Assessment of Heavy Metal Contamination in Dust in Vilnius Schools: Source Identification, Pollution Levels, and Potential Health Risks for Children

被引:11
作者
Unsal, Murat Huseyin [1 ]
Ignatavicius, Gytautas [1 ]
Valiulis, Arunas [2 ,3 ]
Prokopciuk, Nina [2 ]
Valskiene, Roberta [4 ]
Valskys, Vaidotas [1 ,5 ]
机构
[1] Vilnius Univ, Inst Biosci, Life Sci Ctr, Sauletekio Ave 7, LT-10257 Vilnius, Lithuania
[2] Vilnius Univ, Inst Clin Med, Med Fac, Clin Childrens Dis, Antakalnio St 57, LT-10207 Vilnius, Lithuania
[3] Vilnius Univ, Inst Hlth Sci, Med Fac, Dept Publ Hlth, M K Ciurlionio St 21, LT-03101 Vilnius, Lithuania
[4] Nat Res Ctr, Lab Ecotoxicol, Akad St 2, LT-08412 Vilnius, Lithuania
[5] Nat Res Ctr, Lab Climate & Water Res, Akad St 2, LT-08412 Vilnius, Lithuania
关键词
dust pollution; trace elements; indoor dust; dust exposure; environmental health risk; particulate matter; risk assessment; urban pollution; elemental analysis; INDOOR DUST; STREET DUST; ROAD DUST; POPULATION-DENSITY; SOILS; ISTANBUL; LEAD; CLASSROOMS; EXPOSURE; ELEMENTS;
D O I
10.3390/toxics12030224
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The main objective of this study is to thoroughly evaluate the diversity and sources of heavy metals in the school environment. Specifically, this study examines the presence of heavy metals in the dust found and collected from 24 schools in Vilnius. Employing hierarchical cluster analysis, principal component analysis, and positive matrix factorization, we identified combustion-related activities as primary contributors to elevated metal concentrations, notably zinc, scandium, and copper, with PM2.5/PM10 ratios indicating a combustion source. They reveal significant differences in the levels of elements such as arsenic (4.55-69.96 mg/kg), copper (51.28-395.37 mg/kg), zinc, and lead, which are affected by both local environmental factors and human activities. Elevated pollution levels were found in certain school environments, indicating environmental degradation. Pollution assessment and specific element pairings' strong positive correlations suggested shared origins or deposition processes. While this study primarily assesses non-carcinogenic risks to children based on a health risk assessment model, it acknowledges the well-documented carcinogenic potential of substances such as lead and arsenic. The research emphasizes the immediate necessity for efficient pollution management in educational environments, as indicated by the elevated hazard index for substances such as lead and arsenic, which present non-carcinogenic risks to children. This research offers important insights into the composition and origins of dust pollution in schools. It also promotes the need for broader geographic sampling and prolonged data collection to improve our understanding of pollution sources, alongside advocating for actionable strategies such as environmental management and policy reforms to effectively reduce exposure risks in educational settings. Furthermore, it aims to develop specific strategies to safeguard the health of students in Vilnius and similar urban areas.
引用
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页数:24
相关论文
共 77 条
[1]   Heavy metals from non-exhaust vehicle emissions in urban and motorway road dusts [J].
Adamiec, Ewa ;
Jarosz-Krzeminska, Elzbieta ;
Wieszala, Robert .
ENVIRONMENTAL MONITORING AND ASSESSMENT, 2016, 188 (06)
[2]   Heavy Metal Contamination (Cu, Pb, Zn, Fe, and Mn) in Urban Dust and its Possible Ecological and Human Health Risk in Mexican Cities [J].
Aguilera, Anahi ;
Cortes, Jose Luis ;
Delgado, Carmen ;
Aguilar, Yameli ;
Aguilar, Daniel ;
Cejudo, Ruben ;
Quintana, Patricia ;
Goguitchaichvili, Avto ;
Bautista, Francisco .
FRONTIERS IN ENVIRONMENTAL SCIENCE, 2022, 10
[3]   Health risk of heavy metals in street dust [J].
Aguilera, Anahi ;
Bautista, Francisco ;
Goguitchaichvili, Avto ;
Garcia-Oliva, Felipe .
FRONTIERS IN BIOSCIENCE-LANDMARK, 2021, 26 (02) :327-345
[4]   Heavy metal distribution in dust, street dust and soils from the work place in Karak Industrial Estate, Jordan [J].
Al-Khashman, OA .
ATMOSPHERIC ENVIRONMENT, 2004, 38 (39) :6803-6812
[5]  
Barbieri M., 2016, Journal of Geology Geophysics, V5, DOI [10.4172/2381-8719.1000237, DOI 10.4172/2381-8719.1000237, DOI 10.4172/2381-8719.100]
[6]   Characteristics and Health Risk Assessment of Mercury Exposure via Indoor and Outdoor Household Dust in Three Iranian Cities [J].
Behrooz, Reza Dahmardeh ;
Tashakor, Mahsa ;
Asvad, Reza ;
Esmaili-Sari, Abbas ;
Kaskaoutis, Dimitris G. .
ATMOSPHERE, 2022, 13 (04)
[7]  
Belyadi H., 2021, Machine Learning Guide for Oil and Gas Using Python, DOI [10.1016/B978-0-12-821929-4.00002-0, DOI 10.1016/B978-0-12-821929-4.00002-0]
[8]   A Practical Green Infrastructure Intervention to Mitigate Air Pollution in a UK School Playground [J].
Bermudez, Maria del Carmen Redondo ;
Chakraborty, Rohit ;
Cameron, Ross W. ;
Inkson, Beverley J. ;
Val Martin, Maria .
SUSTAINABILITY, 2023, 15 (02)
[9]   Improved enrichment factor calculations through principal component analysis: Examples from soils near breccia pipe uranium mines, Arizona, USA [J].
Bern, Carleton R. ;
Walton-Day, Katie ;
Naftz, David L. .
ENVIRONMENTAL POLLUTION, 2019, 248 :90-100
[10]   PCA- and PMF-based methodology for air pollution sources identification and apportionment [J].
Chavent, Marie ;
Guegan, Herve ;
Kuentz, Vanessa ;
Patouille, Brigitte ;
Saracco, Jerome .
ENVIRONMETRICS, 2009, 20 (08) :928-942