淮河干流及主要支流夏季浮游植物群落生物多样性评价

浮游植物是水生态系统的重要组成部分,其群落变化与水体环境条件密切相关,是反映河流健康的主要生物指标.为揭示淮河流域浮游植物群落特征及其与水质的相互关系,于2015年夏季对淮河流域典型水体—淮河干流、沙颍河、涡河和淠河进行系统的水质及浮游植物调查,探明浮游植物群落及其空间分布特征,并结合水体理化指标和生物指数进行水质评价.结果表明,淮河干流及主要支流27个点位中共获得浮游植物8门71属153种,主要隶属于绿藻门(Chlorophyta)、硅藻门(Bacillariophyta)、蓝藻门(Cyanophyta).浮游植物密度为0.019×10~5~131.824×10~5ind·L~(-1),不同河段浮游植物分布表现出较为显著的空间差异性,平均密度大小呈现沙颖河淮河干流涡河淠河的特点.非参数多维尺度分析(Non-metric Multidimensional Scaling,NMDS)表明,淮河干流、淠河和涡河的浮游植物群落组成和结构的相似性较高,而与沙颍河的浮游植物群落存在一定的差异.Shannon多样性指数H'介于0.78~3.21之间,Margalef丰富度指数D介于1.03~4.79之间,Pielou均匀度指数J介于0.12~0.73之间.水质生物评价结果显示,淮河流域大部分水体处于中等污染状况,部分点位处于重污染状况,其结果与水质综合污染指数评价结果具有较好的一致性.研究结果可为淮河水污染防治和水生态修复提供基础依据.     

深圳市综合水质指数研究及其在水资源资产评估上的应用

自然资源资产评估技术是开展自然资源资产负债表实践和实行环境责任离任审计的重要技术支撑。水资源作为一项重要自然资源,如何有效评估水资源资产是不可回避的问题。论文以深圳市为研究区域,一是采用综合污染指数法和主成分分析法,以总氮、氨氮、总磷、化学需氧量、生化需氧量、固体悬浮物为指标参数构建了深圳市综合水质指数以评价水资源综合水质。二是以该综合水质评估模型为基础,通过采用治污成本法分析综合水质与治污成本间的关系,从而构建深圳市景观水和饮用水资源的价值量评估模型。论文还以深圳市大鹏新区为试点开展了水资源价值量评估,评估结果显示,2015年大鹏新区景观水和饮用水资源的价值量分别为3.60亿、0.35亿元。     

Role of the floodplain lakes in the methylmercury distribution and exchanges with the Amazon River, Brazil

Seasonal variability of dissolved and particulate methylmercury(F-MeHg, P-MeHg) concentrations was studied in the waters of the Amazon River and its associated Curuai floodplain during hydrological year 2005–2006, to understand the MeHg exchanges between these aquatic systems. In the oxic white water lakes, with neutral pH, high F-MeHg and P-MeHg concentrations were measured during the rising water stage(0.70 ± 0.37 pmol/L, n = 26) and flood peak(14.19 ± 9.32 pmol/g, n = 7) respectively, when the Amazon River water discharge into the lakes was at its maximum. The lowest mean values were reported during the dry season(0.18 ± 0.07 pmol/L F-MeHg, n = 10 and 1.35 ± 1.24 pmol/g P-MeHg, n = 8), when water and suspended sediments were outflowing from the lakes into the River. In these lakes,the MeHg concentrations were associated to the aluminium and organic carbon/nitrogen changes. In the black water lakes, with acidic pH and reducing conditions, elevated MeHg concentrations were recorded(0.58 ± 0.32 pmol/L F-MeHg, n = 16 and 19.82 ± 15.13 pmol/g PMeHg, n = 6), and correlated with the organic carbon and manganese concentrations. Elevated values of MeHg partition coefficient(4.87 Kd 5.08 log(L/kg) indicate that MeHg is mainly transported associated with the particulate phase. The P-MeHg enrichment detected in all lakes suggests autochthonous MeHg inputs from the sediments into the water column. The MeHg mass balance showed that the Curuai floodplain is not the source of P-MeHg for the Amazon River.     

污染物在地下水毛细饱水带的运移规律浅释

分析了毛细饱水带的水动力学特性，指出在地下水污染研究中，污染物在毛细饱和水带和潜水怪具有相同的水平运动规律，并以实例分析说明该带对污染物运移的重要性。建议在研究和一非饱和条件地下水及污染物运动问题时把毛细饱水带与潜水含水层统一为饱马毛细饱水带顶面作为饱水面。     

Monitoring Air Quality in Mountains: Designing an Effective Network

A quantitatively robust yet parsimonious air-quality monitoring network in mountainous regions requires special attention to relevant spatial and temporal scales of measurement and inference. The design of monitoring networks should focus on the objectives required by public agencies, namely: 1) determine if some threshold has been exceeded (e.g., for regulatory purposes), and 2) identify spatial patterns and temporal trends (e.g., to protect natural resources). A short-term, multi-scale assessment to quantify spatial variability in air quality is a valuable asset in designing a network, in conjunction with an evaluation of existing data and simulation-model output. A recent assessment in Washington state (USA) quantified spatial variability in tropospheric ozone distribution ranging from a single watershed to the western third of the state. Spatial and temporal coherence in ozone exposure modified by predictable elevational relationships ( 1.3 ppbv ozone per 100 m elevation gain) extends from urban areas to the crest of the Cascade Range. This suggests that a sparse network of permanent analyzers is sufficient at all spatial scales, with the option of periodic intensive measurements to validate network design. It is imperative that agencies cooperate in the design of monitoring networks in mountainous regions to optimize data collection and financial efficiencies.     

红壤丘陵区典型流域地表水水环境特征研究——以浏阳河流域为例

选取浏阳河流域为例,根据近十年河流断面监测数据,采用改进的综合污染指数法来评价水质污染程度,研究了该红壤丘陵区典型河流水质的时空变化特征,并结合土地利用和土壤特征等分析地表水质变化原因。结果表明,改进的综合污染指数法有较好的适用性;从时间特征上看,由于面源污染加剧,使得浏阳河近十年的水质污染呈增长趋势;从空间特征上看,浏阳河从上游到下游,河流污染呈增长趋势,上游水质较好,中游表现为重金属铅和汞的污染较大,而下游则是氨氮污染加剧。     

大气环境质量综合评价加权灰色关联模型的建立与应用

利用灰色理论建立大气环境质量综合评价加权灰色关联模型 ,运用污染贡献率确定权重系数。与其它评价模型相比 ,加权灰色关联模型还具有排序功能 ,实例表明该模型是简便有效的     

Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

环境水体中痕量酚类化合物气相色谱-质谱联用测定法研究

建立了液-液萃取-气相色谱/质谱联用仪测定环境水体中痕量酚类化合物的方法。用乙酸乙酯萃取环境水中的痕量酚类化合物,加入萘-d8作为内标,利用气相色谱-质谱联用仪选择离子监测(SIM)的方式进行检测,内标法定量,定性、定量准确,线性响应良好,回归曲线的相关系数均>0.999,平均回收率在89.4%~104%之间,精密度好,相对标准偏差<7.4%;抗干扰能力强,检测灵敏度高,水样中最低检测浓度可达0.001mg/L,经实际样品测定完全能满足环境水体中痕量酚类化合物监测的要求。     

实验室质量管理体系内部审核的策划

在实施GBT15481-2000(idtISOIEC17025:1999)标准《检测和校准实验室能力的通用要求》的过程中,通过实验室质量管理体系内部审核的实践与系统分析,识别出内部审核策划阶段的关键环节,提出审核范围确定、审核计划和抽样方案制订的技术方法,为有序高效地实施内部审核提供了行动指南。