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In preparation or submitted

Marchetti, Calla, Jonathan Hobbs, Peter Somkuti, and Joshua L. Laughner . "A Study on Inferring Diurnal Cycles of XCO2 from Current and Future Space-Based Missions." Earth Space Sci., submitted

Abstract

Net ecosystem exchange (NEE) measures the net transfer of carbon between terrestrial ecosystems and the atmosphere, and is an important quantity for understanding land-atmosphere feedbacks and constraining the land carbon sink. Atmospheric inverse models and biophysical models provide regional and global NEE estimates, but validation of these models is limited by the sparsity and distribution of flux towers that measure NEE. NEE can also be calculated from diurnal cycles of XCO2. XCO2 is observed by the Orbiting Carbon Observatory 2 and 3 (OCO -2 and -3) satellites, which working together have the potential to observe locations between ∼ 52° S and 52° N twice a day but at a sparse temporal frequency. Here, we investigate the possibility of using machine learning (ML) to extrapolate full diurnal cycles from sparse space-based measurements, which could be in turn be used to derive NEE.

We find that the current temporal sampling from OCO-2 and -3 is not ideal for this purpose, and our ML approach is not able to reliably infer either diurnal cycles or drawdown in simulations mimicking the OCO-2 and -3 overpass times. A thrice-daily observation pattern, such as could be achieved with a GeoCarb-like (geosynchronous) instrument, provides much better performance. However, it is also essential that systematic biases between observations a different times of day be minimized or well characterized, as the ability to predict diurnal cycles or drawdown decreases when the standard error between the means of observations at different times of day exceeds ∼ 0.1 ppm.

Preprints

Fredrickson, C. D., S. J. Janz, L. N. Lamsal, U. A. Jongebloed, J. L. Laughner , and J. A. Thornton. "Remote Sensing Estimates of Time-Resolved HONO and NO2 Emission Rates and Lifetimes in Wildfires." Atmos. Meas. Tech. Discuss., 2024, 1--32, doi: 10.5194/amt-2024-158, 2024

Abstract
Quantification of wildfire emissions is essential for comprehending and simulating the effects of wildfires on atmospheric chemical composition. Sub-orbital measurements of vertical column nitrous acid (HONO) and nitrogen dioxide (NO2) were made during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign using the GeoCAPE Airborne Simulator (GCAS) instrument aboard the NASA ER-2 aircraft. Emission rates and lifetimes of HONO and NO2 from the Sheridan Fire were estimated by fitting exponentially modified Gaussians (EMGs) to line densities, a technique previously used to estimate urban and point source NO2 emissions. As the EMG approach does not capture temporal changes in emissions and lifetimes due to time-varying fire behavior, we developed a Monte Carlo implementation of the Python Editable Chemical Atmospheric Numeric Solver (PECANS) model that includes diurnal fire radiative power (FRP) behavior. We assess the validity of a range of emission rate and lifetime combinations for both HONO and NO2 as the fire evolves by comparing the resulting line density predictions to the observations. We find that our method results in emissions that are lower than top-down biomass burning emissions inventories and higher than bottom-up inventories. Our approach is applicable to interpreting time-resolved remotely sensed measurements of atmospheric trace gases such as those now becoming available with instruments aboard geo-stationary satellites such as the Tropospheric Emissions: Monitoring of Pollution (TEMPO) and the Geostationary Environment Monitoring Spectrometer (GEMS) instruments.

2024

Chan Miller, C., S. Roche, J. S. Wilzewski, X. Liu, K. Chance, A. H. Souri, E. Conway, B. Luo, J. Samra, J. Hawthorne, K. Sun, C. Staebell, A. Chulakadabba, M. Sargent, J. S. Benmergui, J. E. Franklin, B. C. Daube, Y. Li, J. L. Laughner , B. C. Baier, R. Gautam, M. Omara, and S. C. Wofsy. "Methane retrieval from MethaneAIR using the CO2 Proxy Approach: A demonstration for the upcoming MethaneSAT mission." Atmos. Meas. Tech, 17, 5429--5454, doi: 10.5194/amt-17-5429-2024, 2024

Abstract
Reducing methane (CH4) emissions from the oil and gas (O&G) sector is crucial for mitigating climate change in the near term. MethaneSAT is an upcoming satellite mission designed to monitor basin-wide O&G emissions globally, providing estimates of emission rates and helping identify the underlying processes leading to methane release in the atmosphere. MethaneSAT data will support advocacy and policy efforts by helping to track methane reduction commitments and targets set by countries and industries. Here, we introduce a CH4 retrieval algorithm for MethaneSAT based on the CO2 proxy method. We apply the algorithm to observations from the maiden campaign of MethaneAIR, an airborne precursor to the satellite that has similar instrument specifications. The campaign was conducted during winter 2019 and summer 2021 over three major US oil and gas basins. Analysis of MethaneAIR data shows that measurement precision is typically better than 2% at a 20×20 m2 pixel resolution, exhibiting no strong dependence on geophysical variables, e.g., surface reflectance. We show that detector focus drifts over the course of each flight, likely due to thermal gradients that develop across the optical bench. The impacts of this drift on retrieved CH4 can mostly be mitigated by including a parameter that squeezes the laboratory-derived, tabulated instrument spectral response function (ISRF) in the spectral fit. Validation against coincident EM27/SUN retrievals shows that MethaneAIR values are generally within 1% of the retrievals. MethaneAIR retrievals were also intercompared with retrievals from the TROPOspheric Monitoring Instrument (TROPOMI). We estimate that the mean bias between the instruments is 2.5 ppb, and the latitudinal gradients for the two data sets are in good agreement. We evaluate the accuracy of MethaneAIR estimates of point-source emissions using observations recorded over the Permian Basin, an O&G basin, based on the integrated-mass-enhancement approach coupled with a plume-masking algorithm that uses total variational denoising. We estimate that the median point-source detection threshold is 100–150 kg h−1 at the aircraft's nominal above-surface observation altitude of 12 km. This estimate is based on an ensemble of Weather Research and Forecasting (WRF) large-eddy simulations used to mimic the campaign's conditions, with the threshold for quantification set at approximately twice the detection threshold. Retrievals from repeated basin surveys indicate the presence of both persistent and intermittent sources, and we highlight an example from each case. For the persistent source, we infer emissions from a large O&G processing facility and estimate a leak rate between 1.6% and 2.1%, higher than any previously reported emission levels from a facility of its size. We also identify a ruptured pipeline that could increase total basin emissions by 2% if left unrepaired; this pipeline was discovered 2 weeks before it was found by its operator, highlighting the importance of regular monitoring by future satellite missions. The results showcase MethaneAIR's capability to make highly accurate, precise measurements of methane dry-air mole fractions in the atmosphere, with a fine spatial resolution (∼ 20×20 m2) mapped over large swaths (∼ 100×100 km2) in a single flight. The results provide confidence that MethaneSAT can make such measurements at unprecedentedly fine scales from space (∼ 130×400 m2 pixel size over a target area measuring ∼ 200×200 km2), thereby delivering quantitative data on basin-wide methane emissions.

Laughner, J. L., G. C. Toon, J. Mendonca, C. Petri, S. Roche, D. Wunch, J.-F. Blavier, D. W. T. Griffith, P. Heikkinen, R. F. Keeling, M. Kiel, R. Kivi, C. M. Roehl, B. B. Stephens, B. C. Baier, H. Chen, Y. Choi, N. M. Deutscher, J. P. DiGangi, J. Gross, B. Herkommer, P. Jeseck, T. Laemmel, X. Lan, E. McGee, K. McKain, J. Miller, I. Morino, J. Notholt, H. Ohyama, D. F. Pollard, M. Rettinger, H. Riris, C. Rousogenous, M. K. Sha, K. Shiomi, K. Strong, R. Sussmann, Y. Té, V. A. Velazco, S. C. Wofsy, M. Zhou, and P. O. Wennberg. "The Total Carbon Column Observing Network's GGG2020 Data Version." Earth Sys. Sci. Data, 16, 2197--2260, doi: 10.5194/essd-16-2197-2024, 2024

Abstract

The Total Carbon Column Observing Network (TCCON) measures column-average mole fractions of several greenhouse gases (GHGs), beginning in 2004, from over 30 current or past measurement sites around the world using solar absorption spectroscopy in the near-infrared (near-IR) region. TCCON GHG data have been used extensively for multiple purposes, including in studies of the carbon cycle and anthropogenic emissions, as well as to validate and improve observations from space-based sensors. Here, we describe an update to the retrieval algorithm used to process the TCCON near-IR solar spectra and to generate the associated data products. This version, called GGG2020, was initially released in April 2022. It includes updates and improvements to all steps of the retrieval, including but not limited to the conversion of the original interferograms into spectra, the spectroscopic information used in the column retrieval, post hoc air mass dependence correction, and scaling to align with the calibration scales of in situ GHG measurements.

All TCCON data are available through https://tccondata.org/ (last access: 22 April 2024) and are hosted on CaltechDATA (https://data.caltech.edu/, last access: 22 April 2024). Each TCCON site has a unique DOI for its data record. An archive of all the sites' data is also available with the DOI https://doi.org/10.14291/TCCON.GGG2020 (Total Carbon Column Observing Network (TCCON) Team, 2022). The hosted files are updated approximately monthly, and TCCON sites are required to deliver data to the archive no later than 1 year after acquisition. Full details of data locations are provided in the “Code and data availability” section.

2023

Wu, D., J. L. Laughner , J. Liu, P. I. Palmer, J. C. Lin, and P. O. Wennberg. "A simplified non-linear chemistry transport model for analyzing NO2 column observations: STILT--NOx." Geosci. Model Dev., 16, 6161--6185, doi: 10.5194/gmd-16-6161-2023, 2023

Abstract
Satellites monitoring air pollutants (e.g., nitrogen oxides; NOx = NO + NO2) or greenhouse gases (GHGs) are widely utilized to understand the spatiotemporal variability in and evolution of emission characteristics, chemical transformations, and atmospheric transport over anthropogenic hotspots. Recently, the joint use of space-based long-lived GHGs (e.g., carbon dioxide; CO2) and short-lived pollutants has made it possible to improve our understanding of emission characteristics. Some previous studies, however, lack consideration of the non-linear NOx chemistry or complex atmospheric transport. Considering the increase in satellite data volume and the demand for emission monitoring at higher spatiotemporal scales, it is crucial to construct a local-scale emission optimization system that can handle both long-lived GHGs and short-lived pollutants in a coupled and effective manner. This need motivates us to develop a Lagrangian chemical transport model that accounts for NOx chemistry and fine-scale atmospheric transport (STILT–NOx) and to investigate how physical and chemical processes, anthropogenic emissions, and background may affect the interpretation of tropospheric NO2 columns (tNO2). Interpreting emission signals from tNO2 commonly involves either an efficient statistical model or a sophisticated chemical transport model. To balance computational expenses and chemical complexity, we describe a simplified representation of the NOx chemistry that bypasses an explicit solution of individual chemical reactions while preserving the essential non-linearity that links NOx emissions to its concentrations. This NOx chemical parameterization is then incorporated into an existing Lagrangian modeling framework that is widely applied in the GHG community. We further quantify uncertainties associated with the wind field and chemical parameterization and evaluate modeled columns against retrieved columns from the TROPOspheric Monitoring Instrument (TROPOMI v2.1). Specifically, simulations with alternative model configurations of emissions, meteorology, chemistry, and inter-parcel mixing are carried out over three United States (US) power plants and two urban areas across seasons. Using the U.S. Environmental Protection Agency (EPA)-reported emissions for power plants with non-linear NOx chemistry improves the model–data alignment in tNO2 (a high bias of ≤ 10 % on an annual basis), compared to simulations using either the Emissions Database for Global Atmospheric Research (EDGAR) model or without chemistry (bias approaching 100 %). The largest model–data mismatches are associated with substantial biases in wind directions or conditions of slower atmospheric mixing and photochemistry. More importantly, our model development illustrates (1) how NOx chemistry affects the relationship between NOx and CO2 in terms of the spatial and seasonal variability and (2) how assimilating tNO2 can quantify systematic biases in modeled wind directions and emission distribution in prior inventories of NOx and CO2, which laid a foundation for a local-scale multi-tracer emission optimization system.

Chiarella, R., M. Buschmann, J. Laughner , I. Morino, J. Notholt, C. Petri, G. Toon, V. A. Velazco, and T. Warneke. "A retrieval of xCO2 from ground-based mid-infrared NDACC solar absorption spectra and comparison to TCCON." Atmos. Meas. Tech., 16, 3987--4007, doi: 10.5194/amt-16-3987-2023, 2023

Abstract
Two global networks of ground-based Fourier transform spectrometers are measuring abundances of atmospheric trace gases that absorb in the near and mid infrared, Network for the Detection of Atmospheric Composition Change (NDACC) and Total Carbon Column Observing Network (TCCON). The first lacks a CO2 product, therefore this study focuses on developing a xCO2 retrieval method for NDACC from a spectral window in the 4800 cm−1 region. This retrieval will allow to extend ground-based measurements back in time, which we will demonstrate with historical data available from Ny-Ålesund. This region is covered by both TCCON and NDACC, which is an advantage for collocated comparisons where available. The results are compared with collocated TCCON measurements of column-averaged dry-air mole fractions of CO2 (denoted by xCO2) in Ny-Ålesund, Svalbard and only TCCON in Burgos, Philippines. We found that it is possible to retrieve xCO2 from NDACC spectra with a precision from 0.2 % . The comparison between the new retrieval to TCCON showed that the sensitivity of the new retrieval is high in the troposphere and lower in the upper stratosphere, similar to TCCON, and that the seasonality is well captured. We determined an optimal retrieval setup covered in section 7.

Taylor, T. E., C. W. O'Dell, D. Baker, C. Bruegge, A. Chang, L. Chapsky, A. Chatterjee, C. Cheng, F. Chevallier, D. Crisp, L. Dang, B. Drouin, A. Eldering, L. Feng, B. Fisher, D. Fu, M. Gunson, V. Haemmerle, G. R. Keller, M. Kiel, L. Kuai, T. Kurosu, A. Lambert, J. Laughner , R. Lee, J. Liu, L. Mandrake, Y. Marchetti, G. McGarragh, A. Merrelli, R. R. Nelson, G. Osterman, F. Oyafuso, P. I. Palmer, V. H. Payne, R. Rosenberg, P. Somkuti, G. Spiers, C. To, B. Weir, P. O. Wennberg, S. Yu, and J. Zong. "Evaluating the consistency between OCO-2 and OCO-3 XCO2 estimates derived from the NASA ACOS version 10 retrieval algorithm." Atmos. Meas. Tech., 16, 3173--3209, doi: 10.5194/amt-16-3173-2023, 2023

Abstract
The version 10 (v10) Atmospheric Carbon Observations from Space (ACOS) Level 2 full-physics (L2FP) retrieval algorithm has been applied to multiyear records of observations from NASA's Orbiting Carbon Observatory 2 and 3 sensors (OCO-2 and OCO-3, respectively) to provide estimates of the carbon dioxide (CO2) column-averaged dry-air mole fraction (XCO2). In this study, a number of improvements to the ACOS v10 L2FP algorithm are described. The post-processing quality filtering and bias correction of the XCO2 estimates against multiple truth proxies are also discussed. The OCO v10 data volumes and XCO2 estimates from the two sensors for the time period of August 2019 through February 2022 are compared, highlighting differences in spatiotemporal sampling but demonstrating broad agreement between the two sensors where they overlap in time and space. A number of evaluation sources applied to both sensors suggest they are broadly similar in data and error characteristics. Mean OCO-3 differences relative to collocated OCO-2 data are approximately 0.2 and −0.3 ppm for land and ocean observations, respectively. Comparison of XCO2 estimates to collocated Total Carbon Column Observing Network (TCCON) measurements shows root mean squared errors (RMSEs) of approximately 0.8 and 0.9 ppm for OCO-2 and OCO-3, respectively. An evaluation against XCO2 fields derived from atmospheric inversion systems that assimilated only near-surface CO2 observations, i.e., did not assimilate satellite CO2 measurements, yielded RMSEs of 1.0 and 1.1 ppm for OCO-2 and OCO-3, respectively. Evaluation of uncertainties in XCO2 over small areas, as well as XCO2 biases across land–ocean crossings, also indicates similar behavior in the error characteristics of both sensors. Taken together, these results demonstrate a broad consistency of OCO-2 and OCO-3 XCO2 measurements, suggesting they may be used together for scientific analyses.

Parker, H. A., J. L. Laughner , G. C. Toon, D. Wunch, C. M. Roehl, L. T. Iraci, J. R. Podolske, K. McKain, B. Baier, and P. O. Wennberg. "Inferring the vertical distribution of CO and CO2 from TCCON total column values using the TARDISS algorithm." Atmos. Meas. Tech., 16, 2601--2625, doi: 10.5194/amt-16-2601-2023, 2023

Abstract

We describe an approach for determining limited information about the vertical distribution of carbon monoxide (CO) and carbon dioxide (CO2) from total column ground-based Total Carbon Column Observation Network (TCCON) observations. For CO and CO2, it has been difficult to retrieve information about their vertical distribution from spectral line shapes because of the errors in the spectroscopy and the atmospheric temperature profile that mask the effects of variations in their mixing ratio with altitude. For CO2 the challenge is especially difficult given that these variations are typically 2 % or less. Nevertheless, if sufficient accuracy can be obtained, such information would be highly valuable for evaluation of retrievals from satellites and more generally for improving the estimate of surface sources and sinks of these trace gases.

We present here the Temporal Atmospheric Retrieval Determining Information from Secondary Scaling (TARDISS) retrieval algorithm. TARDISS uses several simultaneously obtained total column observations of the same gas from different absorption bands with distinctly different vertical averaging kernels. The different total column retrievals are combined in TARDISS using a Bayesian approach where the weights and temporal covariance applied to the different retrievals include additional constraints on the diurnal variation in the vertical distribution for these gases. We assume that the near-surface part of the column varies rapidly over the course of a day (from surface sources and sinks, for example) and that the upper part of the column has a larger temporal covariance over the course of a day.

Using measurements from the five North American TCCON sites, we find that the retrieved lower partial column (between the surface and ∼ 800 hPa) of the CO and CO2 dry mole fractions (DMFs) have slopes of 0.999 ± 0.002 and 1.001 ± 0.003 with respect to lower column DMF from integrated in situ data measured directly from aircraft and in AirCores. The average error for our lower column CO retrieval is 1.51 ppb (∼ 2 %) while the average error for our CO2 retrieval is 5.09 ppm (∼ 1.25 %). Compared with classical line-shape-derived vertical profile retrievals, our algorithm reduces the influence of forward model errors such as imprecision in spectroscopy (line shapes and intensities) and in the instrument line shape. In addition, because TARDISS uses the existing retrieved column abundances from TCCON (which themselves are computationally much less intensive than profile retrieval algorithms), it is very fast and processes years of data in minutes. We anticipate that this approach will find broad application for use in carbon cycle science.

Someya, Y., Y. Yoshida, H. Ohyama, S. Nomura, A. Kamei, I. Morino, H. Mukai, T. Matsunaga, J. L. Laughner , V. A. Velazco, B. Herkommer, Y. Té, M. K. Sha, R. Kivi, M. Zhou, Y. S. Oh, N. M. Deutscher, and D. W. T. Griffith. "Update on the GOSAT TANSO–FTS SWIR Level 2 retrieval algorithm." Atmos. Meas. Tech., 16, 1477--1501, doi: 10.5194/amt-16-1477-2023, 2023

Abstract
The National Institute for Environmental Studies has provided the column-averaged dry-air mole fraction of carbon dioxide and methane (XCO2 and XCH4) products (L2 products) obtained from the Greenhouse gases Observing SATellite (GOSAT) for more than a decade. Recently, we updated the retrieval algorithm used to produce the new L2 product, V03.00. The main changes from the previous version (V02) of the retrieval algorithm are the treatment of cirrus clouds, the degradation model of the Thermal And Near-infrared Spectrometer for carbon Observation–Fourier Transform Spectrometer (TANSO–FTS), solar irradiance spectra, and gas absorption coefficient tables. The retrieval results from the updated algorithm showed improvements in fitting accuracies in the O2 A, weak CO2, and CH4 bands of TANSO–FTS, although the residuals increase in the strong CO2 band over the ocean. The direct comparison of the new product obtained from the updated (V03) algorithm with the previous version V02.90/91 and the validations using the Total Carbon Column Observing Network revealed that the V03 algorithm increases the amount of data without diminishing the data qualities of XCO2 and XCH4 over land. However, the negative bias of XCO2 is larger than that of the previous version over the ocean, and bias correction is still necessary. Additionally, the V03 algorithm resolves the underestimation of the XCO2 growth rate compared with the in situ measurements over the ocean recently found using V02.90/91 and V02.95/96.

MacDonald, C. G., J.-P. Mastrogiacomo, J. L. Laughner , J. K. Hedelius, R. Nassar, and D. Wunch. "Estimating enhancement ratios of nitrogen dioxide, carbon monoxide, and carbon dioxide using satellite observations." Atmos. Chem. Phys., 23, 3516, doi: 10.5194/acp-23-3493-2023, 2023

Abstract
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.

Mostafavi Pak, N., J. Hedelius, S. Roche, L. Cunningham, B. Baier, C. Sweeney, C. Roehl, J. Laughner , G. Toon, P. Wennberg, H. Parker, C. Arrowsmith, J. Mendonca, P. Fogal, T. Wizenberg, B. Herrera, K. Strong, K. A. Walker, F. Vogel, and D. Wunch. "Using portable low-resolution spectrometers to evaluate Total Carbon Column Network (TCCON) biases in North America." Atmos. Meas. Tech., 16, 1239--1261, doi: 10.5194/amt-16-1239-2023, 2023

Abstract
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.

Laughner, J. L., S. Roche, M. Kiel, G. C. Toon, D. Wunch, B. C. Baier, S. Biraud, H. Chen, R. Kivi, T. Laemmel, K. McKain, P.-Y. Quéhé, C. Rousogenous, B. B. Stephens, K. Walker, and P. O. Wennberg. "A new algorithm to generate a priori trace gas profiles for the GGG2020 retrieval algorithm." Atmos. Meas. Tech., 16, 1121--1146, doi: 10.5194/amt-16-1121-2023, 2023

Abstract
Optimal estimation retrievals of trace gas total columns require prior vertical profiles of the gases retrieved to drive the forward model and ensure the retrieval problem is mathematically well posed. For well-mixed gases, it is possible to derive accurate prior profiles using an algorithm that accounts for general patterns of atmospheric transport coupled with measured time series of the gases in questions. Here we describe the algorithm used to generate the prior profiles for GGG2020, a new version of the GGG retrieval that is used to analyze spectra from solar-viewing Fourier transform spectrometers, including the Total Carbon Column Observing Network (TCCON). A particular focus of this work is improving the accuracy of CO2, CH4, N2O, HF, and CO across the tropopause and into the lower stratosphere. We show that the revised priors agree well with independent in situ and space-based measurements and discuss the impact on the total column retrievals.

2022

Zhu, Q., J. L. Laughner , and R. C. Cohen. "Estimate of OH Trends over One Decade in North American Cities." PNAS, 119, e2117399119, doi: 10.1073/pnas.2117399119, 2022

Abstract
The hydroxyl radical (OH) is the most important oxidant on global and local scales in the troposphere. Urban OH controls the removal rate of primary pollutants and triggers the production of ozone. Interannual trends of OH in urban areas are not well documented or understood due to the short lifetime and high spatial heterogeneity of OH. We utilize machine learning with observational inputs emphasizing satellite remote sensing observations to predict surface OH in 49 North American cities from 2005 to 2014. We observe changes in the summertime OH over one decade, with wide variation among different cities. In 2014, compared to the summertime OH in 2005, 3 cities show a significant increase of OH, whereas, in 27 cities, OH decreases in 2014. The year-to-year variation of OH is mapped to the decline of the NO2 column. We conclude that these cities in this analysis are either in the NOx-limited regime or at the transition from a NOx suppressed regime to a NOx-limited regime. The result emphasizes that, in the future, controlling NOx emissions will be most effective in regulating the ozone pollution in these cities.

Zhu, Q., J. L. Laughner , and R. C. Cohen. "Combining Machine Learning and Satellite Observations to Predict Spatial and Temporal Variation of near Surface OH in North American Cities." Environ. Sci. Technol., 56, 7362--7371, doi: 10.1021/acs.est.1c05636, 2022

Abstract
The hydroxyl radical (OH) is the primary cleansing agent in the atmosphere. The abundance of OH in cities initiates the removal of local pollutants; therefore, it serves as the key species describing the urban chemical environment. We propose a machine learning (ML) approach as an efficient alternative to OH simulation using a computationally expensive chemical transport model. The ML model is trained on the parameters simulated from the WRF-Chem model, and it suggests that six predictive parameters are capable of explaining 76% of the OH variability. The parameters are the tropospheric NO2 column, the tropospheric HCHO column, J(O1D), H2O, temperature, and pressure. We then use observations of the tropospheric NO2 column and HCHO column from OMI as input to the ML model to enable measurement-based prediction of daily near surface OH at 1:30 pm local time across 49 North American cities over the course of 10 years between 2005 and 2014. The result is validated by comparing the OH predictions to measurements of isoprene, which has a source that is uncorrelated with OH and is removed rapidly and almost exclusively by OH in the daytime. We demonstrate that the predicted OH is, as expected, anticorrelated with isoprene. We also show that this ML model is consistent with our understanding of OH chemistry given the solely data-driven nature.

2021

Laughner, J.L., J.L. Neu, D. Schimel, P.O. Wennberg, K. Barsanti, K.W. Bowman, A. Chatterjee, B.E. Croes, H.L. Fitzmaurice, D.K. Henze, J. Kim, E.A. Kort, Z. Liu, K. Miyazaki, A.J. Turner, S. Anenberg, J. Avise, H. Cao, D. Crisp, J. de Gouw, A. Eldering, J.C. Fyfe, D.L. Goldberg, K.R. Gurney, S. Hasheminassab, F. Hopkins, C.E. Ivey, D.B.A. Jones, J. Liu, N.S. Lovenduski, R.V. Martin, G.A. McKinley, L. Ott, B. Poulter, M. Ru, S.P. Sander, N. Swart, Y.L. Yung, and Z.-C. Zeng. "Societal shifts due to COVID-19 reveal large-scale complexities and feedbacks between atmospheric chemistry and climate change." PNAS, 118, e2109481118, doi: https://doi.org/10.1073/pnas.2109481118, 2021

Abstract
The COVID-19 global pandemic and associated government lockdowns dramatically altered human activity, providing a window into how changes in individual behavior, enacted en masse, impact atmospheric composition. The resulting reductions in anthropogenic activity represent an unprecedented event that yields a glimpse into a future where emissions to the atmosphere are reduced. Furthermore, the abrupt reduction in emissions during the lockdown periods led to clearly observable changes in atmospheric composition, which provide direct insight into feedbacks between the Earth system and human activity. While air pollutants and greenhouse gases share many common anthropogenic sources, there is a sharp difference in the response of their atmospheric concentrations to COVID-19 emissions changes, due in large part to their different lifetimes. Here, we discuss several key takeaways from modeling and observational studies. First, despite dramatic declines in mobility and associated vehicular emissions, the atmospheric growth rates of greenhouse gases were not slowed, in part due to decreased ocean uptake of CO2 and a likely increase in CH4 lifetime from reduced NOx emissions. Second, the response of O3 to decreased NOx emissions showed significant spatial and temporal variability, due to differing chemical regimes around the world. Finally, the overall response of atmospheric composition to emissions changes is heavily modulated by factors including carbon-cycle feedbacks to CH4 and CO2, background pollutant levels, the timing and location of emissions changes, and climate feedbacks on air quality, such as wildfires and the ozone climate penalty.

Roche, S., K. Strong, D. Wunch, J. Mendonca, C. Sweeny, B. Baier, S. C. Biraud, J. L. Laughner , G. Toon, and B. Connor. "Retrieval of atmospheric CO2 vertical profiles from ground-based near-infrared spectra." Atmos. Meas. Tech., 14, 3087--3118, doi: 10.5194/amt-14-3087-2021, 2021

Abstract
We evaluate vertical profile retrievals of CO2 from 0.02 cm−1 resolution ground-based near-infrared solar absorption spectra with the GFIT2 algorithm, using improved spectroscopic line lists and line shapes. With these improvements, CO2 profiles were obtained from sequential retrievals in five spectral windows with different vertical sensitivities using synthetic and real spectra. A sensitivity study using synthetic spectra shows that the leading source of uncertainty in the retrieved CO2 profiles is the error in the a priori temperature profile, even with 3-hourly reanalysis a priori profiles. A 2 ∘C error in the temperature profile in the lower troposphere between 0.6 and 0.85 atm causes deviations in the retrieved CO2 profiles that are larger than the typical vertical variations of CO2. To distinguish the effect of errors in the a priori meteorology and trace gas concentration profiles from those in the instrument alignment and spectroscopic parameters, we retrieve CO2 profiles from atmospheric spectra while using an a priori profile built from coincident AirCore, radiosonde, and surface in situ measurements at the Lamont, Oklahoma (USA), Total Carbon Column Observing Network station. In those cases, the deviations in retrieved CO2 profiles are also larger than typical vertical variations of CO2, suggesting that remaining errors in the forward model limit the accuracy of the retrieved profiles. Implementing a temperature retrieval or correction and quantifying and modeling an imperfect instrument alignment are critical to improve CO2 profile retrievals. Without significant advances in modeling imperfect instrument alignment, and improvements in the accuracy of the temperature profile, the CO2 profile retrieval with GFIT2 presents no clear advantage over scaling retrievals for the purpose of ascertaining the total column.

Müller, A., H. Tanimoto, T. Sugita, T. Machida, S. Nakaoka, P. K. Patra, J. Laughner , and D. Crisp. "New approach to evaluate satellite-derived XCO2 over oceans by integrating ship and aircraft observations." Atmospheric Chemistry and Physics, 21, 8255--8271, doi: 10.5194/acp-21-8255-2021, 2021

Abstract

2020

Taylor, T. E., A. Eldering, A. Merrelli, M. Kiel, P. Somkuti, Ce. Cheng, R. Rosenberg, B. Fisher, D. Crisp, R. Basilio, M. Bennett, D. Cervantes, A. Chang, L. Dang, C. Frankenberg, V. R. Haemmerle, G. R. Keller, T. Kurosu, J. L. Laughner , R. Lee, Y. Marchetti, R. R. Nelson, C. W. O'Dell, G. Osterman, R. Pavlick, C. Roehl, R. Schneider, G. Spiers, C. To, C. Wells, P. O. Wennberg, A. Yelamanchili, and S. Yu. "OCO-3 early mission operations and initial (vEarly) XCO2 and SIF retrievals." Rem. Sens. Environ., 251, 112032, doi: 10.1016/j.rse.2020.112032, 2020

Abstract
NASA's Orbiting Carbon Observatory-3 (OCO-3) was installed on the International Space Station (ISS) on 10 May 2019. OCO-3 combines the flight spare spectrometer from the Orbiting Carbon Observatory-2 (OCO-2) mission, which has been in operation since 2014, with a new Pointing Mirror Assembly (PMA) that facilitates observations of non-nadir targets from the nadir-oriented ISS platform. The PMA is a new feature of OCO-3, which is being used to collect data in all science modes, including nadir (ND), sun-glint (GL), target (TG), and the new snapshot area mapping (SAM) mode. This work provides an initial assessment of the OCO-3 instrument and algorithm performance, highlighting results from the first 8 months of operations spanning August 2019 through March 2020. During the In-Orbit Checkout (IOC) phase, critical systems such as power and cooling were verified, after which the OCO-3 spectrometer and PMA were subjected to a series of rigorous tests. First light of the OCO-3 spectrometer was on 26 June 2019, with full science operations beginning on 6 August 2019. The OCO-3 spectrometer on-orbit performance is consistent with that seen during preflight testing. Signal to noise ratios are in the expected range needed for high quality retrievals of the column-averaged carbon dioxide (CO2) dry-air mole fraction (XCO2) and solar-induced chlorophyll fluorescence (SIF), which will be used to help quantify and constrain the global carbon cycle. The first public release of OCO-3 Level 2 (L2) data products, called “vEarly”, is being distributed by NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC). The intent of the vEarly product is to evaluate early mission performance, facilitate comparisons with OCO-2 products, and identify key areas to improve for the next data release. The vEarly XCO2 exhibits a root-mean-squared-error (RMSE) of ≃ 1, 1, 2 ppm versus a truth proxy for nadir-land, TG&SAM, and glint-water observations, respectively. The vEarly SIF shows a correlation with OCO-2 measurements of >0.9 for highly coincident soundings. Overall, the Level 2 SIF and XCO2 products look very promising, with performance comparable to OCO-2. A follow-on version of the OCO-3 L2 product containing a number of refinements, e.g., instrument calibration, pointing accuracy, and retrieval algorithm tuning, is anticipated by early in 2021.

Lapierre, J., J. Laughner , J. Geddes, W. Koshack, R. Cohen, and S. Pusede. "Observing regional variability in lightning NO2 production rates." J. Geophys. Res. Atmos., 125, e2019JD031362, doi: 10.1029/2019JD031362, 2020

Abstract
Lightning is a large and variable source of nitrogen oxides (NOx ≡ NO + NO2) to the upper troposphere. Precise estimates of lightning NOx (LNOx) production rates are needed to constrain tropospheric oxidation chemistry; however, controls over LNOx variability are poorly understood. Here, we describe an observational analysis of variability in LNO2 with lightning type by exploiting U.S. regional differences in lightning characteristics in the Southeast, South Central, and North Central United States. We use satellite NO2 measurements from the Ozone Monitoring Instrument with Berkeley High Resolution vertical column densities, a combined lightning data set derived from the Earth Networks Total Lightning Network and National Lightning Detection Network (TM) measurements, and hourly winds from the European Centre for Medium‐Range Weather Forecasts climate reanalysis data set (ERA5) over May–August 2014–2015. We find evidence that cloud‐to‐ground (CG) strokes produce a factor of 9–11 more NO2 than intracloud (IC) strokes for storms with stroke rates of at least 2,800 strokes·cell−1·hr−1. We show that regional differences in LNO2 production rates are generally consistent with regional patterns CG and IC stroke frequency and stroke current density. A comparison of stroke‐based and flash‐based CG/IC LNO2 estimates suggests that CG LNO2 is potentially underestimated when derived with flash data due to the operational definition of CG lightning. We find that differences in peak current explain a large portion of CG/IC LNO2 variability, but that other factors must also be important, including minimum stroke rate. Because IC and CG strokes produce NOx in distinct areas of the atmosphere, we test the sensitivity of our results against the atmospheric NO2 vertical distribution assumed in the a priori profiles; we show that the relative CG to IC LNO2 was generally insensitive to the assumed NO2 vertical distribution.

2019

Zhu, Q., J. L. Laughner , and R. C. Cohen. "Lightning NO2 simulation over the contiguous US and its effects on satellite NO2 retrievals." Atmos. Chem. Phys., 19, 13067--13078, doi: 10.5194/acp-19-13067-2019, 2019

Abstract
Lightning is an important NOx source representing ∼10 % of the global source of odd N and a much larger percentage in the upper troposphere. The poor understanding of spatial and temporal patterns of lightning contributes to a large uncertainty in understanding upper tropospheric chemistry. We implement a lightning parameterization using the product of convective available potential energy (CAPE) and convective precipitation rate (PR) coupled with the Kain–Fritsch convective scheme (KF/CAPE-PR) into the Weather Research and Forecasting-Chemistry (WRF-Chem) model. Compared to the cloud-top height (CTH) lightning parameterization combined with the Grell 3-D convective scheme (G3/CTH), we show that the switch of convective scheme improves the correlation of lightning flash density in the southeastern US from 0.30 to 0.67 when comparing against the Earth Networks Total Lightning Network; the switch of lightning parameterization contributes to the improvement of the correlation from 0.48 to 0.62 elsewhere in the US. The simulated NO2 profiles using the KF/CAPE-PR parameterization exhibit better agreement with aircraft observations in the middle and upper troposphere. Using a lightning NOx production rate of 500 mol NO flash−1, the a priori NO2 profile generated by the simulation with the KF/CAPE-PR parameterization reduces the air mass factor for NO2 retrievals by 16 % on average in the southeastern US in the late spring and early summer compared to simulations using the G3/CTH parameterization. This causes an average change in NO2 vertical column density 4 times higher than the average uncertainty.

Laughner, J. L. and R. C. Cohen. "Direct observation of changing NOx lifetime in North American cities." Science, 366, 723--727, doi: 10.1126/science.aax6832, 2019

Coverage in the media:

Abstract
NOx lifetime relates nonlinearly to its own concentration; therefore, by observing how NOx lifetime changes with changes in its concentration, inferences can be made about the dominant chemistry occurring in an urban plume. We used satellite observations of NO2 from a new high-resolution product to show that NOx lifetime in approximately 30 North American cities has changed between 2005 and 2014 in a manner consistent with our understanding of NOx chemistry.

Silvern, R. F., D. J. Jacob, L. J. Mickley, M. P. Sulprizio, K. R. Travis, E. A. Marais, R. C. Cohen, J. L. Laughner , S. Choi, J. Joiner, and L. N. Lamsal. "Using satellite observations of tropospheric NO2 columns to infer long-term trends in US NOx emissions: the importance of accounting for the free tropospheric NO2 background." Atmos. Chem. Phys., 19, 8863--8878, doi: 10.5194/acp-19-8863-2019, 2019

Abstract
The National Emission Inventory (NEI) of the US Environmental Protection Agency (EPA) reports a steady decrease in US NOx emissions over the 2005–2017 period at a rate of 0.1 Tg N a−1 (53 % decrease over the period), reflecting sustained efforts to improve air quality. Tropospheric NO2 columns observed by the satellite-based Ozone Monitoring Instrument (OMI) over the US show a steady decrease until 2009 but a flattening afterward, which has been attributed to a flattening of NOx emissions, contradicting the NEI. We show here that the steady 2005–2017 decrease in NOx emissions reported by the NEI is in fact largely consistent with observed network trends of surface NO2 and ozone concentrations. The OMI NO2 trend is instead similar to that observed for nitrate wet deposition fluxes, which is weaker than that for anthropogenic NOx emissions, due to a large and increasing relative contribution of non-anthropogenic background sources of NOx (mainly lightning and soils). This is confirmed by contrasting OMI NO2 trends in urban winter, where the background is low and OMI NO2 shows a 2005–2017 decrease consistent with the NEI, and rural summer, where the background is high and OMI NO2 shows no significant 2005–2017 trend. A GEOS-Chem model simulation driven by NEI emission trends for the 2005–2017 period reproduces these different trends, except for the post-2009 flattening of OMI NO2, which we attribute to a model underestimate of free tropospheric NO2. Better understanding is needed of the factors controlling free tropospheric NO2 in order to relate satellite observations of tropospheric NO2 columns to the underlying NOx emissions and their trends. Focusing on urban winter conditions in the satellite data minimizes the effect of this free tropospheric background.

Laughner, J. L., Q. Zhu, and R. Cohen. "Evaluation of version 3.0B of the BEHR OMI NO2 product." Atmos. Meas. Tech., 12, 129--146, doi: 10.5194/amt-12-129-2019, 2019

Abstract
Version 3.0B of the Berkeley High Resolution (BEHR) Ozone Monitoring Instrument (OMI) NO2 product is designed to accurately retrieve daily variation in the high-spatial-resolution mapping of tropospheric column NO2 over continental North America between 25 and 50∘ N. To assess the product, we compare against in situ aircraft profiles and Pandora vertical column densities (VCDs). We also compare the WRF-Chem simulation used to generate the a priori NO2 profiles against observations. We find that using daily NO2 profiles improves the VCDs retrieved in urban areas relative to low-resolution or monthly a priori NO2 profiles by amounts that are large compared to current uncertainties in NOx emissions and chemistry (of the order of 10 % to 30 %). Based on this analysis, we offer suggestions to consider when designing retrieval algorithms and validation procedures for upcoming geostationary satellites.

2018

Laughner, J. L., Q. Zhu, and R. C. Cohen. "The Berkeley High Resolution Tropospheric NO2 Product." Earth System Science Data, 10, 2069--2095, doi: 10.5194/essd-10-2069-2018, 2018

Abstract
We describe upgrades to the Berkeley High Resolution (BEHR) NO2 satellite retrieval product. BEHR v3.0B builds on the NASA version 3 standard Ozone Monitoring Instrument (OMI) tropospheric NO2 product to provide a high spatial resolution product for a domain covering the continental United States and lower Canada that is consistent with daily variations in the 12 km a priori NO2 profiles. Other improvements to the BEHR v3.0 product include surface reflectance and elevation, and factors affecting the NO2 a priori profiles such as lightning and anthropogenic emissions. We describe the retrieval algorithm in detail and evaluate the impact of changes to the algorithm between v2.1C and v3.0B on the retrieved NO2 vertical column densities (VCDs). Not surprisingly, we find that, on average, the changes to the a priori NO2 profiles and the update to the new NASA slant column densities have the greatest impact on the retrieved VCDs. More significantly, we find that using daily a priori profiles results in greater average VCDs than using monthly profiles in regions and times with significant lightning activity. The BEHR product is available as four subproducts on the University of California DASH repository, using monthly a priori profiles at native OMI pixel resolution (https://doi.org/10.6078/D1N086) and regridded to 0.05° × 0.05° (https://doi.org/10.6078/D1RQ3G) and using daily a priori profiles at native OMI (https://doi.org/10.6078/D1WH41) and regridded (https://doi.org/10.6078/D12D5X) resolutions. The subproducts using monthly profiles are currently available from January 2005 to July 2017, and will be expanded to more recent years. The subproducts using daily profiles are currently available for years 2005–2010 and 2012–2014; 2011 and 2015 on will be added as the necessary input data are simulated for those years.

Silvern, R. F., D. J. Jacob, K. R. Travis, T. Sherwen, M. J. Evans, R. C. Cohen, J. L. Laughner , S. R. Hall, K. Ullmann, J. D. Crounse, P. O. Wennberg, J. Peischl, and I. B. Pollack. "Observed NO/NO2 Ratios in the Upper Troposphere Imply Errors in NO‐NO2‐O3 Cycling Kinetics or an Unaccounted NOx Reservoir." Geophys. Res. Lett., 45, 4466--4474, doi: 10.1029/2018GL077728, 2018

Abstract
Observations from the SEAC4RS aircraft campaign over the southeast United States in August–September 2013 show NO/NO2 concentration ratios in the upper troposphere that are approximately half of photochemical equilibrium values computed from Jet Propulsion Laboratory (JPL) kinetic data. One possible explanation is the presence of labile NOx reservoir species, presumably organic, decomposing thermally to NO2 in the instrument. The NO2 instrument corrects for this artifact from known labile HNO4 and CH3O2NO2 NOx reservoirs. To bridge the gap between measured and simulated NO2, additional unaccounted labile NOx reservoir species would have to be present at a mean concentration of ~40 ppt for the SEAC4RS conditions (compared with 197 ppt for NOx). An alternative explanation is error in the low‐temperature rate constant for the NO + O3 reaction (30% 1‐σ uncertainty in JPL at 240 K) and/or in the spectroscopic data for NO2 photolysis (20% 1‐σ uncertainty). Resolving this discrepancy is important for understanding global budgets of tropospheric oxidants and for interpreting satellite observations of tropospheric NO2 columns.

2017

Laughner, J. L. and R. C. Cohen. "Quantification of the effect of modeled lightning NO2 on UV-visible air mass factors." Atmos. Meas. Tech., 10, 4403--4419, doi: 10.5194/amt-10-4403-2017, 2017

Abstract
Space-borne measurements of tropospheric nitrogen dioxide (NO2) columns are up to 10x more sensitive to upper tropospheric (UT) NO2 than near-surface NO2 over low-reflectivity surfaces. Here, we quantify the effect of adding simulated lightning NO2 to the a priori profiles for NO2 observations from the Ozone Monitoring Instrument (OMI) using modeled NO2 profiles from the Weather Research and Forecasting–Chemistry (WRF-Chem) model. With observed NO2 profiles from the Deep Convective Clouds and Chemistry (DC3) aircraft campaign as observational truth, we quantify the bias in the NO2 column that occurs when lightning NO2 is not accounted for in the a priori profiles. Focusing on late spring and early summer in the central and eastern United States, we find that a simulation without lightning NO2 underestimates the air mass factor (AMF) by 25 % on average for common summer OMI viewing geometry and 35 % for viewing geometries that will be encountered by geostationary satellites. Using a simulation with 500 to 665 mol NO flash−1 produces good agreement with observed NO2 profiles and reduces the bias in the AMF to  <  ±4 % for OMI viewing geometries. The bias is regionally dependent, with the strongest effects in the southeast United States (up to 80 %) and negligible effects in the central US. We also find that constraining WRF meteorology to a reanalysis dataset reduces lightning flash counts by a factor of 2 compared to an unconstrained run, most likely due to changes in the simulated water vapor profile.

Nault, B. A., J. L. Laughner , P. J. Wooldridge, J. D. Crounse, J. Dibb, G. Diskin, J. Peischl, J. R. Podolske, I. B. Pollack, T. B. Ryerson, E. Scheuer, P. O. Wennberg, and R. C. Cohen. "Lightning NOx Emissions: Reconciling Measured and Modeled Estimates With Updated NOx Chemistry." Geophys. Res. Lett., 44, 9479--9488, doi: 10.1002/2017GL074436, 2017

Abstract
Lightning is one of the most important sources of upper tropospheric NOx; however, there is a large spread in estimates of the global emission rates (2–8 Tg N yr−1). We combine upper tropospheric in situ observations from the Deep Convective Clouds and Chemistry (DC3) experiment and global satellite‐retrieved NO2 tropospheric column densities to constrain mean lightning NOx (LNOx) emissions per flash. Insights from DC3 indicate that the NOx lifetime is ~3 h in the region of outflow of thunderstorms, mainly due to production of methyl peroxy nitrate and alkyl and multifunctional nitrates. The lifetime then increases farther downwind from the region of outflow. Reinterpreting previous analyses using the 3 h lifetime reduces the spread among various methods that have been used to calculate mean LNOx emissions per flash and indicates a global LNOx emission rate of ~9 Tg N yr−1, a flux larger than the high end of recent estimates.

2016

Laughner, J. L., A. Zare, and R. C. Cohen. "Effects of daily meteorology on the interpretation of space-based remote sensing of NO2." Atmos. Chem. Phys., 16, 15247--15264, doi: 10.5194/acp-16-15247-2016, 2016

Abstract
Retrievals of tropospheric NO2 columns from UV–visible observations of reflected sunlight require a priori vertical profiles to account for the variation in sensitivity of the observations to NO2 at different altitudes. These profiles vary in space and time but are usually approximated using models that do not resolve the full details of this variation. Currently, no operational retrieval simulates these a priori profiles at both high spatial and high temporal resolution. Here we examine the additional benefits of daily variations in a priori profiles for retrievals already simulating a priori NO2 profiles at sufficiently high spatial resolution to identify variations of NO2 within urban plumes. We show the effects of introducing daily variation into a priori profiles can be as large as 40 % and 3 × 1015 molec. cm−2 for an individual day and lead to corrections as large as −13 % for a monthly average in a case study of Atlanta, GA, USA. Additionally, we show that NOx emissions estimated from space-based remote sensing using daily, high-spatial-resolution a priori profiles are  ∼ 100 % greater than those of a retrieval using spatially coarse a priori profiles, and 26–40 % less than those of a retrieval using monthly averaged high-spatial-resolution profiles.

Travis, K. R., D. J. Jacob, J. A. Fisher, P. S. Kim, E. A. Marais, L. Zhu, K. Yu, C. C. Miller, R. M. Yantosca, M. P. Sulprizio, A. M. Thompson, P. O. Wennberg, J. D. Crounse, J. M. St. Clair, R. C. Cohen, J. L. Laughner , J. E. Dibb, S. R. Hall, K. Ullmann, G. M. Wolfe, I. B. Pollack, J. Peischl, J. A. Neuman, and X. Zhou. "Why do models overestimate surface ozone in the Southeast United States?." Atmos. Chem. Phys., 16, 13561--13577, doi: 10.5194/acp-16-13561-2016, 2016

Abstract
Ozone pollution in the Southeast US involves complex chemistry driven by emissions of anthropogenic nitrogen oxide radicals (NOx  ≡  NO + NO2) and biogenic isoprene. Model estimates of surface ozone concentrations tend to be biased high in the region and this is of concern for designing effective emission control strategies to meet air quality standards. We use detailed chemical observations from the SEAC4RS aircraft campaign in August and September 2013, interpreted with the GEOS-Chem chemical transport model at 0.25°  ×  0.3125° horizontal resolution, to better understand the factors controlling surface ozone in the Southeast US. We find that the National Emission Inventory (NEI) for NOx from the US Environmental Protection Agency (EPA) is too high. This finding is based on SEAC4RS observations of NOx and its oxidation products, surface network observations of nitrate wet deposition fluxes, and OMI satellite observations of tropospheric NO2 columns. Our results indicate that NEI NOx emissions from mobile and industrial sources must be reduced by 30–60 %, dependent on the assumption of the contribution by soil NOx emissions. Upper-tropospheric NO2 from lightning makes a large contribution to satellite observations of tropospheric NO2 that must be accounted for when using these data to estimate surface NOx emissions. We find that only half of isoprene oxidation proceeds by the high-NOx pathway to produce ozone; this fraction is only moderately sensitive to changes in NOx emissions because isoprene and NOx emissions are spatially segregated. GEOS-Chem with reduced NOx emissions provides an unbiased simulation of ozone observations from the aircraft and reproduces the observed ozone production efficiency in the boundary layer as derived from a regression of ozone and NOx oxidation products. However, the model is still biased high by 6 ± 14 ppb relative to observed surface ozone in the Southeast US. Ozonesondes launched during midday hours show a 7 ppb ozone decrease from 1.5 km to the surface that GEOS-Chem does not capture. This bias may reflect a combination of excessive vertical mixing and net ozone production in the model boundary layer.

Pusede, S. E., K. C. Duffey, A. A. Shusterman, A. Saleh, J. L. Laughner , P. J. Wooldridge, Q. Zhang, C. L. Parworth, H. Kim, S. L. Capps, L. C. Valin, C. D. Cappa, A. Fried, J. Walega, J. B. Nowak, A. J. Weinheimer, R. M. Hoff, T. A. Berkoff, A. J. Beyersdorf, J. Olson, J. H. Crawford, and R. C. Cohen. "On the effectiveness of nitrogen oxide reductions as a control over ammonium nitrate aerosol." Atmos. Chem. Phys., 16, 2575--2596, doi: 10.5194/acp-16-2575-2016, 2016

Abstract
Nitrogen oxides (NOx) have fallen steadily across the US over the last 15 years. At the same time, NOx concentrations decrease on weekends relative to weekdays, largely without co-occurring changes in other gas-phase emissions, due to patterns of diesel truck activities. These trends taken together provide two independent constraints on the role of NOx in the nonlinear chemistry of atmospheric oxidation. In this context, we interpret interannual trends in wintertime ammonium nitrate (NH4NO3) in the San Joaquin Valley of California, a location with the worst aerosol pollution in the US and where a large portion of aerosol mass is NH4NO3. Here, we show that NOx reductions have simultaneously decreased nighttime and increased daytime NH4NO3 production over the last decade. We find a substantial decrease in NH4NO3 since 2000 and conclude that this decrease is due to reduced nitrate radical-initiated production at night in residual layers that are decoupled from fresh emissions at the surface. Further reductions in NOx are imminent in California, and nationwide, and we make a quantitative prediction of the response of NH4NO3. We show that the combination of rapid chemical production and efficient NH4NO3 loss via deposition of gas-phase nitric acid implies that high aerosol days in cities in the San Joaquin Valley air basin are responsive to local changes in NOx within those individual cities. Our calculations indicate that large decreases in NOx in the future will not only lower wintertime NH4NO3 concentrations but also cause a transition in the dominant NH4NO3 source from nighttime to daytime chemistry.

2013

Laughner, J. L.. "Virtual Evolving and Self-Producing Rapid Audio (V.E.S.P.R.A.)." Link, , 2013.

Abstract

Laughner, J. L.. "Synthesis and Transport Studies of a Delivery Mechanism for Oxidative in-situ Remediation of Groundwater." Link, , 2013.

Abstract
 
   
 
https://orcid.org/0000-0002-8599-4555