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。     

重力挡土墙地震反应研究评述

首先，对重力挡土墙的地震反应机理进行了探讨，在此基础上简要回顾了国内外抗震设计规范的演变进程；然后，对挡土墙地震反应的研究方法进行了细致评述，包括拟静力极限平衡分析法、简化条件解析法、极限位移法、地震土压力简化公式、集总参数法、整体有限元法、现场地震调查、离心机试验、振动台试验和原型观测实验等；最后，指出了需要解决的问题并提出了今后的研究方向。     

基于DFA法的江苏省极端降水时空分布特征研究

为进一步掌握江苏省极端降水的时空分布特征,基于该省1961-2010年均一性较好的逐日降水数据,利用去趋势波动分析法确定了全省13个站点的极端降水阈值,并通过Morlet小波及Mann-Kendall法分析了江苏省极端降水频数的振荡周期及其突变。结果表明,江苏省极端降水年频数和夏季极端降水均呈现8～10 a的变化周期,且1998年和2006年分别为其突变增加年,而秋季极端降水主要呈2～3 a与5～7 a的变化周期;极端降水与降水总量的空间分布具有较好的一致性,均呈南部大、北部小的特征。     

Exploring the spatial dimension of community-level flood risk perception: a cognitive mapping approach

Environmental perceptions are central to individuals’ behavioural interactions with the environment. Cognitive maps, portraying a spatial representation of an individual’s environmental perception, can be aggregated to gain insight into the collective environmental perception of groups and populations. This paper uses cognitive mapping techniques to examine one aspect of environmental perception, flood risk perception, within a residential population (n?=?305). Flood risk perception was examined for the whole sample and six subgroup pairs. Using subgroups allowed examination of how factors previously shown to influence flood risk perception influence the cognitive map production in this population. We use a novel technique (slope analysis) to examine how the population’s perception of flood risk compares with expert assessments of flood risk, and compare the results of this novel technique with a commonly used cognitive map analysis technique (majority threshold method). Both methods identify areas where there is consensus within the population as to which areas are at risk of flooding. However, slope analysis usefully identifies areas where the population’s perception of flood risk lacks consensus, and is at odds with expert assessments of flood risk, without the loss of information inherent in the majority threshold method. Thus, this technique provides a novel approach to studies of environmental perception that can be widely applied within many fields.     

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。