Seeking a balance: a procedure-based evaluation of localized approaches for brownfield management in the USA

Brownfield programs in the USA now use bottom–up approaches where the principle agent is no longer federal but local government. Although the approaches by federal government to manage national priority sites are well established, clear approaches for local brownfields and to engage nearby communities are difficult to find. This study sought to determine whether the current approaches adopted by local municipalities are effective and identify the challenges experienced to develop guidelines tailored to meet the needs of local projects. The results revealed that the effectiveness of local brownfield programs is often challenged by the existing normative assessment procedure utilized by the federal government. Experts’ interviews provided evidence that legislation set up to eliminate contamination is actually hurting efforts to reuse lightly polluted local sites. The challenges were associated with outreach activities, particularly those involving reluctant property owners and developers. Community residents had only a minimal opportunity to participate in decision-making.     

Matches and mismatches between conservation investments and biodiversity values in the European Union

Recently, the European Commission adopted a new strategy to halt the loss of biodiversity. Member states are expected to favor a more effective collection and redistribution of European Union (EU) funds under the current Multiannual Financial Framework for 2014–2020. Because of the large spatial variation in the distribution of biodiversity and conservation needs at the continental scale, EU instruments should ensure that countries with higher biodiversity values get more funds and resources for the conservation than other countries. Using linear regressions, we assessed the association between conservation investments and biodiversity values across member states, accounting for a variety of conservation investment indicators, taxonomic groups (including groups of plants, vertebrates, and invertebrates), and indicators of biodiversity value. In general, we found clear overall associations between conservation investments and biodiversity variables. However, some countries received more or less investment than would be expected based on biodiversity values in those countries. We also found that the extensive use of birds as unique indicators of conservation effectiveness may lead to biased decisions. Our results can inform future decisions regarding funding allocation and thus improve distribution of EU conservation funds.     

河湖水系连通分类体系探讨

河湖水系连通是保障国家水安全的治水新方略,科学的分类体系是开展河湖水系连通研究和生产实践的必然要求。论文结合河湖水系连通特点和内涵,提出五项分类原则:科学性、系统性、主导性、区域性和可操作性。综合考虑河湖水系连通的自然属性和经济社会属性,遵循五项分类原则,从连通性质、连通功能、连通区域、连通尺度、连通对象、连通时效、空间格局和连通方向等方面进行分类,初步构建了河湖水系连通分类体系,并对国内典型案例进行了归类;选择基于连通性质的分类、基于连通功能的分类和基于地区水资源特征的分类等三个主要分类展开分析,探讨了三种类型的连通特性、连通目标等主要问题。     

Comparison and ranking of different modelling techniques for prediction of site index in Mediterranean mountain forests

Forestry science has a long tradition of studying the relationship between stand productivity and abiotic and biotic site characteristics, such as climate, topography, soil and vegetation. Many of the early site quality modelling studies related site index to environmental variables using basic statistical methods such as linear regression. Because most ecological variables show a typical non-linear course and a non-constant variance distribution, a large fraction of the variation remained unexplained by these linear models. More recently, the development of more advanced non-parametric and machine learning methods provided opportunities to overcome these limitations. Nevertheless, these methods also have drawbacks. Due to their increasing complexity they are not only more difficult to implement and interpret, but also more vulnerable to overfitting. Especially in a context of regionalisation, this may prove to be problematic. Although many non-parametric and machine learning methods are increasingly used in applications related to forest site quality assessment, their predictive performance has only been assessed for a limited number of methods and ecosystems.In this study, five different modelling techniques are compared and evaluated, i.e. multiple linear regression (MLR), classification and regression trees (CART), boosted regression trees (BRT), generalized additive models (GAM), and artificial neural networks (ANN). Each method is used to model site index of homogeneous stands of three important tree species of the Taurus Mountains (Turkey): Pinus brutia, Pinus nigra and Cedrus libani. Site index is related to soil, vegetation and topographical variables, which are available for 167 sample plots covering all important environmental gradients in the research area. The five techniques are compared in a multi-criteria decision analysis in which different model performance measures, ecological interpretability and user-friendliness are considered as criteria.When combining these criteria, in most cases GAM is found to outperform all other techniques for modelling site index for the three species. BRT is a good alternative in case the ecological interpretability of the technique is of higher importance. When user-friendliness is more important MLR and CART are the preferred alternatives. Despite its good predictive performance, ANN is penalized for its complex, non-transparent models and big training effort.     

基于空间数据的太子河河流生境分类

在文献调研的基础上,结合河流特征和专家经验确定分类使用的指标,利用DEM、河流水系等空间数据,在ArcGIS软件下提取子流域,并计算子流域内河流系统的坡降、蜿蜒度、河网密度和河流等级4个分类指标值,应用聚类分析方法对太子河河流生境进行分类,将太子河河流生境分为源头陡峭河流生境、源头弯曲河流生境、源头河流生境、支流中下游河流生境、平原支流密集河网生境、支流弯曲河流生境、干流下游生境和干流蜿蜒河流生境等8种类型,各类型河流长度在223.8~773.1km之间,其中支流弯曲河流生境最长,而干流下游生境最短. 根据各生境类型的特征,提出了我国东北地区河流生境分类的指标参考值;根据不同生境类型的河道侵蚀、水量以及多样性潜力等特征,提出了不同河流生境类型的环境管理对策.      

Groundwater quality in the major industrial area of Thessaloniki,Greece part 1: Chemical composition‐geochemical processes

Adsorption rates of Sb(V) ions on an activated alumina (AA) were analyzed by batchwise experiments, while the continuous adsorption, desorption, regeneration of AA, and multiple reuse cycles were studied by flow column tests. The adsorption rates increased quickly with the increases of shaking speed and operation temperature. The adsorbed Sb(V) ions were desorbed easily by a 50 mM NaOH solution, and a 41–90 times concentrated Sb(V) solution was yielded correspondingly. AA was effectively regenerated by desorption operation and ca. 93% of the initial adsorption capacity was retained after six times adsorption/desorption cycles.     

Modelling global-scale potential grassland changes in spatio-temporal patterns to global climate change

Grassland is one of the most widespread vegetation types worldwide and plays a significant role in global carbon cycling. Understanding the sensitivity of grassland to climate change and the effect of climate changes on the grassland ecosystems is a key issue in global carbon cycling. One of the goals of this study was to evaluate the three net primary productivity (NPP)–climate models, i.e. the Miami model, the Schuur model and the classification indices-based model. Results indicated that the classification indices-based model was the most effective model at estimating large-scale grassland NPP. In this research, changes in the spatial pattern of global potential grassland from recent past (1950–2000) to future (2001–2050) A2a scenario were analysed with the integrated orderly classification system of grassland (IOCSG) approach in a Geographic Information System (GIS) environment. NPP was evaluated with the classification indices-based model. Results indicate that under recent past climatic conditions, the main parts of global grassland are the savanna and tundra and alpine grassland and will be converted into the savanna, steppe and semi-desert grassland in A2a scenario. As a whole, areas of grassland will increase by 31.76 million hectares. The classification indices-based model estimated a 12.40% increase of total NPP in grassland from recent past to A2a scenario. It will impose a new issue for future grassland researches to support sustainable development and to provide action relevant knowledge to meet the challenge of climate change.     

航空人为差错事故/事件分析(ECAR)模型研究

为深入研究航空人为差错事故/事件的影响因素,以人为差错相关理论为基础,对比分析几种典型的人为差错分析模型;通过借鉴ECCAIRS分析框架,并在基元事件分析(EEAM)逻辑和CCAR396部的分类方法基础上,构建航空人为差错事故/事件分析(ECAR)模型,它从事件层、描述层、原因层和组织因素与改进建议层,分析航空事故和不安全事件的人为差错。此外,还将组织因素概念引入该模型。     

城市道路交通事故地点文字表述方法研究

法律文书和交通安全分析要求事故地点记录准确、规范。为规范事故地点记录,在总结国外事故地点记录的点-线法、无规范格式法、线性参照系法、经纬度坐标法基础上,结合国内城市事故定位工作的需求,提出基于线性参照系的"五要素"事故地点文字表述方法。针对城市复杂道路网络,在道路分类的基础上,结合现场记录要求定义和说明"五要素"(事故所在道路、路侧、参照点、方位、距离),最后提出基于"五要素"的文字组合表述方法和事故地点记录实施方案。事故地点"五要素"记录法可供各地在改进事故地点记录时借鉴以提高事故数据的规范性。     

多类支持向量机在煤矿安全评价中的应用研究

针对矿井子系统诸多、环境复杂、影响因素多变和在现实条件下难以获得大量煤矿样本的情况,提出将对非线性、小样本问题有较高处理能力的支持向量机理论引入到机制评价中,并在归纳了支持向量分类机从一对多到一对一再到决策树模式的多渠道多层次分类原理基础上,建立了基于多分类支持向量机原理的煤矿安全多层次评价模型,同时通过提取影响煤矿安全因素的特征参数,引人类权重因子和样本权重因子,较好地解决了训练样本类别数量不平衡、数据干扰导致的错分问题,实现了对煤矿安全较高准确率和较高效率的评价.