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评估重金属污染及其对人群健康的影响。

Assessing Pollution with Heavy Metals and Its Impact on Population Health.

作者信息

Saliba Youssef, Bărbulescu Alina

机构信息

Doctoral School, Technical University of Civil Engineering of Bucharest, 122-124 Bd. Lacul Tei, 020396 Bucharest, Romania.

Department of Civil Engineering, Transilvania University of Brașov, 5 Turnului Str., 500152 Brașov, Romania.

出版信息

Toxics. 2025 Jan 12;13(1):52. doi: 10.3390/toxics13010052.

DOI:10.3390/toxics13010052
PMID:39853050
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11768440/
Abstract

Pollution is one of the most important issues currently affecting the global population and environment. Therefore, determining the zones where stringent measures should be taken is necessary. In this study, Principal Component Analysis (PCA), Factor Analysis (FA), and t-distributed Stochastic Neighbor Embedding (t-SNE) were utilized for dimensionality reduction and clustering of data series containing the concentration of 10 heavy metals collected at 14 locations. The Hazard Quotient () and Hazard Index () were utilized to determine the non-carcinogenic risk to the population in the studied zones. The highest concentrations of metals in the samples were those of Fe, Zn, Mn, and Cr. PCA indicated that Fe and Zn (Co and Cd) had the highest contribution on the first (second) Principal Component (PC). FA showed that the three-factor model is adequate for explaining the variability of pollutant concentrations. The factor loadings revealed the strength of association between variables and factors, e.g., 0.97 for Zn, 0.83 for Cr, and 0.99 for Co. for ingestion, HQing, was the highest for Fe (between 6.10 × 10 and 2.57 × 10). for inhalation, HQinh, was the biggest for Mn (from 1.41 × 10 to 1.95 × 10). varied in the interval [0.172, 0.573], indicating the absence of a non-carcinogenic risk. However, since values above 0.5 were determined at four sites, continuous monitoring of the pollution in the sampling locations is necessary.

摘要

污染是当前影响全球人口和环境的最重要问题之一。因此,确定应采取严格措施的区域很有必要。在本研究中,主成分分析(PCA)、因子分析(FA)和t分布随机邻域嵌入(t-SNE)被用于对在14个地点收集的包含10种重金属浓度的数据系列进行降维和聚类。利用危害商数(HQ)和危害指数(HI)来确定研究区域内人群的非致癌风险。样品中金属浓度最高的是铁、锌、锰和铬。主成分分析表明,铁和锌(钴和镉)对第一(第二)主成分(PC)的贡献最大。因子分析表明,三因子模型足以解释污染物浓度的变异性。因子载荷揭示了变量与因子之间的关联强度,例如,锌为0.97,铬为0.83,钴为0.99。经口摄入的HQ,即HQing,铁的最高(在6.10×10至2.57×10之间)。经吸入的HQ,即HQinh,锰的最大(从1.41×10至1.95×10)。HI在[0.172, 0.573]区间内变化,表明不存在非致癌风险。然而,由于在四个地点测定的值高于0.5,因此有必要对采样地点的污染情况进行持续监测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fb7/11768440/a8e77a7de98e/toxics-13-00052-g012.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fb7/11768440/27b76c882253/toxics-13-00052-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fb7/11768440/c683b9f2d02e/toxics-13-00052-g003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fb7/11768440/7eba82db124e/toxics-13-00052-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fb7/11768440/2e4f49861985/toxics-13-00052-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fb7/11768440/bf7edd609f96/toxics-13-00052-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fb7/11768440/46e4fdbab603/toxics-13-00052-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fb7/11768440/a178d03826f9/toxics-13-00052-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fb7/11768440/b17780652694/toxics-13-00052-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fb7/11768440/a8e77a7de98e/toxics-13-00052-g012.jpg

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