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Abstract. Accurate representation of the hourly variation in the NO2-column-to-surface relationship is essential for interpreting geostationary observations of NO2 columns. Previous research indicated inconsistencies in this hourly variation. This study employs the high-performance configuration of the GEOS-Chem model (GCHP) to analyze daytime hourly NO2 total columns and surface concentrations during summer. We use measurements from globally distributed Pandora sun photometers and aircraft observations over the United States. We correct Pandora total NO2 vertical columns for (1) hourly variations in effective temperature driven by vertically resolved contributions to the total column and (2) changes in local solar time along the Pandora line of sight. These corrections increase the total NO2 columns by 5–6 × 1014 molec. cm−2 at 09:00 and 18:00 across all sites. Fine-scale simulations from GHCP (∼12 km) reduce the normalized bias (NB) against Pandora total NO2 columns from 19 % to 10 % and against aircraft measurements from 25 % to 13 % in Maryland, Texas, and Colorado. Similar reductions are observed in NO2 columns over the eastern US (17 % to 9 %), the western US (22 % to 14 %), Europe (24 % to 15 %), and Asia (29 % to 21 %) when compared to 55 km simulations. Our analysis attributes the weaker hourly variability in the total NO2 column to (1) hourly variations in column effective temperature, (2) local solar time changes along the Pandora line of sight, and (3) differences in hourly NO2 variability from different atmospheric layers, with the lowest 500 m exhibiting greater variability, while the dominant residual column above 500 m exhibits weaker variability. 

Abstract. Solar-induced chlorophyll fluorescence (SIF) has previously been shown to strongly correlate with gross primary productivity (GPP); however this relationship has not yet been quantified for the recently launched TROPOspheric Monitoring Instrument (TROPOMI). Here we use a Gaussian mixture model to develop a parsimonious relationship between SIF from TROPOMI and GPP from flux towers across the conterminous United States (CONUS). The mixture model indicates the SIF–GPP relationship can be characterized by a linear model with two terms. We then estimate GPP across CONUS at 500 m spatial resolution over a 16 d moving window. We observe four extreme precipitation events that induce regional GPP anomalies: drought in western Texas, flooding in the midwestern US, drought in South Dakota, and drought in California. Taken together, these events account for 28 % of the year-to-year GPP differences across CONUS. Despite these large regional anomalies, we find that CONUS GPP varies by less than 4 % between 2018 and 2019. 

Background and Objectives: Prediction of decline to dementia using objective biomarkers in high-risk patients with amnestic mild cognitive impairment (aMCI) has immense utility. Our objective was to use multimodal MRI to (1) determine whether accurate and precise prediction of dementia conversion could be achieved using baseline data alone, and (2) generate a map of the brain regions implicated in longitudinal decline to dementia. Methods: Participants meeting criteria for aMCI at baseline ( N = 55) were classified at follow-up as remaining stable/improved in their diagnosis ( N = 41) or declined to dementia ( N = 14). Baseline T1 structural MRI and resting-state fMRI (rsfMRI) were combined and a semi-supervised support vector machine (SVM) which separated stable participants from those who decline at follow-up with maximal margin. Cross-validated model performance metrics and MRI feature weights were calculated to include the strength of each brain voxel in its ability to distinguish the two groups. Results: Total model accuracy for predicting diagnostic change at follow-up was 92.7% using baseline T1 imaging alone, 83.5% using rsfMRI alone, and 94.5% when combining T1 and rsfMRI modalities. Feature weights that survived the p < 0.01 threshold for separation of the two groups revealed the strongest margin in the combined structural and functional regions underlying the medial temporal lobes in the limbic system. Discussion: An MRI-driven SVM model demonstrates accurate and precise prediction of later dementia conversion in aMCI patients. The multi-modal regions driving this prediction were the strongest in the medial temporal regions of the limbic system, consistent with literature on the progression of Alzheimer’s disease. 

Abstract. Organic nitrate (RONO2) formation in the atmosphere represents a sink of NOx(NOx = NO + NO2) and termination of the NOx/HOx(HOx = HO2 + OH) ozone formation and radical propagation cycles, can act as a NOx reservoirtransporting reactive nitrogen, and contributes to secondary organic aerosol formation. While some fraction of RONO2 is thought to reside in the particle phase, particle-phase organic nitrates (pRONO2) are infrequently measured and thus poorly understood. There is anincreasing prevalence of aerosol mass spectrometer (AMS) instruments, which have shown promise for determining the quantitative total organic nitratefunctional group contribution to aerosols. A simple approach that relies on the relative intensities of NO+ and NO2+ ions inthe AMS spectrum, the calibrated NOx+ ratio for NH4NO3, and the inferred ratio for pRONO2 hasbeen proposed as a way to apportion the total nitrate signal to NH4NO3 and pRONO2. This method is increasingly beingapplied to field and laboratory data. However, the methods applied have been largely inconsistent and poorly characterized, and, therefore, adetailed evaluation is timely. Here, we compile an extensive survey of NOx+ ratios measured for variouspRONO2 compounds and mixtures from multiple AMS instruments, groups, and laboratory and field measurements. All data and analysispresented here are for use with the standard AMS vaporizer. We show that, in the absence of pRONO2 standards, thepRONO2 NOx+ ratio can be estimated using a ratio referenced to the calibrated NH4NO3 ratio, aso-called “Ratio-of-Ratios” method (RoR = 2.75 ± 0.41). We systematically explore the basis for quantifyingpRONO2 (and NH4NO3) with the RoR method using ground and aircraft field measurements conducted over a largerange of conditions. The method is compared to another AMS method (positive matrix factorization, PMF) and other pRONO2 andrelated (e.g., total gas + particle RONO2) measurements, generally showing good agreement/correlation. A broad survey of ground andaircraft AMS measurements shows a pervasive trend of higher fractional contribution of pRONO2 to total nitrate with lower totalnitrate concentrations, which generally corresponds to shifts from urban-influenced to rural/remote regions. Compared to ground campaigns,observations from all aircraft campaigns showed substantially lower pRONO2 contributions at midranges of total nitrate(0.01–0.1 up to 2–5 µg m−3), suggesting that the balance of effects controlling NH4NO3 and pRONO2formation and lifetimes – such as higher humidity, lower temperatures, greater dilution, different sources, higher particle acidity, andpRONO2 hydrolysis (possibly accelerated by particle acidity) – favors lower pRONO2 contributions for thoseenvironments and altitudes sampled. 

Abstract. Gas-phase atmospheric concentrations of peroxyacetyl nitrate (PAN),peroxypropionyl nitrate (PPN), and peroxymethacryloyl nitrate (MPAN) weremeasured on the ground using a gas chromatograph electron capture detector(GC-ECD) during the Southern Oxidants and Aerosols Study (SOAS) 2013 campaign(1 June to 15 July 2013) in Centreville, Alabama, in order to studybiosphere–atmosphere interactions. Average levels of PAN, PPN, and MPAN were169, 5, and 9 pptv, respectively, and the sum accounts for an average of16 % of NO_y during the daytime (10:00 to 16:00 localtime). Higher concentrations were seen on average in air that came to thesite from the urban NO_x sources to the north. PAN levelswere the lowest observed in ground measurements over the past two decades inthe southeastern US. A multiple regression analysis indicates that biogenicvolatile organic compounds (VOCs) account for 66 % of PAN formationduring this study. Comparison of this value with a 0-D model simulation ofperoxyacetyl radical production indicates that at least 50 % of PANformation is due to isoprene oxidation. MPAN has a statistical correlationwith isoprene hydroxynitrates (IN). Organic aerosol mass increases withgas-phase MPAN and IN concentrations, but the mass of organic nitrates inparticles is largely unrelated to MPAN. 

Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales.This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts. 

Abstract. Oxidation of biogenic volatile organic compounds (BVOC) by the nitrate radical (NO₃) represents one of the important interactions between anthropogenic emissions related to combustion and natural emissions from the biosphere. This interaction has been recognized for more than 3 decades, during which time a large body of research has emerged from laboratory, field, and modeling studies. NO₃-BVOC reactions influence air quality, climate and visibility through regional and global budgets for reactive nitrogen (particularly organic nitrates), ozone, and organic aerosol. Despite its long history of research and the significance of this topic in atmospheric chemistry, a number of important uncertainties remain. These include an incomplete understanding of the rates, mechanisms, and organic aerosol yields for NO₃-BVOC reactions, lack of constraints on the role of heterogeneous oxidative processes associated with the NO₃ radical, the difficulty of characterizing the spatial distributions of BVOC and NO₃ within the poorly mixed nocturnal atmosphere, and the challenge of constructing appropriate boundary layer schemes and non-photochemical mechanisms for use in state-of-the-art chemical transport and chemistry–climate models. This review is the result of a workshop of the same title held at the Georgia Institute of Technology in June 2015. The first half of the review summarizes the current literature on NO₃-BVOC chemistry, with a particular focus on recent advances in instrumentation and models, and in organic nitrate and secondary organic aerosol (SOA) formation chemistry. Building on this current understanding, the second half of the review outlines impacts of NO₃-BVOC chemistry on air quality and climate, and suggests critical research needs to better constrain this interaction to improve the predictive capabilities of atmospheric models. 

Abstract We present a comparison of instruments measuring nitrogen oxide species from an aircraft during the 2015 Wintertime INvestigation of Transport, Emissions, and Reactivity (WINTER) campaign over the northeast United States. Instrument techniques compared here include chemiluminescence (CL), thermal dissociation laser‐induced fluorescence (TD‐LIF), cavity ring‐down spectroscopy (CRDS), high‐resolution time of flight, iodide‐adduct chemical ionization mass spectrometry (I^‐CIMS), and aerosol mass spectrometry. Species investigated include NO₂, NO, total nitrogen oxides (NO_y), N₂O₅, ClNO₂, and HNO₃. Particulate‐phase nitrate is also included for comparisons of HNO₃and NO_y. Instruments generally agreed within reported uncertainties, with individual flights sometimes showing much better agreement than the data set taken as a whole, due to flight‐to‐flight slope changes. NO measured by CRDS and CL showed an average relative slope of 1.16 ± 0.01 across all flights, which is outside of combined uncertainties. The source of the error was not identified. For NO₂measured by CRDS and TD‐LIF the average was 1.02 ± 0.00; for NO_ymeasured by CRDS and CL the average was 1.01 ± 0.00; and for N₂O₅measured by CRDS and I^‐CIMS the average was 0.89 ± 0.01. NO_ybudget closure to within 20% is demonstrated. We observe nonlinearity in NO₂and NO_ycorrelations at concentrations above ~30 ppbv that may be related to the NO discrepancy noted above. For ClNO₂there were significant differences between I^‐CIMS and TD‐LIF, potentially due in part to the temperature used for thermal dissociation. Although the fraction of particulate nitrate measured by the TD‐LIF is not well characterized, it improves comparisons to include particulate measurements.