利用GIS实现江苏省地表水省控断面管理

江苏省环境监测中心开发的环境数据可视化地理信息系统是根据断面管理功能,在建立符合管理需求的各类断面图层基础上．采用通用软件开发平台和专业的GIS工具软件相集而成。该系统具有水环境信息的空间查询、表达、统计和绘图等功能．可使环境管理综合决策部门直观、有效地进行水环境质量管理。     

医院低碳经济管理路径探索研究

在建设两型社会的大背景下,我院积极探索低碳经济管理途径,通过实施"四权分离物品管理机制"、全成本核算、打造数字化医院和低碳医疗等手段初步实现了低碳经济管理,并取得了极大的经济效益和社会效益。     

Detection limits can influence the interpretation of pesticide monitoring data in Canadian surface waters

Water quality monitoring programs rely on residue data that are frequently left censored, due to some observations occurring below the Method Detection Limit (MDL). Our objective was to determine the influence the MDL has on the interpretation of pesticide residues in surface waters. Water samples from tributaries in southern and central Ontario were collected by Environment Canada from 2003 to 2008 and were analyzed for 27 pesticides, with MDLs that averaged 7.02 ng⁻¹ L (range 0.39-25.1 ng⁻¹ L). We then simulated MDLs ranging from 25 to 1700 ng⁻¹ L, to determine the impact this would have on the reporting of pesticide concentrations and detections. The mean number of pesticides detected simultaneously declined with increasing, i.e. less sensitive MDLs, from 5.02 pesticides (native MDL) to 0.08 pesticides detected (MDL < 1700 ng⁻¹ L). We compared the proportion of sites where pesticides were detected in surface waters under five MDL scenarios for 13 selected pesticides. The proportions decreased sharply with increasing MDLs. We calculated detection probabilities in an effort to compensate for higher MDLs using maximum likelihood; while adjusting for detection probabilities generally improved estimates of the presence of pesticides, as the MDLs increased the ability to compensate for detection probabilities deteriorated and became unviable at high MDLs. Depending on the method of substitution for observations below MDL (replacement with ½ × or 0 × MDL), the mean and median pesticide residues became increasingly over- and underestimated, respectively, at higher MDLs. Although monitoring programs that are focused on exceedences of water quality guidelines may not require low MDLs, the achievable goals of monitoring programs oriented towards other ecological and toxicological objectives may be limited by higher MDLs.     

Nationwide monitoring of mercury in wild and farmed fish from fresh and coastal waters of Korea

Mercury (Hg) concentrations were monitored in wild and cultured fish collected from fresh and coastal waters in the Korean peninsula from April 2006 to August 2008 nationwide. Total Hg concentrations were reported for 5043 fish samples, including 78 species from 133 locations. Significant interspecies variation was noted in the Hg levels. The average Hg concentration in each fish species ranged from 6.31 μg kg⁻¹ for mullet (Mugil cephalus) to 200 μg kg⁻¹ for mandarin fish (Siniperca scherzeri). Among the species collected, the maximum concentration of Hg, 1720 μg kg⁻¹, was measured in an Amur catfish (Silurus asotus). Only wild freshwater fish exceeded the WHO ingestion standard. Wild freshwater piscivorous fish samples from a large artificial upstream lake contained the highest Hg levels. Hg concentrations were compared between fish groups categorized as wild and farmed fish from freshwater and coastal waters. Although the wild freshwater fish had similar size ranges, their Hg concentrations were higher than those of the other groups. Compared to the feed of farmed marine and freshwater fishes, the prey of wild freshwater fish had a higher Hg concentration, and the total Hg concentrations in freshwater and associated sediment samples were higher than those in coastal water and associated sediment samples. In the freshwater environment, piscivorous fish bioaccumulated two times more Hg than carnivorous and omnivorous fish and four times more than planktivorous fish. The difference in Hg concentrations among trophic groups might have been due to differences in the size of fish, in addition to the variations among different trophic groups. These data will be useful for developing the fish consumption advisory as a management measure to reduce Hg exposure.     

Simulating Dissolved Organic Carbon Dynamics at the Swedish Integrated Monitoring Sites with the Integrated Catchments Model for Carbon,INCA-C

Surface water concentrations of dissolved organic carbon ([DOC]) are changing throughout the northern hemisphere due to changes in climate, land use and acid deposition. However, the relative importance of these drivers is unclear. Here, we use the Integrated Catchments model for Carbon (INCA-C) to simulate long-term (1996–2008) streamwater [DOC] at the four Swedish integrated monitoring (IM) sites. These are unmanaged headwater catchments with old-growth forests and no major changes in land use. Daily, seasonal and long-term variations in streamwater [DOC] driven by runoff, seasonal temperature and atmospheric sulfate (SO₄ ²⁻) deposition were observed at all sites. Using INCA-C, it was possible to reproduce observed patterns of variability in streamwater [DOC] at the four IM sites. Runoff was found to be the main short-term control on [DOC]. Seasonal patterns in [DOC] were controlled primarily by soil temperature. Measured SO₄ ²⁻ deposition explained some of the long-term [DOC] variability at all sites.     

突发性环境污染事故应急监测分析

随着我国经济水平的提高,人们对生活质量的要求也逐渐提高,因此政府也在逐渐加大经济建设和资源开发力度,力求满足人们对生活水平的要求。但是近年来由于资源开采过多,环境的污染程度逐渐加重,由于各种污染物质的相互作用,突发性的环境污染事故发生的次数也逐渐增多。山西是我国的能源大省,拥有很多重工业的基地,产生了大量的工业污染,对水体、大气以及土地都产生了不同程度的污染,引发了突发环境污染事故的出现。本文立足于山西突发性环境污染事故应急监测的现状,分析了山西省在应急监测上所存在的问题,并提出了相应的解决措施,力求降低突发环境污染事故的影响。     

关于大气污染监测与防治措施研究

随着城市化建设的不断发展,大气环境所遭受的破坏也越来越严重,近年常发生的雾霾天气就是大气环境被破坏的证明,人们长期处在这样的大气环境中将令身体健康遭受极其严重的损害。我国对大气环境治理非常重视,正在全面开展大气污染监测与防治工作,本文对此作了简要分析,希望对提升大气污染监测与防治效果具有一定促进作用。     

辐射环境监测数据合理性问题与应对措施研究

本文首先就辐射环境监测数据合理性问题进行了分析,然后提出了几点应对措施以保证监测数据的准确性、一致性以及溯源性,希望能够推动辐射环境监测工作的稳步发展。     

Monitoring the volume and lateral spread of disposed sediments by acoustic methods, Oslo Harbor, Norway

Acoustic equipment, including interferometric sonar and parametric sub-bottom profiler, have been used to determine the volume and lateral spread of dredged sediments disposed in the natural submarine depression in the Bekkelag Basin, inner Oslofjord since the beginning of the Oslo Harbor remediation project in 2006. This natural depression is used as a subaqueous confined disposal facility (CDF). Calculation of the volume of disposed sediments in the CDF is based on elevation change, derived from two high-resolution bathymetric datasets obtained in 2004, i.e. before the onset of the remediation project, and in April 2008. Seismic profiles across the CDF have been used to estimate the settlement of the original seabed, caused by loading-induced dewatering and compaction of the seabed sediments under the disposed masses.Detailed bathymetry and backscatter data demonstrate the lateral spread of disposed sediments within a well-confined area covering ca. 195,000 m². The sea bottom within this area is distinctly softer than the surrounding seabed as shown by very low acoustic backscatter amplitude, signifying a very loose surface character of the disposed sediments. The thickness of the disposed sediments reaches 6 m the deepest part of the original depression. The volume calculation of the disposed sediments in the CDF, based solely on bathymetry data, gives a value of ca. 310,000–320,000 m³. Settlement of the original seabed as a result of loading has been estimated to be 30 cm at 5 m thickness of the disposed sediments. Under the condition that the settlement rate is linearly correlated to the thickness of disposed sediments, the settlement corrected volume of disposed sediments is ca. 330,000–340,000 m³. Presented results demonstrate high accuracy and good reproducibility of acoustic seafloor data, and indicate a great potential of such methods as monitoring tools in environmental projects that involve dredging and subaqueous disposal.     

Modeling biological oxygen demand of the Melen River in Turkey using an artificial neural network technique

Artificial neural networks (ANNs) are being used increasingly to predict and forecast water resources' variables. The feed-forward neural network modeling technique is the most widely used ANN type in water resources applications. The main purpose of the study is to investigate the abilities of an artificial neural networks' (ANNs) model to improve the accuracy of the biological oxygen demand (BOD) estimation. Many of the water quality variables (chemical oxygen demand, temperature, dissolved oxygen, water flow, chlorophyll a and nutrients, ammonia, nitrite, nitrate) that affect biological oxygen demand concentrations were collected at 11 sampling sites in the Melen River Basin during 2001-2002. To develop an ANN model for estimating BOD, the available data set was partitioned into a training set and a test set according to station. In order to reach an optimum amount of hidden layer nodes, nodes 2, 3, 5, 10 were tested. Within this range, the ANN architecture having 8 inputs and 1 hidden layer with 3 nodes gives the best choice. Comparison of results reveals that the ANN model gives reasonable estimates for the BOD prediction.