In this study, we demonstrate how under certain wind conditions, a mobile surface in situ platform, Truck MObile trace Gas (TMOG) Surveyor, that includes a ceilometer to derive boundary layer height (BL) can derive emissions. Field in situ and airborne thermal infrared imaging spectroscopy data were acquired by the thermal infrared imaging spectrometer, Mako, for three adjacent, central California producing oil fields (Kern River, Kern Front, Poso Creek) on 14 Sept. 2018. Derived methane (CH₄) and carbon dioxide (CO₂) emissions from TMOG data were 46.6 ± 15 Mg dy⁻¹ (17 ± 5.6 Gg yr⁻¹) and 3.12 ± 1.02 Mg dy⁻¹ (1140 ± 230 Gg yr⁻¹), respectively, with about half the CH₄ from near-field point-source plumes and half from a well-mixed far field plume. Uncertainty was 33 % from the Monte Carlo simulations. Mako data confirmed that emissions were in the far field and there were no strong, buoyant plumes. The survey vertically profiled a nearby mountain to measure winds at the boundary layer top and validate BL using in situ data.

The CH₄ to CO₂ emissions ratio for plume matched reservoir composition to better than 10 %. The plume anomaly CH₄ to ethane emissions ratio suggested ethane emissions of around 200 kg dy⁻¹ (74 Mg yr⁻¹). Mako data in 2015 and concurrent data in 2018 confirmed that most emissions were from distant plumes in the Poso Creek and Kern Front fields.

在这项研究中，我们展示了在某些风力条件下，移动表面原位平台、卡车移动痕量气体 (TMOG) 测量员如何获得排放量，该平台包括用于推导边界层高度 ( BL )的云高仪。字段原位和空气的热红外成像光谱数据通过热红外成像光谱仪，真子上9月14日2018年衍生的甲烷（CH获取，对于三个相邻，中央加利福尼亚生产油田（克恩河，克恩前，波索溪）₄ ) 和来自 TMOG 数据的二氧化碳 (CO ₂ ) 排放量为 46.6 ± 15 Mg dy ^-1 (17 ± 5.6 Gg yr ^-1 ) 和 3.12 ± 1.02 Mg dy ^-1 (1140 ± 230 Gg yr^-1 )，分别有大约一半的 CH ₄来自近场点源羽流，一半来自混合良好的远场羽流。Monte Carlo 模拟的不确定性为 33%。Mako 的数据证实，排放物发生在远场，没有强烈的、有浮力的羽流。该调查垂直分析附近的一座山，以测量边界层顶部的风，并使用原位数据验证BL。

羽流的 CH ₄与 CO ₂排放比与储层组成相匹配，优于 10%。羽流异常 CH ₄与乙烷排放量之比表明乙烷排放量约为 200 kg dy ^-1 (74 Mg yr ^-1 )。2015 年的 Mako 数据和 2018 年的同期数据证实，大部分排放来自 Poso Creek 和 Kern Front 油田的远距离羽流。