环境基质中药物残留的固相提取与分析

废水流出物常常不可避免地进入地表水和用于饮用水资源的含水层．因废水再循环常常进入饮用水层,各种废水中的污染物最终会污染饮用水．以往环保部门一直比较注重农药和工业污染物,但最近的研究发现:废水流出物中的某些药物残留已达到了相当令人关注(１μｇ·１－１即ｐｐｂ)的程度．传统的分析技术(如液液萃取和ＧＣ/ＭＳ) 对极性较弱的化合物(ＰＣＢｓ和许多农药)比较有效,但对于极性相对较强的药物污染物而言,固相提取(ＳＰＥ)与ＬＣ/ＭＳ技术更适合于样品提取分析。     

Earth-tide-induced fluctuations in the salinity of an inland river,New South Wales,Australia: a short-term study

Wybong Creek discharges salts into the agriculturally and industrially important Hunter River in New South Wales, Australia. Abrupt increases in salinity occur periodically in the mid-Wybong Creek catchment. In order to understand the processes which cause these abrupt increases, changes in surface and groundwater were investigated. It is shown that salinity increases can be attributed to highly discrete groundwater discharge directly into the river from below. Hourly electrical conductivity data measured in the river showed regular, diurnal electrical conductivity fluctuations of up to 350 μS cm^?1. These fluctuations could not be attributed to barometric pressure, temperature, or evapotranspiration. Instead, a similar periodicity in surface water electrical conductivity and groundwater height in nearby groundwater wells was found. Fluctuations were of similar periodicity to the orthotides which cause fluctuations in surface water height and are induced by Earth tides. The geology in the mid-catchment area indicates conditions are optimal for Earth tides to impact groundwater. The reporting of orthotidal changes in water chemistry in this article is believed to be the first of its kind in the scientific literature, with the large fluctuations noted having important implications for water monitoring and management in the catchment. Further research investigating Earth-tide-induced phases of groundwater heights will better constrain the relationships between surface water chemistry and groundwater height.     

Assessing post-industrial land cover change at the Pine Point Mine,NWT, Canada using multi-temporal Landsat analysis and landscape metrics

This study investigates land cover change near the abandoned Pine Point Mine in Canada’s Northwest Territories. Industrial mineral development transforms local environments, and the effects of such disturbances are often long-lasting, particularly in subarctic, boreal environments where vegetation conversion can take decades. Located in the Boreal Plains Ecozone, the Pine Point Mine was an extensive open pit operation that underwent little reclamation when it shut down in 1988. We apply remote sensing and landscape ecology methods to quantify land cover change in the 20 years following the mine’s closure. Using a time series of near-anniversary Landsat images, we performed a supervised classification to differentiate seven land cover classes. We used raster algebra and landscape metrics to track changes in land cover composition and configuration in the 20 years since the mine shut down. We compared our results with a site in Wood Buffalo National Park that was never subjected to extensive anthropogenic disturbance. This space-for-time substitution provided an analog for how the ecosystem in the Pine Point region might have developed in the absence of industrial mineral development. We found that the dense conifer class was dominant in the park and exhibited larger and more contiguous patches than at the mine site. Bare land at the mine site showed little conversion through time. While the combination of raster algebra and landscape metrics allowed us to track broad changes in land cover composition and configuration, improved access to affordable, high-resolution imagery is necessary to effectively monitor land cover dynamics at abandoned mines.     

Foliar nutrient and metal levels of crops in the Mount Cameroon area—reference values for plant nutrition and environmental monitoring

The growing population number and traffic loads, increasing environmental pressures, agricultural intensification, and the establishment of Mount Cameroon National Park demand farsighted environmental management in the region and the definition of a favorable ecological status. Since plants grow in the interface between soils and the atmosphere they can be used as passive biomonitors for the environmental quality. At the same time, the accumulation of nutrients and pollutants in crops is linked to human health, so that foliar elemental levels can be used as an integrative measure for environmental pollution and impact assessment. In the present study, we collected leaf samples of plantain, cassava, cocoyam, and maize on 28 sites at the southern flanks of Mt. Cameroon and determined 20 chemical elements. Air pollution in the study area comes from biomass and waste burning mainly, but emissions from traffic and a large refinery were believed to also play a significant role. However, spatial patterns in foliar elemental concentrations reflected the geochemistry rather than specific sources of pollution. Significant differences in foliar metal and nutrient levels were observed between the four species, indicating a different demand and uptake of specific elements. The results were compared to published data on nutrient concentrations in the tested species and the so-called reference plant. The data can be used as a baseline for future studies in plant nutrition and the environmental monitoring in inner tropical regions where these crops are grown.     

Metal concentrations in American oyster <Emphasis Type="Italic">Crassotrea virginica</Emphasis> and adjacent sediments from harvestable and non-harvestable sites in the Southeastern USA

Human population growth in coastal areas continues to threaten estuarine ecosystems and resources. Populations of Crassostrea virginica have declined across the USA due to water quality degradation, disease pressure, alteration of habitat, and other changes related to anthropogenic impacts. Metals that may be present in estuarine habitats can bioaccumulate in oysters, with potential consequences to the health of oysters and humans consumers. This study (1) evaluated the occurrence and relationships of metal concentrations in oyster tissue versus estuarine sediments, (2) examined oyster tissue concentrations in relation to state water quality designations, and (3) evaluated the potential risk for humans from oyster consumption related to metal concentrations from harvestable waters. Results indicated metal concentrations in sediments and oysters along coastal South Carolina remain low compared to other areas and that concentrations in oyster tissue and adjacent sediments were not highly correlated with each other. However, high concentrations of some metals occurred in oysters sampled from areas designated as Approved for Harvesting. This is important because most harvest area designation systems rely on regular bacterial monitoring when evaluating the safety of consumption. Others safety measurements may be necessary as part of routine monitoring.     

Can we document if regulation and Best Available Techniques (BAT) have any positive impact on the marine environment? A case based on a steel mill in Greece

In order to document the impact of Best Available Techniques (BAT) and implementation of regulation on the improvement of the coastal marine environment state, we examined the case of a representative steel mill located at the Gulf of Elefsis (Greece). The evaluation of metal pollution was based on the analysis of major and trace elements, organic carbon, magnetic properties, and sediment accumulation rates, in sediment cores obtained from the vicinity of the plant. The analytical data are discussed in relation to steel production, changes of production routes, and adoption of BAT introduced in order to fulfill EU and national legislation. The results show that the input of pollutants to sediments and the degree of contamination were reduced by approximately 40–70% in the decade 2003–2015 in comparison to the periods of high discharges (1963–2002), whereas the toxicity risks from “high-to-extremely high” were reduced to “medium-to-high.”     

A Tool for Classification and Regression Using Random Forest Methodology: Applications to Landslide Susceptibility Mapping and Soil Thickness Modeling

Classification and regression problems are a central issue in geosciences. In this paper, we present Classification and Regression Treebagger (ClaReT), a tool for classification and regression based on the random forest (RF) technique. ClaReT is developed in Matlab and has a simple graphic user interface (GUI) that simplifies the model implementation process, allows the standardization of the method, and makes the classification and regression process reproducible. This tool performs automatically the feature selection based on a quantitative criterion and allows testing a large number of explanatory variables. First, it ranks and displays the parameter importance; then, it selects the optimal configuration of explanatory variables; finally, it performs the classification or regression for an entire dataset. It can also provide an evaluation of the results in terms of misclassification error or root mean squared error. We tested the applicability of ClaReT in two case studies. In the first one, we used ClaReT in classification mode to identify the better subset of landslide conditioning variables (LCVs) and to obtain a landslide susceptibility map (LSM) of the Arno river basin (Italy). In the second case study, we used ClaReT in regression mode to produce a soil thickness map of the Terzona catchment, a small sub-basin of the Arno river basin. In both cases, we performed a validation of the results and a comparison with other state-of-the-art techniques. We found that ClaReT produced better results, with a more straightforward and easy application and could be used as a valuable tool to assess the importance of the variables involved in the modeling.     

Spatial Validation of Land Use Change Models Using Multiple Assessment Techniques: A Case Study of Transition Potential Models

Using land use and cover change (LUCC) models for the urban growth planning, environmental assessment, and decision-making needs the establishment of an appropriate level of confidence in their performance. The objective of this research is to explore the importance of using multiple assessment techniques in order to fairly evaluate the performance of land use models. An application is conducted by using the Land Change Modeler for Ecological Sustainability (LCM) which is an empirical and transition potential model. LCM is applied to model the agricultural to developed areas transition in Rennes metropolitan area (France). The land demand is estimated using the Markov Chain model; whereas, the transition potential map is implemented using the Multi-Layer Perceptron Neural Network (MLP) method based on historical changes and driving variables. The model performance is assessed based on a variety of the most commonly used validation techniques. At the study area level, the correctness and disagreement analysis shows that LCM performs better at predicting the amount than the allocation of developed areas. Additionally, landscape metrics reveal that LCM tends to predict a fragmented urban form, which seems evident because of the large number of the individual urban patches. At the municipality level, the error budget analysis shows that the model performance, which varies highly between different subareas, needs to be improved. Moreover, the cross-tabulation between the transition potential map and both the observed and the predicted agricultural to developed areas transitions reveals that the order of the transition potential values does not perfectly fit the observed change; whereas, the predicted change is not solely limited to areas with high potential.