Assessing urban methane emissions using column-observing portable Fourier transform infrared (FTIR) spectrometers and a novel Bayesian inversion framework
Assessing urban methane emissions using column-observing portable Fourier transform infrared (FTIR) spectrometers and a novel Bayesian inversion framework
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DOI：
10.5194/acp-21-13131-2021
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发表时间：
2021-09-06
影响因子：
6.3
通讯作者：
Wofsy, Steven C.
中科院分区：
文献类型：
--
作者：
Jones, Taylor S.;Franklin, Jonathan E.;Wofsy, Steven C.
城市代表了包括甲烷在内的全球温室气体排放的很大一部分。对城市地区的甲烷排放量进行量化是很困难的，而且采用自下而上的核算方法编制的清单往往与通过大气观测得出的自上而下的估算大相径庭。天然气基础设施泄漏产生的排放很难预测，因此自下而上的库存限制很差。天然气基础设施的泄漏和最终用途的排放可能会扩散到整个城市，这种扩散源可能占城市总排放量的很大一部分。在2016年5月的一次实地调查中，我们调查了美国印第安纳波利斯市的弥漫性甲烷排放。一个由五台便携式太阳跟踪傅立叶变换红外光谱仪组成的网络被部署在整个城市。这些仪器测量整个空气柱中甲烷的摩尔分数，使它们比地面的原位传感器对城市更大的区域更敏感。我们提出了一种创新的反演方法，将这些总色谱柱浓度与表面通量联系起来。该方法结合拉格朗日输运模型和贝叶斯反演框架来估计地表排放及其不确定性，同时确定流入城市的空气中甲烷的浓度。在一个典型的日子里，在流入空气中观察到超过10 ppb的变化，这比由于城市排放（城市下风< 5 ppb）造成的增强稍大。我们发现弥漫的甲烷排放量为73(+/- 22)mol(-1)，约占城市总量的50%，比自下而上方法估计的高68%，尽管它比利用塔台和飞机观测的研究估计的要小一些。这里开发的测量和模型技术解决了量化城市温室气体排放时面临的许多挑战，并将有助于设计其他城市的未来测量方案。
Cities represent a large and concentrated portion of global greenhouse gas emissions, including methane. Quantifying methane emissions from urban areas is difficult, and inventories made using bottom-up accounting methods often differ greatly from top-down estimates generated from atmospheric observations. Emissions from leaks in natural gas infrastructure are difficult to predict and are therefore poorly constrained in bottom-up inventories. Natural gas infrastructure leaks and emissions from end uses can be spread throughout the city, and this diffuse source can represent a significant fraction of a city's total emissions.We investigated diffuse methane emissions of the city of Indianapolis, USA, during a field campaign in May 2016. A network of five portable solar-tracking Fourier transform infrared (FTIR) spectrometers was deployed throughout the city. These instruments measure the mole fraction of methane in a total column of air, giving them sensitivity to larger areas of the city than in situ sensors at the surface.We present an innovative inversion method to link these total column concentrations to surface fluxes. This method combines a Lagrangian transport model with a Bayesian inversion framework to estimate surface emissions and their uncertainties, together with determining the concentrations of methane in the air flowing into the city. Variations exceeding 10 ppb were observed in the inflowing air on a typical day, which is somewhat larger than the enhancements due to urban emissions (< 5 ppb downwind of the city). We found diffuse methane emissions of 73(+/- 22) mols(-1), which is about 50% of the urban total and 68% higher than estimated from bottom-up methods, although it is somewhat smaller than estimates from studies using tower and aircraft observations. The measurement and model techniques developed here address many of the challenges present when quantifying urban greenhouse gas emissions and will help in the design of future measurement schemes in other cities.