玄武湖沉积物中磷的形态分布特征

利用分级提取法分析了玄武湖的沉积磷形态,在玄武湖沉积物中,铝结合态磷的含量较低,平均值为64 mg/kg,其余形态磷中,铁结合态磷为241 mg/kg,有机磷为335 mg/kg,钙结合态磷为394 mg/kg.在环境变化的条件下,铁结合态磷可以释放到间隙水和上层水体中,是湖泊产生富营养化的重要因素;铝结合态磷由于含量少,对湖泊富营养化影响很小;钙结合态磷相对稳定且很难被生物利用,对湖泊富营养化影响不大;有机磷对水体有机负荷影响较大,并影响水体富营养化程度.     

Environmental Water-Quality Zones for Streams: A Regional Classification Scheme

Various approaches have been used to classify large geographical areas into smaller regions of similar water quality or extrapolate water-quality data from a few streams to other unmonitored streams. A combination of some of the strengths of existing techniques is used to develop a new approach for these purposes. In this new approach, referred to here as SPARTA (SPAtial Regression-Tree Analysis), environmental characteristics for each monitored stream are first quantified using a Geographic Information System (GIS) and then regression-tree analysis is used to determine which characteristics are most statistically important in describing the distribution of a specific water-quality constituent. GIS coverages of only the most statistically significant environmental characteristics are then used to subdivide the area of interest into relatively homogeneous environmental water-quality zones. Results from the regression-tree analysis not only define the most important environmental characteristics, but also describe how to subdivide the coverage of the specific characteristic (for example, areas with <26% or ≥26% soil clay content). The resulting regionalization scheme is customized for each water-quality constituent based on the environmental characteristics most statistically related to that constituent. SPARTA was used to delineate areas of similar phosphorus, nitrogen, and sediment concentrations (by including land-use characteristics) and areas of similar potential water quality (by excluding land-use characteristics). The SPARTA approach reduced the variability in water-quality concentrations (phosphorus, total nitrogen, Kjeldahl nitrogen, and suspended sediment) within similarly classified zones from that obtained using the US Environmental Protection Agency's nutrient ecoregions.     

Translating habitat class to land cover to map area of habitat of terrestrial vertebrates

Area of habitat (AOH) is defined as the “habitat available to a species, that is, habitat within its range” and is calculated by subtracting areas of unsuitable land cover and elevation from the range. The International Union for the Conservation of Nature (IUCN) Habitats Classification Scheme provides information on species habitat associations, and typically unvalidated expert opinion is used to match habitat to land-cover classes, which generates a source of uncertainty in AOH maps. We developed a data-driven method to translate IUCN habitat classes to land cover based on point locality data for 6986 species of terrestrial mammals, birds, amphibians, and reptiles. We extracted the land-cover class at each point locality and matched it to the IUCN habitat class or classes assigned to each species occurring there. Then, we modeled each land-cover class as a function of IUCN habitat with (SSG, using) logistic regression models. The resulting odds ratios were used to assess the strength of the association between each habitat and land-cover class. We then compared the performance of our data-driven model with those from a published translation table based on expert knowledge. We calculated the association between habitat classes and land-cover classes as a continuous variable, but to map AOH as binary presence or absence, it was necessary to apply a threshold of association. This threshold can be chosen by the user according to the required balance between omission and commission errors. Some habitats (e.g., forest and desert) were assigned to land-cover classes with more confidence than others (e.g., wetlands and artificial). The data-driven translation model and expert knowledge performed equally well, but the model provided greater standardization, objectivity, and repeatability. Furthermore, our approach allowed greater flexibility in the use of the results and uncertainty to be quantified. Our model can be modified for regional examinations and different taxonomic groups.     

基于HFACS的空中相撞事故分析及建议

空中相撞事故往往是由诸多人为差错相互叠加、耦合和作用而导致的,要找出事故的真正诱因,防止类似事故再次发生,难度非常大。为了有效地分析和定位人为差错,以更好地服务于防相撞的管理与决策,提出一种基于人为因素分析分类系统（HFACS）的空中相撞事故分析方法,它按照从显性差错到隐性差错的思路来分析事故的诱因,最终找出组织因素对事故的影响。并利用HFACS对巴西卡欣布上空发生的一起空中相撞事故进行了系统分析。案例分析结果表明,该方法不仅能够找出导致空中相撞事故的人为差错,解释事故发生的原因和过程,而且能够据此提供防止相撞事故发生的安全建议。     

Nutrient dynamics between sediment and overlying water in the inner part of Izmir Bay, Eastern Aegean

In this article a concept is described in order to predict and map the occurrence of benthic communities within and near the German Exclusive Economic Zone (EEZ) of the North Sea. The approach consists of two work steps: (1) geostatistical analysis of abiotic measurement data and (2) calculation of benthic provinces by means of Classification and Regression Trees (CART) and GIS-techniques. From bottom water measurements on salinity, temperature, silicate and nutrients as well as from punctual data on grain size ranges (0–20, 20–63, 63–2,000 μ) raster maps were calculated by use of geostatistical methods. At first the autocorrelation structure was examined and modelled with help of variogram analysis. The resulting variogram models were then used to calculate raster maps by applying ordinary kriging procedures. After intersecting these raster maps with punctual data on eight benthic communities a decision tree was derived to predict the occurrence of these communities within the study area. Since such a CART tree corresponds to a hierarchically ordered set of decision rules it was applied to the geostatistically estimated raster data to predict benthic habitats within and near the EEZ.     

Uncertainty propagation in vegetation distribution models based on ensemble classifiers

Ensemble learning techniques are increasingly applied for species and vegetation distribution modelling, often resulting in more accurate predictions. At the same time, uncertainty assessment of distribution models is gaining attention. In this study, Random Forests, an ensemble learning technique, is selected for vegetation distribution modelling based on environmental variables. The impact of two important sources of uncertainty, that is the uncertainty on spatial interpolation of environmental variables and the uncertainty on species clustering into vegetation types, is quantified based on sequential Gaussian simulation and pseudo-randomization tests, respectively. An empirical assessment of the uncertainty propagation to the distribution modelling results indicated a gradual decrease in performance with increasing input uncertainty. The test set error ranged from 30.83% to 52.63% and from 30.83% to 83.62%, when the uncertainty ranges on spatial interpolation and on vegetation clustering, respectively, were fully covered. Shannon’s entropy, which is proposed as a measure for uncertainty of ensemble predictions, revealed a similar increasing trend in prediction uncertainty. The implications of these results in an empirical distribution modelling framework are further discussed with respect to monitoring setup, spatial interpolation and species clustering.     

Validation of the UN test method N.5

Many substances react with water in such a way that flammable gases are formed. For transport issues this reaction may possess a considerable hazard especially if the cargo is wetted by rain or by water from other sources. In the UN Recommendations on the Transport of Dangerous Goods these kinds of problems are addressed. The UN test N.5 “Test method for substances which in contact with water emit flammable gases” corresponds to this hazard. Classification according to the test method is done by measurement of the gas evolution rate of the flammable gas by any suitable procedure. At BAM a gravimetric approach is used to measure the gas evolution rate. In this paper we present the evaluation of the apparatus by means of an absolute calibration routine utilizing a reaction where a known amount of gas is produced as well as the evaluation of important parameters influencing the gas evolution rate using different substances. It can be shown that the apparatus is capable of measuring absolute gas volumes as low as 6 mL with an acceptable error of about 17% as determined from the reaction of Mg with demineralized water.     

亚临界机组锅炉锅筒缺陷统计及检验建议

锅简作为亚临界机组锅炉的重要部件,及时检验发现其存在缺陷并进行控制处理是保证机组安全稳定运行的重要条件。在收集汇总了近百台300MW级别亚临界机组锅炉的检验结果的基础上,对锅简缺陷的出现比例进行了分类统计。检验人员在编制锅筒的检验方案时,参考该统计结果,可提高检验的缺陷检出率及时效性。     

An analysis of assessment outcomes from eight years' operation of the Australian border weed risk assessment system

The majority of Australian weeds are exotic plant species that were intentionally introduced for a variety of horticultural and agricultural purposes. A border weed risk assessment system (WRA) was implemented in 1997 in order to reduce the high economic costs and massive environmental damage associated with introducing serious weeds. We review the behaviour of this system with regard to eight years of data collected from the assessment of species proposed for importation or held within genetic resource centres in Australia. From a taxonomic perspective, species from the Chenopodiaceae and Poaceae were most likely to be rejected and those from the Arecaceae and Flacourtiaceae were most likely to be accepted. Dendrogram analysis and classification and regression tree (TREE) models were also used to analyse the data. The latter revealed that a small subset of the 35 variables assessed was highly associated with the outcome of the original assessment. The TREE model examining all of the data contained just five variables: unintentional human dispersal, congeneric weed, weed elsewhere, tolerates or benefits from mutilation, cultivation or fire, and reproduction by vegetative propagation. It gave the same outcome as the full WRA model for 71% of species. Weed elsewhere was not the first splitting variable in this model, indicating that the WRA has a capacity for capturing species that have no history of weediness. A reduced TREE model (in which human-mediated variables had been removed) contained four variables: broad climate suitability, reproduction in less or than equal to 1year, self-fertilisation, and tolerates and benefits from mutilation, cultivation or fire. It yielded the same outcome as the full WRA model for 65% of species. Data inconsistencies and the relative importance of questions are discussed, with some recommendations made for improving the use of the system.     

Review of sustainability terms and their definitions

Terminology in the field of sustainable development is becoming increasingly important because the number of terms continues to increase along with the rapid increase in awareness of the importance of sustainability. Various definitions of terms are used by different authors and organizations, for example, green chemistry, cleaner production, pollution prevention, etc. The importance of this topic has stimulated research into the problems of clarifying ambiguity and classifying terms used in the sustainability field. This paper provides results of the literature survey and summarizes the definitions of the terms, focusing on the environmental engineering field. In some cases, it proposes an improved definition. A hierarchical classification of the terms and their relationships has been based on a layer format that is presented graphically.