Exploration of the impact of nearby sources on urban atmospheric inversions using large eddy simulation

Gaudet, Brian; Lauvaux, Thomas; Deng, Aijun; Davis, Kenneth J.

doi:10.1525/elementa.247

Cited by 6 publications

(1 citation statement)

References 53 publications

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“…The WRF-LES code we used was first developed to simulate CO 2 transport in the US Upper Midwest and Indianapolis areas (Lauvaux et al, 2012;Gaudet et al, 2017). Our WRF-LES model can take GRIB2 files of the meteorological data of interest (e.g., HRRR, European Centre for Medium-Range Weather Forecasts, and Global Forecast System data) and static geographical data as inputs.…”

Section: Large-eddy Simulation Based Approachesmentioning

confidence: 99%

Methane Point Source Quantification Using MethaneAIR: A New Airborne Imaging Spectrometer

Chulakadabba,

Sargent,

Lauvaux

et al. 2023

Preprint

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Abstract. The MethaneSAT satellite instrument and its aircraft precursor, MethaneAIR, are imaging spectrometers designed to measure methane concentrations with wide spatial coverage, fine spatial resolution, and high precision compared to currently deployed remote sensing instruments. At 12960 m cruise altitude above ground (13850 above sea level), MethaneAIR datasets have a 4.5 km swath gridded to 10m x 10m pixels with 17–20 ppb standard deviation on a flat scene. It was deployed in the summer of 2021 in the Permian Basin to test the accuracy of the retrieved methane concentrations and emission rates using the algorithms developed for MethaneSAT. We report here point source emissions obtained during a single-blind volume controlled release experiment, using two methods: (1) The modified Integrated Mass Enhancement (mIME) method estimates emission rates using the total mass enhancement of methane in an observed plume combined with winds obtained from Weather Research Forecast driven by High-Resolution Rapid Refresh meteorological data in Large Eddy Simulations mode (WRF-LES-HRRR). WRF-LES-HRRR simulates winds in stochastic eddy-scale (100–1000 m) variability, which is particularly important for low-wind conditions and informing the error budget. The mIME can estimate emission rates of plumes of any size that are detectable by MethaneAIR. (2) The Divergence Integral (DI) method applies Gauss’s theorem to estimate the flux divergence fields through a series of closed surfaces enclosing the sources. The set of boxes grows from the upwind side of the plume through the core of each plume and downwind. No selection of inflow concentration, as used in the mIME, is required. The DI approach can efficiently determine fluxes from large sources and clusters of sources but cannot resolve small point emissions. These methods account for the effects of eddy-scale variation in different ways: the DI averages across many eddies, whereas the mIME re-samples many eddies from the LES simulation; they also use different wind products. Emissions estimates from both the mIME and DI methods agreed closely with the blinded-volume controlled releases experiments (N = 21). The York regression between the estimated emissions and the released emissions has a slope of 0.96 [0.84, 1.08], R = 0.83 and N = 21, with 30 % mean percentage error for the whole data set, which indicates that MethaneAIR can quantify point sources emitting more than 200 kg/hr for the mIME and 500 kg/hr for the DI method. The two methods also agreed on methane emission estimates from various uncontrolled sources in the Permian Basin. The experiment thus demonstrates the powerful potential of our instruments for remote sensing and quantification of methane emissions.

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Section: Large-eddy Simulation Based Approachesmentioning

confidence: 99%

Methane Point Source Quantification Using MethaneAIR: A New Airborne Imaging Spectrometer

Chulakadabba,

Sargent,

Lauvaux

et al. 2023

Preprint

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Joint inverse estimation of fossil fuel and biogenic CO2 fluxes in an urban environment: An observing system simulation experiment to assess the impact of multiple uncertainties

Lauvaux

Davis

et al. 2018

Elementa: Science of the Anthropocene

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The Indianapolis Flux Experiment aims to utilize a variety of atmospheric measurements and a high-resolution inversion system to estimate the temporal and spatial variation of anthropogenic greenhouse gas emissions from an urban environment. We present a Bayesian inversion system solving for fossil fuel and biogenic CO2fluxes over the city of Indianapolis, IN. Both components were described at 1 km resolution to represent point sources and fine-scale structures such as highways in the a priori fluxes. With a series of Observing System Simulation Experiments, we evaluate the sensitivity of inverse flux estimates to various measurement deployment strategies and errors. We also test the impacts of flux error structures, biogenic CO2fluxes and atmospheric transport errors on estimating fossil fuel CO2emissions and their uncertainties. The results indicate that high-accuracy and high-precision measurements produce significant improvement in fossil fuel CO2flux estimates. Systematic measurement errors of 1 ppm produce significantly biased inverse solutions, degrading the accuracy of retrieved emissions by about 1μmol m–2s–1compared to the spatially averaged anthropogenic CO2emissions of 5μmol m–2s–1. The presence of biogenic CO2fluxes (similar magnitude to the anthropogenic fluxes) limits our ability to correct for random and systematic emission errors. However, assimilating continuous fossil fuel CO2measurements with 1 ppm random error in addition to total CO2measurements can partially compensate for the interference from biogenic CO2fluxes. Moreover, systematic and random flux errors can be further reduced by reducing model-data mismatch errors caused by atmospheric transport uncertainty. Finally, the precision of the inverse flux estimate is highly sensitive to the correlation length scale in the prior emission errors. This work suggests that improved fossil fuel CO2measurement technology, and better understanding of both prior flux and atmospheric transport errors are essential to improve the accuracy and precision of high-resolution urban CO2flux estimates.

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Advances in urban greenhouse gas flux quantification: The Indianapolis Flux Experiment (INFLUX)

Whetstone

2018

Elementa: Science of the Anthropocene

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Exploration of the impact of nearby sources on urban atmospheric inversions using large eddy simulation

Cited by 6 publications

References 53 publications

Methane Point Source Quantification Using MethaneAIR: A New Airborne Imaging Spectrometer

Methane Point Source Quantification Using MethaneAIR: A New Airborne Imaging Spectrometer

Joint inverse estimation of fossil fuel and biogenic CO2 fluxes in an urban environment: An observing system simulation experiment to assess the impact of multiple uncertainties

Advances in urban greenhouse gas flux quantification: The Indianapolis Flux Experiment (INFLUX)

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