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 NO x (NO + NO 2 ) 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 NO x . 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.

The kinetics of reactions between the simplest Criegee intermediate, CH2OO, and water vapour have been investigated at temperatures between 262 and 353 K at a total pressure of 760 Torr using laser flash photolysis of CH2I2–O2–N2–H2O mixtures coupled with broadband time-resolved UV absorption spectroscopy. Results indicate that the reaction with water monomers represents a minor contribution to the total loss of CH2OO under the conditions employed in this work, with an estimated rate coefficient for CH2OO + H2O (R1) of (9.8 ± 5.9) × 10−17 cm3 molecule−1 s−1 at 298 K and a temperature dependence described by k1 = (3.2 ± 1.1) × 10−13 exp(−(2410 ± 270)/T) cm3 molecule−1 s−1. The reaction of CH2OO with water dimers, CH2OO + (H2O)2 (R2), dominates under the conditions employed in this work. The rate coefficient for R2 has been measured to be k2 = (9.5 ± 2.5) × 10−12 cm3 molecule−1 s−1 at 298 K, with a negative temperature dependence described by k2 = (2.85 ± 0.40) × 10−15 exp((2420 ± 340)/T) cm3 molecule−1 s−1, where rateR2 = k2[CH2OO][(H2O)2]. For use in atmospheric models, we recommend description of the kinetics for R2 in terms of the product of the rate coefficient k2 and the equilibrium constant KDeq (k2,eff = k2KDeq) for water dimer formation to allow the rate of reaction to be expressed in terms of water monomer concentration as rateR2 = k2,eff[CH2OO][H2O]2 to avoid explicit calculation of dimer concentrations and impacts of differences in values of KDeq reported in the literature. Results from this work give k2,eff = (1.96 ± 0.51) × 10−32 cm6 molecule−2 s−1 at 298 K with a temperature dependence described by k2,eff = (2.78 ± 0.28) × 10−38 exp((4010 ± 400)/T) cm6 molecule−2 s−1. No significant impacts of a reaction between CH2OO and three water molecules were observed in this work, potentially as a result of the relative humidities used in this work (up to 57% at 298 K). Atmospheric implications of the results have been investigated using the global chemistry transport model GEOS-Chem. Model simulations indicate that the reaction with water dimers dominates the loss of CH2OO in the atmosphere and limits the impacts of other reactions of CH2OO, with the reaction with water dimers representing >98% of the total loss of CH2OO in the troposphere.

The island of Hateruma is the southernmost inhabited island of Japan. Here we interpret observations of ethane (C2H6) and propane (C3H8) together with carbon monoxide (CO), nitrogen oxides (NOx and NOy) and ozone (O3) carried out in the island in 2018 with the GEOS-Chem atmospheric chemistry transport model. We simulated the mixing ratios of these species within a nested grid centred over the site, with a model resolution of 0.5∘ × 0.625∘. We use the Community Emissions Data System (CEDS) dataset for anthropogenic emissions and add a geological source of C2H6 and C3H8. The model captured the seasonality of primary pollutants (CO, C2H6, C3H8) at the site – high mixing ratios in the winter months when oxidation rates are low and flow is from the north and low mixing ratios in the summer months when oxidation rates are higher and flow is from the south. It also simulates many of the synoptic-scale events with Pearson's correlation coefficients (r) of 0.74, 0.88 and 0.89 for CO, C2H6 and C3H8, respectively. Mixing ratios of CO are simulated well by the model (slope of the linear fit between model results and measurements is 0.91), but simulated mixing ratios of C2H6 and C3H8 are significantly lower than the observations (slopes of the linear fit between model results and measurements are 0.57 and 0.41, respectively), most noticeably in the winter months. Simulated NOx mixing ratios were underestimated, but NOy appears to be overestimated. The mixing ratio of O3 is moderately well simulated (slope of the linear fit between model results and observations is 0.76, with an r of 0.87), but there is a tendency to underestimate mixing ratios in the winter months. By switching off the model's biomass burning emissions we show that during winter, biomass burning has limited influence on the mixing ratios of compounds but can represent a more sizeable fraction in the summer. We also show that increasing the anthropogenic emissions of C2H6 and C3H8 within the domain by factors of 2.22 and 3.17 increases the model's ability to simulate these species in the winter months, consistent with previous studies.

Abstract Isoprene, arguably the most studied biogenically emitted gas, is thought to have a large impact on tropospheric composition. Other naturally emitted species have been considered to play a less important role. Here the GEOS‐Chem model is used to compare the impacts of isoprene and iodine emissions on present‐day tropospheric composition. Removing isoprene emissions leads to a 3.4% decrease in tropospheric O3 burden, a smaller absolute change than the 5.9% increase from removing iodine emissions. Iodine has a negligible impact on global mean OH concentrations and methane lifetime (+0.6% and +0.05%) whereas isoprene has a substantial impact on both (−4.3% and −4.2%). Isoprene emissions and chemistry are seen as essential for tropospheric chemistry models, but iodine is often not. We suggest that iodine should receive greater attention in model development and experimental research to allow improved predictions of past, present, and future tropospheric O3.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

Atmospheric ozone (O 3 ) is a pollutant produced through chemical chain reactions where volatile organic compounds (VOCs), carbon monoxide and methane are oxidized in the presence of oxides of nitrogen (NO x ). For decades, the controlling chain termination step has been used to separate regions into either ‘NO x limited’ (peroxyl-radical self-reactions dominate) or ‘VOC limited’ (hydroxyl radical (OH) + nitrogen dioxide (NO 2 ) reaction dominates). The controlling regime would then guide policies for reducing emissions and so O 3 concentrations. Using a chemical transport model, we show that a third ‘aerosol inhibited’ regime exists, where reactive uptake of hydroperoxyl radicals (HO 2 ) onto aerosol particles dominates. In 1970, 2% of the Northern Hemisphere population lived in an aerosol-inhibited regime, but by 2014 this had increased to 21%; 60% more than lived in a VOC-limited regime. Aerosol-inhibited chemistry suppressed surface O 3 concentrations in North America and Europe in the 1970s and is currently suppressing surface O 3 over Asia. This third photochemical O 3 regime leads to potential trade-off tensions between reducing particle pollution in Asia (a key current health policy and priority) and increasing surface O 3 , should O 3 precursors emissions not be reduced in tandem.

Abstract. The island of Hateruma is the southernmost inhabited island of Japan. Here we interpret observations of carbon monoxide (CO), ethane (C2H6), propane (C3H8), nitrogen oxides (NOx and NOy) and ozone (O3) made from the island in 2018 with the GEOS-Chem atmospheric chemistry transport model. We simulated the concentrations of these species within a nested grid centered over the site, with a model resolution of 0.5°×0.625°. We use the Community Emissions Data System (CEDS) emissions dataset for anthropogenic emissions and add a geological source of C2H6 and C3H8. The model captured the seasonality of primary pollutants (CO, C2H6, C3H8) at the site - high concentrations in the winter months when oxidation rates are low and flow is from the north, and low concentrations in the summer months when oxidation rates are higher and flow is from the south. It also simulates many of the synoptic scale events with Pearson’s correlation coefficients (r) of 0.74, 0.88 and 0.89 for CO, C2H6 and C3H8, respectively. Concentrations of CO are well simulated by the model (with a gradient of best fit between model and measurements of 0.91) but simulated concentrations of C2H6 and C3H8 are significantly lower than the observations (gradients of best fit between model and measurement of 0.57 and 0.41, respectively), most noticeably in the winter months. Simulated NOx concentrations were underestimated but NOy appear to be overestimated. The concentration of O3 is moderately well simulated (gradient of best fit line of 0.76, with an r of 0.87) but there is a tendency to underestimate concentrations in the winter months. By switching off the model’s biomass burning emissions we show that during winter biomass burning has limited influence on the concentration of compounds in the winter but can represent a sizeable fraction in the summer. We also show that increasing the anthropogenic emissions of C2H6 and C3H8 in Asia by factors of 2.22 and 3.17, respectively, significantly increases the model’s ability to simulate these species in the winter months, consistent with previous studies.

Social-distancing to combat the COVID-19 pandemic has led to widespread reductions in air pollutant emissions. Quantifying these changes requires a business as usual counterfactual that accounts for the synoptic and seasonal variability of air pollutants. We use a machine learning algorithm driven by information from the NASA GEOS-CF model to assess changes in nitrogen dioxide (NO$_{2}$) and ozone (O$_{3}$) at 5,756 observation sites in 46 countries from January through June 2020. Reductions in NO$_{2}$ correlate with timing and intensity of COVID-19 restrictions, ranging from 60% in severely affected cities (e.g., Wuhan, Milan) to little change (e.g., Rio de Janeiro, Taipei). On average, NO$_{2}$ concentrations were 18% lower than business as usual from February 2020 onward. China experienced the earliest and steepest decline, but concentrations since April have mostly recovered and remained within 5% to the business as usual estimate. NO$_{2}$ reductions in Europe and the US have been more gradual with a halting recovery starting in late March. We estimate that the global NO$_{x}$ (NO+NO$_{2}$) emission reduction during the first 6 months of 2020 amounted to 2.9 TgN, equivalent to 5.1% of the annual anthropogenic total. The response of surface O$_{3}$ is complicated by competing influences of non-linear atmospheric chemistry. While surface O$_{3}$ increased by up to 50% in some locations, we find the overall net impact on daily average O$_{3}$ between February - June 2020 to be small. However, our analysis indicates a flattening of the O$_{3}$ diurnal cycle with an increase in night time ozone due to reduced titration and a decrease in daytime ozone, reflecting a reduction in photochemical production. The O$_{3}$ response is dependent on season, time scale, and environment, with declines in surface O$_{3}$ forecasted if NO$_{x}$ emission reductions continue.

Graph‐theoretical methods have revolutionized the exploration of complex systems across scientific disciplines. Here, we demonstrate their applicability to the investigation and comparison of three widely used atmospheric chemical mechanisms of varying complexity: the Master Chemical Mechanism v3.3, GEOS‐Chem v12.6, and the Super‐Fast chemical mechanism. We investigate these mechanisms using a class of graphical models known as species‐reaction graphs and find similarities between these chemical reaction systems and other systems arising in nature. Several graph theoretical properties are consistent across mechanisms, including strong dynamical system disequilibrium and clustering of chemically related species. This formalism also reveals key differences between the mechanisms, some of which have characteristics inconsistent with domain knowledge; e.g., isoprene and peroxy radical chemistry exhibit substantially different graph properties in each mechanism. Graph‐theoretical methods provide a promising set of tools for investigating atmospheric chemical mechanisms, complementing existing computational approaches, and potentially opening new avenues for scientific discovery.

Studies of wintertime air quality in the North China Plain (NCP) show that particulate‐nitrate pollution persists despite rapid reduction in NOx emissions. This intriguing NOx‐nitrate relationship may originate from non‐linear nitrate‐formation chemistry, but it is unclear which feedback mechanisms dominate in NCP. In this study, we re‐interpret the wintertime observations of 17O excess of nitrate (∆17O(NO3−)) in Beijing using the GEOS‐Chem (GC) chemical transport model to estimate the importance of various nitrate‐production pathways and how their contributions change with the intensity of haze events. We also analyze the relationships between other metrics of NOy chemistry and [PM2.5] in observations and model simulations. We find that the model on average has a negative bias of −0.9‰ and −36% for ∆17O(NO3−) and [Ox,major] (≡ [O3] + [NO2] + [p‐NO3−]), respectively, while overestimating the nitrogen oxidation ratio ([NO3−]/([NO3−] + [NO2])) by +0.12 in intense haze. The discrepancies become larger in more intense haze. We attribute the model biases to an overestimate of NO2‐uptake on aerosols and an underestimate in wintertime O3 concentrations. Our findings highlight a need to address uncertainties related to heterogeneous chemistry of NO2 in air‐quality models. The combined assessment of observations and model results suggest that N2O5 uptake in aerosols and clouds is the dominant nitrate‐production pathway in wintertime Beijing, but its rate is limited by ozone under high‐NOx‐high‐PM2.5 conditions. Nitrate production rates may continue to increase as long as [O3] increases despite reduction in [NOx], creating a negative feedback that reduces the effectiveness of air pollution mitigation.

Global modeling of atmospheric chemistry is a great computational challenge because of the cost of integrating the kinetic equations for chemical mechanisms with typically over 100 coupled species. Here we present an adaptive algorithm to ease this computational bottleneck with no significant loss in accuracy and apply it to the GEOS-Chem global 3-D model for tropospheric and stratospheric chemistry (228 species, 724 reactions). Our approach is inspired by unsupervised machine learning clustering techniques and traditional asymptotic analysis ideas. We locally define species in the mechanism as fast or slow on the basis of their total production and loss rates, and we solve the coupled kinetic system only for the fast species assembled in a submechanism of the full mechanism. To avoid computational overhead, we first partition the species from the full mechanism into 13 blocks, using a machine learning approach that analyzes the chemical linkages between species and their correlated presence as fast or slow in the global model domain. Building on these blocks, we then preselect 20 submechanisms, as defined by unique assemblages of the species blocks, and then pick locally and on the fly which submechanism to use in the model based on local chemical conditions. In each submechanism, we isolate slow species and slow reactions from the coupled system of fast species to be solved. Because many species in the full mechanism are important only in source regions, we find that we can reduce the effective size of the mechanism by 70 % globally without sacrificing complexity where/when it is needed. The computational cost of the chemical integration decreases by 50 % with relative biases smaller than 2 % for important species over 8-year simulations. Changes to the full mechanism including the addition of new species can be accommodated by adding these species to the relevant blocks without having to reconstruct the suite of submechanisms.

Effective mitigation of surface ozone pollution entails detailed knowledge of the contributing precursors' sources. We use the GEOS-Chem adjoint model to analyze the precursors contributing to surface ozone in the Beijing-Tianjin-Hebei area (BTH) of China on days of different ozone pollution severities in June 2019. We find that BTH ozone on heavily polluted days is sensitive to local emissions, as well as to precursors emitted from the provinces south of BTH (Shandong, Henan, and Jiangsu, collectively the SHJ area). Heavy ozone pollution in BTH can be mitigated effectively by reducing NOx (from industrial processes and transportation), ≥C3 alkenes (from on-road gasoline vehicles and industrial processes), and xylenes (from paint use) emitted from both BTH and SHJ, as well as by reducing CO (from industrial processes, transportation, and power generation) and ≥C4 alkanes (from industrial processes, paint and solvent use, and on-road gasoline vehicles) emissions from SHJ. In addition, reduction of NOx, xylene, and ≥C3 alkene emissions within BTH would effectively decrease the number of BTH ozone-exceedance days. Our analysis pinpoint the key areas and activities for locally and regionally coordinated emission control efforts to improve surface ozone air quality in BTH.

In assessments of cancer risk from atmospheric polycyclic aromatic hydrocarbons (PAHs), scientists and regulators rarely consider the complex mixture of emitted compounds and degradation products, and they often represent the entire mixture using a single emitted compound-benzo[a]pyrene. Here, we show that benzo[a]pyrene is a poor indicator of PAH risk distribution and management: nearly 90% of cancer risk worldwide results from other PAHs, including unregulated degradation products of emitted PAHs. We develop and apply a global-scale atmospheric model and conduct health impact analyses to estimate human cancer risk from 16 PAHs and several of their N-PAH degradation products. We find that benzo[a]pyrene is a minor contributor to the total cancer risks of PAHs (11%); the remaining risk comes from other directly emitted PAHs (72%) and N-PAHs (17%). We show that assessment and policy-making that relies solely on benzo[a]pyrene exposure provides misleading estimates of risk distribution, the importance of chemical processes, and the prospects for risk mitigation. We conclude that researchers and decision-makers should consider additional PAHs as well as degradation products.

We present an updated mechanism for tropospheric halogen (Cl + Br + I) chemistry in the GEOS-Chem global atmospheric chemical transport model and apply it to investigate halogen radical cycling and implications for tropospheric oxidants. Improved representation of HOBr heterogeneous chemistry and its pH dependence in our simulation leads to less efficient recycling and mobilization of bromine radicals and enables the model to include mechanistic sea salt aerosol debromination without generating excessive BrO. The resulting global mean tropospheric BrO mixing ratio is 0.19 ppt (parts per trillion), lower than previous versions of GEOS-Chem. Model BrO shows variable consistency and biases in comparison to surface and aircraft observations in marine air, which are often near or below the detection limit. The model underestimates the daytime measurements of Cl2 and BrCl from the ATom aircraft campaign over the Pacific and Atlantic, which if correct would imply a very large missing primary source of chlorine radicals. Model IO is highest in the marine boundary layer and uniform in the free troposphere, with a global mean tropospheric mixing ratio of 0.08 ppt, and shows consistency with surface and aircraft observations. The modeled global mean tropospheric concentration of Cl atoms is 630 cm−3, contributing 0.8 % of the global oxidation of methane, 14 % of ethane, 8 % of propane, and 7 % of higher alkanes. Halogen chemistry decreases the global tropospheric burden of ozone by 11 %, NOx by 6 %, and OH by 4 %. Most of the ozone decrease is driven by iodine-catalyzed loss. The resulting GEOS-Chem ozone simulation is unbiased in the Southern Hemisphere but too low in the Northern Hemisphere.

The impact of emissions of volatile organic compounds (VOCs) to the atmosphere on the production of secondary pollutants, such as ozone and secondary organic aerosol (SOA), is mediated by the concentration of nitric oxide (NO). Polluted urban atmospheres are typically considered to be “high-NO” environments, while remote regions such as rainforests, with minimal anthropogenic influences, are considered to be “low NO”. However, our observations from central Beijing show that this simplistic separation of regimes is flawed. Despite being in one of the largest megacities in the world, we observe formation of gas- and aerosol-phase oxidation products usually associated with low-NO “rainforest-like” atmospheric oxidation pathways during the afternoon, caused by extreme suppression of NO concentrations at this time. Box model calculations suggest that during the morning high-NO chemistry predominates (95 %) but in the afternoon low-NO chemistry plays a greater role (30 %). Current emissions inventories are applied in the GEOS-Chem model which shows that such models, when run at the regional scale, fail to accurately predict such an extreme diurnal cycle in the NO concentration. With increasing global emphasis on reducing air pollution, it is crucial for the modelling tools used to develop urban air quality policy to be able to accurately represent such extreme diurnal variations in NO to accurately predict the formation of pollutants such as SOA and ozone.