新型现场自动监控系统的构建与应用

简述了新型移动监测仪器及监控系统的意义,介绍了镇江市环境监测中心站基于业务管理平台建设的现场自动监控系统,详细描述了自动监控系统各个组成部分及其相关功能。对于该系统中存在的不足之处,提出了对今后工作的展望。     

Multicriteria Relocation Analysis of an Off-site Radioactive Monitoring Network for a Nuclear Power Plant

Due to increasing environmental consciousness in most countries, every utility that owns a commercial nuclear power plant has been required to have both an on-site and off-site emergency response plan since the 1980s. A radiation monitoring network, viewed as part of the emergency response plan, can provide information regarding the radiation dosage emitted from a nuclear power plant in a regular operational period and/or abnormal measurements in an emergency event. Such monitoring information might help field operators and decision-makers to provide accurate responses or make decisions to protect the public health and safety. This study aims to conduct an integrated simulation and optimization analysis looking for the relocation strategy of a long-term regular off-site monitoring network at a nuclear power plant. The planning goal is to downsize the current monitoring network but maintain its monitoring capacity as much as possible. The monitoring sensors considered in this study include the thermoluminescence dosimetry (TLD) and air sampling system (AP) simultaneously. It is designed for detecting the radionuclide accumulative concentration, the frequency of violation, and the possible population affected by a long-term impact in the surrounding area regularly while it can also be used in an accidental release event. With the aid of the calibrated Industrial Source Complex–Plume Rise Model Enhancements (ISC-PRIME) simulation model to track down the possible radionuclide diffusion, dispersion, transport, and transformation process in the atmospheric environment, a multiobjective evaluation process can be applied to achieve the screening of monitoring stations for the nuclear power plant located at Hengchun Peninsula, South Taiwan. To account for multiple objectives, this study calculated preference weights to linearly combine objective functions leading to decision-making with exposure assessment in an optimization context. Final suggestions should be useful for narrowing the set of scenarios that decision-makers need to consider in this relocation process.     

应急监测在处置突发性环境污染事故中的思考

针对环境监测部门在处置突发性环境污染事故中承担的任务,提出了应急监测软件支持系统建设内容、目前应着力解决的问题及能力建设的思路与对策。目的是使监测部门从基础信息、技术装备、能力培养和资金渠道等方面全面满足环境应急监测的需要。为有关部门采取控制污染措施、减轻污染危害赢得宝贵时间,最大限度地减少污染造成的损失和危害。     

用VB.NET和ACCESS实现监督监测报告报表编制系统

将Visual basic.net 2003作为前台界面开发,Access2000作为后台数据库的监测数据管理系统用于环境监测报告和报表的编制时,既提高了报告的编制速度和质量,又提高了监测数据的安全性和监测数据应用查询效率.     

The role of optimality in characterizing CO2 seepage from geologic carbon sequestration sites

Storage of large amounts of carbon dioxide (CO₂) in deep geologic formations for greenhouse-gas mitigation is gaining momentum and moving from its conceptual and testing stages towards widespread application. In this work we explore various optimization strategies for characterizing surface leakage (seepage) using near-surface measurement approaches such as accumulation chambers and eddy covariance towers. Seepage characterization objectives and limitations need to be defined carefully from the outset especially in light of large natural background variations that can mask seepage. The cost and sensitivity of seepage detection are related to four critical length scales pertaining to the size of the: (1) region that needs to be monitored; (2) footprint of the measurement approach, and (3) main seepage zone; (4) region in which concentrations or fluxes are influenced by seepage. Seepage characterization objectives may include one or all of the tasks of detecting, locating, and quantifying seepage. Each of these tasks has its own optimal strategy. Detecting and locating seepage in a region in which there is no expected or preferred location for seepage nor existing evidence for seepage requires monitoring on a fixed grid, e.g., using eddy covariance towers. The fixed-grid approaches needed to detect seepage are expected to require large numbers of eddy covariance towers for large-scale geologic CO₂ storage. Once seepage has been detected and roughly located, seepage zones and features can be optimally pinpointed through a dynamic search strategy, e.g., employing accumulation chambers and/or soil-gas monitoring. Quantification of seepage rates can be done through measurements on a localized fixed grid once the seepage is pinpointed. Background measurements are essential for seepage detection in natural ecosystems. Artificial neural networks are considered as regression models useful for distinguishing natural system behavior from anomalous behavior suggestive of CO₂ seepage without need for detailed understanding of natural system processes. Because of the local extrema in CO₂ fluxes and concentrations in natural systems, simple steepest-descent algorithms are not effective and evolutionary computation algorithms are proposed as a paradigm for dynamic monitoring networks to pinpoint CO₂ seepage areas.     

Empirical Social-Ecological System Analysis: From Theoretical Framework to Latent Variable Structural Equation Model

The social-ecological system (SES) approach to natural resource management holds enormous promise towards achieving sustainability. Despite this promise, social-ecological interactions are complex and elusive; they require simplification to guide effective application of the SES approach. The complex, adaptive and place-specific nature of human-environment interactions impedes determination of state and trends in SES parameters of interest to managers and policy makers. Based on a rigorously developed systemic theoretical model, this paper integrates field observations, interviews, surveys, and latent variable modeling to illustrate the development of simplified and easily interpretable indicators of the state of, and trends in, relevant SES processes. Social-agricultural interactions in the Logone floodplain, in the Lake Chad basin, served as case study. This approach is found to generate simplified determinants of the state of SESs, easily communicable across the array of stakeholders common in human-environment interactions. The approach proves to be useful for monitoring SESs, guiding interventions, and assessing the effectiveness of interventions. It incorporates real time responses to biophysical change in understanding coarse scale processes within which finer scales are embedded. This paper emphasizes the importance of merging quantitative and qualitative methods for effective monitoring and assessment of SESs.     

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.     

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.     

The role of Earth Observation (EO) technologies in supporting implementation of the Ramsar Convention on Wetlands

Over one hundred wetland specialists and Earth Observation experts from around the world gathered at the European Space Agency's 'GlobWetland Symposium: Looking at wetlands from space' in Frascati, Italy, from 19 to 20 October, 2006. The aim of the Symposium was to stimulate discussion between the two communities by reviewing the latest developments in Earth Observation (EO) for the inventory, assessment and monitoring of wetlands and identify key scientific, technical and policy-relevant challenges for the future. The results provide an overview of the key areas of current research in the use of EO for mapping and managing wetlands, while also pointing out gaps that could hinder global inventory, assessment and monitoring of wetlands. This paper provides a summary of the main outputs with a focus on the role of EO technologies in supporting the implementation of the Ramsar Convention on Wetlands. The summary contains a qualitative analysis of the state of the art and considers possible directions and priorities for future research, development and application of EO-based technologies in wetland management. In this context we: 1) highlight those applications where EO technologies are ready for wider uptake by wetland managers, and provide suggestions for supporting such uptake; 2) indicate where EO technologies and applications currently in the research and development stages could potentially be useful in wetland management; and 3) provide recommendations for new research and development of EO technologies, that can be utilized to address aspects of wetland management not covered by the range of current EO applications.