State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China.
State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China.
Environ Int. 2022 Jul;165:107330. doi: 10.1016/j.envint.2022.107330. Epub 2022 May 31.
Highly time-resolved data for volatile organic compounds (VOCs) can now be monitored. Source analyses of such high time-resolved concentrations provides key information for controlling VOC emissions. This work reviewed the literature on VOCs source analyses published from 2015 to 2021, and assesses the state-of-the-art and the existing issues with these studies. Gas chromatography system and direct-inlet mass spectrometry are the main monitoring tools. Quality control (QC) of the monitoring process is critical prior to analysis. QC includes inspection and replacement of instrument consumables, calibration curve corrections, and reviewing the data. Approximately 54% published papers lacked details on the quantitative evaluation of the effectiveness of QC measures. Among the reviewed works, the number of monitored species varied from 5 to 119, and fraction of papers with more than 90 monitored species increased yearly. US EPA PMF v5.0 was the most commonly used (∼86%) for VOC source analyses. However, conventional source apportionment directly uses the measured VOCs and may be problematic given the impacts of dispersion and photochemical losses, uncertainty setting of VOCs data, factor resolution, and factor identification. Excluding species with high-reactivity or estimation of corrected concentrations were often applied to reduce the influence of photochemical reactions on the results. However, most reports did not specify the selection criteria or the specific error fraction values in the uncertainty estimation. Model diagnostic indexes were used in 99% of the reports for PMF analysis to determine the factor resolution. Due to lack of known local source profiles, factor identification was mainly achieved using marker species and characteristic species ratios. However, multiple sources had high-collinearity and the same species were often used to identify different sources. Vehicle emissions and fuel evaporation were the primary contributors to VOCs around the world. Contribution of coal combustion in China was substantially higher than in other countries.
现在可以监测挥发性有机化合物 (VOC) 的高时间分辨率数据。对这种高时间分辨率浓度的源分析提供了控制 VOC 排放的关键信息。这项工作回顾了 2015 年至 2021 年发表的关于 VOC 源分析的文献，并评估了这些研究的最新进展和存在的问题。气相色谱系统和直接进样质谱是主要的监测工具。在分析之前，监测过程的质量控制 (QC) 至关重要。QC 包括检查和更换仪器消耗品、校准曲线校正以及审查数据。大约 54%发表的论文缺乏对 QC 措施有效性进行定量评估的详细信息。在所审查的工作中，监测物种的数量从 5 到 119 不等，每年监测物种数量超过 90 种的论文数量都在增加。美国环保署 PMF v5.0 是用于 VOC 源分析的最常用的方法（约 86%）。然而，传统的源分配直接使用测量的 VOC，由于扩散和光化学反应损失的影响、VOC 数据的不确定性设置、因子分辨率和因子识别等问题，可能会出现问题。通常会应用排除高反应性的物种或估计校正浓度的方法来减少光化学反应对结果的影响。然而，大多数报告并未指定不确定性估计中的选择标准或特定的错误分数值。99%的报告都使用模型诊断指标来进行 PMF 分析，以确定因子分辨率。由于缺乏已知的本地源谱，因子识别主要是使用标记物种和特征物种比来实现的。然而，多个源具有高度共线性，并且经常使用相同的物种来识别不同的源。车辆排放和燃料蒸发是全球 VOC 的主要来源。在中国，煤炭燃烧的贡献大大高于其他国家。
