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An uncertainty-based protocol for the setup and measurement of soot–black carbon emissions from gas flares using sky-LOSA
Atmospheric Measurement Techniques ( IF 3.2 ) Pub Date : 2021-02-26 , DOI: 10.5194/amt-14-1573-2021 Bradley M. Conrad , Matthew R. Johnson
Atmospheric Measurement Techniques ( IF 3.2 ) Pub Date : 2021-02-26 , DOI: 10.5194/amt-14-1573-2021 Bradley M. Conrad , Matthew R. Johnson
Gas flaring is an important source of atmospheric
soot–black carbon, especially in sensitive Arctic regions. However,
emissions have traditionally been challenging to measure and remain poorly
characterized, confounding international reporting requirements and adding
uncertainty to climate models. The sky-LOSA optical measurement technique
has emerged as a powerful means to quantify flare black carbon emissions in
the field, but broader adoption has been hampered by the complexity of its
deployment, where decisions during setup in the field can have profound,
non-linear impacts on achievable measurement uncertainties. To address this
challenge, this paper presents a prescriptive measurement protocol and
associated open-source software tool that simplify acquisition of sky-LOSA
data in the field. Leveraging a comprehensive Monte Carlo-based general
uncertainty analysis (GUA) to predict measurement uncertainties over the
entire breadth of possible measurement conditions, general heuristics are
identified to guide a sky-LOSA user toward optimal data collection. These
are further extended in the open-source software utility, SetupSkyLOSA, which interprets
the GUA results to provide detailed guidance for any specific combination of
location, date–time, and flare, plume, and ambient conditions. Finally, a
case study of a sky-LOSA measurement at an oil and gas facility in Mexico is
used to demonstrate the utility of the software tool, where potentially
small regions of optimal instrument setup are easily and quickly
identified. It is hoped that this work will help increase the accessibility
of the sky-LOSA technique and ultimately the availability of field
measurement data for flare black carbon emissions.
中文翻译:
基于不确定性的协议,使用天空-LOSA设置和测量火炬烟尘黑碳排放量
气体燃烧是大气中烟尘黑碳的重要来源,尤其是在北极地区。但是,传统上,排放量一直难以测量,而且表征仍然很差,这混淆了国际报告要求,并增加了气候模型的不确定性。天空-LOSA光学测量技术已成为量化现场火炬黑碳排放的有力手段,但由于其部署的复杂性而阻碍了更广泛的应用,因为现场部署过程中的决策可能具有深远的非线性对可实现的测量不确定度的影响。为了解决这一挑战,本文提出了一种规范性的测量协议和相关的开源软件工具,该工具简化了现场对空中LOSA数据的获取。利用基于蒙特卡洛的全面综合一般不确定性分析(GUA)来预测整个可能的测量条件范围内的测量不确定性,可以识别一般启发式方法,以指导空中LOSA用户朝着最佳数据收集的方向发展。这些在开源软件实用程序SetupSkyLOSA中得到了进一步扩展,该实用程序可解释GUA结果,从而为位置,日期时间,耀斑,羽流和周围环境的任何特定组合提供详细的指导。最后,通过对墨西哥一家石油和天然气设施的空中LOSA测量进行案例研究,以展示该软件工具的实用性,在该工具中,可以轻松,快速地确定最佳仪器设置的潜在小区域。
更新日期:2021-02-26
中文翻译:
基于不确定性的协议,使用天空-LOSA设置和测量火炬烟尘黑碳排放量
气体燃烧是大气中烟尘黑碳的重要来源,尤其是在北极地区。但是,传统上,排放量一直难以测量,而且表征仍然很差,这混淆了国际报告要求,并增加了气候模型的不确定性。天空-LOSA光学测量技术已成为量化现场火炬黑碳排放的有力手段,但由于其部署的复杂性而阻碍了更广泛的应用,因为现场部署过程中的决策可能具有深远的非线性对可实现的测量不确定度的影响。为了解决这一挑战,本文提出了一种规范性的测量协议和相关的开源软件工具,该工具简化了现场对空中LOSA数据的获取。利用基于蒙特卡洛的全面综合一般不确定性分析(GUA)来预测整个可能的测量条件范围内的测量不确定性,可以识别一般启发式方法,以指导空中LOSA用户朝着最佳数据收集的方向发展。这些在开源软件实用程序SetupSkyLOSA中得到了进一步扩展,该实用程序可解释GUA结果,从而为位置,日期时间,耀斑,羽流和周围环境的任何特定组合提供详细的指导。最后,通过对墨西哥一家石油和天然气设施的空中LOSA测量进行案例研究,以展示该软件工具的实用性,在该工具中,可以轻松,快速地确定最佳仪器设置的潜在小区域。