利用泥鳅对重金属富集的现象来指示河流污染变化程度的研究

利用泥鳅鱼在淤泥中寻找食物的生活习性,通过分析不同时期采集的泥鳅体内的重金属浓度,监测河流或底泥的污染程度,即可以把泥鳅作为河流或底泥污染程度的敏感指示动物.建立了用ICP-AES同时测定泥鳅鱼体内多种元素的方法,具有快捷、准确的特点.该方法的回收率为96.0%～106%,精密度RSD为1.7%～5.1%.     

崇明生态岛建设解析

崇明岛是位于长江口、世界上面积最大的河口冲积岛。笔者构建了科学性与可操作性、现实性与前瞻性、针对性与示范性相结合的生态岛建设指标体系,并在崇明世界级生态岛建设中发挥了“引领生态岛建设方向。规范建设行为,调控建设进程”的作用,崇明生态岛建设成效初显。为了进一步发挥崇明生态岛建设的示范作用。笔者还提出了建设生态文明特区等建议。     

山东省典型工业城市土壤重金属来源、空间分布及潜在生态风险评价

选取山东省典型工业城市——莱芜市钢城区为研究区域,系统采集了106个表层土壤样品,测定了As、Cd、Co、Cr、Cu、Hg、Ni、Pb和Zn等9种重金属的含量,分别利用多元统计和地统计方法分析了重金属的来源和空间分布特征,最后对土壤重金属的潜在生态风险进行了评价.结果表明:1研究区9种重金属元素的平均含量均超过了山东省土壤背景值,其中Cd、Hg、Pb和Zn的平均值分别是背景值的2.42、4.69、1.74和1.54倍,在表层土壤中存在明显的富集.2Cd、Pb和Zn主要来源于工业"三废"、交通排放以及农药化肥的施用;Co、Cr和Ni为自然源因子,受到成土母质的控制;As和Hg来源于煤炭燃烧和钢铁冶炼,Cu受自然与人为因素共同影响.3研究区总体上处于中等与高生态风险的临界水平,其中Hg为高生态风险水平,Cd为中等生态风险水平,其他元素则均为低生态风险.     

Biodiversity of the ground-dwelling spider fauna of afforestation habitats

The aim of this study was to assess spider diversity among habitats that are typically used for afforestation in Ireland, and to identify habitat parameters which could potentially be used as indicators of their biodiversity value. Ground-dwelling spiders were surveyed in 24 sites across Ireland, with eight sites of each of the following habitat types: improved grassland, wet grassland and peatland. The spiders were sampled using pitfall traps which were located within the major vegetation types present in each site as well as within supplementary habitat features which may add to biodiversity value of the whole site such as hedgerows, flushes and the edges of ditches and streams.Each habitat supported distinct spider assemblages that reflect major differences in both environmental conditions and management regime. The improved grasslands had low spider species richness and low variation in assemblage structure which is probably related to the intensive management of this habitat. In this case hedgerows maybe an important aspect of the spider diversity within agricultural landscapes. The peatlands, and to a lesser extent wet grasslands, supported a diverse and specialist spider fauna, including a number of rare species; this may be due to differences in soil moisture and plant architecture. Indicators of biodiversity value identified included wet flushes in the peatlands and low grazing pressure in the wet grasslands. This study suggests that in terms of biodiversity value improved grassland is the preferable habitat for afforestation, because of the poor baseline spider diversity. However, it may be unrealistic to expect land owners to afforest their most productive agricultural land, so the management and habitat indicators identified in this study may be of use for assessing habitat quality among the wet grassland and peatlands to allow sites with lower biodiversity value to be identified.     

城市表层土壤重金属与磁化率的多尺度空间变异分析

采集徐州市城区167个表层土壤的样品,并分别测定了磁化率χ的数值及其5种重金属(Cu、Zn、Mo、Cd和Pb)的含量.利用多元因子克里金分析上述研究变量在局部尺度(1 km变程)和区域尺度(5.5 km变程)的空间变异特征.研究表明,徐州城市表土中的磁化率与重金属在局部尺度上主要受到交通、工业和农业等人为因素的影响,在区域尺度上,则以土壤母岩等自然因素为主导.磁化率#与Cu、Zn、Mo、Cd、Pb在局部尺度上的结构相关性较高,在此尺度内选择适当的采样间隔,有助于提高磁化率作为上述重金属污染替代指标进行空间制图的精度.     

Spatial evaluation of the risk of groundwater quality degradation. A comparison between disjunctive kriging and geostatistical simulation

In some previous papers a probabilistic methodology was introduced to estimate a spatial index of risk of groundwater quality degradation, defined as the conditional probability of exceeding assigned thresholds of concentration of a generic chemical sampled in the studied water system. A crucial stage of this methodology was the use of geostatistical techniques to provide an estimation of the above-mentioned probability in a number of selected points by crossing spatial and temporal information. In this work, spatial risk values were obtained using alternatively stochastic conditional simulation and disjunctive kriging. A comparison between the resulting two sets of spatial risks, based on global and local statistical tests, showed that they do not come from the same statistical population and, consequently, they cannot be viewed as equivalent in a statistical sense. At a first glance, geostatistical conditional simulation may appear to represent the spatial variability of the phenomenon more effectively, as the latter tends to be smoothed by DK. However, a close examination of real case study results suggests that disjunctive kriging is more effective than simulation in estimating the spatial risk of groundwater quality degradation. In the study case, the potentially ‘harmful event’ considered, threatening a natural ‘vulnerable groundwater system,’ is fertilizer and manure application.     

Monitoring of air pollution by polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans of pine needles in Korea

The atmospheric contamination levels of polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) were evaluated from the analysis of pine needles in South Korea. Pine needles were collected from 30 sampling points at five main cities in South Korea (Busan, Daegu, Gwangju, Changwon and Jeju island). The highest concentrations of PCDDs/DFs (2.19–26.88 pg I-TEQ/g of dry weight) were measured at Busan, where is the city of the highest population density and traffic volume among five cities. The lowest concentration was detected at Jeju with 0.62 pg I-TEQ/g dry weight, suggesting Jeju could be an environmental background area in Korea. The dominant homologues of PCDDs/DFs in pine needles were the lower chlorine-substituted compounds such as tetra CDDs and CDFs, and the distribution ratios of PCDDs/DFs decreased with increase of the number of chlorine substituents. Homologue profiles of pine needle samples were similar to PCDDs/DFs profiles of the vapor phase in the ambient air, and thus the pine needles absorbed the vapor phase of PCDDs/DFs from air. Results suggested that pine needles could be used as an indicator of the atmospheric contamination for PCDDs/DFs in Korea.     

Delineating high-density areas in spatial Poisson fields from strip-transect sampling using indicator geostatistics: application to unexploded ordnance removal

An approach for delineating high anomaly density areas within a mixture of two or more spatial Poisson fields based on limited sample data collected along strip transects was developed. All sampled anomalies were transformed to anomaly count data and indicator kriging was used to estimate the probability of exceeding a threshold value derived from the cdf of the background homogeneous Poisson field. The threshold value was determined so that the delineation of high-density areas was optimized. Additionally, a low-pass filter was applied to the transect data to enhance such segmentation. Example calculations were completed using a controlled military model site, in which accurate delineation of clusters of unexploded ordnance (UXO) was required for site cleanup.     

OPTIMAL BATHYMETRY OF TYRRHENIAN SEA BY STOCHASTIC INTERPOLATORS1

ABSTRACT: The analysis of the sea depth in the vicinity of a thermal power plant is important in view of the heat dispersion and transport of the cooling water discharged from the energy production processes. The bathymetry of the Tyrrhenian Sea in the area facing the thermoelectric plant being built at Montalto di Castro, Italy, is reconstructed with the aid of the kriging technique. The large number of measurements (2038) precludes the use of a global interpolation model. At the same time, the steepness of the variogram suggests that the stochastic process is likely non-stationary. The latter problem is managed by detrending the observed records with a fourth-order polynomial drift determined with the least squares method. The global approach is replaced with local models with an influence radius of 70 m and a minimal number of interpolation records equal to 10. The detrended residuals appear to be second-order stationary having an isotropic vaniogram that is fitted equally well by a linear or a spherical function. The average size of the local interpolation models is 28, which ensures a high cemputational efficiency. The bathymetry of the sea area of interest is then reconstructed over a regular grid with a total of 3570 nodes. The estimation standard deviation maps show that the accuracy of the prediction is even greater than the prescribed tolerance (= 0.2 m) and indicate that future data collection campaigns require a less dense and, therefore, less expensive recording network. The redundant measurement profiles are identified. Their elimination still allows for bathymetry estimates affected by interpolation errors that fall within the project specifications.     

A method to combine non-probability sample data with probability sample data in estimating spatial means of environmental variables

In estimating spatial means of environmental variables of a region from datacollected by convenience or purposive sampling, validity of the results canbe ensured by collecting additional data through probability sampling. Theprecision of the estimator that uses the probability sample can beincreased by interpolating the values at the nonprobability sample points tothe probability sample points, and using these interpolated values as anauxiliary variable in the difference or regression estimator. Theseestimators are (approximately) unbiased, even when the nonprobability sampleis severely biased such as in preferential samples. The gain in precisioncompared to the estimator in combination with Simple Random Samplingis controlled by the correlation between the target variable andinterpolated variable. This correlation is determined by the size (density)and spatial coverage of the nonprobability sample, and the spatialcontinuity of the target variable. In a case study the average ratio of thevariances of the simple regression estimator and estimator was 0.68for preferential samples of size 150 with moderate spatial clustering, and0.80 for preferential samples of similar size with strong spatialclustering. In the latter case the simple regression estimator wassubstantially more precise than the simple difference estimator.