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Evaluation of factors influencing secondary organic carbon (SOC) estimation by CO and EC tracer methods

机译:影响CO和EC示踪方法影响二次有机碳(SOC)估计因素的评价

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摘要

Secondary organic carbon (SOC) is known to account for a substantial fraction of fine-mode carbonaceous aerosol. Owing to a limited understanding of SOC formation processes and the absence of direct measurement methods, SOC concentrations are mostly estimated using a tracer-based method utilizing either elemental carbon (EC) or carbon monoxide (CO) as tracers. The performance of these tracer-based methods depends heavily on accurate determination of the (OC/Tracer)(pri) value. The minimum R squared (MRS) method is currently recognized as a relatively reasonable tool to determine (OC/Tracer)(pri). This study estimated SOC based on the MRS method with EC and CO as tracers, followed by the Monte Carlo method to analyze quantitatively the effects of measurement uncertainty, emission scenario and sample size on SOC estimates. We report here four major findings: i) the concentration of O-3 was used as an indicator to atmospheric secondary reaction potential, and it was found that the mass proportion of SOC in total OC estimated by CO as the tracer is more consistent with the seasonality of actual secondary reaction potential; ii) the estimation results are highly sensitive to the measurement uncertainty in different emission scenarios, which leads us to conclude that the CO tracer method is more robust than the EC tracer method due to large inherent uncertainties in current EC measurements; iii) oversimplification of emission scenarios has substantial impacts on the estimated SOC value, and careful evaluation of the interdependence between sources should be performed to minimize this bias; and iv) the estimation bias of SOC can be reduced by increasing the sample size, and the tracer method can be expected to generate robust results for sample sizes over 1000. These findings are important in terms of providing a reference to choose appropriate tracers, emission scenarios and sample sizes for robust estimation of SOC in future studies. (C) 2019 Published by Elsevier B.V.
机译:已知二次有机碳(SoC)考虑了大部分微型碳质气溶胶。由于对SoC形成过程的有限理解和没有直接测量方法,使用基于基于型碳(EC)或一氧化碳(CO)作为示踪剂的基于基于碳(EC)或一氧化碳的方法,主要估计SOC浓度。这些基于示踪剂的方法的性能很大程度上取决于(OC /示踪)(PRI)值的准确确定。最小R平方(MRS)方法目前被识别为确定(OC / TRACER)(PRI)的相对合理的工具。本研究基于MRS方法对EC和CO作为示踪剂的方法来估计SOC,其次是蒙特卡罗方法,以定量分析测量不确定性,发射场景和SOC估计上的样本量的影响。我们在此报告四个主要发现:i)O-3的浓度被用作大气二次反应潜力的指标,并发现由CO作为示踪剂估计的SOC的质量比例与示踪剂更符合实际二次反应潜力的季节性; ii)估计结果对不同发射场景中的测量不确定性非常敏感,这导致我们得出结论,由于当前EC测量中的大固有不确定性,CO跟踪方法比EC示踪方法更稳健; iii)发射情景的过度简化对估计的SoC价值影响大幅影响,应仔细评估来源之间的相互依存,以尽量减少这种偏见;并且IV)通过增加样本大小可以减少SOC的估计偏压,并且可以预期示踪方法可以在1000上产生对样本尺寸的鲁棒结果。这些发现在提供了选择合适的示踪剂,发射的参考方面是重要的在未来的研究中,SOC的强大估计的情景和示例尺寸。 (c)2019年由elestvier b.v发布。

著录项

  • 来源
    《The Science of the Total Environment》 |2019年第10期|915-930|共16页
  • 作者单位

    Sun Yat Sen Univ Sch Atmospher Sci Guangzhou 510275 Guangdong Peoples R China;

    Indian Inst Sci Educ & Res IISER Kolkata Dept Earth Sci Nadia 741246 W Bengal India|Indian Inst Sci Educ & Res IISER Kolkata Ctr Climate & Environm Studies Nadia 741246 W Bengal India;

    Jinan Univ Inst Environm & Climate Res Guangzhou 510632 Guangdong Peoples R China;

    Guangzhou Environm Monitoring Ctr Guangzhou 510030 Guangdong Peoples R China;

    Jinan Univ Inst Environm & Climate Res Guangzhou 510632 Guangdong Peoples R China;

    Natl Univ Singapore Dept Chem & Biomol Engn Singapore 117576 Singapore;

    China Univ Min & Technol Sch Safety Engn Xuzhou 221000 Jiangsu Peoples R China;

    Sun Yat Sen Univ Sch Atmospher Sci Guangzhou 510275 Guangdong Peoples R China|Sun Yat Sen Univ Guangdong Prov Key Lab Climate Change & Nat Disas Guangzhou 510275 Guangdong Peoples R China|Indian Inst Sci Educ & Res IISER Kolkata Dept Earth Sci Nadia 741246 W Bengal India;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Secondary organic carbon; Organic carbon; Elemental carbon; Carbon monoxide; Minimum R squared (MRS) method; Monte Carlo simulation;

    机译:二次有机碳;有机碳;元素碳;一氧化碳;最小R平方(MRS)方法;蒙特卡罗模拟;

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