文章摘要
潘宇迪,杨红,吴建辉,王春峰.长江口口门海域水体重金属时间变化趋势及预测[J].上海海洋大学学报,2020,29(5):685-698
长江口口门海域水体重金属时间变化趋势及预测
Research on the temporal variation trend and prediction of heavy metals in the Yangtze River Estuary
投稿时间:2020-05-26  修订日期:2020-07-07
DOI:10.12024/jsou.20200503063
中文关键词: 长江口  时间序列  重金属  预测  影响因素
英文关键词: Yangtze River Estuary  sequentially  heavy metals  forecast  factors affecting
基金项目:海洋公益性行业科研经费专项(2012050-10);长江口中华鲟保护区及附近海域重金属监测项目(D-8006-18-0040)
作者单位E-mail
潘宇迪 上海海洋大学 海洋生态与环境学院, 上海 201306  
杨红 上海海洋大学 海洋生态与环境学院, 上海 201306 hyang@shou.edu.cn 
吴建辉 上海市水生野生动植物保护研究中心, 上海 200092  
王春峰 上海海洋大学 海洋生态与环境学院, 上海 201306  
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中文摘要:
      通过对2004—2017年长江口口门区域水体中Cu、Zn、Pb、Hg和As 5种重金属含量的调查,分析了北支、南支北港和北港北沙3个区域水体重金属含量的变化趋势及影响因素,并对未来几年重金属的含量进行了预测研究。结果显示,Cu和Pb在2011—2017年间整体呈现下降趋势,下降幅度低于2004—2008年, Zn和As在2011—2017年间一直处于稳定的下降趋势,Hg的下降趋势较小,5种重金属均在2011年和2015年前后污染物排放量增加时出现不同幅度的增长,且径流量较大的区域增长幅度较大;分析其影响因素得出,由于早期水体中重金属含量较高,治理投入成效大于污染物排放的影响,故2004—2008年Cu、Zn、Pb和As含量与环境治理投入呈显著负相关,与排污量之间相关性不显著;而在重金属含量控制到较低水平后,治理难度增加,成效减弱,污染物排放量成为了控制重金属含量的主要影响因素,故2011—2017年的重金属含量与环境治理投入相关性不显著,与排污量呈显著正相关;由于长江口3个区域在盐度和径流量等因素上存在差异,采用了ARIMA模型对不同区域的重金属分别进行预测,预测得出2020—2022年长江口口门处3个区域水体中重金属含量较低,变化趋势较为平稳,该模型具有较高的精度,误差在5.19%~11.82%之间,分区域预测可以突出不同区域重金属含量及变化特征,预测结果更具针对性,能够为未来治理方案的拟定提供一定依据。
英文摘要:
      By investigating the contents of five heavy metals Cu, Zn, Pb, Hg, and As in the water body of the Yangtze River Estuary area from 2004 to 2017, the change trends and influencing factors of water heavy metal contents in the three areas of Beizhi, Nanzhi Beigang and Beigang Beisha were analyzed and the contents of heavy metals were predicted in the next few years. The results show that Cu and Pb showed a downward trend as a whole from 2011 to 2017, and the decline rate was lower than that from 2004 to 2008. Zn and As were in a stable downward trend from 2011 to 2017. The downward trend of Hg is small, and five heavy metals increased in 2011 and 2015 when pollutant emissions increased, and regions with larger runoffs experienced larger increases; Analyzing the influencing factors, it is concluded that due to the high content of heavy metals in the early water body, the effectiveness of the treatment investment is greater than the impact of pollutant discharge. Therefore, the contents of Cu, Zn, Pb, and As from 2004 to 2008 were significantly negatively correlated with the environmental treatment investment, and the correlation with the amount of discharge is not significant; After the heavy metal content was controlled to a low level, the difficulty of governance increased and the effectiveness was weakened. Pollutant emissions became the main influencing factor for the control of heavy metal content. Therefore, the correlation between heavy metal content and environmental governance investment from 2011 to 2017 was not significant, and there is a significant positive correlation with the amount of discharge; Due to the differences in salinity and runoff in the three regions of the Yangtze River Estuary, ARIMA model was used to predict the heavy metals in different regions, and the heavy metal content in the water bodies of the three regions at the mouth of the Yangtze River Estuary from 2020 to 2022 was predicted to be low and the change trend is relatively stable, the model has a high accuracy, the error is between 5.19% and 11.82%. The regional prediction can highlight the heavy metal content and change characteristics of different regions, the prediction results are more targeted, and can be used for future governance .
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