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多藓种监测大气重金属污染方法改进
引用本文:王亚南,胡荣,周晓丽,方炎明.多藓种监测大气重金属污染方法改进[J].环境科学学报,2019,39(5):1464-1473.
作者姓名:王亚南  胡荣  周晓丽  方炎明
作者单位:南京林业大学南方现代林业协同创新中心/亚热带森林生物多样性保护国家林业局重点实验室/生物与环境学院,南京,210037;南京林业大学南方现代林业协同创新中心/亚热带森林生物多样性保护国家林业局重点实验室/生物与环境学院,南京,210037;南京林业大学南方现代林业协同创新中心/亚热带森林生物多样性保护国家林业局重点实验室/生物与环境学院,南京,210037;南京林业大学南方现代林业协同创新中心/亚热带森林生物多样性保护国家林业局重点实验室/生物与环境学院,南京,210037
基金项目:江苏高校优势学科建设工程项目(No.PAPD);国家自然科学基金(No.30070155)
摘    要:为弥补单藓种监测途径的弊端,克服因藓种分布区局限或不均匀带来的欠缺,本文通过引入多藓种监测和参考苔藓标样技术途径,采用ICP-AES和ICP-MS技术对洪泽湖区域的18种地面藓类植物体内重金属含量进行测定和分析,以研究多藓种监测途径和藓类种间校正方法.同时,测定了欧洲标准藓样M2和M3中的重金属含量,对实验仪器误差进行评估.结果表明,藓类植物中重金属含量差异显著.根据藓类对元素富集能力的不同将藓类分为4类:一般型、富集型、富集/排斥型和排斥型,本研究推荐一般型和富集型藓类应用于江苏省大气重金属沉降监测.对M2和M3中金属含量的推荐值和实测值进行对比,发现M2和M3中金属含量的实测值与推荐值的差异在15%以内,显示本实验采用的ICP-AES和ICP-MS设备精密度良好.根据洪泽湖区细叶小羽藓Haplocladium microphyllum的重金属含量建立了适宜本地重金属监测的种间校准因子,并建议不同地区采用多种藓类监测大气时,应根据当地的苔藓物种建立单独的种间校准方法.

关 键 词:苔藓  重金属  多藓种监测  校准因子
收稿时间:2018/9/18 0:00:00
修稿时间:2019/1/25 0:00:00

An improved method for monitoring air heavy metal pollution by multiple mosses
WANG Yanan,HU Rong,ZHOU Xiaoli and FANG Yanming.An improved method for monitoring air heavy metal pollution by multiple mosses[J].Acta Scientiae Circumstantiae,2019,39(5):1464-1473.
Authors:WANG Yanan  HU Rong  ZHOU Xiaoli and FANG Yanming
Institution:Co-Innovation Center for Sustainable Forestry in Southern China, Key Laboratory of State Forestry Administration on Subtropical Forest Biodiversity Conservation, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037,Co-Innovation Center for Sustainable Forestry in Southern China, Key Laboratory of State Forestry Administration on Subtropical Forest Biodiversity Conservation, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037,Co-Innovation Center for Sustainable Forestry in Southern China, Key Laboratory of State Forestry Administration on Subtropical Forest Biodiversity Conservation, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037 and Co-Innovation Center for Sustainable Forestry in Southern China, Key Laboratory of State Forestry Administration on Subtropical Forest Biodiversity Conservation, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037
Abstract:This article introduced a technical approach of multi-moss monitoring combined with the reference moss sample measurement to remedy the disadvantages of single-moss indication method which may have shortcomings due to limited or uneven distribution of the moss species. In order to develop a multiple-moss monitoring pathway and an interspecific calibration of multiple mosses, samples of 18 terrestrial bryophyte species were collected over the territory of Hongze Lake region and the concentrations of several heavy metals in these samples were determined and analyzed by using ICP-AES and ICP-MS techniques. Simultaneously, heavy metal concentrations in the European standard samples M2 and M3 were measured to evaluate the error of the experimental instruments. The results showed that the concentrations of heavy metals in different mosses were significantly different. According to their differential capacity for heavy metal enrichment, mosses could be separated into four categories:general mosses, enrichment mosses, enrichment/exclusion mosses, and exclusion mosses. General and enrichment mosses were recommended to be applied for monitoring the atmospheric heavy metal deposition in Jiangsu Province. Furthermore, the variation between the obtained and recommended concentrations in M2 and M3 was found to be less than 15%, indicating that the precision of ICP-AES and ICP-MS is quite high. Based on the heavy metal concentrations of Haplocladium microphyllum in Hongze Lake region, an interspecific calibration factor suitable for local heavy metal monitoring was established. It was suggested that when using the multiple-moss monitoring approach for air deposition surveys in various areas, specific calibration factors may be set up according to the local bryophyte species.
Keywords:moss  heavy metal  multiple-mosses monitoring  calibration factor
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