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Using co-located space-based measurements of carbon dioxide (CO2) from the Orbiting Carbon Observatory-2 and Orbiting Carbon Observatory-3 (OCO-2/3) and carbon monoxide (CO) and nitrogen dioxide (NO2) from the TROPOspheric Monitoring Instrument (TROPOMI), we calculate total column enhancements for observations influenced by anthropogenic emissions from urban regions relative to clean background values. We apply this method to observations taken over or downwind of 27 large (population of >1 million) urban areas from around the world. Enhancement ratios between species are calculated and compared to emissions ratios derived from four globally gridded anthropogenic emissions inventories. We find that these global inventories underestimate CO emissions in many North American and European cities relative to our observed enhancement ratios, while smaller differences were found for NO2 emissions. We further demonstrate that the calculation and intercomparison of enhancement ratios of multiple tracers can help to identify the underlying biases leading to disagreement between observations and inventories. Additionally, we use high-resolution CO2 inventories for two cities (Los Angeles and Indianapolis) to estimate emissions of CO and NO2 using our calculated enhancement ratios and find good agreement with both a previous modelling study for the megacity of Los Angeles and California Air Resources Board (CARB) inventory estimates.

EM27/SUN devices are portable solar-viewing Fourier transform spectrometers (FTSs) that are being widely used to constrain measurements of greenhouse gas emissions and validate satellite trace gas measurements. On a 6-week-long campaign in the summer of 2018, four EM27/SUN devices were taken to five Total Carbon Column Observing Network (TCCON) stations in North America, to measure side by side, to better understand their durability, the accuracy and precision of retrievals from their trace gas measurements, and to constrain site-to-site bias among TCCON sites. We developed new EM27/SUN data products using both previous and current versions of the retrieval algorithm (GGG2014 and GGG2020) and used coincident AirCore measurements to tie the gas retrievals to the World Meteorological Organization (WMO) trace gas standard scales. We also derived air-mass-dependent correction factors for the EM27/SUN devices. Pairs of column-averaged dry-air mole fractions (denoted with an X) measured by the EM27/SUN devices remained consistent compared to each other during the entire campaign, with a 10 min averaged precision of 0.3 ppm (parts per million) for XCO2, 1.7 ppb (parts per billion) for XCH4, and 2.5 ppb for XCO. The maximum biases between TCCON stations were reduced in GGG2020 relative to GGG2014 from 1.3 to 0.5 ppm for XCO2 and from 5.4 to 4.3 ppb for XCH4 but increased for XCO from 2.2 to 6.1 ppb. The increased XCO biases in GGG2020 are driven by measurements at sites influenced by urban emissions (Caltech and the Armstrong Flight Research Center) where the priors overestimate surface CO. In addition, in 2020, one EM27/SUN instrument was sent to the Canadian Arctic TCCON station at Eureka, and side-by-side measurements were performed in March–July. In contrast to the other TCCON stations that showed an improvement in the biases with the newer version of GGG, the biases between Eureka's TCCON measurements and those from the EM27/SUN degraded with GGG2020, but this degradation was found to be caused by a temperature dependence in the EM27/SUN oxygen retrievals that is not apparent in the GGG2014 retrievals.

Observations of carbon monoxide (CO) from the Measurements Of Pollution In The Troposphere (MOPITT) instrument aboard the Terra spacecraft were expected to have an accuracy of 10 % prior to the launch in 1999. Here we evaluate MOPITT Version 7 joint (V7J) thermal-infrared and near-infrared (TIR–NIR) retrieval accuracy and precision and suggest ways to further improve the accuracy of the observations. We take five steps involving filtering or bias corrections to reduce scatter and bias in the data relative to other MOPITT soundings and ground-based measurements. (1) We apply a preliminary filtering scheme in which measurements over snow and ice are removed. (2) We find a systematic pairwise bias among the four MOPITT along-track detectors (pixels) on the order of 3–4 ppb with a small temporal trend, which we remove on a global scale using a temporally trended bias correction. (3) Using a small-region approximation (SRA), a new filtering scheme is developed and applied based on additional quality indicators such as the signal-to-noise ratio (SNR). After applying these new filters, the root-mean-squared error computed using the local median from the SRA over 16 years of global observations decreases from 3.84 to 2.55 ppb. (4) We also use the SRA to find variability in MOPITT retrieval anomalies that relates to retrieval parameters. We apply a bias correction to one parameter from this analysis. (5) After applying the previous bias corrections and filtering, we compare the MOPITT results with the GGG2014 ground-based Total Carbon Column Observing Network (TCCON) observations to obtain an overall global bias correction. These comparisons show that MOPITT V7J is biased high by about 6 %–8 %, which is similar to past studies using independent validation datasets on V6J. When using TCCON spectrometric column retrievals without the standard airmass correction or scaling to aircraft (WMO scale), the ground- and satellite-based observations overall agree to better than 0.5 %. GEOS-Chem data assimilations are used to estimate the influence of filtering and scaling to TCCON on global CO and tend to pull concentrations away from the prior fluxes and closer to the truth. We conclude with suggestions for further improving the MOPITT data products.

We estimate the overall CO2, CH4, and CO flux from the South Coast Air Basin using an inversion that couples Total Carbon Column Observing Network (TCCON) and Orbiting Carbon Observatory-2 (OCO-2) observations, with the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the Open-source Data Inventory for Anthropogenic CO2 (ODIAC). Using TCCON data we estimate the direct net CO2 flux from the SoCAB to be 104 ± 26 Tg CO2 yr−1 for the study period of July 2013–August 2016. We obtain a slightly higher estimate of 120 ± 30 Tg CO2 yr−1 using OCO-2 data. These CO2 emission estimates are on the low end of previous work. Our net CH4 (360 ± 90 Gg CH4 yr−1) flux estimate is in agreement with central values from previous top-down studies going back to 2010 (342–440 Gg CH4 yr−1). CO emissions are estimated at 487 ± 122 Gg CO yr−1, much lower than previous top-down estimates (1440 Gg CO yr−1). Given the decreasing emissions of CO, this finding is not unexpected. We perform sensitivity tests to estimate how much errors in the prior, errors in the covariance, different inversion schemes, or a coarser dynamical model influence the emission estimates. Overall, the uncertainty is estimated to be 25 %, with the largest contribution from the dynamical model. Lessons learned here may help in future inversions of satellite data over urban areas.

We estimate the amount of methane (CH4) emitted by the largest dairies in the southern California region by combining measurements from four mobile solar-viewing ground-based spectrometers (EM27/SUN), in situ isotopic 13∕12CH4 measurements from a CRDS analyzer (Picarro), and a high-resolution atmospheric transport simulation with a Weather Research and Forecasting model in large-eddy simulation mode (WRF-LES). The remote sensing spectrometers measure the total column-averaged dry-air mole fractions of CH4 and CO2 (XCH4 and XCO2) in the near infrared region, providing information on total emissions of the dairies at Chino. Differences measured between the four EM27/SUN ranged from 0.2 to 22 ppb (part per billion) and from 0.7 to 3 ppm (part per million) for XCH4 and XCO2, respectively. To assess the fluxes of the dairies, these differential measurements are used in conjunction with the local atmospheric dynamics from wind measurements at two local airports and from the WRF-LES simulations at 111 m resolution. Our top-down CH4 emissions derived using the Fourier transform spectrometers (FTS) observations of 1.4 to 4.8 ppt s−1 are in the low end of previous top-down estimates, consistent with reductions of the dairy farms and urbanization in the domain. However, the wide range of inferred fluxes points to the challenges posed by the heterogeneity of the sources and meteorology. Inverse modeling from WRF-LES is utilized to resolve the spatial distribution of CH4 emissions in the domain. Both the model and the measurements indicate heterogeneous emissions, with contributions from anthropogenic and biogenic sources at Chino. A Bayesian inversion and a Monte Carlo approach are used to provide the CH4 emissions of 2.2 to 3.5 ppt s−1 at Chino.

The Total Carbon Column Observing Network (TCCON) has become the standard for long-term column-averaged measurements of CO2 and CH4. Here, we use a pair of portable spectrometers to test for intra-network bias among the four currently operating TCCON sites in the United States (US). A previous analytical error analysis has suggested that the maximum 2σ site-to-site relative (absolute) bias of TCCON should be less than 0.2 % (0.8 ppm) in XCO2 and 0.4 % (7 ppb) in XCH4. We find here experimentally that the 95 % confidence intervals for maximum pairwise site-to-site bias among the four US TCCON sites are 0.05–0.14 % for XCO2 and 0.08–0.24 % for XCH4. This is close to the limit of the bias we can detect using this methodology.

Methane emissions inventories for Southern California's South Coast Air Basin (SoCAB) have underestimated emissions from atmospheric measurements. To provide insight into the sources of the discrepancy, we analyze records of atmospheric trace gas total column abundances in the SoCAB starting in the late 1980s to produce annual estimates of the ethane emissions from 1989 to 2015 and methane emissions from 2007 to 2015. The first decade of measurements shows a rapid decline in ethane emissions coincident with decreasing natural gas and crude oil production in the basin. Between 2010 and 2015, however, ethane emissions have grown gradually from about 13 ± 5 to about 23 ± 3 Gg yr−1, despite the steady production of natural gas and oil over that time period. The methane emissions record begins with 1 year of measurements in 2007 and continuous measurements from 2011 to 2016 and shows little trend over time, with an average emission rate of 413 ± 86 Gg yr−1. Since 2012, ethane to methane ratios in the natural gas withdrawn from a storage facility within the SoCAB have been increasing by 0.62 ± 0.05 % yr−1, consistent with the ratios measured in the delivered gas. Our atmospheric measurements also show an increase in these ratios but with a slope of 0.36 ± 0.08 % yr−1, or 58 ± 13 % of the slope calculated from the withdrawn gas. From this, we infer that more than half of the excess methane in the SoCAB between 2012 and 2015 is attributable to losses from the natural gas infrastructure.

Bruker™ EM27/SUN instruments are commercial mobile solar-viewing near-IR spectrometers. They show promise for expanding the global density of atmospheric column measurements of greenhouse gases and are being marketed for such applications. They have been shown to measure the same variations of atmospheric gases within a day as the high-resolution spectrometers of the Total Carbon Column Observing Network (TCCON). However, there is little known about the long-term precision and uncertainty budgets of EM27/SUN measurements. In this study, which includes a comparison of 186 measurement days spanning 11 months, we note that atmospheric variations of Xgas within a single day are well captured by these low-resolution instruments, but over several months, the measurements drift noticeably. We present comparisons between EM27/SUN instruments and the TCCON using GGG as the retrieval algorithm. In addition, we perform several tests to evaluate the robustness of the performance and determine the largest sources of errors from these spectrometers. We include comparisons of XCO2, XCH4, XCO, and XN2O. Specifically we note EM27/SUN biases for January 2015 of 0.03, 0.75, –0.12, and 2.43 % for XCO2, XCH4, XCO, and XN2O respectively, with 1σ running precisions of 0.08 and 0.06 % for XCO2 and XCH4 from measurements in Pasadena. We also identify significant error caused by nonlinear sensitivity when using an extended spectral range detector used to measure CO and N2O.

We demonstrate the use of compact solar-tracking Fourier transform spectrometers (Bruker EM27/SUN) for differential measurements of the column-averaged dry-air mole fractions of CH4 and CO2 within urban areas. Using Allan variance analysis, we show that the differential column measurement has a precision of 0.01 % for XCO2 and XCH4 with an optimum integration time of 10 min, corresponding to Allan deviations of 0.04 ppm and 0.2 ppb, respectively. The sensor system is very stable over time and after relocation across the continent. We report tests of the differential column measurement, and its sensitivity to emission sources, by measuring the downwind-minus-upwind column difference ΔXCH4 across dairy farms in the Chino area, California, and using the data to verify emissions reported in the literature. Ratios of spatial column differences ΔXCH4∕ΔXCO2 were observed across Pasadena within the Los Angeles basin, indicating values consistent with regional emission ratios from the literature. Our precise, rapid measurements allow us to determine significant short-term variations (5–10 min) of XCO2 and XCH4 and to show that they represent atmospheric phenomena.Overall, this study helps establish a range of new applications for compact solar-viewing Fourier transform spectrometers. By accurately measuring the small differences in integrated column amounts across local and regional sources, we directly observe the mass loading of the atmosphere due to the influence of emissions in the intervening locale. The inference of the source strength is much more direct than inversion modeling using only surface concentrations and less subject to errors associated with small-scale transport phenomena.