温带典型草地土壤净氮矿化作用研究

应用树脂芯方法,研究了内蒙古锡林河流域不同降水强度3种草地类型土壤净氮矿化作用.结果表明,7～10月份,羊草草原的平均净氮矿化率为0.333 kg·(hm²·d)^-1,贝加尔针茅草原为0.316 kg·(hm²·d)^-1,克氏针茅草原为0.211 kg·(hm²·d)^-1;在相同的培养周期内,分阶段培养和连续培养对土壤的净氮矿化量和净氮矿化速率有显著影响;降雨是影响该区域氮素矿化的主要因素之一,3种草地类型土壤水分变化量与土壤净氮矿化速率呈正相关关系,相关系数分别为0.80、0.61、0.56.     

Analysis of perfluorooctanoate (PFOA) and other perfluorinated compounds (PFCs) in the River Po watershed in N-Italy

C7-C11 perfluorinated carboxylates (PFACs) and perfluorooctansulfonate (PFOS) were analysed in selected stretches of the River Po and its major tributaries. Analyses were performed by solid-phase extraction (SPE) with Oasis HLB cartridges and methanol elution followed by LC-MS-MS detection using 13C-labelled internal standards. High concentration levels ( approximately 1.3 microg l(-1)) of perfluorooctanoate (PFOA) were detected in the Tánaro River close to the city Alessandria. After this tributary, levels between 60 and 337 ng l(-1) were measured in the Po River on several occasions. The PFOA concentration close to the river mouth in Ferrara was between 60 and 174 ng l(-1). Using the river discharge flow data in m3 s(-1) at this point (average approximately 920 m3 s(-1) for the year 2006), a mass load of approximately 0.3 kg PFOA per hour or approximately 2.6 tons per year discharged in the Adriatic Sea has been calculated. PFOS concentration levels in the Po River at Ferrara were approximately 10 ng l(-1).     

Biomonitoring zur wirkungsbezogenen Ermittlung der Schadstoffbelastung in terrestrischen Ökosystemen

Biomonitoring programmes provide relevant information, which may supplement ambient air pollution monitoring or modelling around emission sources. As a prerequisite, assessment scales for biomonitoring data have to be derived based on an objective evaluation of available data, as well as on a scheme of presentation, which is suggestive and easily understandable even for laymen. Based on an evaluation of numerous monitoring programmes, assessment scales for biomonitoring results are derived for plant biomonitoring, which also serve as a basis for the graphical presentation of monitoring results. This study is focussed on bioindicator plants like mosses (passive biomonitoring) and exposed lichens (active biomonitoring), in which 14 metal elements are investigated. As an example, data from a local biomonitoring network around a cement plant were used to demonstrate the use of the assessment scales derived and the presentation scheme developed. Data sets from about 15 moss and 24 lichen biomonitoring programmes, comprising more than 1000 specimens, were sorted by their pollutant characteristics in order to form the database. Data on the metal contents of species demonstrating similar values with respect to growth characteristics and habit, and representing background or low pollution levels, are aggregated and their statistical distributions are evaluated. Spacing of the assessment scales and their colour designations are derived from the 50-, 75-, 90- and 95-percentile values. Graphical presentation allows a comparison of the absolute values of metal contents and a relative association of measured values. Exemplary results from moss and lichen monitoring around a cement plant are generally below or slightly above the median values at background and low-pollution sites. Metal contents are higher in lichens compared to mosses for 7 elements (Cd, Cu, Hg, Pb, Sb, Sn, Zn), and are lower in lichens only for thallium. The assessment scheme presented is mainly aimed at the practitioner in the field of biomonitoring in order to provide a reliable and sound scale of assessment by comparison on an absolute scale rather than presenting the basis of ecological risk assessment. Differences in metal content of co-located samples of various moss species and possible correction procedures are briefly discussed- as well as the consequences of pooling monitoring data across various moss species for the quality of assessment scales. Further evaluations shall focus on species-specific rather than on pooled databases and will investigate the consequences of the use of correction factors when extrapolating metal data from one monitoring species to another.     

The BIOTA Biodiversity Observatories in Africa—a standardized framework for large-scale environmental monitoring

The international, interdisciplinary biodiversity research project BIOTA AFRICA initiated a standardized biodiversity monitoring network along climatic gradients across the African continent. Due to an identified lack of adequate monitoring designs, BIOTA AFRICA developed and implemented the standardized BIOTA Biodiversity Observatories, that meet the following criteria (a) enable long-term monitoring of biodiversity, potential driving factors, and relevant indicators with adequate spatial and temporal resolution, (b) facilitate comparability of data generated within different ecosystems, (c) allow integration of many disciplines, (d) allow spatial up-scaling, and (e) be applicable within a network approach. A BIOTA Observatory encompasses an area of 1?km² and is subdivided into 100 1-ha plots. For meeting the needs of sampling of different organism groups, the hectare plot is again subdivided into standardized subplots, whose sizes follow a geometric series. To allow for different sampling intensities but at the same time to characterize the whole square kilometer, the number of hectare plots to be sampled depends on the requirements of the respective discipline. A hierarchical ranking of the hectare plots ensures that all disciplines monitor as many hectare plots jointly as possible. The BIOTA Observatory design assures repeated, multidisciplinary standardized inventories of biodiversity and its environmental drivers, including options for spatial up- and downscaling and different sampling intensities. BIOTA Observatories have been installed along climatic and landscape gradients in Morocco, West Africa, and southern Africa. In regions with varying land use, several BIOTA Observatories are situated close to each other to analyze management effects.     

World coal outlook: 1990s

In the 1990s for the newly industrializing nations of the Pacific Rim and for the OECD countries as well, the demand for energy is expected to increase at a rate in excess of that of the increase in GNP. The demand for coal is likely to increase as well but probably to a lesser degree than GNP. This is because coal can expect increasing competition not from oil, but from natural gas. For a whole host of reasons, economic as well as environmental, gas could be the preferred fuel of the 1990s. Nevertheless, coal prices can be expected to increase but low cost production due to come on stream shortly, is likely to keep those increases modest.