区域空气监测网络建设策略与实践

根据区域空气质量管理的发展形势,提出建设区域空气自动监测网络的思路和建设内容,探索建立区域空气监测QA/QC技术体系的策略与解决方案。     

泰山区水环境监测网络优化研究

对泰山区目前水环境监测网络系统进行了综合分析评价 ,采用专家权重评估、物元分析方法对原监测断面进行了优化研究 ,在此基础上建立起新型监测网络的地理信息系统     

Evaluation and optimization of an urban PM2.5 monitoring network

The objective of this study was to evaluate the PM(2.5) monitoring network established in the Greater Cincinnati and Northern Kentucky metropolitan area for measuring the 24 h integrated PM(2.5) concentration, as well as-at selected sites-hourly PM(2.5) concentration and 24 h integrated PM(2.5) speciation. The data collected during three years at 13 measurement sites were analyzed for spatial and temporal variations. It was found that both daily and hourly concentrations of PM(2.5) have low spatial variation due to a regional influence of secondary ammonium sulfate. In contrast, the trace element concentrations had high spatial variation. Seasonal variation accounted for most of the total temporal variation (60%), while yearly, monthly, weekly and daily variations were lower. The variance components and cluster analyses were applied to optimize the number of sites for measuring the 24 h PM(2.5) concentration. It was found that the 13-site network may be optimized by reducing the number of sites to 8, which would result in a relative precision reduction of 9% and a relative cost reduction of 36%. At the same time, the data suggest that the spatial resolution of speciation monitors and real-time PM(2.5) mass monitors should be increased to better represent spatial and temporal variations of the markers of local air pollution sources.     

Multiple-point variance analysis for optimal adjustment of a monitoring network

The selection of sampling sites is one of the major tasks in thedesign of a monitoring network. Many environmental networkssuffer from either insufficient information or redundantinformation. This study presents a new, effective algorithm thataddresses the issues of insufficient and reduction information.The new algorithm is denoted as Multiple-Point Variance Analysis(MPV). MPV includes both Multiple-Point Variance ReductionAnalysis (MPVR) for adding information-effectives sites, andMultiple-Point Variance Increase Analysis (MPVI) for deletinginformation-redundant sites. The MPVR and MPVI equations areverified under two hypothetical cases. The optimal procedures ofthis new algorithm include determination of simultaneousadditions or deletions of groups of sampling points. Theseproposed optimization procedures eliminate the need for anyspatial discretizations or sequential selections. The efficiencyof these optimal procedures is tested under actual fieldconditions. The results show that the optimal MPV is aneffective tool for adjustment of existing sampling networks.     

对全国环境监测信息系统建设总体架构的探讨

文章对全国环境监测网络信息系统的总体框架进行探讨 ,描述了该框架的各部分组成和功能 ,旨在探讨环境监测信息化工作的技术思路。     

河北省环境自动监测网络支持系统的研究与应用

河北省环境自动监测网络支持系统综合应用GPRS/GSM无线传输技术、VSAT卫星通信网络、网络数据库、WEBGIS等信息技术,在省一级环保网络构架上以较高的性价比给出了系统的、完备的环境自动监测数据传输、处理的解决方案.     

Uncertainty based optimal monitoring network design for a chlorinated hydrocarbon contaminated site

An application of a newly developed optimal monitoring network for the delineation of contaminants in groundwater is demonstrated in this study. Designing a monitoring network in an optimal manner helps to delineate the contaminant plume with a minimum number of monitoring wells at optimal locations at a contaminated site. The basic principle used in this study is that the wells are installed where the measurement uncertainties are minimum at the potential monitoring locations. The development of the optimal monitoring network is based on the utilization of contaminant concentration data from an existing initial arbitrary monitoring network. The concentrations at the locations that were not sampled in the study area are estimated using geostatistical tools. The uncertainty in estimating the contaminant concentrations at such locations is used as design criteria for the optimal monitoring network. The uncertainty in the study area was quantified by using the concentration estimation variances at all the potential monitoring locations. The objective function for the monitoring network design minimizes the spatial concentration estimation variances at all potential monitoring well locations where a monitoring well is not to be installed as per the design criteria. In the proposed methodology, the optimal monitoring network is designed for the current management period and the contaminant concentration data estimated at the potential observation locations are then used as the input to the network design model. The optimal monitoring network is designed for the consideration of two different cases by assuming different initial arbitrary existing data. Three different scenarios depending on the limit of the maximum number of monitoring wells that can be allowed at any period are considered for each case. In order to estimate the efficiency of the developed optimal monitoring networks, mass estimation errors are compared for all the three different scenarios of the two different cases. The developed methodology is useful in coming up with an optimal number of monitoring wells within the budgetary limitations. The methodology also addresses the issue of redundancy, as it refines the existing monitoring network without losing much information of the network. The concept of uncertainty-based network design model is useful in various stages of a potentially contaminated site management such as delineation of contaminant plume and long-term monitoring of the remediation process.     

河南省环境空气质量监测网优化的研究

在全省城市环境空气质量监测网优化并运行六年的基础上 ,采用历史数据计算法对河南省环境空气质量监测网进行了优化。通过优化方法和监测项目的探索 ,确定了省控站数目 ,特别是提出了系统、完整的优化指标 ,优化结果是令人满意的。     

Public participation in environmental monitoring: A means of attaining network capability

In the Puget Sound region of the United States a task force of community volunteers using bees monitored environmental pollution. This paper discusses advantages and limitations of public involvement in the assessment of regional environmental problems, particularly with respect to biological monitoring. This approach not only yielded extensive information about pollution levels but also was very cost effective.Work supported by Cooperative Agreement CR-810035-01-0 with the U.S. Environmental Protection Agency, Environmental Research Laboratory, Corvallis, Oregon, U.S.A.     

重庆市生态环境智慧监测管理体系研究

以重庆市为例,从生态环境监测管理需求出发,分析了智慧监测的现状与存在的问题,提出了构建生态环境智慧监测管理体系的技术路线。以监测业务为核心,涵盖水、气、声、态、土等多种要素,构建了要素齐全、上下统筹、自动预警、服务应用的生态环境监测网络,实现了环境质量、污染源和生态状况监测全覆盖,预期取得规范监测业务流程、促进监测业务协同、加快产学研用结合等成效。     

South Florida Water Management District ambient pesticide monitoring network: 1992 to 2007

The South Florida Water Management District has collected surface water and sediment samples for analysis of over 80 pesticides since 1992. Residues of atrazine and DDE-p,p(') are nearly ubiquitous throughout the sampling area. Surface water concentrations of atrazine at nine of 14 selected monitoring locations exhibited a downward trend and none of the detected concentrations exceeded established levels of concern. Seventy-five percent of the sampled locations had average sediment residues of DDE-p,p(') at levels that may impact sediment-dwelling organisms. Monitoring locations with the highest average DDE-p,p(') concentrations (based on detected values) and the highest percentage of pesticide detections did not exhibit consistent trends. Some locations exhibited increasing trends while trends at other locations showed a decrease in concentrations. Additionally, specific location concentrations for ethion, diazinon, and endosulfan documented periods of surface water quality exceedances. However, product label changes and grower education have substantially contributed to the reduced number of exceedances over time.     

A water quality monitoring network design using fuzzy theory and multiple criteria analysis

A proper water quality monitoring design is required in a watershed, particularly in a water resource protected area. As numerous factors can influence the water quality monitoring design, this study applies multiple criteria analysis to evaluate the suitability of the water quality monitoring design in the Taipei Water Resource Domain (TWRD) in northern Taiwan. Seven criteria, which comprise percentage of farmland area, percentage of built-up area, amount of non-point source pollution, green cover ratio, landslide area ratio, ratio of over-utilization on hillsides, and density of water quality monitoring stations, are selected in the multiple criteria analysis. The criteria are normalized and weighted. The weighted method is applied to score the subbasins. The density of water quality stations needs to be increased in priority in the subbasins with a higher score. The fuzzy theory is utilized to prioritize the need for a higher density of water quality monitoring stations. The results show that the need for more water quality stations in subbasin 2 in the Bei-Shih Creek Basin is much higher than those in the other subbasins. Furthermore, the existing water quality station in subbasin 2 requires maintenance. It is recommended that new water quality stations be built in subbasin 2.     

Cokriging optimization of monitoring network configuration based on fuzzy and non-fuzzy variogram evaluation

A number of optimization approaches regarding monitoring networkdesign and sampling optimization procedures have been reported inthe literature. Cokriging Estimation Variance (CEV) is a usefuloptimization tool to determine the influence of the spatial configuration of monitoring networks on parameter estimations. Itwas used in order to derive a reduced configuration of a nitrateconcentration monitoring well network. The reliability of the reduced monitoring configuration suffers from the uncertainties caused by the variographer's choices and several inherent assumptions. These uncertainties can be described considering thevariogram parameters as fuzzy numbers and the uncertainties by means of membership functions.Fuzzy and non-fuzzy approaches were used to evaluate differencesamong well network configurations. Both approaches permitted estimates of acceptable levels of information loss for nitrate concentrations in the monitoring network of the aquifer of the Plain of Modena, Northern Italy. The fuzzy approach was found torequire considerably more computational time and numbers of wellsat comparable level of information loss.     

Tailoring groundwater quality monitoring to vulnerability: a GIS procedure for network design

Monitoring networks aiming to assess the state of groundwater quality and detect or predict changes could increase in efficiency when fitted to vulnerability and pollution risk assessment. The main purpose of this paper is to describe a methodology aiming at integrating aquifers vulnerability and actual levels of groundwater pollution in the monitoring network design. In this study carried out in a pilot area in central Italy, several factors such as hydrogeological setting, groundwater vulnerability, and natural and anthropogenic contamination levels were analyzed and used in designing a network tailored to the monitoring objectives, namely, surveying the evolution of groundwater quality relating to natural conditions as well as to polluting processes active in the area. Due to the absence of an aquifer vulnerability map for the whole area, a proxi evaluation of it was performed through a geographic information system (GIS) methodology, leading to the so called “susceptibility to groundwater quality degradation”. The latter was used as a basis for the network density assessment, while water points were ranked by several factors including discharge, actual contamination levels, maintenance conditions, and accessibility for periodical sampling in order to select the most appropriate to the network. Two different GIS procedures were implemented which combine vulnerability conditions and water points suitability, producing two slightly different networks of 50 monitoring points selected out of the 121 candidate wells and springs. The results are compared with a “manual” selection of the points. The applied GIS procedures resulted capable to select the requested number of water points from the initial set, evaluating the most confident ones and an appropriate density. Moreover, it is worth underlining that the second procedure (point distance analysis [PDA]) is technically faster and simpler to be performed than the first one (GRID?+?PDA).     

Multi-objective, decision-based assessment of a water quality monitoring network in a river system

Water quality monitoring network design has historically tended to use experience, intuition and subjective judgement in locating monitoring stations. Better design procedures to optimize monitoring systems need to simultaneously identify significant planning objectives and consider a number of social, economic and environmental constraints. The consideration of multiple objectives may require further decision analysis to determine the preference weights associated with the objectives to aid in the decision-making process. This may require the application of an optimization study to extract such information from decision makers or experts and to evaluate the overall effectiveness of locating strategies. This paper assesses the optimal expansion and relocation strategies of a water quality monitoring network using a two-stage analysis. The first stage focuses on the information retrieval of preference weights with respect to the designated planning objectives. With the aid of a pre-emptive goal programming model, data analysis is applied to obtain the essential information from the questionnaire outputs. The second stage then utilizes a weighted multi-objective optimization approach to search for the optimal locating strategies of the monitoring stations in the river basin. Practical implementation is illustrated by a case study in the Kao-Ping River Basin, south Taiwan.     

扬尘污染精细化管控思路探讨

通过分析传统扬尘污染防治模式的弊端,提出了一种“精准监测、排量切入、总量考核、职责共担”的新模式。该模式在技术手段上使用以扬尘在线监测数据为基准的扬尘排放量计算模式,以及基于机器学习的扬尘源排放量计算方法,实现了扬尘排放量的自动、实时、在线计算;在管理手段上将传统的扬尘浓度点控制转变为易扬尘单位扬尘排量控制,通过总量控制、指标分解,增强了政府与企业对于环境效益的职责分工,有助于将扬尘防控责任有效落实,实现对扬尘污染的精细化、常态化管控。