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Potential toxic trace element (PTE) contamination in Baoji urban soil (NW China): spatial distribution, mobility behavior, and health risk.宝鸡市城区土壤中潜在有毒微量元素(PTE)污染:空间分布、迁移行为及健康风险。
Environ Sci Pollut Res Int. 2017 Aug;24(24):19749-19766. doi: 10.1007/s11356-017-9526-z. Epub 2017 Jul 6.
3
Pollution characteristics and risk assessment of human exposure to oral bioaccessibility of heavy metals via urban street dusts from different functional areas in Chengdu, China.中国成都不同功能区城市街道灰尘中经口腔生物有效性摄取的重金属的污染特征及人体暴露风险评估。
Sci Total Environ. 2017 May 15;586:1076-1084. doi: 10.1016/j.scitotenv.2017.02.092. Epub 2017 Feb 22.
4
Contamination and health risks of heavy metals in street dust from a coal-mining city in eastern China.中国东部某煤矿城市街道灰尘中重金属的污染及健康风险
Ecotoxicol Environ Saf. 2017 Apr;138:83-91. doi: 10.1016/j.ecoenv.2016.11.003. Epub 2016 Dec 22.
5
Profiles of lead in urban dust and the effect of the distance to multi-industry in an old heavy industry city in China.中国一个老重工业城市城市灰尘中铅的分布特征及其与多行业距离的影响。
Ecotoxicol Environ Saf. 2017 Mar;137:281-287. doi: 10.1016/j.ecoenv.2016.11.031. Epub 2016 Dec 19.
6
Long-term Geochemical Evolution of Lithogenic Versus Anthropogenic Distribution of Macro and Trace Elements in Household Attic Dust.家庭阁楼灰尘中生源与人为源的常量和微量元素的长期地球化学演化
Arch Environ Contam Toxicol. 2017 Jan;72(1):88-107. doi: 10.1007/s00244-016-0336-y. Epub 2016 Nov 29.
7
Health risk implications of potentially toxic metals in street dust and surface soil of Tehran, Iran.伊朗德黑兰街道灰尘和表层土壤中潜在有毒金属对健康的风险影响
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8
Geochemical investigation of potentially harmful elements in household dust from a mercury-contaminated site, the town of Idrija (Slovenia).对斯洛文尼亚伊德里亚镇一个汞污染场地的家庭灰尘中潜在有害元素的地球化学调查。
Environ Geochem Health. 2017 Jun;39(3):443-465. doi: 10.1007/s10653-016-9819-z. Epub 2016 Apr 7.
9
A comparison of metal distribution in surface dust and soil among super city, town, and rural area.超级城市、城镇和农村地区地表灰尘与土壤中金属分布的比较。
Environ Sci Pollut Res Int. 2016 Apr;23(8):7849-60. doi: 10.1007/s11356-015-5911-7. Epub 2016 Jan 13.
10
Spatial and temporal variations of trace element distribution in soils and street dust of an industrial town in NW Spain: 15years of study.西班牙西北部一工业城镇土壤和街道尘埃中微量元素分布的时空变化:15 年的研究。
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两种间接测量大气降尘方法的比较:基于高光谱图像数据的街道尘埃成分和植被健康状况。

Comparison of two methods for indirect measurement of atmospheric dust deposition: Street-dust composition and vegetation-health status derived from hyperspectral image data.

机构信息

Geological Survey of Slovenia, Dimičeva ulica 14, 1000, Ljubljana, Slovenia.

Czech Geological Survey, Klárov 3, Prague 1, 118 21, Czech Republic.

出版信息

Ambio. 2019 Apr;48(4):423-435. doi: 10.1007/s13280-018-1093-0. Epub 2018 Aug 25.

DOI:10.1007/s13280-018-1093-0
PMID:30145733
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6411812/
Abstract

This study presents a statistical comparison between the in situ measurements of the elemental composition of street dust and a forest health status classification derived from aerial hyperspectral image data (HyMap). Combining these two methods allowed us to indirectly pinpoint at a high spatial resolution the atmospheric dust emissions and its effects in a study area around the open-pit lignite mine in Sokolov, Czech Republic. The results reveal a statistically significant relationship between increased Al, Na, Li and Sr levels in street dust and decreased forest health status, and the highest number of statistically significant correlations within a 100 m distance from the street-dust sampling points. Differences in lithological composition were unable to sufficiently explain these changes, therefore anthropogenic factors like dust emissions from coal mining and coal combustion, as well as urbanisation and other industries might be the reason for this link. Such studies are a crucial step in developing new high spatial resolution methods for determining atmospheric dust deposition and their effects.

摘要

本研究对街道灰尘元素组成的原位测量值与航空高光谱图像数据(HyMap)得出的森林健康状况分类进行了统计比较。这两种方法的结合使我们能够以高空间分辨率间接确定捷克索科洛夫露天褐煤矿周围研究区域的大气灰尘排放及其影响。结果表明,街道灰尘中 Al、Na、Li 和 Sr 水平的升高与森林健康状况的降低之间存在统计学上的显著关系,在距离街道灰尘采样点 100 米范围内,存在的统计学上显著相关的数量最多。岩性组成的差异无法充分解释这些变化,因此,人为因素如采煤和煤燃烧产生的灰尘排放,以及城市化和其他工业可能是造成这种联系的原因。此类研究是开发用于确定大气灰尘沉积及其影响的新的高空间分辨率方法的关键步骤。