Use of electron microscopy to determine presence of coal dust in a neighborhood bordering an open-air coal terminal in Curtis Bay, Baltimore, Maryland, USA.

IF 8.2 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES
Science of the Total Environment Pub Date : 2024-12-20 Epub Date: 2024-10-11 DOI:10.1016/j.scitotenv.2024.176842
Matthew A Aubourg, Kenneth J T Livi, Gregory G Sawtell, Carlos C Sanchez-Gonzalez, Nicholas J Spada, Russell R Dickerson, Wen-An Chiou, Conchita Kamanzi, Gurumurthy Ramachandran, Ana M Rule, Christopher D Heaney
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引用次数: 0

Abstract

Background: Despite decreasing US consumption, over 90 million metric tons of coal were exported by the US in 2023, requiring significant infrastructure for transport, handling, and storage of coal at export terminals. Residents in Curtis Bay, Baltimore, Maryland, USA live at the fenceline of an open-air coal terminal and have, for decades, reported rapid accumulation of black dust at their homes. Community-level exposure to coal dust originating from coal handling and storage terminals has remained largely unexplored.

Objectives: To investigate community-identified concerns and use a community-driven approach to determine the presence/absence of coal dust on Curtis Bay surfaces.

Methods: Passive settled dust samples were collected from two residential areas, 345 m and 1235 m from the coal terminal, using conductive carbon tape. Scanning electron microscopy and energy dispersive X-ray spectroscopy (SEM-EDX) of standard reference coal material and positive control material from the coal terminal in Curtis Bay were used to optimize the morphological and elemental classification criteria for coal dust. A manual SEM-EDX protocol was developed to identify coal particles in settled dust collected on conductive carbon tape in community settings.

Results: SEM-EDX analysis confirmed presence of coal dust sampled at both residential locations. Estimated coal dust particle loading at the proximal and distal site were 13.2 and 3.4 coal particles/mm2, respectively. The coal dust particles identified met specific criteria, including size (>5 μm), morphology, and elemental composition (≥75 % carbon, ≤20 % oxygen).

Discussion: These findings are consistent with longstanding community concerns and lived experiences regarding the presence of coal dust in Curtis Bay, which neighbors a major open-air coal terminal. This approach has potential for other communities neighboring coal terminals to assess similar concerns with residential coal dust exposure.

利用电子显微镜确定美国马里兰州巴尔的摩市柯蒂斯湾露天煤炭码头附近居民区是否存在煤尘。
背景:尽管美国的煤炭消费量在不断减少,但到 2023 年,美国的煤炭出口量仍将超过 9000 万吨,这就需要在出口终端建设大量的基础设施,用于运输、处理和储存煤炭。美国马里兰州巴尔的摩市柯蒂斯湾(Curtis Bay)的居民居住在露天煤炭码头的边缘地带,数十年来,他们一直报告说自己家中的黑色粉尘迅速积累。社区对煤炭装卸和储存码头产生的煤尘的接触情况在很大程度上仍未得到研究:调查社区关注的问题,采用社区驱动的方法确定柯蒂斯湾表面是否存在煤尘:方法:使用导电碳带从距离煤炭码头 345 米和 1235 米的两个居民区收集被动沉降的粉尘样本。使用扫描电子显微镜和能量色散 X 射线光谱(SEM-EDX)对标准参考煤炭材料和来自柯蒂斯湾煤炭码头的阳性对照材料进行分析,以优化煤尘的形态和元素分类标准。制定了手动 SEM-EDX 方案,用于识别社区环境中导电碳带上收集的沉降粉尘中的煤炭颗粒:结果:SEM-EDX 分析证实了在两个居民点采样的煤尘的存在。估计近端和远端地点的煤尘颗粒负荷分别为 13.2 和 3.4 煤尘颗粒/平方毫米。确定的煤尘颗粒符合特定标准,包括大小(>5 μm)、形态和元素组成(碳含量≥75%,氧含量≤20%):这些发现与社区长期以来对柯蒂斯湾煤尘存在的担忧和生活经验是一致的,柯蒂斯湾毗邻一个大型露天煤炭码头。这种方法适用于邻近煤炭码头的其他社区,以评估类似的居民煤尘暴露问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Science of the Total Environment
Science of the Total Environment 环境科学-环境科学
CiteScore
17.60
自引率
10.20%
发文量
8726
审稿时长
2.4 months
期刊介绍: The Science of the Total Environment is an international journal dedicated to scientific research on the environment and its interaction with humanity. It covers a wide range of disciplines and seeks to publish innovative, hypothesis-driven, and impactful research that explores the entire environment, including the atmosphere, lithosphere, hydrosphere, biosphere, and anthroposphere. The journal's updated Aims & Scope emphasizes the importance of interdisciplinary environmental research with broad impact. Priority is given to studies that advance fundamental understanding and explore the interconnectedness of multiple environmental spheres. Field studies are preferred, while laboratory experiments must demonstrate significant methodological advancements or mechanistic insights with direct relevance to the environment.
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