Department of Electrical Engineering, Mathematics and Science, Faculty of Engineering and Sustainable Development, University of Gävle, Gavle, Sweden.
Department of Building Engineering, Energy Systems and Sustainability Science, Faculty of Engineering and Sustainable Development, University of Gävle, Gavle, Sweden.
Environ Monit Assess. 2021 Apr 8;193(5):251. doi: 10.1007/s10661-021-09033-x.
Field calibrations of NO, NO, and PM from AQMesh Air Quality Monitors (AQMs) were conducted during a summer and an autumn period in a busy street in a midsize Swedish city. All the three linear calibration procedures studied (postscaled, bisquare, and orthogonal data) significantly reduced the ranges and magnitudes of the performance indicators to yield more reliable results than the raw data. The improvements were sufficient to satisfy the European Union (EU) Data Quality Objective (DQO) for indicative measurements as compared to reference data only for NO (above 50 µg m) and NO (above 30 µg m) during the autumn calibration period. The relatively simple bisquare procedure had the best performance overall. The bisquare procedure improved the root mean square error by the same amount as other studies using complex multivariate calibration methods. Low concentrations of pollutants were measured, far below the EU Environmental Quality Standard thresholds and even satisfying the future goals for the Environmental Quality Objectives. Cleaning the raw data by removing data points in the reference data that were below the reference station limit of detections (and the synchronous data points in the AQM prescaled data) was found to improve the performances of the calibration procedures appreciably. Many NO and almost all PM data points in this study fell below the AQM limit of detection. These low concentrations will probably be a common problem in many field studies, at least in areas with relatively low air pollution. However, the relative errors were sufficiently low for these data points that they could be interpreted as accurately representing low concentrations and did not need to be removed from the datasets. For the NO measurements, a slight periodic error correlated with sunlight and increased ambient temperature was noted. NO measurements correlated strongly with increased traffic.
在瑞典一个中等城市繁忙街道的夏季和秋季期间，对 AQMesh 空气质量监测器（AQM）的 NO、NO 和 PM 进行了现场校准。所研究的所有三种线性校准程序（后缩放、双平方和正交数据）都显著缩小了性能指标的范围和幅度，从而产生了比原始数据更可靠的结果。与仅使用参考数据相比，在秋季校准期间，改进足以满足欧盟（EU）数据质量目标（DQO）对于指示性测量的要求，仅对于 NO（高于 50μg/m）和 NO（高于 30μg/m）是如此。相对简单的双平方程序总体上表现最佳。双平方程序将均方根误差提高了与其他使用复杂多元校准方法的研究相同的量。测量到的污染物浓度较低，远低于欧盟环境质量标准阈值，甚至满足未来环境质量目标的目标。通过从参考数据中删除低于参考站检测限（以及 AQM 预缩放数据中的同步数据点）的数据点来清洁原始数据，发现可以显著提高校准程序的性能。本研究中的许多 NO 和几乎所有 PM 数据点都低于 AQM 的检测限。这些低浓度在许多现场研究中可能是一个常见问题，至少在空气污染相对较低的地区是如此。然而，这些数据点的相对误差足够低，以至于可以将其解释为准确代表低浓度，并且不需要从数据集。对于 NO 测量，注意到与阳光和环境温度升高相关的轻微周期性误差。NO 测量与交通量增加密切相关。
