Near-field atmospheric inversions for the localization and quantification of controlled methane releases using stationary and mobile measurements

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY(2022)

引用 8|浏览9
暂无评分
摘要
This study evaluates two local-scale atmospheric inversion approaches for the monitoring of methane (CH4) emissions from industrial sites based on in situ atmospheric CH4 mole fraction measurements from stationary or mobile sensors. We participated in a two-week campaign of CH4 controlled-release experiments at TotalEnergies Anomaly Detection Initiatives (TADI) in Lacq, France in October 2019. We analyzed releases from various points within a 40 m x 50 m area with constant rates of 0.16 to 30 g CH4 s(-1) over 25 to 75 mins, using fixed-point and mobile measurements, and testing different inversion configurations with a Gaussian dispersion model. An inlet switching system, combining a limited number (6-7) of high-precision gas analyzers with a higher number (16) of sampling lines, ensured that a sufficient number of fixed measurement points sampled the plume downwind of the sources and the background mole fractions for any wind direction. The inversions using these fixed-point measurements provide release rate estimates with approximately 23%-30% average errors and estimates of the location of the releases with approximately 8-10 m average errors. The inversions using the mobile measurements provide estimates with approximately 20%-30% average errors for the release rates and approximately 30 m average errors for the release locations. The precision of the release rate estimates from both inversion frameworks corresponds to the best estimation precision documented on site-scale CH4 inversions. However, the use of continuous measurements from fixed stations provides much more robust estimates of the source locations than that of the mobile measurements.
更多
查看译文
关键词
atmospheric inversion, controlled CH4 release experiments, facility-scale methane emission, source term estimation, stationary and mobile measurements
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要