SELECTION OF THE MOST EFFECTIVE BIOLOGICAL EARLY WARNING SYSTEM, BASED ON AHP AND REMBRANDT ANALYSIS

J. Chmist, K. Szoszkiewicz, M. Hämmerling
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引用次数: 1

Abstract

In paper, the ability to use of the biological early warning systems, in tap water quality biomonitoring was analyzed, based on multiple-criteria decision analysis. Five groups of organisms (invertebrates, fishes, algae, fungi and bacteria) were analyzed for the sensitivity to disturbance, the area of use, the amount of detected components, the rate of reaction and the data interpretation. Both analyzes revealed, that invertebrates are the most sensitive bioindicators (49% AHP, 29% Rembrandt). The other organisms which are useful in BEWS systems are algae and fishes. More problematic may be systems based on fungi and bacteria.Both analysis Rembrandt, as well as analytic hierarchy process(AHP) have indicated the rate of reaction as the most important factor in BEWS. All of BEWS systems are focused on reduce the time required to obtain the information about pollution presence, because the standard monitoring of tap water quality, based on physical and chemical methods, are usually time consuming.
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选择最有效的生物预警系统,基于层次分析法和伦勃朗分析法
本文基于多准则决策分析,对生物预警系统在自来水水质生物监测中的应用能力进行了分析。分析了五类生物(无脊椎动物、鱼类、藻类、真菌和细菌)对干扰的敏感性、使用面积、检测成分的数量、反应速率和数据解释。两项分析都显示,无脊椎动物是最敏感的生物指标(49% AHP, 29%伦勃朗)。在BEWS系统中有用的其他生物是藻类和鱼类。更有问题的可能是基于真菌和细菌的系统。伦勃朗的分析和层次分析法(AHP)都表明,反应速率是BEWS中最重要的因素。所有BEWS系统都专注于减少获取污染信息所需的时间,因为基于物理和化学方法的自来水质量标准监测通常非常耗时。
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来源期刊
CiteScore
0.40
自引率
25.00%
发文量
1
审稿时长
50 weeks
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