Abstract Recent research has used mobile methane (CH4) measurements to identify and quantify emissions, but the effect of instrument response time on concentration measurements is rarely considered. Furthermore, stable isotope ratios are increasingly used in mobile measurements to attribute sources, but the precision of mobile isotopic measurements depend on a combination of instrument and measurement conditions. Here we tested the effect of instrument speed on concentration measurements by outfitting a vehicle with isotopic and concentration-only gas analysers with different response times and conducting multiple mobile surveys. Additionally, we performed a sensitivity analysis for the isotopic precision achievable under different conditions by programming a physical model, validated with empirical data from our mobile surveys. We found that slower response time led to a greater underestimation of measured CH4 concentration, during both driving and stationary measurements, while the area under peaks in concentration is consistent and provides a robust means of comparing data between instruments. We also explore the use of an algorithm to improve instrument response. Our sensitivity analysis showed that the precision of isotopic measurements increases with the concentration range and the duration of the measurement following a power law. Our findings have important implications for the reporting and comparability of results between surveys with different instrumental setups and provide a framework for optimising sampling strategies under given objectives, conditions, and instrument capabilities.

中文翻译：

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移动式甲烷测量：仪器规格对数据解释、再现性和同位素精度的影响

摘要 最近的研究使用移动甲烷 (CH4) 测量来识别和量化排放，但很少考虑仪器响应时间对浓度测量的影响。此外，在移动测量中越来越多地使用稳定同位素比来归因源，但移动同位素测量的精度取决于仪器和测量条件的组合。在这里，我们通过为车辆配备具有不同响应时间的同位素和仅浓度气体分析仪并进行多次移动调查来测试仪器速度对浓度测量的影响。此外，我们通过对物理模型进行编程，对不同条件下可实现的同位素精度进行了敏感性分析，并通过我们的移动调查的经验数据进行了验证。我们发现，在行驶和静止测量期间，较慢的响应时间导致对测量的 CH4 浓度的更大低估，而浓度峰值下的面积是一致的，并提供了比较仪器之间数据的可靠方法。我们还探索了使用算法来改善仪器响应。我们的敏感性分析表明，同位素测量的精度随着浓度范围和测量持续时间的增加而增加，遵循幂律。我们的发现对不同仪器设置的调查之间结果的报告和可比性具有重要意义，并提供了一个框架，用于在给定的目标、条件和仪器能力下优化抽样策略。