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首页> 外文期刊>Atmospheric Measurement Techniques >Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: systematic intercomparison of calibration methods for US measurement network samples
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Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: systematic intercomparison of calibration methods for US measurement network samples

机译:红外光谱法中大气气溶胶官能团的分析:对我们测量网络样本的校准方法的系统互相

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Peak fitting (PF) and partial least squares (PLS) regression have been independently developed for estimation of functional groups (FGs) from Fourier transform infrared (FTIR) spectra of ambient aerosol collected on Teflon filters. PF is a model that quantifies the functional group composition of the ambient samples by fitting individual Gaussian line shapes to the aerosol spectra. PLS is a data-driven, statistical model calibrated to laboratory standards of relevant compounds and then extrapolated to ambient spectra. In this work, we compare the FG quantification using the most widely used implementations of PF and PLS, including their model parameters, and also perform a comparison when the underlying laboratory standards and spectral processing are harmonized. We evaluate the quantification of organic FGs (alcohol COH, carboxylic COOH, alkane CH, carbonyl CO) and ammonium, using external measurements (organic carbon (OC) measured by thermal optical reflectance (TOR) and ammonium by balance of sulfate and nitrate measured by ion chromatography). We evaluate our predictions using 794 samples collected in the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network (USA) in 2011 and 238 laboratory standards from Ruthenburg et al. (2014) (available at https://doi. org/10.1016/j.atmosenv.2013.12.034). Each model shows different biases. Overall, estimates of OC by FTIR show high correlation with TOR OC. However, PLS applied to unprocessed (raw spectra) appears to underpredict oxygenated functional groups in rural samples, while other models appear to underestimate aliphatic CH bonds and OC in urban samples. It is possible to adjust model parameters (absorption coefficients for PF and number of latent variables for PLS) within limits consistent with calibration data to reduce these biases, but this analysis reveals that further progress in parameter selection is required. In addition, we find that the influence of scattering and anomalous transmittance of infrared in coarse particle samples can lead to predictions of OC by FTIR which are inconsistent with TOR OC. We also find through several means that most of the quantified carbonyl is likely associated with carboxylic groups rather than ketones or esters. In evaluating state-of-the-art methods for FG abundance by FTIR, we suggest directions for future research.
机译:峰值配合(PF)和局部最小二乘(PLS)回归被独立开发用于估计来自在Teflon过滤器上收集的环境气溶胶的傅里叶变换红外(FTIR)光谱的官能团(FGS)。 PF是一种模型,通过将单独的高斯线形状拟合到气溶胶光谱来定量环境样本的功能组组成。 PLS是一种数据驱动的统计模型,校准相关化合物的实验室标准,然后推断为环境光谱。在这项工作中,我们使用PF和PL的最广泛使用的实现的FG量化,包括其模型参数,并且在统一的实验室标准和谱处理协调时,还执行比较。我们使用外部测量(通过通过硫酸盐平衡测量的热光学反射(TOR)测量的有机碳(OC)来评估有机FGS(醇COH,羧基,烷烃CH,羰基CO)和铵的定量(有机碳(OC)和通过硫酸盐的平衡测量离子色谱法)。我们在2011年和来自Ruthenburg等人的受保护视觉环境(改进)网络(USA)的间际监测中收集的794个样本中收集的794个样本评估了我们的预测。 (2014)(可在https:// doi提供.ORG / 10.1016 / J.ATMOSEV.2013.12.034)。每个模型都显示出不同的偏差。总体而言,FTIR的OC估计显示与TOR OC的高相关。然而,将应用于未加工的(原始光谱)的PLS出现在农村样本中的未氧化官能团,而其他模型似乎低估了城市样本中的脂族CH键和OC。可以在与校准数据一致的范围内调整模型参数(用于PF的吸收系数和PLS的潜在变量的数量),以减少这些偏差,但该分析显示需要参数选择的进一步进展。此外,我们发现红外线在粗颗粒样品中的散射和异常透射率的影响可以通过FTIR导致OC的预测,其与TOR OC不一致。我们还通过几种方法发现,大多数量化的羰基可能与羧基或酮或酯相关。通过FTIR评估FG丰富的最先进的方法,我们建议未来研究的指示。

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