Epidemiological studies have documented that elevated airborne particulate matter (PM) concentrations, especially those with an aerodynamic diameter less than 10 μm (PM10), are associated with adverse health effects. Two receptor models, UNMIX and positive matrix factorization (PMF), were used to identify and quantify the sources of PM10 concentrations in Tubarão and Capivari de Baixo, Santa Catarina, Brazil. This region is known for its high pollution levels due to intense industrial activity and exploitation of natural resources. PM10 samples were collected using high volume samplers at two sites in the region and statistical exploratory analysis techniques were applied to identify and assess PM10 sources. The two primary PM10 sources were identified as soil re-suspension/road dust emissions and coal burning emissions, contributing 65–75% and 15–25% of the PM10, respectively. The study confirmed the significance of the influence of local PM10 emissions (power plants, soil re-suspension and road dust emissions) on regional air quality, although no violations of the Brazilian PM10 standards (limit of 150 μg/m3) were observed, with a mean concentration of 27.6 μg/m3 measured in this study. This study demonstrated the usefulness of statistical exploratory analysis techniques in assessing the validity of modelling results and contributing to the interpretation of ambient air quality data.

中文翻译：

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图解分析结合受体建模调查巴西圣卡塔琳娜州PM10源

流行病学研究表明，空气中颗粒物 (PM) 浓度升高，尤其是那些空气动力学直径小于 10 微米 (PM10) 的颗粒物，与不利的健康影响有关。使用 UNMIX 和正矩阵分解 (PMF) 这两个受体模型来识别和量化巴西圣卡塔琳娜州 Tubarão 和 Capivari de Baixo 的 PM10 浓度来源。由于密集的工业活动和自然资源的开采，该地区以其高污染水平而闻名。PM10 样本是在该地区的两个地点使用大容量采样器收集的，并应用统计探索性分析技术来识别和评估 PM10 来源。两个主要 PM10 来源被确定为土壤再悬浮/道路扬尘排放和燃煤排放，分别占 PM10 的 65-75% 和 15-25%。该研究证实了当地 PM10 排放（发电厂、土壤再悬浮和道路粉尘排放）对区域空气质量的影响，尽管没有观察到违反巴西 PM10 标准（限制为 150 微克/立方米），与本研究中测得的平均浓度为 27.6 μg/m3。这项研究证明了统计探索性分析技术在评估建模结果的有效性和有助于解释环境空气质量数据方面的有用性。本研究中测得的平均浓度为 27.6 μg/m3。这项研究证明了统计探索性分析技术在评估建模结果的有效性和有助于解释环境空气质量数据方面的有用性。本研究中测得的平均浓度为 27.6 μg/m3。这项研究证明了统计探索性分析技术在评估建模结果的有效性和有助于解释环境空气质量数据方面的有用性。