Abstract. The portable microAeth® MA200 (MA200) is widely applied for measuring black carbon (BC) in human exposure characterization and mobile air quality monitoring. However, the field lacks information about this instrument's performance under various settings. This study evaluated the real-time performance of the MA200 in an urban area, Augsburg, Germany. Noise reduction and negative value mitigation were explored using different data processing methods: local polynomial regression (LPR), optimized noise reduction averaging (ONA), and centered moving average (CMA) under different interval time (5 s, 10 s, and 30 s). After noise reduction, the data were evaluated and compared by (1) the relative number of negative values; (2) more detailed microenvironmental change information retained after noise reduction; (3) the reduction of the peak values and number of peak samples; (4) more detailed microenvironmental change retained after the background correction. Our results showed that CMA showed a good prospect to analyze the raw BC concentration data in terms of the interval time due to its proportions of negative values and the detail microenvironmental change. Moreover, the CMA method has the highest reduction peak values and the number of peak samples compared to ONA and LPR. Furthermore, after background correction, the CMA treatment results remained more detailed microenvironmental changes in pollutants than others. Therefore, based on a comprehensive comparison, CMA offered a good approach to post-process the raw BC concentration data. These findings provide new insight for the noise reduction approach that applied in mobile monitoring campaign using BC instruments.

中文翻译：

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分析来自microAeth®MA200的移动监控数据，以测量奥格斯堡路边的黑碳变化

摘要。便携式microAeth®MA200（MA200）广泛用于人体暴露特征和移动空气质量监测中的黑碳（BC）测量。但是，该领域缺乏有关该仪器在各种设置下的性能的信息。这项研究评估了MA200在德国奥格斯堡市区的实时性能。使用不同的数据处理方法探索了降噪和负值缓解：局部多项式回归（LPR），优化的降噪平均值（ONA）和不同间隔时间（5 s，10 s和30 s）的中心移动平均值（CMA） ）。降噪后，通过（1）负值的相对数量对数据进行评估和比较；（2）降噪后保留更详细的微环境变化信息；（3）减少峰值和减少峰值样本；（4）在进行背景校正后保留了更详细的微环境变化。我们的结果表明，由于CMA的负值比例和详细的微环境变化，因此根据间隔时间来分析原始BC浓度数据具有良好的前景。此外，与ONA和LPR相比，CMA方法具有最高的还原峰值和峰样本数。此外，经过背景校正后，CMA处理结果仍然比其他污染物更详细地反映了污染物的微环境变化。因此，基于全面的比较，CMA提供了一种对原始BC浓度数据进行后处理的好方法。