Quantifying NOx point sources with Landsat and Sentinel-2 satellite observations of NO2 plumes.

We show that the Landsat and Sentinel-2 satellites can detect NO2 plumes from large point sources at 10 to 60 m pixel resolution in their blue and ultrablue bands. We use the resulting NO2 plume imagery to quantify nitrogen oxides (NOx) emission rates for several power plants in Saudi Arabia and the United States, including a 13-y analysis of 132 Landsat plumes from Riyadh power plant 9 from 2009 through 2021. NO2 in the plumes initially increases with distance from the source, likely reflecting recovery from ozone titration. The fine pixel resolutions of Landsat and Sentinel-2 enable separation of individual point sources and stacks, including in urban background, and the long records enable examination of multidecadal emission trends. Our inferred NOx emission rates are consistent with previous estimates to within a precision of about 30%. Sources down to ~500 kg h-1 can be detected over bright, quasi-homogeneous surfaces. The 2009 to 2021 data for Riyadh power plant 9 show a strong summer peak in emissions, consistent with increased power demand for air conditioning, and a marginal slow decrease following the introduction of Saudi Arabia's Ambient Air Standard 2012.

Transpacific Transport of Asian Peroxyacetyl Nitrate (PAN) Observed from Satellite: Implications for Ozone.

Peroxyacetyl nitrate (PAN) is produced in the atmosphere by photochemical oxidation of non-methane volatile organic compounds in the presence of nitrogen oxides (NOx), and it can be transported over long distances at cold temperatures before decomposing thermally to release NOx in the remote troposphere. It is both a tracer and a precursor for transpacific ozone pollution transported from East Asia to North America. Here, we directly demonstrate this transport with PAN satellite observations from the infrared atmospheric sounding interferometer (IASI). We reprocess the IASI PAN retrievals by replacing the constant prior vertical profile with vertical shape factors from the GEOS-Chem model that capture the contrasting shapes observed from aircraft over South Korea (KORUS-AQ) and the North Pacific (ATom). The reprocessed IASI PAN observations show maximum transpacific transport of East Asian pollution in spring, with events over the Northeast Pacific offshore from the Western US associated in GEOS-Chem with elevated ozone in the lower free troposphere. However, these events increase surface ozone in the US by less than 1 ppbv because the East Asian pollution mainly remains offshore as it circulates the Pacific High.

Lifestyle Coaching May Be an Effective Treatment for Schizophrenia.

This commentary critiques the Danish CHANGE trial, which evaluated 3 levels of outpatient intervention intensity, in a group of outpatients with obesity and schizophrenia. Neither adding care coordination with weekly nurse contacts alone nor combining this treatment with assertive community lifestyle coaching as compared to treatment as usual improved outcomes, which included cardiovascular disease risk calculation, cardiorespiratory fitness, weight, and self-reported behaviors such as smoking, physical activity, and diet. The CHANGE trial investigators appear strongly averse to recommending the development and implementation of lifestyle medicine programs as a major component when treating outpatients with severe mental disorders. The potential dismissal of lifestyle medicine as a component of treatment for severe mental disorders is problematic. Valuable lessons can be learned from more thoroughly analyzing secondary outcomes such as medical and psychiatric hospitalization rates and total health care cost. The CHANGE trial data analysis needs to be expanded beyond the focus on changes in weight and serum cholesterol. Insulin resistance and high refined carbohydrate intake may be major factors in determining both the medical and psychiatric clinical course of schizophrenia. Assertive community lifestyle coaching is a novel treatment modality. Evidence strongly suggests assertive community lifestyle coaching substantially decreases both psychiatric and medical hospitalization rates.

Impacts of updated reaction kinetics on the global GEOS-Chem simulation of atmospheric chemistry.

We updated the chemical mechanism of the GEOS-Chem global 3-D model of atmospheric chemistry to include new recommendations from the NASA Jet Propulsion Laboratory (JPL) chemical kinetics Data Evaluation 19-5 and from the International Union of Pure and Applied Chemistry (IUPAC) and to balance carbon and nitrogen. We examined the impact of these updates on the GEOS-Chem version 14.0.1 simulation. Notable changes include 11 updates to reactions of reactive nitrogen species, resulting in a 7% net increase in the stratospheric NOx (NO + NO2) burden; an updated CO + OH rate formula leading to a 2.7% reduction in total tropospheric CO; adjustments to the rate coefficient and branching ratios of propane + OH, leading to reduced tropospheric propane (-17%) and increased acetone (+3.5%) burdens; a 41% increase in the tropospheric burden of peroxyacetic acid due to a decrease in the rate coefficient for its reaction with OH, further contributing to reductions in peroxyacetyl nitrate (PAN; -3.8%) and acetic acid (-3.4%); and a number of minor adjustments to halogen radical cycling. Changes to the global tropospheric burdens of other species include -0.7% for ozone, +0.3% for OH (-0.4% for methane lifetime against oxidation by tropospheric OH), +0.8% for formaldehyde, and -1.7% for NOx. The updated mechanism reflects the current state of the science, including complex chemical dependencies of key atmospheric species on temperature, pressure, and concentrations of other compounds. The improved conservation of carbon and nitrogen will facilitate future studies of their overall atmospheric budgets.

North Korean CO emissions reconstruction using DMZ ground observations, TROPOMI space-borne data, and the CMAQ air quality model.

Emission uncertainty in North Korea can act as an obstacle when developing air pollution management plans in the country and neighboring countries when the transboundary transport of air pollutants is considered. This study introduces a novel approach for adjusting and reallocating North Korean CO emissions, aiming to complement the limited observational and emissions data on the country's air pollutants. We utilized ground observations from demilitarized zone (DMZ) and vertical column density (VCD) data from a TROPOspheric Monitoring Instrument (TROPOMI), which were combined with the Community Multi-Scale Air Quality (CMAQ) chemistry transport model simulations. The Clean Air Support System (CAPSS) and Satellite Integrated Joint Monitoring of Air Quality (SIJAQ) emissions inventories served as the basis for our initial simulations. A two-step procedure was proposed to adjust both the emission intensity and the spatial distribution of emissions. First, air quality simulations were conducted to explore model sensitivity to changes in North Korean CO emissions with respect to ground concentrations. DMZ observations then constrained these simulations to estimate corresponding emission intensity. Second, the spatial structure of North Korean CO emission sources was reconstructed with the help of TROPOMI CO VCD distributions. Our two-step hybrid method outperformed individual emissions adjustment and spatial reallocation based solely on surface or satellite observations. Validation using ground observations from the Chinese Dandong site near the China-North Korea border revealed significantly improved model simulations when applying the updated CO emissions. The adjusted CO emissions were 10.9 times higher than those derived from the bottom-up emissions used in this study, highlighting the lack of information on North Korean pollutants and emission sources. This approach offers an efficient and practical solution for identifying potential missing emission sources when there is limited on-site information about air quality on emissions.

Geostationary satellite observations of extreme and transient methane emissions from oil and gas infrastructure.

We demonstrate geostationary satellite monitoring of large transient methane point sources with the US Geostationary Operational Environmental Satellites (GOES). GOES provides continuous 5- to 10-min coverage of the Americas at 1 to 2 km nadir pixel resolution in two shortwave infrared spectral bands from which large methane plumes can be retrieved. We track the full evolution of an extreme methane release from the El Encino-La Laguna natural gas pipeline in Durango, Mexico on 12 May 2019. The release lasted 3 h at a variable rate of 260 to 550 metric tons of methane per hour and totaled 1,130 to 1,380 metric tons. We report several other detections of transient point sources from oil/gas infrastructure, from which we infer a detection limit of 10 to 100 t h-1. Our results show that extreme releases of methane can last less than an hour, as from deliberate venting, and would thus be difficult to identify and quantify with low-Earth orbit satellites.

A Gridded Inventory of Annual 2012-2018 U.S. Anthropogenic Methane Emissions.

Nationally reported greenhouse gas inventories are a core component of the Paris Agreement's transparency framework. Comparisons with emission estimates derived from atmospheric observations help identify improvements to reduce uncertainties and increase the confidence in reported values. To facilitate comparisons over the contiguous United States, we present a 0.1° × 0.1° gridded inventory of annual 2012-2018 anthropogenic methane emissions, allocated to 26 individual source categories, with scale-dependent error estimates. Our inventory is consistent with the U.S. Environmental Protection Agency (EPA) Inventory of U.S. Greenhouse Gas Emissions and Sinks (GHGI), submitted to the United Nations in 2020. Total emissions and patterns (spatial/temporal) reflect the activity and emission factor data underlying the GHGI, including many updates relative to a previous gridded version of the GHGI that has been extensively compared with observations. These underlying data are not generally available in global gridded inventories, and comparison to EDGAR version 6 shows large spatial differences, particularly for the oil and gas sectors. We also find strong regional variability across all sources in annual 2012-2018 spatial trends, highlighting the importance of understanding regional- and facility-level activities. Our inventory represents the first time series of gridded GHGI methane emissions and enables robust comparisons of emissions and their trends with atmospheric observations.

National quantifications of methane emissions from fuel exploitation using high resolution inversions of satellite observations.

Reducing methane emissions from fossil fuel exploitation (oil, gas, coal) is an important target for climate policy, but current national emission inventories submitted to the United Nations Framework Convention on Climate Change (UNFCCC) are highly uncertain. Here we use 22 months (May 2018-Feb 2020) of satellite observations from the TROPOMI instrument to better quantify national emissions worldwide by inverse analysis at up to 50 km resolution. We find global emissions of 62.7 ± 11.5 (2σ) Tg a-1 for oil-gas and 32.7 ± 5.2 Tg a-1 for coal. Oil-gas emissions are 30% higher than the global total from UNFCCC reports, mainly due to under-reporting by the four largest emitters including the US, Russia, Venezuela, and Turkmenistan. Eight countries have methane emission intensities from the oil-gas sector exceeding 5% of their gas production (20% for Venezuela, Iraq, and Angola), and lowering these intensities to the global average level of 2.4% would reduce global oil-gas emissions by 11 Tg a-1 or 18%.

NMR metabolite quantification of a synthetic urine sample: an inter-laboratory comparison of processing workflows.

INTRODUCTION: Absolute quantification of individual metabolites in complex biological samples is crucial in targeted metabolomic profiling. OBJECTIVES: An inter-laboratory test was performed to evaluate the impact of the NMR software, peak-area determination method (integration vs. deconvolution) and operator on quantification trueness and precision. METHODS: A synthetic urine containing 32 compounds was prepared. One site prepared the urine and calibration samples, and performed NMR acquisition. NMR spectra were acquired with two pulse sequences including water suppression used in routine analyses. The pre-processed spectra were sent to the other sites where each operator quantified the metabolites using internal referencing or external calibration, and his/her favourite in-house, open-access or commercial NMR tool. RESULTS: For 1D NMR measurements with solvent presaturation during the recovery delay (zgpr), 20 metabolites were successfully quantified by all processing strategies. Some metabolites could not be quantified by some methods. For internal referencing with TSP, only one half of the metabolites were quantified with a trueness below 5%. With peak integration and external calibration, about 90% of the metabolites were quantified with a trueness below 5%. The NMRProcFlow integration module allowed the quantification of several additional metabolites. The number of quantified metabolites and quantification trueness improved for some metabolites with deconvolution tools. Trueness and precision were not significantly different between zgpr- and NOESYpr-based spectra for about 70% of the variables. CONCLUSION: External calibration performed better than TSP internal referencing. Inter-laboratory tests are useful when choosing to better rationalize the choice of quantification tools for NMR-based metabolomic profiling and confirm the value of spectra deconvolution tools.

Multi-omics quantitative data of tomato fruit unveils regulation modes of least variable metabolites.

BACKGROUND: The composition of ripe fruits depends on various metabolites which content evolves greatly throughout fruit development and may be influenced by the environment. The corresponding metabolism regulations have been widely described in tomato during fruit growth and ripening. However, the regulation of other metabolites that do not show large changes in content have scarcely been studied. RESULTS: We analysed the metabolites of tomato fruits collected on different trusses during fruit development, using complementary analytical strategies. We identified the 22 least variable metabolites, based on their coefficients of variation. We first verified that they had a limited functional link with the least variable proteins and transcripts. We then posited that metabolite contents could be stabilized through complex regulations and combined their data with the quantitative proteome or transcriptome data, using sparse partial-least-square analyses. This showed shared regulations between several metabolites, which interestingly remained linked to early fruit development. We also examined regulations in specific metabolites using correlations with individual proteins and transcripts, which revealed that a stable metabolite does not always correlate with proteins and transcripts of its known related pathways. CONCLUSIONS: The regulation of the least variable metabolites was then interpreted regarding their roles as hubs in metabolic pathways or as signalling molecules.

Observation-derived 2010-2019 trends in methane emissions and intensities from US oil and gas fields tied to activity metrics.

The United States is the world's largest oil/gas methane emitter according to current national reports. Reducing these emissions is a top priority in the US government's climate action plan. Here, we use a 2010 to 2019 high-resolution inversion of surface and satellite observations of atmospheric methane to quantify emission trends for individual oil/gas production regions in North America and relate them to production and infrastructure. We estimate a mean US oil/gas methane emission of 14.8 (12.4 to 16.5) Tg a-1 for 2010 to 2019, 70% higher than reported by the US Environmental Protection Agency. While emissions in Canada and Mexico decreased over the period, US emissions increased from 2010 to 2014, decreased until 2017, and rose again afterward. Increases were driven by the largest production regions (Permian, Anadarko, Marcellus), while emissions in the smaller production regions generally decreased. Much of the year-to-year emission variability can be explained by oil/gas production rates, active well counts, and new wells drilled, with the 2014 to 2017 decrease driven by reduction in new wells and the 2017 to 2019 surge driven by upswing of production. We find a steady decrease in the oil/gas methane intensity (emission per unit methane gas production) for almost all major US production regions. The mean US methane intensity decreased from 3.7% in 2010 to 2.5% in 2019. If the methane intensity for the oil/gas supply chain continues to decrease at this pace, we may expect a 32% decrease in US oil/gas emissions by 2030 despite projected increases in production.

Long-lifetime water-washable ceramic catalyst filter for air purification.

Particulate matter (PM) and volatile organic compounds (VOCs) are recognised as hazardous air pollutants threatening human health. Disposable filters are generally used for air purification despite frequent replacement and waste generation problems. However, the development of a novel regenerable and robust filter for long-term use is a huge challenge. Here, we report on a new class of facile water-washing regenerable ceramic catalyst filters (CCFs), developed to simultaneously remove PM (>95%) and VOCs (>82%) in single-pass and maximized space efficiency by coating the inner and outer filter channels with an inorganic membrane and a Cu2O/TiO2 photocatalyst, respectively. The CCFs reveal four-fold increase in the maximum dust loading capacity (approximately 20 g/L) in relation to conventional filters (5 g/L), and can be reused after ten regeneration capability with simple water washing retaining initial PM and VOC removal performances. Thus, the CCFs can be well-suited for indoor and outdoor air purification for 20 years, which shows a huge increase in lifetime compared to the 6-month lifespan of conventional filters. Finally, we believe that the development and implementation of CCFs for air purification can open new avenues for sustainable technology through renewability and zero-waste generation.

Development, Validation, and Use of 1H-NMR Spectroscopy for Evaluating the Quality of Acerola-Based Food Supplements and Quantifying Ascorbic Acid.

Acerola (Malpighia emarginata D.C.) is an exotic fruit with high agro-industrial potential due to its high content of ascorbic acid (AA), phenolic compounds, and carotenoid pigments. Acerola fruit is processed into concentrated juice or powder to be incorporated into food supplements. The ascorbic acid content of concentrated juice or powders must be controlled and well assessed. Therefore, the development of optimal methods and procedures for the rapid and accurate determination of the ascorbic acid content in juice concentrate and juice powder remains of considerable commercial interest. NMR spectroscopy is currently a powerful spectroscopic tool for the qualitative and quantitative analysis of molecules of all types and sizes. Firstly, this article presents the NMR-based metabolomic profiling of acerola juice and concentrate powder to describe and compare their composition. Thirty-six metabolites were identified. The AA over choline ratio and the NMR metabolomic profiles could be used for authentication in the future. Secondly, a rapid (8 min), reliable, and non-destructive method for the quantification of ascorbic acid by 1D 1H-NMR spectroscopy was developed and validated. The LOD and LOQ were 0.05 and 0.15 mg/mL, respectively. These two approaches could be combined to better characterize ingredients derived from acerola and incorporated into food supplements.

Aerosol-Radiation Interactions in China in Winter: Competing Effects of Reduced Shortwave Radiation and Cloud-Snowfall-Albedo Feedbacks Under Rapidly Changing Emissions.

Since 2013, Chinese policies have dramatically reduced emissions of particulates and their gas-phase precursors, but the implications of these reductions for aerosol-radiation interactions are unknown. Using a global, coupled chemistry-climate model, we examine how the radiative impacts of Chinese air pollution in the winter months of 2012 and 2013 affect local meteorology and how these changes may, in turn, influence surface concentrations of PM2.5, particulate matter with diameter <2.5 µm. We then investigate how decreasing emissions through 2016 and 2017 alter this impact. We find that absorbing aerosols aloft in winter 2012 and 2013 heat the middle- and lower troposphere by ∼0.5-1 K, reducing cloud liquid water, snowfall, and snow cover. The subsequent decline in surface albedo appears to counteract the ∼15-20 W m-2 decrease in shortwave radiation reaching the surface due to attenuation by aerosols overhead. The net result of this novel cloud-snowfall-albedo feedback in winters 2012-2013 is a slight increase in surface temperature of ∼0.5-1 K in some regions and little change elsewhere. The aerosol heating aloft, however, stabilizes the atmosphere and decreases the seasonal mean planetary boundary layer (PBL) height by ∼50 m. In winter 2016 and 2017, the ∼20% decrease in mean PM2.5 weakens the cloud-snowfall-albedo feedback, though it is still evident in western China, where the feedback again warms the surface by ∼0.5-1 K. Regardless of emissions, we find that aerosol-radiation interactions enhance mean surface PM2.5 pollution by 10%-20% across much of China during all four winters examined, mainly though suppression of PBL heights.

PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management.

INTRODUCTION: Accuracy of feature annotation and metabolite identification in biological samples is a key element in metabolomics research. However, the annotation process is often hampered by the lack of spectral reference data in experimental conditions, as well as logistical difficulties in the spectral data management and exchange of annotations between laboratories. OBJECTIVES: To design an open-source infrastructure allowing hosting both nuclear magnetic resonance (NMR) and mass spectra (MS), with an ergonomic Web interface and Web services to support metabolite annotation and laboratory data management. METHODS: We developed the PeakForest infrastructure, an open-source Java tool with automatic programming interfaces that can be deployed locally to organize spectral data for metabolome annotation in laboratories. Standardized operating procedures and formats were included to ensure data quality and interoperability, in line with international recommendations and FAIR principles. RESULTS: PeakForest is able to capture and store experimental spectral MS and NMR metadata as well as collect and display signal annotations. This modular system provides a structured database with inbuilt tools to curate information, browse and reuse spectral information in data treatment. PeakForest offers data formalization and centralization at the laboratory level, facilitating shared spectral data across laboratories and integration into public databases. CONCLUSION: PeakForest is a comprehensive resource which addresses a technical bottleneck, namely large-scale spectral data annotation and metabolite identification for metabolomics laboratories with multiple instruments. PeakForest databases can be used in conjunction with bespoke data analysis pipelines in the Galaxy environment, offering the opportunity to meet the evolving needs of metabolomics research. Developed and tested by the French metabolomics community, PeakForest is freely-available at https://github.com/peakforest .

Predictive metabolomics of multiple Atacama plant species unveils a core set of generic metabolites for extreme climate resilience.

Current crop yield of the best ideotypes is stagnating and threatened by climate change. In this scenario, understanding wild plant adaptations in extreme ecosystems offers an opportunity to learn about new mechanisms for resilience. Previous studies have shown species specificity for metabolites involved in plant adaptation to harsh environments. Here, we combined multispecies ecological metabolomics and machine learning-based generalized linear model predictions to link the metabolome to the plant environment in a set of 24 species belonging to 14 families growing along an altitudinal gradient in the Atacama Desert. Thirty-nine common compounds predicted the plant environment with 79% accuracy, thus establishing the plant metabolome as an excellent integrative predictor of environmental fluctuations. These metabolites were independent of the species and validated both statistically and biologically using an independent dataset from a different sampling year. Thereafter, using multiblock predictive regressions, metabolites were linked to climatic and edaphic stressors such as freezing temperature, water deficit and high solar irradiance. These findings indicate that plants from different evolutionary trajectories use a generic metabolic toolkit to face extreme environments. These core metabolites, also present in agronomic species, provide a unique metabolic goldmine for improving crop performances under abiotic pressure.

Catalytic role of formaldehyde in particulate matter formation.

Formaldehyde (HCHO), the simplest and most abundant carbonyl in the atmosphere, contributes to particulate matter (PM) formation via two in-cloud processing pathways. First, in a catalytic pathway, HCHO reacts with hydrogen peroxide (H2O2) to form hydroxymethyl hydroperoxide (HMHP), which rapidly oxidizes dissolved sulfur dioxide (SO2,aq) to sulfate, regenerating HCHO. Second, HCHO reacts with dissolved SO2,aq to form hydroxymethanesulfonate (HMS), which upon oxidation with the hydroxyl radical (OH) forms sulfate and also reforms HCHO. Chemical transport model simulations using rate coefficients from laboratory studies of the reaction rate of HMHP with SO2,aq show that the HMHP pathways reduce the SO2 lifetime by up to a factor of 2 and contribute up to ∼18% of global sulfate. This contribution rises to >50% in isoprene-dominated regions such as the Amazon. Combined with recent results on HMS, this work demonstrates that the one-carbon molecules HMHP and HCHO contribute significantly to global PM, with HCHO playing a crucial catalytic role.

The Effects of Lifestyle on the Risk of Lyme Disease in the United States: Evaluation of Market Segmentation Systems in Prevention and Control Strategies.

The aim of this study was to investigate lifestyles at risk of Lyme disease, and to geographically identify target populations/households at risk based on their lifestyle preferences. When coupled with geographically identified patient health information (e.g., incidence, diagnostics), lifestyle data provide a more solid base of information for directing public health objectives in minimizing the risk of Lyme disease and targeting populations with Lyme-disease-associated lifestyles. We used an ESRI Tapestry segmentation system that classifies U.S. neighborhoods into 67 unique segments based on their demographic and socioeconomic characteristics. These 67 segments are grouped within 14 larger "LifeModes" that have commonalities based on lifestyle and life stage. Our dataset contains variables denoting the dominant Tapestry segments within each U.S. county, along with annual Lyme disease incidence rates from 2000 through 2017, and the average incidence over these 18 years. K-means clustering was used to cluster counties based on yearly incidence rates for the years 2000-2017. We used analysis of variance (ANOVA) statistical testing to determine the association between Lyme disease incidence and LifeModes. We further determined that the LifeModes Affluent Estates, Upscale Avenues, GenXurban, and Cozy Country Living were associated with higher Lyme disease risk based on the results of analysis of means (ANOM) and Tukey's post hoc test, indicating that one of these LifeModes is the LifeMode with the greatest Lyme disease incidence rate. We further conducted trait analysis of the high-risk LifeModes to see which traits were related to higher Lyme disease incidence. Due to the extreme regional nature of Lyme disease incidence, we carried out our national-level analysis at the regional level. Significant differences were detected in incidence rates and LifeModes in individual regions. We mapped Lyme disease incidence with associated LifeModes in the Northeast, Southeast, Midcontinent, Rocky Mountain, and Southwest regions to reflect the location-dependent nature of the relationship between lifestyle and Lyme disease.

Improved Mechanistic Model of the Atmospheric Redox Chemistry of Mercury.

We present a new chemical mechanism for Hg0/HgI/HgII atmospheric cycling, including recent laboratory and computational data, and implement it in the GEOS-Chem global atmospheric chemistry model for comparison to observations. Our mechanism includes the oxidation of Hg0 by Br and OH, subsequent oxidation of HgI by ozone and radicals, respeciation of HgII in aerosols and cloud droplets, and speciated HgII photolysis in the gas and aqueous phases. The tropospheric Hg lifetime against deposition in the model is 5.5 months, consistent with observational constraints. The model reproduces the observed global surface Hg0 concentrations and HgII wet deposition fluxes. Br and OH make comparable contributions to global net oxidation of Hg0 to HgII. Ozone is the principal HgI oxidant, enabling the efficient oxidation of Hg0 to HgII by OH. BrHgIIOH and HgII(OH)2, the initial HgII products of Hg0 oxidation, respeciate in aerosols and clouds to organic and inorganic complexes, and volatilize to photostable forms. Reduction of HgII to Hg0 takes place largely through photolysis of aqueous HgII-organic complexes. 71% of model HgII deposition is to the oceans. Major uncertainties for atmospheric Hg chemistry modeling include Br concentrations, stability and reactions of HgI, and speciation and photoreduction of HgII in aerosols and clouds.