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对湖泊中溶解有机物组成的表征和可追溯性研究的新观点

Juan Huan¹, Jialong Yuan¹, Xiangen Xu²

¹School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213164, China.

The Science of the total environment

|November 23, 2024

概括

在丹湖中溶解的有机物 (DOM) 用光光谱分析. 结果确定了湿物质和蛋白质,表明水产养殖和织染料的混合污染源对湖泊管理至关重要.

科学领域:

环境科学环境科学
分析水质分析水质
有机地化学有机地化学

背景情况:

加快的城市化和社会经济发展加剧了水污染,造成了重大的生态和人类健康风险.
了解溶解有机物 (DOM) 分数及其来源对于减轻湖泊污染和生态压力至关重要.
长丹湖作为一个案例研究,以调查污染水环境中的DOM特征.

研究的目的:

分析了丹湖DOM的三维光光谱特性和特征参数.
通过将其组成与周围环境因素相关联,识别和追踪湖中DOM的来源.
为当地环境保护工作提供数据支持,并为其他湖泊盆地的污染可追溯性提供信息.

主要方法:

三维光光谱学被用来分析DOM.
峰值寻找方法,塔克系数和自我组织的神经网络被用于数据分析.
集成了传统的水质参数,以确定DOM和污染源之间的相关性.

主要成果:

确定了四个主要的DOM组件:湿性物质 (C1,C2,C4) 和蛋白质 (C3).
光指数 (FI),BIX和HIX值表明了内源和外源DOM输入的混合.
DOM的光特性与周围的水产养殖和织品印刷/染色活动的光特性非常相匹配.

结论:

该研究成功地描述了丹湖的DOM,确定了关键组件及其起源.
水产养殖和织品染色被确定为对湖泊DOM污染的重要贡献者.
这些发现为环境管理和湖泊生态系统中的污染源追踪提供了宝贵的见解.

关键词:

长达湖是长达湖的一个组成部分.有机污染并行因素分析自组织神经网络自组织神经网络这就是TC系数.三维光的三维光.

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