基于复合指纹图谱和贝叶斯模型的茅尾海悬浮颗粒物源解析

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摘要为明确茅尾海中悬浮颗粒物的来源,采集了茅尾海流域红树林土壤、堤岸土、河口颗粒物、茅尾海沉积物以及湾外颗粒物等悬浮颗粒物潜在源样品.基于多元统计复合指纹图谱方法,筛选出最佳指纹因子组合,进而通过贝叶斯混合模型得出五种潜在源对茅尾海悬浮颗粒物的贡献率.结果表明:Mg、Al、Mn、Pb、Fe五种指纹元素可作为最佳指纹因子组合,累计判别正确率为78%.贝叶斯混合模型结果显示,茅尾海悬浮颗粒物主要来源于河口和湾外输送,贡献率最高达到58.9%和68.6%.其中,靠近河口区域主要受河流汇入影响,其贡献率达到42.2%~58.9%;靠近湾外区域则以湾外颗粒物贡献为主,贡献率达到44.9%~68.6%.各点位的沉积物贡献率均较低,红树林土壤和堤岸土的贡献率都在10%左右.总的来说,由河口汇入和潮汐作用带入的颗粒物是茅尾海悬浮颗粒物的主要来源.

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	刘海霞
	李素霞
	刘广龙
	黄凯旋
	杨斌
	苏静君
	王杰
	张晋谊
	侯景耀

关键词 ：贝叶斯模型, 复合指纹图谱, 颗粒物, 源解析

Abstract：Toreveal the source of suspended particulate matter in Maoweisea, samples of potential sources of suspended particulate matter such as mangrove soil, embankment soil, estuarine particulate matter, Maowei Sea sediment and particulate matter outside the Bay in Maowei Sea Basin were collected. Based on multivariate statistical composite fingerprinting method, the optimal fingerprint factor combination was formatted, and then the contribution rates of five potential sources to suspended particulate matter in Maowei Sea are obtained by Bayesian mixed model. The results show that five fingerprint elements of Mg, Al, Mn, Pb and Fe can be used as the best combination of fingerprint factors, and the cumulative discrimination accuracy rate is 78%. The results of the Bayesian mixed model showed that the suspended particulate matter in Maowei Sea is mainly derived from the estuary and the outer bay transport, and the contribution rate reaches 58.9% and 68.6%. Among them, the area near the estuary is mainly affected by the river inflow, and the contribution rate of estuarine particulate matter reaches 42.2%~58.9%; In the areas close to the outer bay, the contribution rate of particulate matter outside the bay was 44.9%~68.6%. The contribution rate of sediment at each point was low, and the contribution rate of mangrove soil and embankment soil was about 10%. In general, particulate matter brought in by estuarine inflow and tidal action is the main source of suspended particulate matter in the Maowei Sea.

Key words： Bayesian model composite fingerprinting particulate matter source resolution

收稿日期: 2021-11-12

PACS:

X55

基金资助:国家自然科学基金资助项目(31960242);广西自然科学基金资助项目(2020GXNSFAA297080,2016GXNSFAA380242)

通讯作者: 李素霞,教授,284137449@qq.com E-mail: 284137449@qq.com

作者简介: 刘海霞(1998-),女,湖北仙桃人,桂林理工大学硕士研究生,主要从事水体污染控制与生态修复研究.

引用本文:

刘海霞, 李素霞, 刘广龙, 黄凯旋, 杨斌, 苏静君, 王杰, 张晋谊, 侯景耀. 基于复合指纹图谱和贝叶斯模型的茅尾海悬浮颗粒物源解析[J]. 中国环境科学, 2022, 42(6): 2844-2851. LIU Hai-xia, LI Su-xia, LIU Guang-long, HUANG Kai-xuan, YANG Bin, SU Jing-jun, WANG Jie, ZHANG Jin-yi, HOU Jing-yao. Analysis of the source of suspended particulate matter in the Maowei Sea based on composite fingerprint map and Bayesian model. CHINA ENVIRONMENTAL SCIENCECE, 2022, 42(6): 2844-2851.

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http://www.zghjkx.com.cn/CN/ 或 http://www.zghjkx.com.cn/CN/Y2022/V42/I6/2844

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