Top-down studies have found consistent underestimations in the United States Environmental Protection Agency (EPA) methane emissions inventory from the oil and gas (O&G) sector. Many of these studies use observations that bias towards hours when worktime activity occurs. In this study we analyze over two years of methane measurements from a tower network in the Delaware basin to analyze hourly temporal emission patterns. Inversion results suggest a range in emissions from 134 Mg/hr at night to 196 Mg/hr during the day, present during both weekdays and weekends. If these results are applicable to other basins, daytime-influenced methodologies may overestimate daily emission rates by up to 27%. This bias does not reconcile the more than 200% difference between the EPA inventory and top-down estimates in the Delaware basin. This study demonstrates how continuous measurement networks can be combined with detailed activity data to improve bottom-up inventories.

Improved urban greenhouse gas (GHG) flux estimates are crucial for informing policy and mitigation efforts. Atmospheric inversion modelling (AIM) is a widely used technique combining atmospheric measurements of trace gas, meteorological modelling, and a prior emission map to infer fluxes. Traditionally, AIM relies on mid-afternoon observations due to the well-represented atmospheric boundary layer in meteorological models. However, confining flux assessement to daytime observations is problematic for the urban scale, where air masses typically move over a city in a few hours and AIM therefore cannot provide improved constraints on emissions over the full diurnal cycle. We hypothesized that there are atmospheric conditions beyond the mid-afternoon under which meteorological models also perform well. We tested this hypothesis using tower-based measurements of CO2 and CH4, wind speed observations, weather model outputs from INFLUX (Indianapolis Flux Experiment), and a prior emissions map. By categorizing trace gas vertical gradients according to wind speed classes and identifying when the meteorological model satisfactorily simulates boundary layer depth (BLD), we found that non-afternoon observations can be assimilated when wind speed is >5 m/s. This condition resulted in small modeled BLD biases (<40%) when compared to calmer conditions (>100%). For Indianapolis, 37% of the GHG measurements meet this wind speed criterion, almost tripling the observations retained for AIM. Similar results are expected for windy cities like Auckland, Melbourne, and Boston, potentially allowing AIM to assimilate up to 60% the total (24-h) observations. Incorporating these observations in AIMs should yield a more diurnally comprehensive evaluation of urban GHG emissions.

We evaluated the ability of a simple ecosystem carbon dioxide (CO2) flux model, the Vegetation Photosynthesis and Respiration Model (VPRM), to capture complex CO2 background conditions observed in Indianapolis, IN. Using simulated biogenic CO2 fluxes and mole fraction tower influence functions, we estimated biogenic CO2 mole fractions at three background towers in the Indianapolis Flux Experiment (INFLUX) network from April 2017 to March 2020. The model captures afternoon average CO2 enhancements, the difference between the background towers and a common reference tower, at a monthly time scale with no significant bias, with monthly mean residuals rarely differing significantly from zero. Although not central to our application, the model could not capture day-to-day variations of observed afternoon average CO2 enhancements. Random errors, when averaged over monthly to yearly time scales, were an order of magnitude smaller than typical urban enhancements. VPRM captured site-to-site differences in the average observed daily cycle of CO2 fluxes at agricultural eddy covariance flux sites well. For 13 of 14 site-months, the modeled peak afternoon NEE was within 30% of that observed despite the observed peaks ranging from about -7 to -70 µmol m-2s-1. VPRM can be effectively used in CO2 inversions to represent complex seasonal variations in background conditions observed in Indianapolis. Indianapolis, a modest-size city surrounded by strong ecosystem fluxes, represents a rigorous test for the VPRM system. Further, this study presents an evaluation system that can be applied to assess the performance of other ecosystem CO2 flux models in cities with similar monitoring networks.

Synoptic weather systems are a major driver of spatial gradients in atmospheric CO2 mole fractions. During frontal passages, air masses from different regions meet at the frontal boundary creating significant gradients in CO2 mole fractions. We quantitatively describe the atmospheric transport of CO2 mole fractions during a mid-latitude cold front passage and explore the impact of various sources of CO2. We focus here on a cold front passage over Lincoln, Nebraska on August 4th, 2016 observed by aircraft during the Atmospheric Carbon and Transport (ACT)-America campaign. A band of air with elevated CO2was located along the frontal boundary. Observed and simulated differences in CO2 across the front were as high as 25 ppm. Numerical simulations using WRF-Chem at cloud resolving resolutions (3km), coupled with CO2 surface fluxes and boundary conditions from CarbonTracker (CT-NRTv2017x), were performed to explore atmospheric transport at the front. Model results demonstrate that the frontal CO2 difference in the upper troposphere can be explained largely by inflow from outside of North America. This difference is modified in the atmospheric boundary layer and lower troposphere by continental surface fluxes, dominated in this case by biogenic and fossil fuel fluxes. Horizontal and vertical advection are found to be responsible for the transport of CO2 mole fractions along the frontal boundary. We show that cold front passages lead to large CO2 transport events including a significant contribution from vertical advection, and that mid-continent frontal boundaries are formed from a complex mixture of CO2 sources.

Nitrous oxide (N2O), a potent greenhouse gas and ozone depleting substance, plays a crucial role in the atmosphere. Anthropogenic emissions from agriculture contribute to a rising trend in global N2O emissions and atmospheric concentrations. However, due to insufficient direct observations, regional N2O emissions derived in bottom-up and top-down studies are highly uncertain. The U.S. Midwest is one of the most intensive agriculture areas worldwide and hence may contribute significantly to the observed trend. Recent top-down studies suggest that bottom-up estimates underestimate agricultural emissions in that area by up to an order of magnitude. Here we quantify nitrous oxide emissions in the Midwest in October 2017 and June-July 2019 with a top-down approach. Unique continuous aircraft-based measurements of N2O conducted during the ACT-America campaign together with forward WRF-Chem model simulations are used to scale the EDGAR inventory thus quantifying emissions. On average we had to upscale October 2017 and June-July 2019 agricultural EDGAR 4.3.2/5.0 emissions by a factor of 6.3/3.5 and 11.4/9.9, resulting in 0.42 nmol m-2 s-1 and 1.06 nmol m-2 s-1 emissions in the Midwest, respectively. Finally, calculations of direct soil N2O emissions from the DayCent biogeochemical model are compared to our estimates.

The Atmospheric Carbon and Transport (ACT) – America NASA Earth Venture Suborbital Mission set out to improve regional atmospheric greenhouse gas (GHG) inversions by exploring the intersection of the strong GHG fluxes and vigorous atmospheric transport that occurs within the midlatitudes. Two research aircraft instrumented with remote and in situ sensors to measure GHG mole fractions, associated trace gases, and atmospheric state variables collected 1140.7 flight hours of research data, distributed across 305 individual aircraft sorties, coordinated within 121 research flight days, and spanning five, six-week seasonal flight campaigns in the central and eastern United States. Flights sampled 31 synoptic sequences, including fair weather and frontal conditions, at altitudes ranging from the atmospheric boundary layer to the upper free troposphere. The observations were complemented with global and regional GHG flux and transport model ensembles. We found that midlatitude weather systems contain large spatial gradients in GHG mole fractions, in patterns that were consistent as a function of season and altitude. We attribute these patterns to a combination of regional terrestrial fluxes and inflow from the continental boundaries. These observations, when segregated according to altitude and air mass, provide a variety of quantitative insights into the realism of regional CO2 and CH4 fluxes and atmospheric GHG transport realizations. The ACT-America data set and ensemble modeling methods provide benchmarks for the development of atmospheric inversion systems. As global and regional atmospheric inversions incorporate ACT-America’s findings and methods, we anticipate these systems will produce increasingly accurate and precise sub-continental GHG flux estimates.

We present observations of local enhancements in carbon dioxide (CO2) from local emissions sources over three eastern US regions during four deployments of the Atmospheric Carbon Transport-America (ACT-America) campaign between summer 2016 and spring 2018. Local CO2 emissions were characterized by carbon monoxide (CO) to CO2 enhancement ratios (i.e. ΔCO/ΔCO2) in airmass mixing observed during aircraft transects within the atmospheric boundary layer. By analyzing regional-scale variability of CO2 enhancements as a function of ΔCO/ΔCO2 enhancement ratios, observed relative contributions to CO2 emissions were contrasted between different combustion regimes across regions and seasons. Ninety percent of observed summer combustion in all regions was attributed to high efficiency fossil fuel (FF) combustion (ΔCO/ΔCO2 < 0.5%). In other seasons, regional contributions increased from less efficient forms of FF combustion (ΔCO/ΔCO2 0.5-2%) to as much as 60% of observed combustion. CO2 emission contributions attributed to biomass burning (BB) (ΔCO/ΔCO2 > 4%) were negligible during summer and fall in all regions, but climbed to 10-12% of observed combustion in the South during winter and spring. Vulcan v3 CO2 2015 emission analysis showed increases in residential and commercial sectors seasonally matching increases in less efficient FF combustion, but could not explain regional trends. WRF-Chem modeling, driven by CarbonTracker CO2 fire emissions, matched observed winter and spring BB contributions, but conflictingly predicted similar levels of BB during fall. Satellite fire data from MODIS and VIIRS suggested higher spatial resolution fire data might improve modeled BB emissions.

Atmospheric nitrous oxide (N2O) is, after carbon dioxide and methane, the third most important long-lived anthropogenic greenhouse gas in terms of radiative forcing. Since preindustrial times a rising trend in the global N2O concentrations is observed. Anthropogenic emissions of N2O, mainly from agricultural activity, contribute considerably to this trend. Sparse observational constraints have made it difficult to quantify these emissions. The few studies on top-down approaches in the U.S. that exist are mainly based on Lagrangian models and ground-based measurements. They all propose a significant underestimation of anthropogenic N2O emission sources in established inventories, such as the Emissions Database for Global Atmospheric Research (EDGAR). In this study we quantify anthropogenic N2O emissions in the Midwest of the U.S., an area of high agricultural activity. In the course of the Atmospheric Carbon and Transport – America (ACT-America) campaign spanning from summer 2016 to summer 2019, an extensive dataset over four seasons has been collected including in-situ N2O aircraft based measurements in the lower and middle troposphere onboard NASA’s C-130 and B-200 aircraft. During fall 2017 and summer 2019 we conducted measurements onboard the NASA-C130 with a Quantum-Cascade-Laser-Spectrometer (QCLS) and on both aircraft over the whole campaign flask measurements (NOAA) were collected. More than 300 joint flight hours were conducted and more than 500 flask samples were collected over the U.S. Midwest. The QCLS system collected continuous N2O data for approximately 60 flight hours in this region. The Eulerian Weather Research and Forecasting model with chemistry enabled (WRF-Chem) is being used to quantify regional agricultural N2O emissions using the spatial characteristics of these atmospheric N2O mole fraction observations. The numerical simulations enable potential surface emission distributions to be compared to our airborne measurements, and source estimates can be adjusted to minimize the differences, thus quantifying N2O sources. These results are then compared to emission rates in the EDGAR inventory.

The U.S. Midwest, with its intensive agriculture, is a prominent source of nitrous oxide (N2O) but top-down and bottom-up N2O emission estimates differ significantly. We quantify Midwest N2O emissions by combining observations from the Atmospheric Carbon and Transport-America campaign with model simulations to scale the Emissions Database for Global Atmospheric Research (EDGAR). In October 2017 we increased agricultural EDGAR version 4.3.2/5.0 emissions by a factor of 6.3±4.6/3.5±2.7, resulting in Midwest N2O emissions of 0.42±0.28 nmol m-2 s-1. In June/July 2019, a period when extreme flooding was occurring in the Midwest, EDGAR was increased by a factor of 11.4±6.6/9.9±5.7, resulting in N2O emissions of 1.06±0.57 nmol m-2 s-1. Agricultural emissions estimated with the process-based model DayCent (Daily version of the CENTURY ecosystem model) were larger than in EDGAR but still substantially smaller than our estimates. Due to the complexity of N2O emissions, further studies are necessary to fully characterize Midwest emissions.

Terrestrial biosphere models (TBMs) play a key role in detection and attribution of carbon cycle processes at local to global scales and in projections of the coupled carbon-climate system. TBM evaluation commonly involves direct comparison to eddy-covariance flux measurements. This study uses atmospheric CO2 mole fraction ([CO2]) measured in situ from aircraft and tower, in addition to flux-measurements from summer 2016 to evaluate the CASA TBM. WRF-Chem is used to simulate [CO2] using biogenic CO2 fluxes from a CASA parameter-based ensemble and CarbonTracker version 2017 (CT2017) in addition to transport and CO2 boundary condition ensembles. The resulting “super ensemble” of modeled [CO2] demonstrates that the biosphere introduces the majority of uncertainty to the simulations. Both aircraft and tower [CO2] data show that the CASA ensemble net ecosystem exchange (NEE) of CO2 is biased high (NEE too positive) and identify the maximum light use efficiency Emax a key parameter that drives the spread of the CASA ensemble. These findings are verified with flux-measurements. The direct comparison of the CASA flux ensemble with flux-measurements indicates that modeled [CO2] biases are mainly due to missing sink processes in CASA. Separating the daytime and nighttime flux, we discover that the underestimated net uptake results from missing sink processes that result in overestimation of respiration. NEE biases are smaller in the CT2017 posterior biogenic fluxes, which assimilates observed [CO2]. Flux tower analyses, however, reveal unrealistic overestimation of nighttime respiration in CT2017.