生态毒理学报2024,Vol.19Issue(4) :120-130.DOI:10.7524/AJE.1673-5897.20240220002

非参数核密度估计模型预测双酚A的物种敏感度分布规律

Application of Non-Parametric Kernel Density Estimation Model in Prediction of Species Sensitivity Distribution of Bisphenol A

杨瑞君 张楚 杨评 冯承莲 李丹 陶建伟 叶璟
生态毒理学报2024,Vol.19Issue(4) :120-130.DOI:10.7524/AJE.1673-5897.20240220002

非参数核密度估计模型预测双酚A的物种敏感度分布规律

Application of Non-Parametric Kernel Density Estimation Model in Prediction of Species Sensitivity Distribution of Bisphenol A

杨瑞君 1张楚 1杨评 2冯承莲 3李丹 4陶建伟 2叶璟5
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作者信息

  • 1. 上海应用技术大学计算机科学与信息工程学院,上海 201418
  • 2. 上海应用技术大学化学与环境工程学院,上海 201418
  • 3. 中国环境科学研究院环境基准与风险评估国家重点实验室,北京 100012
  • 4. 上海应用技术大学生态技术与工程学院,上海 201418
  • 5. 上海应用技术大学化学与环境工程学院,上海 201418;中国环境科学研究院环境基准与风险评估国家重点实验室,北京 100012
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摘要

双酚A(bisphenol A,BPA)已被证实是内分泌干扰物,可干扰生物体正常的激素功能,对生殖、发育和免疫系统产生不良影响.BPA进入环境后可能会对水生生物和陆地生物造成毒性效应,破坏生态平衡.针对BPA对水生生物的毒性特点,利用Python语言,基于非参数核密度估计模型构建BPA淡水水生生物的敏感度分布曲线,选用4种传统参数模型进行对比,并推导出保护淡水水生生物的BPA水质基准建议值.结果表明,Python构建模型简单高效,相较于传统的参数模型,非参数核密度估计方法在推导BPA的水质基准建议值中更加稳健和精准,其中3种参数模型和非参数核密度估计模型计算得到的雌激素效应毒性的 HC5 值分别为 4.175、5.096、3.888 和 1.179 μg·L-1;其他毒性的 HC5 值为 7.139、7.452、7.533 和 5.869 μg·L-1.非参数核密度估计的方法能够更好地构建物种敏感度分布曲线,为进一步研究BPA的水质基准和更好地保护淡水水生生物提供了有力支持,同时研究成果以期为我国地表水环境质量标准的制修订做出贡献.

Abstract

Bisphenol A(BPA)has been proven to be an endocrine disruptor that interferes with normal hormonal functions in organisms,adversely affecting reproduction,development,and the immune system.Once BPA enters the environment,it may cause toxic effects on aquatic and terrestrial organisms,disrupting ecological balance.This study focuses on the toxicity characteristics of BPA to aquatic organisms.Using the open-source Python language and its extensive libraries,a non-parametric kernel density estimation model was constructed to develop a sensitivity distribution curve for BPA's impact on freshwater aquatic species.Four traditional parametric models were selected for comparison,and the derived water quality criteria for BPA aimed to protect freshwater aquatic life.The results demonstrated that the Python model is simple and efficient to construct.Compared to traditional parametric models,the non-parametric kernel density estimation method proved to be more robust and accurate in deriving BPA water quality criteria.The HC5 values for estrogenic toxicity calculated by three parametric models and the non-parametric kernel density estimation model were 4.175,5.096,3.888,and 1.179 μg·L-1,respectively.For other toxicities,the HC5 values were 7.139,7.452,7.533,and 5.869 μg·L-1 for the four models,respectively.Therefore,the non-parametric kernel density method can provide a better way to construct species sensitivity distribution curves,providing strong support for further research on BPA water quality criteria and improved protection of freshwater aquatic organisms.The findings are expected to contribute to the formulation and revision of surface water environmental quality standards for BPA in China.

关键词

双酚A/淡水生物/雌激素效应/非参数核密度估计/物种敏感度分布/水质基准阈值

Key words

bisphenol A/freshwater organisms/estrogen effects/non-parametric kernel density estimation/species sensitivity distribution/water quality criteria threshold

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基金项目

国家重点研发计划(2021YFC3201001)

国家自然科学基金青年基金(21307082)

国家自然科学基金面上项目(42277274)

上海市自然科学基金面上项目(18ZR1438000)

上海应用技术大学协同创新基金-跨学科、多领域合作研究专项(XTCX2024-03)

出版年

2024
生态毒理学报
中国科学院生态环境研究中心

生态毒理学报

CSTPCDCSCD北大核心
影响因子:0.857
ISSN:1673-5897
参考文献量46
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