用机器学习和各种风险演变指数评估孟加拉国城市室内环境的微塑料污染及其相关风险
Baytune Nahar Netema1, Tapos Kumar Chakraborty1, Md Simoon Nice1
1Department of Environmental Science and Technology, Jashore University of Science and Technology, Jashore, 7408, Bangladesh.
Environmental pollution (Barking, Essex : 1987)
|July 29, 2024
概括
孟加拉国家庭的微塑料 (MP) 污染很大,纤维是最常见的. 室内国会议员对健康构成中等至高风险,特别是对儿童,达卡的风险水平最高.
科学领域:
- 环境科学 环境科学
- 毒理学 毒理学 毒理学
- 公共卫生 公共卫生
背景情况:
- 微塑料 (MP) 污染是一个日益严重的全球性问题,越来越多地出现在室内环境中.
- 塑料的使用有助于广泛的MP污染,造成潜在的人类健康威胁.
研究的目的:
- 在孟加拉国的城市室内环境中识别和描述MP污染.
- 评估MP暴露对人类健康的相关风险.
- 调查机器学习在预测MP污染方面的有效性.
主要方法:
- 从孟加拉国的城市室内环境收集了80个家庭灰尘样本.
- 分析了MP特性,包括形状,尺寸,颜色和聚合物类型.
- 利用污染指数和聚合物危险指数来评估风险.
- 应用机器学习模型 (随机森林,支持矢量机) 用于MP预测.
主要成果:
- 在家用灰尘 (25.8 ± 6.43 颗粒/g) 中,MPs 普遍存在,主要是纤维 (73%),0.5-1.00 毫米大小 (58%),蓝色 (21%) 和聚乙烯 (34%).
- 污染指数表明中度至高MP污染,并确定了严重的健康风险.
- 儿童和成人估计的每日摄入量分别为4.12±1.01和2.27±0.57颗粒.
- 达卡地区呈现出最高的MP诱导健康风险.
结论:
- 在孟加拉国,室内PM污染严重,对健康构成重大风险,特别是对儿童.
- 机器学习可以有效地利用环境因素预测MP水平.
- 需要采取紧急措施,以减轻室内MP暴露,并保护公共健康.
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