋场为例进行应用研究。结果表明:在备选的5种场地地下水修复技术(监测自然衰减技术、渗透反应格栅、多相抽提技术、抽出-处理技术、原位微生物修复技术)中,抽出-处理技术、原位微生物修复技术较为理想。综合考虑该污染场地条件、地下水污染治理要求及附近受体分布情况,得到最佳修复方案为:高污染风险区域采用抽出-处理技术和原位微生物修复技术组合;低污染风险区域采用监测自然衰减技术。     

关于多氯联苯测定的探讨

对PCB测定中所使用的Aroclor和单体标准品的区别、联系和使用进行了分析阐述,并对PCB测定中的气相色谱法、气相色谱质谱联用法、生物分析法、免疫分析法的优点、局限性进行了比较.对今后的PCB的测定提出了建议。     

鄱阳湖典型湿地沉水植物的分布格局及其水环境影响因子

沉水植物是湖泊湿地生态系统中关键组分,调查研究沉水植物分布格局及其水环境影响因子,对于沉水植被的恢复与重建具有重要的指导意义。2013年5月初期分别对鄱阳湖典型湿地区域中有沉水植物的25个样地进行群落结构调查,采用系统取样方法对沉水植物进行调查采样并监测水环境因子,在野外调查的基础上运用GIS软件制作鄱阳湖典型区域沉水植物的生物量分布图,并采用主成分分析(PCA)和典范对应分析(CCA)方法分析其主要影响因子。结果表明:鄱阳湖湿地沉水植物以苦草(Vallisneria natans)为广布种,其中蚌湖及白沙湖以黑藻(Hydrilla verticillata)为优势种,白沙洲及乐安河龙口段以苦草为优势种,伴生种主要有金鱼藻(Ceratophyllum demersum)、马来眼子菜(Potamogeton malaianus)、菹草(P.crispus)、小茨藻(Najas minor)、大茨藻(N.marina)、刺苦草(V.spinulosa)和水车前(Ottelia alismoides)等。采用双向指示种分析法将研究区沉水植物分为6个群落;5月初大部分沉水植物尚处于生长季初期,生物量相对较低,仅菹草的生物量较大;沉水植物与浮叶植物共存现象明显。主成分分析(PCA)结果显示,第一主成分中水深、总磷和溶解氧等因子的系数值较大,第二主成分中pH值、化学需氧量和水体透明度等因子的系数值较大,是影响沉水植物分布的关键因子;典范对应分析(CCA)结果显示,水深、总磷和总氮对苦草和黑藻的影响显著,水体透明度是马来眼子菜的主要影响因子。     

城市生态系统复合下垫面碳通量特征——以上海市奉贤大学城为例

随着城市化进程的加速和城市人口规模的增加,城市已成为最大的碳源,研究城市生态系统对大气二氧化碳的贡献成为碳循环研究的焦点问题之一。基于研究区域内土地利用现状和一年的涡动观测系统观测数据,结合地理信息技术(Arc GIS)和通量计算工具(Eddypro及ART Footprint Tool)以及碳通量足迹模型分析了上海奉贤大学城碳通量足迹特征,基于此探讨不同下垫面类型,包括以草本和木本等透水层为主的下垫面(称为自然系统),以建筑物、道路等不透水层为主的下垫面(称为社会系统)碳通量的变化特征。研究结果表明:1)在不同风向上,碳通量贡献区范围随着大气稳定度的增加而扩大。大气处于稳定条件下,非主风向上的碳通量贡献区范围(最大范围1 100 m)比主风向上的碳通量贡献区范围(最大范围780m)要大;当大气处于不稳定条件下时主风向和非主风向下的碳通量贡献区范围相差不大(最大范围分别为321和351m)。2)不同下垫面其源汇特征不同,以绿色植物为主的自然系统年碳通量均值为–4.1μmol/m~2/s,表现为碳汇;社会系统的年碳通量均值为8.6μmol/m~2/s,表现为碳源。3)自然系统的碳通量日变化具有较明显的季节分异,变化特征大致呈"U"型;社会系统的碳通量日变化没有明显的季节分异,变化特征大致呈"M"型。绿色植物对城市生态系统的大气二氧化碳有降低作用,结合自然和社会系统的碳通量变化特征可以为以后合理规划城市布局,建立低碳城市提供服务。     

大气微生物与气象条件及大气污染物的灰色关联分析

根据大气微生物浓度、气象因子和大气污染理化因子的监测结果，应用灰色关联分析原理，分析研究大气微生物浓度与气象条件和大气污染物的关联程度，说明气象因子对各类微生物浓度的影响大于大气污染因子，特别是对耐高渗透压霉菌。     

基于内容分析法的土地利用总体规划目标偏好研究

土地利用总体规划需要统筹区域发展多元目标以增强对区域发展的指导力和约束性,因此全面了解我国土地利用总体规划的政策目标偏好,能为优化规划技术方法和改革规划管理体制提供政策参考。鉴于此,本文在分析我国土地利用总体规划多元目标及其关系的基础上,采用内容分析法基于全国土地利用总体规划纲要进行词频挖掘构建目标偏好测量维度及体系,进而对两轮省级土地利用总体规划文本进行目标偏好的定量测度,结果表明:(1)土地利用总体规划是多目标规划,通过内容分析法可以构建由经济、社会、生态三大目标构成的目标偏好测量体系;(2)从目标偏好排序来看,三大目标中社会目标始终是两轮土地利用总体规划的首要偏好目标,生态目标是土地利用总体规划的次要偏好目标,经济目标排在最后;同时相比上轮规划,本轮规划耕地保护子目标次序提前,土地整治子目标次序推后;(3)从目标偏好程度来看,社会目标的首位偏好程度有所下降,但其中耕地保护子目标的首位偏好度明显上升;生态目标和经济目标的首位偏好程度基本不变,总体而言本轮规划三大目标偏好程度的差异缩小。研究结果说明,我国土地利用总体规划始终坚持以耕地保护为核心的社会目标偏好,符合其是国土资源管理部门主导的部门规划的定位;虽然土地利用总体规划对经济、社会、生态三大目标的偏好程度差异缩小,但其若要在空间规划体系中发挥更大的作用,还需要通过优化规划技术和改革规划管理体制进一步均衡经济、社会、生态目标,以承担起统领全区域空间发展的要求。