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Changes in neuronal inhibition have been implicated in age-related declines in sensorimotor performance. While indirect evidence suggests that inhibitory mechanisms are also involved in rhythm entrainment, this association has not been tested. Using magnetic resonance spectroscopy, we tested the association between dorsomedial frontal GABA+/H2O concentrations and musical rhythm production in healthy younger (n = 14; 18-35) and older (n = 12; 55-79) adults, hypothesizing that lower GABA+/H2O concentrations would be associated with increased timing error, particularly on more difficult exercises, and intra-individual variability (quantified via mean successive squared difference (MSSD)). Rhythm learning exercises were presented in order of complexity. Linear mixed effects modeling revealed GABA+/H2O-by-exercise number interaction (β = -0.59, p = 0.006) such that participants with lower GABA+/H2O showed greater performance decrement with increasing exercise difficulty. GABA+/H2O trended toward an inverse association with MSSD (β = -0.25, p = 0.089), such that higher GABA+/H2O was associated with lower variability in performance. Older age was associated with increased absolute timing error (β = 0.66, p

Cities represent a significant and growing portion of global carbon dioxide (CO2) emissions. Quantifying urban emissions and trends over time is needed to evaluate the efficacy of policy targeting emission reductions as well as to understand more fundamental questions about the urban biosphere. A number of approaches have been proposed to measure, report, and verify (MRV) changes in urban CO2 emissions. Here we show that a modest capital cost, spatially dense network of sensors, the Berkeley Environmental Air Quality and CO2 Network (BEACO2N), in combination with Bayesian inversions, result in a synthesis of measured CO2 concentrations and meteorology to yield an improved estimate of CO2 emissions and provide a cost-effective and accurate assessment of CO2 emissions trends over time. We describe nearly 5 years of continuous CO2 observations (2018-2022) in a midsized urban region (the San Francisco Bay Area). These observed concentrations constrain a Bayesian inversion that indicates the interannual trend in urban CO2 emissions in the region has been a modest decrease at a rate of 1.8 ± 0.3%/year. We interpret this decrease as primarily due to passenger vehicle electrification, reducing on-road emissions at a rate of 2.6 ± 0.7%/year.

Brain aging and common conditions of aging (e.g., hypertension) affect networks important in organizing information, processing speed and action programming (i.e., executive functions). Declines in these networks may affect timing and could have an impact on the ability to perceive and perform musical rhythms. There is evidence that participation in rhythmic musical activities may help to maintain and even improve executive functioning (near transfer), perhaps due to similarities in brain regions underlying timing, musical rhythm perception and production, and executive functioning. Rhythmic musical activities may present as a novel and fun activity for older adults to stimulate interacting brain regions that deteriorate with aging. However, relatively little is known about neurobehavioral interactions between aging, timing, rhythm perception and production, and executive functioning. In this review, we account for these brain-behavior interactions to suggest that deeper knowledge of overlapping brain regions associated with timing, rhythm, and cognition may assist in designing more targeted preventive and rehabilitative interventions to reduce age-related cognitive decline and improve quality of life in populations with neurodegenerative disease. Further research is needed to elucidate the functional relationships between brain regions associated with aging, timing, rhythm perception and production, and executive functioning to direct design of targeted interventions.

The extent to which emission control technologies and policies have reduced anthropogenic NOx emissions from motor vehicles is large but uncertain. We evaluate a fuel-based emission inventory for southern California during the June 2021 period, coinciding with the Re-Evaluating the Chemistry of Air Pollutants in CAlifornia (RECAP-CA) field campaign. A modified version of the Fuel-based Inventory of Vehicle Emissions (FIVE) is presented, incorporating 1.3 km resolution gridding and a new light-/medium-duty diesel vehicle category. NOx concentrations and weekday-weekend differences were predicted using the WRF-Chem model and evaluated using satellite and aircraft observations. Model performance was similar on weekdays and weekends, indicating appropriate day-of-week scaling of NOx emissions and a reasonable distribution of emissions by sector. Large observed weekend decreases in NOx are mainly due to changes in on-road vehicle emissions. The inventory presented in this study suggests that on-road vehicles were responsible for 55-72% of the NOx emissions in the South Coast Air Basin, compared to the corresponding fraction (43%) in the planning inventory from the South Coast Air Quality Management District. This fuel-based inventory suggests on-road NOx emissions that are 1.5 ± 0.4, 2.8 ± 0.6, and 1.3 ± 0.7 times the reference EMFAC model estimates for on-road gasoline, light- and medium-duty diesel, and heavy-duty diesel, respectively.

Los Angeles is a major hotspot for ozone and particulate matter air pollution in the United States. Ozone and PM2.5 in this region have not improved substantially for the past decade, despite a reduction in vehicular emissions of their precursors, NOx and volatile organic compounds (VOCs). This reduction in traditional sources has made the current emission mixture of air pollutant precursors more uncertain. To map and quantify emissions of a wide range of VOCs in this urban area, we performed airborne eddy covariance measurements with wavelet analysis. VOC fluxes measured include tracers for source categories, such as traffic, vegetation, and volatile chemical products (VCPs). Mass fluxes were dominated by oxygenated VOCs, with ethanol contributing ∼29% of the total. In terms of OH reactivity and aerosol formation potential, terpenoids contributed more than half. Observed fluxes were compared with two commonly used emission inventories: the California Air Resources Board inventory and the combination of the Biogenic Emission Inventory System with the Fuel-based Inventory of Vehicle Emissions combined with Volatile Chemical Products (FIVE-VCP). The comparison shows mismatches regarding the amount, spatial distribution, and weekend effects of observed VOC emissions with the inventories. The agreement was best for typical transportation related VOCs, while discrepancies were larger for biogenic and VCP-related VOCs.

ConspectusThe atmosphere-biosphere exchange of nitrogen oxides plays a key role in determining the composition of reactive nitrogen in terrestrial vegetated environments. The emission of nitric oxide (NO) from soils is an important atmospheric source of reactive nitrogen. NO is rapidly interconverted with NO2, making up the chemical family NOx (NOx ≡ NO2 + NO). NOx further reacts with the oxidation products of volatile organic compounds (VOCs) to form the functionalized nitrogen oxide groups acyl peroxynitrates (APNs = R(O)O2NO2) and alkyl nitrates (ANs = RONO2). Both canopy-level field measurements and laboratory studies suggest that the absorption of nitrogen dioxide NO2 and APNs by vegetation is a significant sink of atmospheric NOx, removing a large fraction of global soil-emitted NOx and providing key control on the amounts and lifetimes of NOx and reactive nitrogen in the atmosphere. Nitrogen oxides influence the production of surface O3 and secondary aerosols. The balance of the emission and uptake of nitrogen oxides thus provides a mechanism for the regulation of regional air quality. The biosphere, via this biogeochemical cycling of nitrogen oxides, is becoming an increasingly important determining factor for airborne pollutants as much of the world continues to reduce the amount of combustion-related nitrogen oxide emissions. Understanding the function of the biosphere as a source and sink of reactive nitrogen is therefore ever more critical in evaluating the effects of future and current emissions of nitrogen oxides on human and ecosystem health.Laboratory measurements of the foliar deposition of NO2 and other reactive nitrogen species suggest that there is a substantial diversity of uptake rates under varying environmental conditions and for different species of vegetation that is not currently reflected in the widely utilized chemical transport models. Our branch chamber measurements on a wide variety of North American tree species highlight the variability in the rates of both photosynthesis and nitrogen oxide deposition among several different nitrogen oxide compounds. Box-modeling and satellite measurement approaches demonstrate how disparities between our understanding of nitrogen oxide foliar exchange in the laboratory and what is represented in models can lead to misrepresentations of the net ecosystem exchange of nitrogen. This has important implications for assumptions of in-canopy chemistry, soil emissions of NO, canopy reductions of NOx, lifetimes of trace gases, and the impact of the biosphere on air quality.

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.

Urban regions emit a large fraction of anthropogenic emissions of greenhouse gases (GHG) such as carbon dioxide (CO2) and methane (CH4) that contribute to modern-day climate change. As such, a growing number of urban policymakers and stakeholders are adopting emission reduction targets and implementing policies to reach those targets. Over the past two decades research teams have established urban GHG monitoring networks to determine how much, where, and why a particular city emits GHGs, and to track changes in emissions over time. Coordination among these efforts has been limited, restricting the scope of analyses and insights. Here we present a harmonized data set synthesizing urban GHG observations from cities with monitoring networks across North America that will facilitate cross-city analyses and address scientific questions that are difficult to address in isolation.

The role of anthropogenic NOx emissions in secondary organic aerosol (SOA) production is not fully understood but is important for understanding the contribution of emissions to air quality. Here, we examine the role of organic nitrates (RONO2) in SOA formation over the Korean Peninsula during the Korea-United States Air Quality field study in Spring 2016 as a model for RONO2 aerosol in cities worldwide. We use aircraft-based measurements of the particle phase and total (gas + particle) RONO2 to explore RONO2 phase partitioning. These measurements show that, on average, one-fourth of RONO2 are in the condensed phase, and we estimate that ≈15% of the organic aerosol (OA) mass can be attributed to RONO2. Furthermore, we observe that the fraction of RONO2 in the condensed phase increases with OA concentration, evidencing that equilibrium absorptive partitioning controls the RONO2 phase distribution. Lastly, we model RONO2 chemistry and phase partitioning in the Community Multiscale Air Quality modeling system. We find that known chemistry can account for one-third of the observed RONO2, but there is a large missing source of semivolatile, anthropogenically derived RONO2. We propose that this missing source may result from the oxidation of semi- and intermediate-volatility organic compounds and/or from anthropogenic molecules that undergo autoxidation or multiple generations of OH-initiated oxidation.

Observations of winds in the planetary boundary layer remain sparse making it challenging to simulate and predict atmospheric conditions that are most important for describing and predicting urban air quality. Short-lived chemicals are observed as plumes whose location is affected by boundary layer winds and whose lifetime is affected by boundary layer height and mixing. Here we investigate the application of data assimilation of NO2 columns as will be observed from geostationary orbit to improve predictions and retrospective analysis of wind fields in the boundary layer.

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 500ĝ€¯m spatial resolution over a 16ĝ€¯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 28ĝ€¯% of the year-to-year GPP differences across CONUS. Despite these large regional anomalies, we find that CONUS GPP varies by less than 4ĝ€¯% between 2018 and 2019.

NASA's Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ, conducted in 2011-2014) campaign in the United States and the joint NASA and National Institute of Environmental Research (NIER) Korea-United States Air Quality Study (KORUS-AQ, conducted in 2016) in South Korea were two field study programs that provided comprehensive, integrated datasets of airborne and surface observations of atmospheric constituents, including nitrogen dioxide (NO2), with the goal of improving the interpretation of spaceborne remote sensing data. Various types of NO2 measurements were made, including in situ concentrations and column amounts of NO2 using ground- and aircraft-based instruments, while NO2 column amounts were being derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This study takes advantage of these unique datasets by first evaluating in situ data taken from two different instruments on the same aircraft platform, comparing coincidently sampled profile-integrated columns from aircraft spirals with remotely sensed column observations from ground-based Pandora spectrometers, intercomparing column observations from the ground (Pandora), aircraft (in situ vertical spirals), and space (OMI), and evaluating NO2 simulations from coarse Global Modeling Initiative (GMI) and high-resolution regional models. We then use these data to interpret observed discrepancies due to differences in sampling and deficiencies in the data reduction process. Finally, we assess satellite retrieval sensitivity to observed and modeled a priori NO2 profiles. Contemporaneous measurements from two aircraft instruments that likely sample similar air masses generally agree very well but are also found to differ in integrated columns by up to 31.9 %. These show even larger differences with Pandora, reaching up to 53.9 %, potentially due to a combination of strong gradients in NO2 fields that could be missed by aircraft spirals and errors in the Pandora retrievals. OMI NO2 values are about a factor of 2 lower in these highly polluted environments due in part to inaccurate retrieval assumptions (e.g., a priori profiles) but mostly to OMI's large footprint (> 312 km2).

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.

Solar-induced chlorophyll fluorescence (SIF) has been shown to be a powerful proxy for photosynthesis and gross primary productivity (GPP). The recently launched TROPOspheric Monitoring Instrument (TROPOMI) features the required spectral resolution and signal-to-noise ratio to retrieve SIF from space. Here, we present a downscaling method to obtain 500 m spatial resolution SIF over California. We report daily values based on a 14 d window. TROPOMI SIF data show a strong correspondence with daily GPP estimates at AmeriFlux sites across multiple ecosystems in California. We find a linear relationship between SIF and GPP that is largely invariant across ecosystems with an intercept that is not significantly different from zero. Measurements of SIF from TROPOMI agree with MODerate Resolution Imaging Spectroradiometer (MODIS) vegetation indices - the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and near-infrared reflectance of vegetation index (NIRv) - at annual timescales but indicate different temporal dynamics at monthly and daily timescales. TROPOMI SIF data show a double peak in the seasonality of photosynthesis, a feature that is not present in the MODIS vegetation indices. The different seasonality in the vegetation indices may be due to a clear-sky bias in the vegetation indices, whereas previous work has shown SIF to have a low sensitivity to clouds and to detect the downregulation of photosynthesis even when plants appear green. We further decompose the spatiotemporal patterns in the SIF data based on land cover. The double peak in the seasonality of California's photosynthesis is due to two processes that are out of phase: grasses, chaparral, and oak savanna ecosystems show an April maximum, while evergreen forests peak in June. An empirical orthogonal function (EOF) analysis corroborates the phase offset and spatial patterns driving the double peak. The EOF analysis further indicates that two spatiotemporal patterns explain 84 % of the variability in the SIF data. Results shown here are promising for obtaining global GPP at sub-kilometer spatial scales and identifying the processes driving carbon uptake.

NO x lifetime relates nonlinearly to its own concentration; therefore, by observing how NO x 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 NO x lifetime in approximately 30 North American cities has changed between 2005 and 2014 in a manner consistent with our understanding of NO x chemistry.

Organic nitrates contribute significantly to the total organic aerosol burden. However, the formation and loss mechanisms of particulate organic nitrates (PONs) remain poorly understood. In this study, with the CMAQ modeling system, we implement a detailed biogenic volatile organic carbon gas phase oxidation mechanism and an explicit representation of multiphase organic nitrate formation and loss, including both aqueous-phase uptake and vapor-pressure driven partitioning into organic aerosol as well as condensed-phase reactions. We find vapor-pressure dependent partitioning is the leading mechanism for formation of PONs and hydrolysis is a major loss mechanism for PON resulting in substantial amounts of organic aerosol that originate as an organic nitrate. Partitioning and hydrolysis together can produce high concentrations (up to 5 μg/m3) of PON-derived aerosols over the southeast United States. The main source of PON-derived aerosols is monoterpene nitrates that have been chemically processed to lose their nitrate functionality through aqueous chemistry. In contrast, the major portion of aqueous aerosol and in-cloud PON, which retains its nitrate moiety, are soluble isoprene nitrates. We evaluate the model using the observations from the Southern Oxidant and Aerosol Study (SOAS) campaign in the Southeast US in summer 2013 and show implementing aerosol-phase pathways for organic nitrates dramatically improves the magnitude of total alkyl nitrates (ANs) in CMAQ. The contribution of PONs to the total ANs at the SOAS site is estimated to be ~20%, a value in the range of the measurements. The predicted AN composition is shifted from monoterpene to isoprene and anthropogenic organic nitrates.

BackgroundThe long-term effects of marijuana on cognition, particularly in the context of HIV is not clear, as extant research shows mixed findings.ObjectiveTo determine associations between current and cumulative exposure to marijuana and changes in cognitive processing speed and flexibility in 788 HIV-seropositive (HIV+) and 1,132 HIV-seronegative (HIV-) men followed for up to 17 years in the Multicenter AIDS Cohort Study.ResultsAmong HIV+ men only, current daily marijuana use compared to none-use, was significantly associated with a greater annual percentage decline in cognitive processing speed assessed with the Trail Making Test A (TMTA) (β=-0.41, 95% confidence interval (CI): -0.88, -0.03, p=0.03)] and Symbol Digit Modalities Test (SDMT) (β= -0.14, 95% CI: -0.28, -0.01, p=0.04). Further, monthly marijuana use was associated with greater annual percentage decline in cognitive flexibility assessed with the Trail Making Test B (TMTB) (β= -0.70, 95% CI: -1.34, -0.05; p=0.03] and cognitive processing speed (SDMT) (β= -0.21, 95% CI: -0.40, -0.01, p=0.03). Among the HIV- men only, each 5-marijuana use-years (equivalent to 5-years of daily marijuana use) was significantly associated with a 0.17 annual percentage decline in cognitive processing speed only (TMTA) (β= -0.18, 95% CI: -0.36, -0.01; p=0.04).ConclusionsOur findings suggest that marijuana use, particularly current use, may be associated with worse cognitive processing speed, but the magnitude of the estimates was not clinically meaningful.

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 FROM AUTHOR]