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。     

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.     

High-frequency measurements reveal spatial and temporal patterns of dissolved organic matter in an urban water conveyance

Stormwater runoff in urban areas can contribute high concentrations of dissolved organic matter (DOM) to receiving waters, potentially causing impairment to the aquatic ecosystem of urban streams and downstream water bodies. Compositional changes in DOM due to storm events in forested, agricultural, and urban landscapes have been well studied, but in situ sensors have not been widely applied to monitor stormwater contributions in urbanized areas, leaving the spatial and temporal characteristics of DOM within these systems poorly understood. We deployed fluorescent DOM (FDOM) sensors at upstream and downstream locations within a study reach to characterize the spatial and temporal changes in DOM quantity and sources within an urban water conveyance that receives stormwater runoff. Baseflow FDOM decreased over the summer season as seasonal flows upstream transported less DOM. FDOM fluctuated diurnally, the amplitude of which also declined as the summer season progressed. During storms, FDOM concentrations were rapidly elevated to values orders of magnitude greater than baseflow measurements, with greater concentrations at the downstream monitoring site, revealing high contributions from stormwater outfalls between the two locations. Observations from custom, in situ fluorometers resembled results obtained using laboratory methods for identifying DOM source material and indicated that DOM transitioned to a more microbially derived composition as the summer season progressed, while stormwater contributions contributed DOM from terrestrial sources. Deployment of a mobile sensing platform during varying flow conditions captured spatial changes in DOM concentration and composition and revealed contributions of DOM from outfalls during stormflows that would have otherwise been unobserved.     

<Emphasis Type="Italic">Noctiluca</Emphasis> and copepods grazing on the phytoplankton community in a nutrient-enriched coastal environment along the southwest coast of India

The relative grazing impact of Noctiluca scintillans (hereafter referred only Noctiluca) and copepods (Acrocalanus gracilis, Paracalanus parvus, Acartia danae and Oithona similis) on the phytoplankton community in an upwelling–mudbank environment along the southwest coast India is presented here. This study was carried out during the Pre-Southwest Monsoon (April–May) to the Late Southwest Monsoon (August) period in 2014. During the sampling period, large hydrographical transformation was evident in the study area (off Alappuzha, Southwest coast of India); warmer Pre-Southwest Monsoon water column condition got transformed into cooler and nitrate-rich hypoxic waters during the Southwest Monsoon (June–August) due to intense coastal upwelling. Copepods were present in the study area throughout the sampling period with a noticeable increase in their abundance during the Southwest Monsoon. On the other hand, the first appearance of Noctiluca in the sampling location was during the Early Southwest Monsoon (mid-June) and thereafter their abundance increased towards the Peak Southwest Monsoon. The grazing experiments carried out as per the food removal method showed noticeable differences in the feeding preferences of Noctiluca and copepods, especially on the different size fractions of phytoplankton. Noctiluca showed the highest positive electivity for the phytoplankton micro-fraction (av. 0.49 ± 0.04), followed by nano-fraction (av. 0.17 ± 0.04) and a negative electivity for the pico-fraction (av. ?0.66 ± 0.06). In total ingestion of Noctiluca, micro-fraction contribution (83.7%) was significantly higher compared to the nano- (15.7%) and pico-fractions (0.58%). On the other hand, copepods showed the highest positive electivity for the phytoplankton nano-fraction (av. 0.38 ± 0.04) followed by micro- (av. -0.17 ± 0.05) and pico-fractions (av. ?0.35 ± 0.05). Similarly, in total ingestion of copepods, nano-fraction (69.7%) was the highest followed by micro- (28.9%) and pico-fractions (1.37%). The grazing pressure of Noctiluca on the total phytoplankton was found to be 27.7% of the standing stock and 45.6% of the production, whereas in the case of copepods, it was 9.95% of the standing stock and 16.6% of the production. The study showed that the grazing pressure of Noctiluca on the total phytoplankton as well as larger phytoplankton fraction was 2.8- and 8-folds higher than that of the copepods. This suggests the leading role of Noctiluca as an effective grazer of larger phytoplankton along the southwest west coast of India, especially during the Peak/Late Southwest Monsoon.     

Source identification and apportionment of PM2.5 and PM2.5−10 in iron and steel scrap smelting factory environment using PMF,PCFA and UNMIX receptor models

To identify the potential sources responsible for the particulate matter emission from secondary iron and steel smelting factory environment, PM_2.5 and PM_2.5?10 particles were collected using the low-volume air samplers twice a week for a year. The samples were analyzed for the elemental and black carbon content using x-ray fluorescence spectrometer and optical transmissometer, respectively. The average mass concentrations were 216.26, 151.68, and 138. 62 μg/m³ for PM_2.5 and 331.36, 190.01, and 184.60 μg/m³ for PM_2.5?10 for the production, outside M1 and outside M2 sites, respectively. The same size resolved data set were used as input for the positive matrix factorization (PMF), principal component factor analysis (PCFA), and Unmix (UNMIX) receptor modeling in order to identify the possible sources of particulate matter and their contribution. The PMF resolved four sources with their respective contributions were metal processing (33 %), e-waste (33 %), diesel emission (22 %) and soil (12 %) for PM_2.5, and coking (50 %), soil (29 %), metal processing (16 %) and diesel combustion (5 %) for PM_2.5?10. PCFA identified soil, metal processing, Pb source, and diesel combustion contributing 45, 41, 9, and 5 %, respectively to PM_2.5 while metal processing, soil, coal combustion and open burning contributed 43, 38, 12, and 7 %, respectively to the PM_2.5?10. Also, UNMIX identified metal processing, soil, and diesel emission with 43, 42 and 15 % contributions, respectively for the fine fraction, and metal processing (71 %), soil (21 %) and unidentified source (1 %) for the coarse fraction. The study concluded that metal processing and e-waste are the major sources contributing to the fine fraction while coking and soil contributed to the coarse fraction within the factory environment. The application of PMF, PCFA and UNMIX receptor models improved the source identification and apportionment of particulate matter drive in the study area.