镇江地区土壤中重金属Cu和Pb污染状况与空间分布

为了锯镇江地区土壤中重金属Cu和Ph的污染状况与空间分布,对镇江地区表层土壤中的Cu和Pb进行了采样监测。结果表明,镇江地区表层土壤中cu的含量为19．2～273mg／kg,Pb的含量为20．6～3846mg／kg。与全省土壤背景值相比,均有一定程度的富集。对cu和Pb的相互关系进行分析可得出,镇江地区土壤在一定程度上受到农业面源的污染。     

江苏省霾污染遥感监测业务化运行研究

从霾污染遥感监测业务化流程出发,选取EOS/MODIS为主要数据源,MODIS气溶胶产品及气象数据为辅,在数据预处理的基础上,利用LM-BP人工神经网络模型算法反演区域大气颗粒物浓度,分析了可获取的遥感监测指标及气象指标对霾污染的贡献率,筛选出可业务化的霾污染遥感评价指标。对2013年1月江苏省2次典型的霾污染进行了星地同步分析,从分析结果来看,霾污染遥感监测结果与地面实测结果基本一致,霾污染遥感监测可以作为地面监测的有效补充,宏观反映区域霾污染空间分布,为大气污染防治提供有力的技术支撑。     

农药企业搬迁土地挥发性有机物风险评价

对常州某农药生产场地土壤中挥发性有机物(VOCs)污染状况以及健康风险和生态风险进行了调查评价。结果表明,该场地土壤中挥发性有机物污染以苯系物和卤代烃为主。苯系物质量浓度为0~56.6 mg/kg,卤代烃质量浓度为0~1.14 mg/kg。健康风险评价结果均在可接受范围内,而生态风险评价显示生产车间内的土壤VOCs生态风险较大,存在着对生物的危害。     

交通干道沿线土壤重金属监测与评估综述

公路运营所带来的铅、镉、锌等重金属污染物对人体健康安全存在着潜在和长期的影响。近年来,开展交通干道沿线重金属污染监测与评估工作已经成为环境监测工作的重要内容。从监测技术、评估方法、可能影响因素等几个方面对该领域的研究进展及成果进行了综述。采样段面的选取、点位的布设与样品的收集应该同时遵循全面性和代表性的原则。在同一交通干道内,均匀布置采样段面的同时可以尽量包含高车流量、中车流量与低车流量3种类型。考虑到重金属在横向距离上的分布规律,可以在0~100 m处设置密集采样点位,在100~300 m处设置适量采样点位。评估方法一般同时采用Kriging空间插值分析、污染指数分析、多元统计分析,生态风险评价与健康风险评价等多种分析方法。     

渤海湾入海溶解无机氮总量控制研究

基于渤海湾近岸海域的实际调查结果,采取生态物理耦合模型,对渤海湾的主要污染物-溶解无机氮(DIN)的基准环境容量和极小剩余海洋环境容量进行了计算。结果表明,渤海湾DIN的极小剩余海洋环境容量在Ⅰ类和Ⅱ类水质标准下均为负值,渤海湾的DIN已经超标。结合实际的海水功能区水质管理目标,应重点控制非点源的排放,加强上游携带入境污染物的处理,从总量上控制DIN入海污染通量,改善渤海湾水质。     

全二维气相色谱-飞行时间质谱法分离复杂体系中7种指示剂 多氯联苯

采用全二维气相色谱-飞行时间质谱法(GC×GC TOF-MS)分析了混标样品Aroclor 1260、Aroclor 1254、Aroclor 1242中的多氯联苯(PCBs)单体,考察了在复杂体系下对7种PCBs指示剂的分离能力。结果表明,与优化柱系统的分离效果相比,136种单体的混标样品中共分离出121种单体,7种指示剂经一维和二维的保留时间及质谱定性,在121种单体的2D斑点图中清晰可辨。全二维对于复杂体系的PCBs和指示剂的分离表明其强大的分离能力和对于检测复杂体系中指示剂的分辨能力,对该类物质的定性和定量检测具有重要意义。     

Sources and seasonal variation of PAHs in the sediments of drinking water reservoirs in Hong Kong and the Dongjiang River (China)

The main objective of this study was to investigate occurrence of polycyclic aromatic hydrocarbons (PAHs) in the sources of the drinking water supply of Hong Kong. The main emphasis was on the Dongjiang River in mainland China which is the major source, supplying 80% of the total consumption in Hong Kong (the remaining 20% is obtained from rain water). Sediments were collected from four sites along the Dongjiang River and four reservoirs in Hong Kong during both the dry and wet weather seasons. The concentrations of total PAHs in the sediments ranged between 36 and 539 microg/kg dry wt. The lower levels were detected at the upstream site on the Dongjiang River and at the reservoirs in Hong Kong (44-85 microg/kg dry wt), while the mid- and downstream sites on the Dongjiang River were more polluted (588-658 microg/kg dry wt). Examination of the PAH profiles revealed that the mid- and downstream sections of the Dongjiang River contained high percentages of 4,5,6-ring PAHs, similar to the amounts of atmospheric particulate matter and road dust collected during the dry weather season from the Pearl River Delta region as reported in the literature. Seasonal changes were revealed in the reservoirs of Hong Kong, with higher PAH levels in the wet weather season than in the dry weather season. For those reservoirs in Hong Kong that store water from the Dongjiang River, a distinct seasonal pattern was also observed, namely, that under dry weather season conditions the PAHs found in the sediments were primarily from petrogenic source, while under wet weather season conditions they were from pyrolytic sources. No such pattern was detected in the reservoirs which stored only rain water.     

Status and habitat preferences for endemic inhabitants of fiddler crab Uca formosensis in Hsiang-Shan wetland, Taiwan

This article reports on soil samples collected from Hsiang-Shan wetland, Taiwan. Canonical discriminant analysis (CDA) was applied to identify an existing habitat type's scheme by identifying the physico-chemical properties of sediment in Hsiang-Shan wetland. The three constructed discriminant functions (CDFs) showed a marked contribution by most of the discriminant variables, and the recognition capacities in these three CDFs were 49.5, 32.8 and 17.7%. Our study revealed that the most important latent factors in Hsiang-Shan wetland are soil texture-caused factor, ocean current-caused factor, nutrient-caused factor, and the redox reaction-caused factor. And the most sensitivity parameters in this habitat followed the descending order: OBD, EC, Eh, sand, TN, porosity, STP, silt, VCP and pH. And the inhabited sediment properties for U. formosensis in terms of soil texture are sand, silt, and clay (34.05, 29.72, and 32.35%, respectively): that is clay loam soil. We also found that U. formosensis preferred to inhabit the upper intertidal zone, spending 8.41% of the time submerged. Vegetation coverage on the ground was less than 2.20%, showing that it preferred to live in a bare intertidal habitat. Concerning nest choosing, excavating burrows is more difficult when a high soil penetration force is required, and in this study the soil penetration force for 20 cm was found to be is 45.98 N/cm(2). The results will be helpful in developing a methodology for use by the government in refining its management programs.     

改性沸石分离富集-火焰原子吸收光谱法测定长江水中镉

采用改性沸石分离富集-火焰原子吸收光谱法测定长江水中微量镉,优化了富集和洗脱条件,讨论了干扰离子的影响。方法在0μg~4.00μg范围内线性良好,检出限为0.214μg/L,长江水平行测定的RSD为1.8%,加标回收率为99.0%~104%。     

The backend design of an environmental monitoring system upon real-time prediction of groundwater level fluctuation under the hillslope

The groundwater level represents a critical factor to evaluate hillside landslides. A monitoring system upon the real-time prediction platform with online analytical functions is important to forecast the groundwater level due to instantaneously monitored data when the heavy precipitation raises the groundwater level under the hillslope and causes instability. This study is to design the backend of an environmental monitoring system with efficient algorithms for machine learning and knowledge bank for the groundwater level fluctuation prediction. A Web-based platform upon the model-view controller-based architecture is established with technology of Web services and engineering data warehouse to support online analytical process and feedback risk assessment parameters for real-time prediction. The proposed system incorporates models of hydrological computation, machine learning, Web services, and online prediction to satisfy varieties of risk assessment requirements and approaches of hazard prevention. The rainfall data monitored from the potential landslide area at Lu-Shan, Nantou and Li-Shan, Taichung, in Taiwan, are applied to examine the system design.