Faculty of Physics, University of Rijeka, Radmile Matejčić 2, 51000 Rijeka, Croatia.
Int J Environ Res Public Health. 2024 Jun 13;21(6):768. doi: 10.3390/ijerph21060768.
Metal workshops are workplaces with the substantial production of particulate matter (PM) with high metal content, which poses a significant health risk to workers. The PM produced by different metal processing techniques differs considerably in its elemental composition and size distribution and therefore poses different health risks. In some previous studies, the pollution sources were isolated under controlled conditions, while, in this study, we present a valuable alternative to characterize the pollution sources that can be applied to real working environments. Fine PM was sampled in five units (partially specializing in different techniques) of the same workshop. A total of 53 samples were collected with a temporal resolution of 30 min and 1 h. The mass concentrations were determined gravimetrically, and the elemental analysis, in which the concentrations of 14 elements were determined, was carried out using the X-ray fluorescence technique. Five sources of pollution were identified: background, steel grinding, metal active gas welding, tungsten inert gas welding, and machining. The sources were identified by positive matrix factorization, a statistical method for source apportionment. The identified sources corresponded well with the work activities in the workshop and with the actual sources described in previous studies. It is shown that positive matrix factorization can be a valuable tool for the identification and characterization of indoor sources.
金属车间是颗粒物(PM)大量产生的工作场所,其中含有高浓度的金属,这对工人的健康构成了重大威胁。不同金属加工技术产生的 PM 在元素组成和粒径分布上有很大差异,因此对健康的威胁也不同。在之前的一些研究中,污染来源是在受控条件下被隔离的,而在这项研究中,我们提出了一种有价值的方法来对污染源进行特征描述,这种方法可以应用于实际的工作环境中。在同一家车间的五个单元(部分专门从事不同的技术)中采集了细颗粒物(PM)。总共采集了 53 个样本,时间分辨率为 30 分钟和 1 小时。采用重量法测定质量浓度,采用 X 射线荧光技术测定元素分析,其中测定了 14 种元素的浓度。确定了五个污染源:背景、钢磨、金属活性气体焊接、钨极惰性气体焊接和机械加工。通过正矩阵因子分解(一种用于源分配的统计方法)识别污染源。所识别的来源与车间的工作活动以及之前研究中描述的实际来源非常吻合。结果表明,正矩阵因子分解可以成为识别和描述室内污染源的一种有价值的工具。