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作 者:张汲伟 蔡琨[2] 于海燕[3] 姜永伟[4] 李旭文[2] 周胜利[3] 谢志才[5] 王业耀[6] 金小伟[6] 王备新[1] ZHANG Jiwei;CAI Kun;YU Haiyan;JIANG Yongwei;LI Xuwen;ZHOU Shengli;XIE Zhicai;WANG Yeyao;JIN Xiaowei;WANG Beixin(Laboratory of Aquatie Insects and Stream Ecology,Nanjing Agrieuhural University,Nanjing 210095,China;Jiangsu Province Environmental Monitoring Centre,Nanjing 210036,China;Zhejiang Province Environmental Monitoring Centre,Hangzhou 310012,China;Liaoning Environmental Monitoring and Experiment Centre,Shenyang 120031,China;Institute of Hydrobiology,Chinese Academy of Scienees,Wuhan 430072,China;State Environmental Protection Key Laboratory of Quality Control in Environmental Monitoring,China National Environmental Monitoring Centre,Beijing 100012,China)
机构地区:[1]南京农业大学,水生昆虫与溪流生态实验室,江苏南京210095 [2]江苏省环境监测中心,江苏南京210036 [3]浙江省环境监测中心,浙江杭州310012 [4]辽宁省环境监测实验中心,辽宁沈阳120031 [5]中国科学院武汉水生生物研究所,湖北武汉430072 [6]中国环境监测总站,国家环境保护环境监测质量控制重点实验室,北京100012
出 处:《中国环境监测》2018年第6期10-18,共9页Environmental Monitoring in China
基 金:江苏省环境监测基金(1608);江苏省自然科学基金(BK20171385);国家水体污染控制与治理科技重大专项(2017ZX07302-001).
摘 要:水质生物监测是水生态环境质量管理的重要内容,构建实用性强的生物指数有助于推动中国的水质生物监测工作。根据江苏、浙江、辽宁、江西和湖南等省份的溪流与河流湖泊共计839个底栖动物数据,将中国已有的底栖动物科级分类单元水质敏感性分值打分表扩充和修订至159个科。采用统计法分别构建了符合中国可涉水水体(溪流等)和不可涉水水体(河流、湖泊等)底栖动物分值指数(Chinese Macroinvertebrate Score Index,CMSI)和底栖动物平均分值指数(Average Chinese Macroinvertebrate Score Index,ACMSI)及水质评价等级体系。CMSI和ACMSI与总氮、总磷、高锰酸盐指数和溶解氧之间Pearson相关性显著,表明研究构建的CMSI和ACMSI是可以反映水质变化的。建议通过实践进一步验证CMSI和ACMSI的可靠性和实用性。Water quality biomonitoring is the key component of water eco-environment quality management. The development of a sound biological index is very important for developing a national-wide biomonitoring program. In this study, we firstly re-established scores of 159 benthic macroinvertebrate families based on the data of streams, rivers and lakes collecting from provinces of Jiangsu, Zhejiang, Liaoning, Jiangxi and Hunan. Then we applied statistical method to build water quality boundary of Chinese Macroinvertebrate Score Index(CMSI) and Average Chinese Macroinvertebrate Score Index(ACMSI) for streams, rivers and lakes, respectively, based on 839 samples. Both CMSI and ACMSI had the significant Pearson’s relationship with total nitrogen, total phosphorus, permanganate index and dissolved oxygen, indicating CMSI and ACMSI were the potential indicators of water quality. We suggested more tests on the robustness and practicability were required before CMSI and ACMSI could be used in routine water quality monitoring.
分 类 号:X826[环境科学与工程—环境工程]
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