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Abstract Building upon recent advancements in AI‐driven atmospheric emulation, we present a novel framework for AI‐based ocean emulation, downscaling, and bias correction, with a specific focus on high‐resolution modeling of the regional ocean in the Gulf of Mexico. Emulating regional ocean dynamics poses distinct challenges due to intricate bathymetry, complex lateral boundary conditions, and inherent limitations of deep learning models, including instability and the potential for hallucinations. In this study, we introduce a deep learning framework that autoregressively integrates ocean surface variables at 8 km spatial resolution over the Gulf of Mexico, maintaining physical consistency over decadal time scales. Simultaneously, the framework downscales and bias‐corrects the outputs to 4 km resolution using a physics‐informed generative model. Our approach demonstrates short‐term predictive skill comparable to high‐resolution physics‐based simulations, while also accurately capturing long‐term statistical properties, including temporal mean and variability. 

Dinitrogen is a challenging molecule to reduce to useful products under ambient conditions. The range of d-block metal complexes that can catalyze dinitrogen reduction to ammonia or tris(silyl)amines under ambient conditions has increased recently but lacks electropositive metal complexes, such as those of the f-block, which lack filled d-orbitals that would support classical binding modes of N2. Here, metallacyclic phenolate structures with lanthanide or group 4 cations can bind dinitrogen and catalyze its conversion to bis(silyl)amines under ambient conditions. The formation of this unusual product is controlled by metallacycle sterics. The group 4 complexes featuring small cavities are most selective for bis(silyl)amine, while lanthanide complexes and the solvated uranium(IV) congener, with larger cavities, can also make a conventional tris(silyl)amine product. These results offer new catalytic applications for plentiful titanium and more earth-abundant members of the lanthanides that are also less toxic than many base metals used in catalysis. 

Abstract. Dry deposition is a key process for surface ozone(O3) removal. Stomatal uptake is a major component of O3 drydeposition, which is parameterized differently in current land surfacemodels and chemical transport models. We developed and used a standaloneterrestrial biosphere model, driven by a unified set of prescribedmeteorology, to evaluate two widely used dry deposition modeling frameworks,Wesely (1989) and Zhang et al. (2003), with different configurations ofstomatal resistance: (1) the default multiplicative method in the Weselyscheme (W89) and Zhang et al. (2003) scheme (Z03), (2) the traditionalphotosynthesis-based Farquhar–Ball–Berry (FBB) stomatal algorithm, and (3) theMedlyn stomatal algorithm (MED) based on optimization theory. We found thatusing the FBB stomatal approach that captures ecophysiological responses toenvironmental factors, especially to water stress, can generally improve thesimulated dry deposition velocities compared with multiplicative schemes.The MED stomatal approach produces higher stomatal conductance than FBB andis likely to overestimate dry deposition velocities for major vegetationtypes, but its performance is greatly improved when spatially varying slopeparameters based on annual mean precipitation are used. Large discrepancieswere also found in stomatal responses to rising CO2 levels from 390to 550 ppm: the multiplicative stomatal method with an empirical CO2response function produces reduction (−35 %) in global stomatalconductance on average much larger than that with the photosynthesis-basedstomatal method (−14 %–19 %). Our results show the potential biases inO3 sink caused by errors in model structure especially in the Weselydry deposition scheme and the importance of using photosynthesis-basedrepresentation of stomatal resistance in dry deposition schemes under achanging climate and rising CO2 concentration. 

Abstract. Our work explores the impact of two important dimensions of landsystem changes, land use and land cover change (LULCC) as well as directagricultural reactive nitrogen (Nr) emissions from soils, on ozone(O3) and fine particulate matter (PM2.5) in terms of air quality overcontemporary (1992 to 2014) timescales. We account for LULCC andagricultural Nr emissions changes with consistent remote sensingproducts and new global emission inventories respectively estimating theirimpacts on global surface O3 and PM2.5 concentrations as well as Nrdeposition using the GEOS-Chem global chemical transport model. Over thistime period, our model results show that agricultural Nr emissionchanges cause a reduction of annual mean PM2.5 levels over Europe andnorthern Asia (up to −2.1 µg m−3) while increasing PM2.5 levels in India, China and the eastern US (up to +3.5 µg m−3). Land cover changes induce small reductions in PM2.5 (up to −0.7 µg m−3) over Amazonia, China and India due to reduced biogenic volatile organic compound (BVOC) emissions and enhanced deposition of aerosol precursor gases (e.g., NO2, SO2). Agricultural Nr emissionchanges only lead to minor changes (up to ±0.6 ppbv) in annual meansurface O3 levels, mainly over China, India and Myanmar. Meanwhile, ourmodel result suggests a stronger impact of LULCC on surface O3 over the time period across South America; the combination of changes in drydeposition and isoprene emissions results in −0.8 to +1.2 ppbv surfaceozone changes. The enhancement of dry deposition reduces the surface ozone level (up to −1 ppbv) over southern China, the eastern US and central Africa. The enhancement of soil NO emission due to crop expansion also contributes to surface ozone changes (up to +0.6 ppbv) over sub-Saharan Africa. Incertain regions, the combined effects of LULCC and agricultural Nr emission changes on O3 and PM2.5 air quality can be comparable (>20 %) to anthropogenic emission changes over the same time period. Finally, we calculate that the increase in global agricultural Nr emissions leads to a net increase in global land area (+3.67×106km2) that potentially faces exceedance of the critical Nr load (>5 kg N ha−1 yr−1). Our result demonstrates the impacts of contemporary LULCC and agricultural Nr emission changes on PM2.5 and O3 in terms of air quality, as well as the importanceof land system changes for air quality over multidecadal timescales. 

We report the facile activation of aryl E–H (ArEH; E = N, O, S; Ar = Ph or C 6 F 5 ) or ammonia N–H bonds via coordination-induced bond weakening to a redox-active boron center in the complex, (1 − ). Substantial decreases in E–H bond dissociation free energies (BDFEs) are observed upon substrate coordination, enabling subsequent facile proton-coupled electron transfer (PCET). A drop of >50 kcal mol −1 in H 2 N–H BDFE upon coordination was experimentally determined. 

Abstract Reductions in anthropogenic emissions have drawn increasing attention to the role of the biosphere in O₃production chemistry in U.S. cities. We report the results of chemical transport model sensitivity simulations exploring the relative impacts of biogenic isoprene and soil nitrogen oxides (NOx) emissions on O₃and its temporal variability. We compare scenarios with high and low anthropogenic NOx emissions representing the reductions that have occurred in recent decades. As expected, summertime O₃concentrations become less sensitive to perturbations in biogenic isoprene emissions as anthropogenic NOx emissions decline. However, we demonstrate for the first time that across policy relevant O₃nonattainment areas of the United States, O₃becomes more sensitive to perturbations in soil NOx emissions than to identical perturbations in isoprene emissions. We show that interannual variability in soil NOx emissions may now have larger impacts on interannual O₃variability than isoprene emissions in many areas where the latter would have dominated in the recent past. 

Abstract We report the facile and efficient synthesis of common electrophilic haloboranes via a protonolysis reaction between Piers’ borane, HB(C₆F₅)₂, and H−X (X=Cl, Br). This route benefits from fast reaction times, easy setup, and minimal workup to yield the analytically pure etherates, (C₆F₅)₂BCl(OEt₂) (1) and (C₆F₅)₂BBr(OEt₂) (2), as well as the ether‐free tri‐coordinate species, (C₆F₅)₂BBr (3).