Inhalable, elongate mineral particles from lake sediment records trace mining activities in northern Minnesota

Journal of Paleolimnology(2022)

引用 2|浏览0
暂无评分
摘要
Atmospheric deposition of inhalable and respirable airborne particulate matter contributes to lake sediments, providing a mineralogical and chemical record of what was in the air at the time of deposition. A subset of respirable airborne particulate matter referred to as elongate mineral particles (EMPs) are of special interest because of their potential for aggravating or inducing diseases. Dust-generating anthropogenic activities such as mining contribute to the atmospheric load of these particles. Because atmospheric exposure to certain minerals increases the risk of developing the asbestos-related disease mesothelioma, and because of mesothelioma’s long latency period, characterizing EMPs preserved in lake sediments can provide historical insights about what was in the air around mining operations and nearby communities. Sediments from two lakes located in northern Minnesota’s iron mining district, the Mesabi Iron Range, were therefore targeted for retrospective characterization of accumulated particulate matter and other geochemical indicators related to human development. Catchment development, including urban development and mining activities, were clearly visible in geochemical strata early in the twentieth century. Detrital minerals characteristic to local bedrock comprised a baseline of downcore particles, but peak mining periods were characterized by corresponding increases in EMPs likely derived from mining and ore processing facilities. While separating and distinguishing between atmospheric and surface runoff sources is challenging, stratigraphic results from age-dated lake sediment have potential to track fugitive dust fallout from historic iron ore and taconite mining activity and may indicate prevailing atmospheric concentrations of commercial asbestos.
更多
查看译文
关键词
Elongate mineral particles, Mining, Inhalable, Minnesota, Mesothelioma, Lake sediments
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要