Real-time monitoring of water quality using fish and crayfish as bio-indicators: a review

Water quality monitoring using fish and crayfish as bio-indicators requires an understanding of the state of pollution of waters, choice of bio-indicators, physiological and behavioral endpoints of fish and crayfish, and principles of the methodology and their potential applications. Here, we discuss telemetry, acoustic monitoring, vision-based monitoring, measures of ventilatory activity, electrocardiography, and fiber-optic plethysmography. Assessment of water quality must be based, not only on physicochemical characteristics of the current environment as determined by chemical analyses, but also on observations of the physiology and behavior of its inhabitants. Real-time biomonitoring is suggested as the most reliable method, since it incorporates living organisms into the system to serve as biosensors. The potential application of the methods discussed includes use at water treatment plants and water supply stations for prevention of hazardous toxicological events, and, for aquaculture, in ponds, lakes, and aquariums for monitoring growth, population size, and behavior traits.     

Developing an environmental water quality monitoring program for Haraz River in Northern Iran

Water quality management plans are an indispensable strategy for conservation and utilization of water resources in a sustainable manner. One common industrial use of water is aquaculture. The present study is an attempt to use statistical analyses in order to prepare an environmental water quality monitoring program for Haraz River, in Northern Iran. For this purpose, the analysis of a total number of 18 physicochemical parameters was performed at 15 stations during a 1-year sampling period. According to the results of the multivariate statistical methods, the optimal monitoring would be possible by only 3 stations and 12 parameters, including NH₃, EC, BOD, TSS, DO, PO₄, NO₃, TDS, temperature, turbidity, coliform, and discharge. In other words, newly designed network, with a total number of 36 measurements (3 stations × 12 parameters = 36 parameters), could achieve exactly the same performance as the former network, designed based on 234 measurements (13 stations × 18 parameters = 234 parameters). Based on the results of cluster, principal component, and factor analyses, the stations were divided into three groups of high pollution (HP), medium pollution (MP), and low pollution (LP). By clustering the stations, it would be possible to track the water quality of Haraz River, only by one station at each cluster, which facilitates rapid assessment of the water quality in the river basin. Emphasizing on three main axes of monitoring program, including measurement parameters, sampling frequency, and spatial pattern of sampling points, the water quality monitoring program was optimized for the river basin based on natural conditions of the study area, monitoring objectives, and required financial resources (a total annual cost of about US $2625, excluding the overhead costs).     

Intensive water quality monitoring in a Taiwan bathing beach

A total of 357 water samples were collected from a public beach in northern Taiwan during beach season, and the densities of enterococci were analyzed by Enterolert methods. The mean enterococci level was 356 MPN/100 ml and ranged from <10 to 2,005 MPN/100 ml, which was classified as high contamination level according to the WHO water quality guideline (95 percentile >1,000 MPN/100 ml). Most of the deteriorated water quality conditions occurred during rainfall. By excluding data from the rain days, the overall beach water quality would be considered in the moderate contamination level (95 percentile 200-1,000 MPN/100 ml). Among the selected microbiological parameters tested, the densities of total coliforms and enterococci exhibited the highest correlation (r = 0.449, p = 0.009), followed by the concentrations of total coliforms and fecal coliforms (r = 0.403, p = 0.02). Nonetheless, no significant correlation was found between enterococci and fecal coliform levels (r = 0.197, p = 0.271).     

和田地区环境监测质量管理工作初探

结合和田地区环境监测站环境监测质量管理现状,就提高环境监测质量管理水平,充分发挥其在环境管理中的基础性作用,初步探讨了环境质量管理的必要性和基本思路。     

Optimization models for siting water quality monitoring stations in a catchment

A water quality monitoring network (WQMN) must be designed so as to adequately protect the water quality in a catchment. Although a simulated annealing (SA) method was previously applied to design a WQMN, the SA method cannot ensure the solution it obtained is the global optimum. Therefore, two new linear optimization models are proposed in this study to minimize the deviation of the cost values expected to identify the possible pollution sources based on uniform cost (UC) and coverage elimination uniform cost (CEUC) schemes. The UC model determines the expected cost values by considering each sub-catchment being covered by which station, while the CEUC model determines the coverage of each station by eliminating the area covered by any upstream station. The proposed models are applied to the Derchi reservoir catchment in Taiwan. Results show that the global optimal WQMN can be effectively determined by using the UC or CEUC model, for which both results are better than those from the SA method, especially when the number of stations becomes large.     

Statistical needs in national water quality monitoring programs

The concept that a few well chosen, strategically placed, water quality stations can provide valuable scientific information to water managers is common to many countries. Historically within Canada, water quality regional networks (Great Lakes network, Prairie Provinces Water Board network, Long Range Transport of Airborne Pollutants network, etc.) have been successfully operating for many years. This paper will describe the difficulties associated with developing a national water quality network for a country the size of Canada. In particular, it will describe some of the statistical tools presently being used in regional networks which are suitable for a national network, and discuss the need to develop new statistical tools for environmental monitoring in the 1990's.     

Ensuring quality in long term environmental monitoring for chemical speciation

The awareness regarding quality assurance (QA) and quality control (QC) for environmental monitoring has considerably increased in the past few years, especially with respect to the determination of chemical species, since errors occurring at various levels may considerably affect the interpretation of results (e.g. studies of toxic impact, geochemical pathways, etc.). QA for environmental analysis covers a broad range of activities from sample collection to laboratory work and the approach for ensuring quality data should be considered in a global context. However, whereas great emphasis has been placed on QA within the laboratory, there have been few systematic attempts to evaluate risks of discrepancies related, for example, to field manipulations. The situation is even worse when monitoring is applied to relatively new fields such as chemical speciation. This paper outlines some of the main aspects of quality control of environmental analysis, including the validation of methods, sampling and sample handling, storage, etc., with special emphasis on the monitoring of chemical forms of elements (e.g. species of tin, mercury, lead and selenium).     

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.     

Industrial effluent quality, pollution monitoring and environmental management

Royal Commission Environmental Control Department (RC-ECD) at Yanbu industrial city in Kingdom of Saudi Arabia has established a well-defined monitoring program to control the pollution from industrial effluents. The quality of effluent from each facility is monitored round the clock. Different strategic measures have been taken by the RC-ECD to implement the zero discharge policy of RC. Industries are required to pre-treat the effluent to conform pretreatment standards before discharging to central biological treatment plant. Industries are not allowed to discharge any treated or untreated effluent in open channels. After treatment, reclaimed water must have to comply with direct discharge standards before discharge to the sea. Data of industrial wastewater collected from five major industries and central industrial wastewater treatment plant (IWTP) is summarized in this report. During 5-year period, 3,705 samples were collected and analyzed for 43,436 parameters. There were 1,377 violations from pretreatment standards from all the industries. Overall violation percentage was 3.17%. Maximum violations were recorded from one of the petrochemical plants. The results show no significant pollution due to heavy metals. Almost all heavy metals were within RC pretreatment standards. High COD and TOC indicates that major pollution was due to hydrocarbons. Typical compounds identified by GC-MS were branched alkanes, branched alkenes, aliphatic ketones, substituted thiophenes, substituted phenols, aromatics and aromatic alcohols. Quality of treated water was also in compliance with RC direct discharge standards. In order to achieve the zero discharge goal, further studies and measures are in progress.