Optimal extension of the rain gauge monitoring network of the Apulian Regional Consortium for Crop Protection

The goal of this paper is to provide a methodology for assessing the optimal localization of new monitoring stations within an existing rain gauge monitoring network. The methodology presented, which uses geostatistics and probabilistic techniques (simulated annealing) combined with GIS instruments, could be extremely useful in any area where an extension of whatever existing environmental monitoring network is planned. The methodology has been applied to the design of an extension to a rainfall monitoring network in the Apulia region (South Italy). The considered monitoring network is managed by the Apulian Regional Consortium for Crop Protection (ARCCP), and, currently consists of 45 gauging stations distributed over the regional territory, mainly located on the basis of administrative needs. Fifty new stations have been added to the existing monitoring network, split in two groups: 15 fixed and 35 mobile stations. Two different methods were applied and tested: the Minimization of the Mean of Shortest Distances method (MMSD) and Ordinary Kriging (OK) whose related objective function is estimation variance. The MMSD, being a purely geometric method, produced a spatially uniform configuration of the gauging stations. On the contrary, the approach based on the minimization of the average of the kriging estimation variances, produced a less regular configuration, though a more reliable one from a spatial standpoint. Nevertheless, the MMSD approach was chosen, since the ARCCP's intention was to create a new monitoring network characterized by uniform spatial distribution throughout the regional territory. This was the most important constraint given to the project by the ARCCP, whose main objective was to accomplish a territorial network capable of detecting hazardous events quickly. A seasonal aggregation of the available rainfall data was considered. The choice of the temporal aggregation in quarterly averages allowed four different optimal configurations to be determined per season. The overlapping of the four configurations allowed a number of new station locations, which tended to remain fixed season after season, to be identified. Other stations, instead, changed their coordinates considerably over the four seasons. Constraints were defined in order to avoid placing new monitoring locations either near existing stations, belonging to other Agencies, or near the coast line.     

Calculating of river water quality sampling frequency by the analytic hierarchy process (AHP)

River water quality sampling frequency is an important aspect of the river water quality monitoring network. A suitable sampling frequency for each station as well as for the whole network will provide a measure of the real water quality status for the water quality managers as well as the decision makers. The analytic hierarchy process (AHP) is an effective method for decision analysis and calculation of weighting factors based on multiple criteria to solve complicated problems. This study introduces a new procedure to design river water quality sampling frequency by applying the AHP. We introduce and combine weighting factors of variables with the relative weights of stations to select the sampling frequency for each station, monthly and yearly. The new procedure was applied for Jingmei and Xindian rivers, Taipei, Taiwan. The results showed that sampling frequency should be increased at high weighted stations while decreased at low weighted stations. In addition, a detailed monitoring plan for each station and each month could be scheduled from the output results. Finally, the study showed that the AHP is a suitable method to design a system for sampling frequency as it could combine multiple weights and multiple levels for stations and variables to calculate a final weight for stations, variables, and months.     

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.     

面向智慧城市的分布式噪声管理系统设计

针对城市噪声污染多头管理、监测方法单一、治理效率低等问题,基于Android 4G技术城市环境噪声分布式监测设计思想,介绍智慧城市噪声分布式监测的应用方法。以移动终端作为传感器节点替代传统集中式噪声监测的分布式监测方法,依托云计算数据处理平台,解决了监测网络数据管理分散、定点检测站和一些手持检测设备收集数据引起的信息滞后的问题,有益于实现城市环境噪声污染数据分析、处理和融合等复杂功能,使各种质控任务和标准传递等复杂任务得到自动化执行与反馈,将对城市噪声污染联防联控起到积极推动作用。     

Spatial�Ctemporal assessment and redesign of groundwater quality monitoring network: a case study

Assessment of groundwater quality monitoring networks requires methods to determine the potential efficiency and cost-effectiveness of the current monitoring programs. To this end, the concept of entropy has been considered as a promising method in previous studies since it quantitatively measures the information produced by a network. In this study, the measure of transinformation in the discrete entropy theory and the transinformation?Cdistance (T?CD) curves, which are used frequently by other researchers, are used to quantify the efficiency of a monitoring network. This paper introduces a new approach to decrease dispersion in results by performing cluster analysis that uses fuzzy equivalence relations. As a result, the sampling (temporal) frequency determination method also recommends the future sampling frequencies for each location based on certain criteria such as direction, magnitude, correlation with neighboring stations, and uncertainty of the concentration trend derived from representative historical concentration data. The proposed methodology is applied to groundwater resources in the Tehran?CKaradj aquifer, Tehran, Iran.     

融合拓扑信息与气象信息的空气质量预测网络

通过空气质量监测数据对正在形成或即将到来的空气污染进行预测是一项具有重要意义的工作,而空气质量监测站只能检测其周围一定范围内的空气污染情况。为了衡量整个城市的空气污染情况,获取任意时间、任意位置的空气质量信息,结合交叉注意力机制,提出了一种融合拓扑信息与气象信息的空气质量预测网络(CGMIM)。将西安市空气质量监测数据与气象数据转换为图像拼接起来,作为输入信息。在高阶非线性时空动态神经网络(MIM)的基础上引入注意力机制,并增加拓扑图编码器模块,提高模型提取能力以及对空气质量监测数据中的空间特征的利用率。最后,使用时空损失函数替代传统的均方误差损失函数,提高模型对空间关系的关注。结果表明：CGMIM网络模型能够在准确预测的同时,对位置区域合理填充,能够有效提升空气质量监测数据的空间分辨率。     

The MYSound Project: building an estuary-wide monitoring network for Long Island Sound,USA

A network of five water quality monitoring stations has been established in Long Island Sound, measuring temperature, salinity, and dissolved oxygen since 1999. The stations are located in areas of extreme water quality degradation (western Long Island Sound) as well as in pristine areas (eastern Long Island Sound). The data from these stations are collected every 15 minutes and posted to the project web site in real time as provisional data. After subsequent quality assurance procedures, the data are archived to the project File Transfer Protocol (FSP) site for downloading by the user community. The network of stations is in part supported logistically by a number of partners, including state and local agencies, schools, and non-governmental organizations. Data from the monitoring programs of some of these partners are also published to the project website providing a more comprehensive and complete picture of the status of the Sound than can be provided independently. This repository of information is used by marine educators, resource managers, scientists, and the general public, each with a different end purpose. We use the data from two of the stations to show that these high frequency time series measurements can be used to complement and enhance other monitoring programs within the Sound, documenting in greater detail the occurrence and duration of hypoxic events.     

Methodology for designing air quality monitoring networks: I. Theoretical aspects

An objective methodology is presented for determining the number and disposition of ambient air quality stations in a monitoring network for the primary purpose of compliance with air quality standards. The methodolgy utilizes a data base with real or simulated data from an air quality dispersion model for application with a two-step process for ascertaining the optimal monitoring network. In the first step, the air quality patterns in the data base are collapsed into a single composite pattern through a figure-of-merit (FOM) concept. The most desirable locations are ranked and identified using the resultant FOM fields. In the second step the network configuration is determined on the basis of the concept of spheres of influence (SOI) developed from cutoff values of spatial correlation coefficients between potential monitoring sites and adjacent locations. The minimum number of required stations is then determined by deletion of lower-ranked stations whose SOIs overlap. The criteria can be set to provide coverage of less than some fixed, user-provided percentage of the coverage of tha SOIs of the higher ranked stations and for some desired level of minimum detection capability of concentration fluctuations.The methodology is applied in a companion paper (McElroy et al., 1986) to the Las Vegas, Nevada, metropolitan area for the pollutant carbon monoxide.Although the research described in this article has been funded wholly or in part by the United States Environmental Protection Agency through Contract No. 68-03-2446 to Systems Applications, Inc., it has not been subjected to Agency review and therefore does not necessarily reflect the views of the Agency and no official endorsement should be inferred.     

Assessing temporal representativeness of water quality monitoring data

The effectiveness of different monitoring methods in detecting temporal changes in water quality depends on the achievable sampling intervals, and how these relate to the extent of temporal variation. However, water quality sampling frequencies are rarely adjusted to the actual variation of the monitoring area. Manual sampling, for example, is often limited by the level of funding and not by the optimal timing to take samples. Restrictions in monitoring methods therefore often determine their ability to estimate the true mean and variance values for a certain time period or season. Consequently, we estimated how different sampling intervals determine the mean and standard deviation in a specific monitoring area by using high frequency data from in situ automated monitoring stations. Raw fluorescence measurements of chlorophyll a for three automated monitoring stations were calibrated by using phycocyanin fluorescence measurements and chlorophyll a analyzed from manual water samples in a laboratory. A moving block bootstrap simulation was then used to estimate the standard errors of the mean and standard deviations for different sample sizes. Our results showed that in a temperate, meso-eutrophic lake, relatively high errors in seasonal statistics can be expected from monthly sampling. Moreover, weekly sampling yielded relatively small accuracy benefits compared to a fortnightly sampling. The presented method for temporal representation analysis can be used as a tool in sampling design by adjusting the sampling interval to suit the actual temporal variation in the monitoring area, in addition to being used for estimating the usefulness of previously collected data.     

Air quality monitoring for multiple pollutants: Optimization of a network around a hypothetical potash plant and two thermal power stations in open countryside

A method is presented for the design of multi-pollutant air quality monitoring networks (AQMN). This technique leads to an optimal network, i.e. a network providing a maximum of information with a minimum of measurement devices. The spatial correlation analysis technique is used to compare the information given by the potential sites that may form the network. The concept of potential of violation is defined to take into account the number of times that the maximum emission values tolerated by law are exceeded. Both objectives are weighted automatically through an adjustable parameter, b, for which an estimation procedure has been developed in this study, depending on the purpose of the network. Several methods are described, allowing simultaneous consideration of different pollutants. As an illustration of these methods, a number of air quality monitoring networks is designed to perform an analysis of the environmental impact due to a hypothetical potash processing plant and two thermal power stations.     

关于环境监测社会化的调查与思考

环境监测社会化在我国还处于探索阶段,社会化的根本目的是有序引入社会力量共同参与,提供更多、更好的监测服务。为此,环境监测社会化应坚持政府主导、社会参与的总体格局,引导环保监测机构重点强化环境监测网络运行管理、技术标准研发制定、监督性或执法性监测、环境质量预报预警及污染事故应急监测、监测数据质量控制及汇总分析等职能,同时因地制宜地确定环境监测社会化区域策略,严格规范社会检测的行为,确保监测市场有序开放、公平竞争、风险可控。     

Estimating soil temperature using neighboring station data via multi-nonlinear regression and artificial neural network models

The aim of this study is to estimate the soil temperatures of a target station using only the soil temperatures of neighboring stations without any consideration of the other variables or parameters related to soil properties. For this aim, the soil temperatures were measured at depths of 5, 10, 20, 50, and 100 cm below the earth surface at eight measuring stations in Turkey. Firstly, the multiple nonlinear regression analysis was performed with the “Enter” method to determine the relationship between the values of target station and neighboring stations. Then, the stepwise regression analysis was applied to determine the best independent variables. Finally, an artificial neural network (ANN) model was developed to estimate the soil temperature of a target station. According to the derived results for the training data set, the mean absolute percentage error and correlation coefficient ranged from 1.45% to 3.11% and from 0.9979 to 0.9986, respectively, while corresponding ranges of 1.685–3.65% and 0.9988–0.9991, respectively, were obtained based on the testing data set. The obtained results show that the developed ANN model provides a simple and accurate prediction to determine the soil temperature. In addition, the missing data at the target station could be determined within a high degree of accuracy.     

美国环境空气监测数据质量核查工作的经验与启示

国控网城市环境空气自动监测点位的监测事权上收后,对监测数据精密度和准确度的定量化评价已成为考核运维公司工作成果、评估国控网数据质量、编制数据质量报告的迫切需求。为加强中国环境空气数据质量核查体系的建设,总结了美国环境空气监测数据质量核查体系及其相关的技术规范,简要介绍其包含的各类核查项目和主要特点,提出了建设中国环境空气数据质量核查体系的建议。     

Evaluation of the best compromise between the urban air quality monitoring resolution by diffusive sampling and resource requirements

The need to collect data representative of overall urban pollution is all-important in order to monitor the population exposure. High spatial resolution monitoring using diffusive samplers allows studying of the urban pollutant distribution, thus enabling deeper investigation of their generation and diffusion mechanisms. Nevertheless, such a monitoring campaign has a certain cost. In this study we point out how to find the best compromise between the number of necessary measurements and the affordable costs for monitoring campaigns. We also describe an innovative method for the proper design of a fixed urban monitoring network by means of preliminary high spatial resolution campaigns using diffusive samplers. Four European capital cities (Dublin, Madrid, Paris and Rome) were monitored six times, each time for seven days. Benzene, toluene, ethylbenzene, xylenes (BTEX) and NO(2) concentrations were measured at 146 sites in Dublin, 293 in Madrid, 339 in Paris and 290 in Rome. Multiscale grids have been drawn which ranged in mesh size from 500 m to 2 km. The statistical processing of data produced a twofold result: the creation of isoconcentration maps with geostatistical procedures, and an algorithm aimed at locating the minimum number of sampling sites where the fixed monitoring stations should be placed. Average urban levels estimated on the basis of these selected sites differ by less than 8% from those calculated on the whole populations of the sampled points. The aim of this work is to investigate how far the resolution of a monitoring campaign of urban pollution by diffusive sampling can be reduced, thus making the monitoring less expensive in terms of human and financial resources, while preserving the same quality of the results that could be achieved with a higher resolution. We found that there is no significant loss of information when the resolution of the monitoring grid for BTEX is lowered to a mesh size of 1.85 km, that is a sampling site each 3.4 km(2), and that the minimum number of sampling sites to be used is N = 0.29 A, where A is the urban surface to be monitored (in km(2)). As the spatial distribution of NO(2) is less sensitive to the distance from the emission source than that of BTEX, this relationship could be retained as a valid lower limit for the mesh grid size also for NO(2) monitoring.     

Reference Point Approach for Multi-objective Assessment and Reduction of Ground-Level O<Subscript>3</Subscript> Air Quality Monitoring Network in Vojvodina Province,Serbia

A monitoring network of ground-level ozone (O₃) concentration levels in Vojvodina Province, Serbia, has been established in several phases, resulting in nine sampling sites (monitoring stations). Because maintenance of a monitoring network is financially very demanding, identifying potentially redundant ozone sites and reducing the network to a cost-effective and functional one are challenging and complex tasks. To provide an easily applicable but reliable analytical framework that will allow decision-makers and other stakeholders to identify redundant ground O₃ monitors, the reference point approach, presented by Cetinkaya and Harmancioglu (Journal of Hydrology, 2014), is adopted for a multi-objective assessment of the O₃ monitoring network. The evaluation process of the stations’ performance and their ranking is implemented in several phases. Firstly, a comprehensive set of 13 performance attributes is defined and associated with location and environmental criteria, followed by defining the set of alternatives. Next, all required attribute data are collected and stations are evaluated using the reference point approach. Finally, verification of the results is performed by aggregation of ranks obtained using the ideal point multi-criteria methods compromise programing and Technique for Order of Preference by Similarity to Ideal Solution. The aggregation process is performed using the Borda count and Kemeny social choice theory methods. Results indicate that the number of stations can be significantly reduced by 67%. Also, selection of the three best performing stations enabled identification of a core network that is expected to be functionally and financially sustainable under growing environmental and economic pressure.     

江苏省环境监测站标准化建设成效评价

江苏省在2013年底通过了国家环境监测站标准化建设整体验收,成为全国第一个整体达到国家建设标准的省份。在总结江苏省主要建设经验的基础上,为定量评估江苏省各级环境监测站标准化建设成效水平,以《国家环境监测站标准化验收评分办法》评价指标为基础,尝试构建环境监测站建设成效评价指标体系,并应用层次分析法确定指标及其权重,共设1项一级指标、5项二级指标和12项三级指标。通过专家综合决策打分,确定各项评价指标的权重值,赋值计算综合成效评价指数。结果表明,全省实验室条件、仪器设备、监测数据、论文发表、能力认证等方面发展迅速,但人员扩编有待进一步加强。该方法为政府部门考核财政资金投入绩效、优化管理决策提供了定量评价参考。     

基于聚类分析的颗粒物监测网络优化研究

为了优化香港环境监测网络,收集香港14个监测站2011年1月1日至2015年11月30日的颗粒物PM_(2.5)、PM_(10)的小时数据进行统计分析。对PM_(2.5)进行聚类,并利用日均浓度变化图进行验证,结果表明,可将监测站分为4类(A、B、C、D类),A类位于城市郊区,B类则位于港口附近,且A、B类的PM_(2.5)日变化特征均呈现双峰型分布,峰值分别出现在09:00和21:00。对PM_(10)进行类似分析结果表明,监测站同样可以分为4类,A类位于九龙区,B类则位于港口附近,而且A、B类的PM_(10)日变化双峰分别出现在11:00和20:00左右。说明污染源头及地形的相似致使某些监测站颗粒物浓度的变化出现相同的趋势,导致监测设备的浪费和管理的冗余。建议建立更高效的空气管理系统,将冗余设备转移到其他地区,扩大空气监控区域。对PM_(2.5)/PM_(10)聚类结果表明,将监测站分为4类,B类均属于路边站,C类则位于居民区。同时还发现同类监测站PM_(2.5)/PM_(10)数值变化相同,并且可以用其中一个站的PM_(2.5)和PM_(10)浓度及另一个站的PM_(2.5)或PM_(10)浓度预测PM_(2.5)或PM_(10)浓度,为优化监测资源提供了一种新的思路。     

Application and validation of a new biotic index using data from several water systems

Protozoans of Lake Donghu were collected from five stations using the PFU method. The sampling was conducted for one year and two times a month. The aim of this research was to test the applicability of a new protozoa biotic index, species pollution value (SPV) and community pollution value (CPV), established by the authors using data from the River Hanjiang. Each station's CPV was calculated from the SPV and the correlation analysis between the CPV and the comprehensive chemical index of stations I, II, III showed a significant correlation between them. The pollution status of the five stations was correctly evaluated by the CPV. These results suggested that the biotic index could be applied in water systems other than the River Hanjiang. The SPV of some protozoa species in Lake Donghu, not observed in the River Hanjiang were established. In order to further test the applicability of the biotic index, protozoan and chemistry data from the Rivers Torrente Stirone and Parma of Italy were used. The results showed that the CPV for the two rivers had a close relationship with the chemical water quality, which indicated that the biotic index could be applied in other parts of the world for the monitoring and estimating of water quality. Since the results of testing and verifying the biotic index in some other water systems in China were also satisfactory, this indicated that the biotic index has an extensive suitability for freshwater ecosystems. As long as more than 50% of the species in a sample have a SPV, the CPV calculated from the SPV is reliable for monitoring and evaluating water quality.     

A methodology for treating missing data applied to daily rainfall data in the Candelaro River Basin (Italy)

Environmental time series are often affected by the “presence” of missing data, but when dealing statistically with data, the need to fill in the gaps estimating the missing values must be considered. At present, a large number of statistical techniques are available to achieve this objective; they range from very simple methods, such as using the sample mean, to very sophisticated ones, such as multiple imputation. A brand new methodology for missing data estimation is proposed, which tries to merge the obvious advantages of the simplest techniques (e.g. their vocation to be easily implemented) with the strength of the newest techniques. The proposed method consists in the application of two consecutive stages: once it has been ascertained that a specific monitoring station is affected by missing data, the “most similar” monitoring stations are identified among neighbouring stations on the basis of a suitable similarity coefficient; in the second stage, a regressive method is applied in order to estimate the missing data. In this paper, four different regressive methods are applied and compared, in order to determine which is the most reliable for filling in the gaps, using rainfall data series measured in the Candelaro River Basin located in South Italy.     

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.