生态环境学报 ›› 2021, Vol. 30 ›› Issue (6): 1249-1259.DOI: 10.16258/j.cnki.1674-5906.2021.06.016

• 研究论文 • 上一篇    下一篇

盐城滨海湿地土壤多环芳烃分布特征及影响因素

蔡杨1,2(), 李伟1,2,*, 左雪燕1,2, 崔丽娟1,2, 雷茵茹1,2, 赵欣胜1,2, 翟夏杰1,2, 李晶1,2, 潘旭1,2   

  1. 1.中国林业科学研究院湿地研究所,北京 100091
    2.湿地生态功能与恢复北京市重点实验室,北京 100091
  • 收稿日期:2020-11-24 出版日期:2021-06-18 发布日期:2021-09-10
  • 通讯作者: *
  • 作者简介:蔡杨(1994年生),女,硕士研究生,主要从事湿地生态恢复研究。E-mail: caiy9160@163.com
  • 基金资助:
    国家重点研发计划项目(2017YFC0506200)

Distribution Characteristics and Influencing Factors of PAHs in Yancheng Coastal Wetland Soil

CAI Yang1,2(), LI Wei1,2,*, ZUO Xueyan1,2, CUI Lijuan1,2, LEI Yinru1,2, ZHAO Xinsheng1,2, ZHAI Xiajie1,2, LI Jing1,2, PAN Xu1,2   

  1. 1. Institute of Wetland Research, Chinese Academy of Forestry, Beijing 100091, China
    2. Beijing Key Laboratory of Wetland Services and Restoration, Beijing 100091, China
  • Received:2020-11-24 Online:2021-06-18 Published:2021-09-10

摘要:

多环芳烃(PAHs)是一类具有致癌、致畸和致突变作用的环境污染物,研究盐城滨海湿地土壤中PAHs的分布特征、来源以及环境因子对其分布的影响,可揭示盐城滨海湿地的污染现状,并为PAHs污染区域修复提供理论依据,进而为我国滨海湿地的生态修复与保护提供科学参考。2019年8月,分别采集研究区域内4种优势植被(互花米草Spartina alterniflora、海三稜藨草Scirpus×mariqueter、白茅Imperata cylindrica和盐地碱蓬Suaeda salsa)覆盖下的表层土壤(0—20 cm)样本21个,并测定PAHs的质量分数。结果显示,(1)盐城滨海湿地土壤中16种多环芳烃(∑16PAHs)的检出率为100%,质量分数范围为227—884 ng∙g-1,均值为479 ng∙g-1,其中7种致癌多环芳烃(∑7PAHs)质量分数范围为79.8—553 ng∙g-1,均值为286 ng∙g-1。研究区内21个点位中,有4个点位处于中度污染水平,其余点位均为轻度污染。不同植被覆盖下土壤中4种PAHs单体质量分数及总质量分数存在显著差异。(2)采用特征比值法和主成分分析法对研究区内土壤PAHs来源进行解析发现,PAHs主要来源于燃烧过程。(3)针对环境因素和PAHs的相关性分析得出,萘(Nap)、芴(Flu)和?(Chr)与土壤含水率(SWC)呈显著正相关关系(P<0.05);Chr和二苯并[a, h]蒽(DahA)与土壤有机质(SOM)呈极显著正相关关系(P<0.01);苊烯(Acy)与土壤粘粒呈显著正相关关系(P<0.05)。通过偏相关性分析发现,剔除土壤粒径这一因素后,SOM和SWC与PAHs的相关性显著减弱。剔除植被密度(VD)或土壤pH的影响后,减轻了SOM与PAHs关系的显著程度,而增加了SWC与PAHs的相关性。

关键词: 滨海湿地, 多环芳烃, 分布特征, 来源, 影响因素

Abstract:

Polycyclic aromatic hydrocarbons (PAHs) are environmental pollutants with carcinogenic, teratogenic, and mutagenic effects. Determining the distribution characteristics and sources of PAHs in Yancheng coastal wetland soil and the influence of environmental factors can reveal the characteristics of Yancheng coastal wetland Pollution status, and provide a theoretical basis for the restoration of PAHs contaminated areas, and then provide a scientific reference for ensuring the ecological restoration and protection of coastal wetlands in China. In August 2019, we collected samples and determined the mass concentration of PAHs of four dominant types of vegetation (Scirpus×mariqueter, Imperata cylindrica, Spartina alterniflora and Suaeda salsa) that covered the topsoil (0-20 cm) in the study area. The results showed the following. Firstly, the detection rate of 16 PAHs (∑16PAHs) in Yancheng coastal wetland soil was 100%, and the content of ∑16PAHs ranged from 227 to 884 ng∙g-1, with an average of 479 ng∙g-1, of which 7 carcinogenic PAHs (∑7PAHs) were 79.8-553 ng∙g-1, with an average of 286 ng∙g-1. Moreover, among the 21 sites in the study area, 4 were at moderate pollution level, and the rest were slightly polluted. Secondly, the characteristic component ratio method and principal component analysis method were used to analyze the sources of PAHs in the study area. Results showed that combustion process may have been the sources of these compounds. Thirdly, according to the analysis of the correlation between environmental factors and PAHs, Naphthalene (Nap), Fluorene (Flu) and Chrysene (Chr) have a significant positive correlation with soil moisture content (SWC) (P<0.05); Chr and Dibenz[a, h]anthracene (DahA) are extremely significant positively correlated with soil organic matter (SOM) (P<0.01); Acenaphthylene (Acy) and soil clay have a significant positive correlation (P<0.05). Through partial correlation analysis, it is found that after controlling the factor of soil grain size, the correlation between SOM, SWC and PAHs is significantly weakened. After excluding the effects of vegetation density (VD) or soil pH, the significance of the relationship between SOM and PAHs was reduced, and the correlation between SWC and PAHs was increased.

Key words: coastal wetland, PAHs, distribution characteristics, source, influencing factors

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