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We describe a new 4D-Var inversion framework for N2O based on the GEOS-Chem chemical transport model and its adjoint, and apply this framework in a series of observing system simulation experiments to assess how well N2O sources and sinks can be constrained by the current global observing network. The employed measurement ensemble includes approximately weekly and quasi-continuous N2O measurements (hourly averages used) from several long-term monitoring networks, N2O measurements collected from discrete air samples aboard a commercial aircraft (CARIBIC), and quasi-continuous measurements from an airborne pole-to-pole sampling campaign (HIPPO). For a two-year inversion, we find that the surface and HIPPO observations can accurately resolve a uniform bias in emissions during the first year; CARIBIC data provide a somewhat weaker constraint. Variable emission errors are much more difficult to resolve given the long lifetime of N2O, and major parts of the world lack significant constraints on the seasonal cycle of fluxes. Current observations can largely correct a global bias in the stratospheric sink of N2O if emissions are known, but do not provide information on the temporal and spatial distribution of the sink. However, for the more realistic scenario where source and sink are both uncertain, we find that simultaneously optimizing both would require unrealistically small errors in model transport. Regardless, a bias in the magnitude of the N2O sink would not affect the a posteriori N2O emissions for the two-year timescale used here, given realistic initial conditions, due to the timescale required for stratosphere-troposphere exchange (STE). The same does not apply to model errors in the rate of STE itself, which we show exerts a larger influence on the tropospheric burden of N2O than does the chemical loss rate over short (< 3 year) timescales. We use a stochastic estimate of the inverse Hessian for the inversion to evaluate the spatial resolution of emission constraints provided by the observations, and find that significant, spatially explicit constraints can be achieved in locations near and immediately upwind of surface measurements and the HIPPO flight tracks; however, these are mostly confined to North America, Europe, and Australia. None of the current observing networks are able to provide significant spatial information on tropical N2O emissions. There, averaging kernels are highly smeared spatially and extend even to the midlatitudes, so that tropical emissions risk being conflated with those elsewhere. For global inversions, therefore, the current lack of constraints on the tropics also places an important limit on our ability to understand extratropical emissions. Based on the error reduction statistics from the inverse Hessian, we characterize the atmospheric distribution of unconstrained N2O, and identify regions in and downwind of South America, Central Africa, and Southeast Asia where new surface or profile measurements would have the most value for reducing present uncertainty in the global N2O budget. [ABSTRACT FROM AUTHOR]

The wealth of air quality information provided by satellite infrared observations of ammonia (NH3), carbon monoxide (CO), formic acid (HCOOH), and methanol (CH3OH) is currently being explored and used for number of applications, especially at regional or global scales. These applications include air quality monitoring, trend analysis, emissions, and model evaluation. This study provides one of the first direct validations of Tropospheric Emission Spectrometer (TES) satellite retrieved profiles of NH3, CH3OH, and HCOOH through comparisons with coincident aircraft profiles. The comparisons are performed over the Canadian oil sands region during the intensive field campaign (August-September 2013) in support of the Joint Canada-Alberta Implementation Plan for the Oil Sands Monitoring (JOSM). The satellite/aircraft comparisons over this region during this period produced errors of: (i) +0.08±0.25 ppbv for NH3, (ii) +7.5±23 ppbv for CO, (iii) +0.19±0.46 ppbv for HCOOH, and (iv) -1.1±0.39 ppbv for CH3OH. These values mostly agree with previously estimated retrieval errors; however, the relatively large negative bias in CH3OH and the significantly greater positive bias for larger HCOOH and CO values observed during this study warrant further investigation. Satellite and aircraft ammonia observations during the field campaign are also used in an initial effort to perform preliminary evaluations of Environment Canada's Global Environmental Multi-scale - Modelling Air quality and CHemistry (GEM-MACH) air quality mod elling system at high-resolution (2.5km×2.5 km). These initial results indicate model under-prediction of ~ 0.6 ppbv (~ 60 %) for NH3, during the field campaign period. The TES-model CO comparison differences are ~ +20 ppbv (~ +20 %), but given that under these conditions the TES/aircraft comparisons also show a small positive TES CO bias indicates that the overall model under-prediction of CO is closer to ~ 10% at 681 hPa (~ 3 km) during this period. [ABSTRACT FROM AUTHOR]

The Arctic is a climatically sensitive region that has experienced warming at almost 3 times the global average rate in recent decades, leading to an increase in Arctic greenness and a greater abundance of plants that emit biogenic volatile organic compounds (BVOCs). These changes in atmospheric emissions are expected to significantly modify the overall oxidative chemistry of the region and lead to changes in VOC composition and abundance, with implications for atmospheric processes. Nonetheless, observations needed to constrain our current understanding of these issues in this critical environment are sparse. This work presents novel atmospheric in situ proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS) measurements of VOCs at Toolik Field Station (TFS; 68°38' N, 149°36' W), in the Alaskan Arctic tundra during May-June 2019. We employ a custom nested grid version of the GEOS-Chem chemical transport model (CTM), driven with MEGANv2.1 (Model of Emissions of Gases and Aerosols from Nature version 2.1) biogenic emissions for Alaska at 0.25° × 0.3125° resolution, to interpret the observations in terms of their constraints on BVOC emissions, total reactive organic carbon (ROC) composition, and calculated OH reactivity (OHr) in this environment. We find total ambient mole fraction of 78 identified VOCs to be 6.3 ± 0.4 ppbv (10.8 ± 0.5 ppbC), with overwhelming (> 80 %) contributions are from short-chain oxygenated VOCs (OVOCs) including methanol, acetone and formaldehyde. Isoprene was the most abundant terpene identified. GEOS-Chem captures the observed isoprene (and its oxidation products), acetone and acetaldehyde abundances within the combined model and observation uncertainties (±25 %), but underestimates other OVOCs including methanol, formaldehyde, formic acid and acetic acid by a factor of 3 to 12. The negative model bias for methanol is attributed to underestimated biogenic methanol emissions for the Alaskan tundra in MEGANv2.1. Observed formaldehyde mole fractions increase exponentially with air temperature, likely reflecting its biogenic precursors and pointing to a systematic model underprediction of its secondary production. The median campaign-calculated OHr from VOCs measured at TFS was 0.7 s -1 , roughly 5 % of the values typically reported in lower-latitude forested ecosystems. Ten species account for over 80 % of the calculated VOC OHr, with formaldehyde, isoprene and acetaldehyde together accounting for nearly half of the total. Simulated OHr based on median-modeled VOCs included in GEOS-Chem averages 0.5 s -1 and is dominated by isoprene (30 %) and monoterpenes (17 %). The data presented here serve as a critical evaluation of our knowledge of BVOCs and ROC budgets in high-latitude environments and represent a foundation for investigating and interpreting future warming-driven changes in VOC emissions in the Alaskan Arctic tundra., Competing Interests: Competing interests. The contact author has declared that none of the authors has any competing interests.

India is an air pollution mortality hot spot, but regional emissions are poorly understood. We present a high-resolution nested chemical transport model (GEOS-Chem) simulation for the Indian subcontinent and use it to interpret formaldehyde (HCHO) observations from two satellite sensors (OMI and GOME-2A) in terms of constraints on regional volatile organic compound (VOC) emissions. We find modeled biogenic VOC emissions to be overestimated by ~30-60% for most locations and seasons, and derive a best estimate biogenic flux of 16 Tg C/year subcontinent-wide for year 2009. Terrestrial vegetation provides approximately half the total VOC flux in our base-case inversions (full uncertainty range: 44-65%). This differs from prior understanding, in which biogenic emissions represent >70% of the total. Our derived anthropogenic VOC emissions increase slightly (13-16% in the base case, for a subcontinent total of 15 Tg C/year in 2009) over RETRO year 2000 values, with some larger regional discrepancies. The optimized anthropogenic emissions agree well with the more recent CEDS inventory, both subcontinent-wide (within 2%) and regionally. An exception is the Indo-Gangetic Plain, where we find an underestimate for both RETRO and CEDS. Anthropogenic emissions thus constitute 37-50% of the annual regional VOC source in our base-case inversions and exceed biogenic emissions over the Indo-Gangetic Plain, West India, and South India, and over the entire subcontinent during winter and post-monsoon. Fires are a minor fraction (<7%) of the total regional VOC source in the prior and optimized model. However, evidence suggests that VOC emissions in the fire inventory used here (GFEDv4) are too low over the Indian subcontinent.

India is currently experiencing degraded air quality, and future economic development will lead to challenges for air quality management. Scenarios of sectoral emissions of fine particulate matter and its precursors were developed and evaluated for 2015-2050, under specific pathways of diffusion of cleaner and more energy-efficient technologies. The impacts of individual source sectors on PM 2.5 concentrations were assessed through systematic simulations of spatially and temporally resolved particulate matter concentrations, using the GEOS-Chem model, followed by population-weighted aggregation to national and state levels. We find that PM 2.5 pollution is a pan-India problem, with a regional character, and is not limited to urban areas or megacities. Under present-day emissions, levels in most states exceeded the national PM 2.5 annual standard (40 μg m -3 ). Sources related to human activities were responsible for the largest proportion of the present-day population exposure to PM 2.5 in India. About 60 % of India's mean population-weighted PM 2.5 concentrations come from anthropogenic source sectors, while the remainder are from "other" sources, windblown dust and extra-regional sources. Leading contributors are residential biomass combustion, power plant and industrial coal combustion and anthropogenic dust (including coal fly ash, fugitive road dust and waste burning). Transportation, brick production and distributed diesel were other contributors to PM 2.5 . Future evolution of emissions under regulations set at current levels and promulgated levels caused further deterioration of air quality in 2030 and 2050. Under an ambitious prospective policy scenario, promoting very large shifts away from traditional biomass technologies and coal-based electricity generation, significant reductions in PM 2.5 levels are achievable in 2030 and 2050. Effective mitigation of future air pollution in India requires adoption of aggressive prospective regulation, currently not formulated, for a three-pronged switch away from (i) biomass-fuelled traditional technologies, (ii) industrial coal-burning and (iii) open burning of agricultural residue. Future air pollution is dominated by industrial process emissions, reflecting larger expansion in industrial, rather than residential energy demand. However, even under the most active reductions envisioned, the 2050 mean exposure, excluding any impact from windblown mineral dust, is estimated to be nearly 3 times higher than the WHO Air Quality Guideline., Competing Interests: Competing interests. The authors declare that they have no conflict of interest.

Tropospheric aerosol optical depth (AOD) over India was simulated by Goddard Earth Observing System (GEOS)-Chem, a global 3-D chemical-transport model, using SMOG (Speciated Multi-pOllutant Generator from Indian Institute of Technology Bombay) and GEOS-Chem (GC) (current inventories used in the GEOS-Chem model) inventories for 2012. The simulated AODs were ~80% (SMOG) and 60% (GC) of those measured by the satellites (Moderate Resolution Imaging Spectroradiometer and Multi-angle Imaging SpectroRadiometer). There is no strong seasonal variation in AOD over India. The peak AOD values are observed/simulated during summer. The simulated AOD using SMOG inventory has particulate black and organic carbon AOD higher by a factor ~5 and 3, respectively, compared to GC inventory. The model underpredicted coarse-mode AOD but agreed for fine-mode AOD with Aerosol Robotic Network data. It captured dust only over Western India, which is a desert, and not elsewhere, probably due to inaccurate dust transport and/or noninclusion of other dust sources. The calculated AOD, after dust correction, showed the general features in its observed spatial variation. Highest AOD values were observed over the Indo-Gangetic Plain followed by Central and Southern India with lowest values in Northern India. Transport of aerosols from Indo-Gangetic Plain and Central India into Eastern India, where emissions are low, is significant. The major contributors to total AOD over India are inorganic aerosol (41-64%), organic carbon (14-26%), and dust (7-32%). AOD over most regions of India is a factor of 5 or higher than over the United States.