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Incorporating hopane degradation into chemical mass balance model: Improving accuracy of vehicular source contribution estimation

机译:将料料劣化掺入化学质量平衡模型:提高车辆源贡献估计的准确性

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摘要

Hopanes are useful molecular markers for tracking airborne fine particulate matter (PM2.5) associated with vehicular exhaust in receptor models. However, they undergo atmospheric degradation. This causes deviations from the underlying assumption of mass conservation in receptor models and leads to biased estimation for source contributions. Little work has been conducted to account for this issue in receptor modelling. In this study, we analyzed the PM2.5 chemical speciation data including C-27-C-31 hopanes from two urban sites in the Pearl River Delta region, China. We developed an approach using ambient-to-source ratio of hopane homologues to show evidence of hopane degradation. Organic carbon (OC) and PM2.5 were then apportioned using the chemical mass balance (CMB) model, with the emphasis on considering hopane degradation. We applied a set of volatility-dependent degradation factors to correct for the loss, and determined the extent of degradation through identifying the statistically optimal CMB solution. The results reveal that neglecting hopane degradation would underestimate the primary vehicular OC and PM2.5 contributions by similar to 55% in warm season and by similar to 35% in cold season in our subtropical study region. The method developed in this work could be used to improve accuracy of vehicular source contribution estimation in other urban locations.
机译:霍帕斯是用于跟踪受体模型中与车辆排气相关的空气传播细颗粒物质(PM2.5)的有用的分子标记。然而,它们发生大气降解。这导致来自受体模型中的大规模保护的潜在假设的偏差,并导致源贡献的偏差估计。已经进行了很少的工作,以解释在受体建模中的这个问题。在这项研究中,我们分析了PM2.5化学品格数据,包括来自中国珠江三角洲地区的两个城市地点的C-27-C-31霍帕。我们开发了一种利用血鹿同源物的环境与源极比的方法,以表明血液脱落的证据。然后使用化学质量平衡(CMB)模型分配有机碳(OC)和PM2.5,重点考虑血液脱落。我们应用了一组波动依赖性的劣化因子来纠正损失,并通过识别统计上最佳的CMB解决方案来确定劣化程度。结果表明,忽视血液损失将低估主要车辆OC和PM2.5的贡献,在温暖季节中的55%,在我们的亚热带研究区域中的寒冷季节相似。本工作中开发的方法可用于提高其他城市地点的车辆源贡献估计的准确性。

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