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热带海洋学报 ›› 2026, Vol. 45 ›› Issue (4): 153-161.doi: 10.11978/2025163CSTR: 32234.14.2025163

• 海洋环境科学 • 上一篇    下一篇

钦州湾水体硝酸盐分布特征及其主要来源解析*

娄志凤1,2,3(), 李雨辰1,2,3, 殷雪华1,2,3, 孙溶1,2, 田崇国1,2,4()   

  1. 1 中国科学院烟台海岸带研究所, 海岸带环境过程与生态修复重点实验室, 山东 烟台 264003
    2 山东省海岸带环境过程重点实验室, 山东 烟台 264003
    3 中国科学院大学, 北京 100049
    4 陆海统筹生态治理与系统调控重点实验室(山东省生态环境规划研究院), 山东 济南 250101
  • 收稿日期:2025-09-10 修回日期:2025-10-20 出版日期:2026-07-10 发布日期:2026-07-31
  • 通讯作者: 田崇国。email:
  • 作者简介:

    娄志凤(2000—), 女, 河南省新乡市人, 硕士研究生, 环境工程专业。email:

    *感谢匿名审稿专家提出的宝贵修改意见和建议

  • 基金资助:
    国家自然科学基金项目(42177089); 中国科学院仪器设备功能开发技术创新项目(E32P030301)

Distribution characteristics and main sources of nitrate in the waters of Qinzhou Bay*

LOU Zhifeng1,2,3(), LI Yuchen1,2,3, YIN Xuehua1,2,3, SUN Rong1,2, TIAN Chongguo1,2,4()   

  1. 1 Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China
    2 Shandong Key Laboratory of Coastal Environmental Processes, Yantai 264003, China
    3 University of Chinese Academy of Sciences, Beijing 100049, China
    4 Key Laboratory of Land and Sea Ecological Governance and Systematic Regulation, Shandong Academy for Environmental Planning, Jinan 250101, China
  • Received:2025-09-10 Revised:2025-10-20 Online:2026-07-10 Published:2026-07-31
  • Contact: TIAN Chongguo. email:
  • Supported by:
    National Natural Science Foundation of China(42177089); Instrument Function Development and Technological Innovation Project of the Chinese Academy of Sciences(E32P030301)

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摘要：

作为发展对外贸易与旅游业的“黄金海岸”, 钦州湾近年来经济与农业的快速发展致使其水体富营养化问题日益凸显。本研究基于2023年9月、10月和12月的实地监测数据, 分析了钦州湾硝酸盐($\text{NO}_{3}^{-}$)浓度时空分布规律, 并结合氮氧同位素数据, 应用贝叶斯混合模型(Bayesian mixing model, MixSIAR), 对9月、10月的硝酸盐来源进行初步分析。结果表明, 钦州湾$\text{NO}_{3}^{-}$浓度在空间分布上总体呈现自北向南、自内湾向外湾递减的趋势, 高浓度区主要集中在茅尾海以及钦江等河流入海口附近。在时间变化上, 钦州湾12月$\text{NO}_{3}^{-}$浓度[(2.01±1.58)mg·L-1]高于9月[(0.64±0.36)mg·L-1]和10月[(0.35±0.28)mg·L-1], 这主要与季节性生物活动及陆源输入量的变化有关。进一步分析表明, 9月和10月钦州湾水体中的$\text{NO}_{3}^{-}$转化以硝化作用为主, 反硝化作用并不明显。在来源方面, 粪肥和污水是钦州湾9月和10月$\text{NO}_{3}^{-}$最主要的来源, 贡献率约为66%, 其次为土壤氮, 贡献率约为32%, 大气沉降与化肥对钦州湾的贡献率均较低, 二者各自贡献率均约为1%。

关键词: 硝酸盐, MixSIAR模型, 污染源识别, 钦州湾

Abstract:

As a “golden” coastal area for foreign trade and tourism development, Qinzhou Bay has experienced increasingly severe eutrophication in recent years, driven by the rapid expansion of economic and agricultural activities. This study investigated the spatiotemporal distribution of nitrate $(\text{NO}_{3}^{-})$in the bay using field monitoring data collected in September, October, and December 2023. Furthermore, a preliminary assessment of nitrate sources was conducted specifically for September and October, employing nitrogen and oxygen isotope analysis coupled with a Bayesian mixing model (MixSIAR). The results revealed that nitrate concentrations generally exhibited a decreasing trend from north to south and from the inner bay to the bay mouth, with high-concentration zones mainly distributed near Maowei Sea and the estuaries of rivers such as the Qinjiang River. Temporally, the nitrate concentration in December [(2.01 ± 1.58) mg·L-1] was markedly higher than those in September [(0.64 ± 0.36) mg·L-1] and October [(0.35 ± 0.28) mg·L-1], which was attributed to seasonal variations in biological activity and terrestrial inputs. Further analysis indicated that nitrification was the dominant transformation process for nitrate during September and October, while denitrification was not significant. Source apportionment results showed that manure and domestic sewage were the primary nitrate sources, contributing approximately 66% of the total input, followed by soil nitrogen (~32%). In contrast, atmospheric deposition and chemical fertilizers made minimal contributions, each accounting for about 1%.

Key words: nitrate, MixSIAR model, pollution source identification, Qinzhou Bay

中图分类号: 

  • P734