Atmospheric Chemistry Model Research Articles

A Scheme for Representing Aromatic Secondary Organic Aerosols in Chemical Transport Models: Application to Source Attribution of Organic Aerosols Over South Korea During the KORUS‐AQ Campaign

AbstractWe present a new volatility basis set (VBS) representation of aromatic secondary organic aerosol (SOA) for atmospheric chemistry models by fitting a statistical oxidation model with aerosol microphysics (SOM‐TOMAS) to results from laboratory chamber experiments. The resulting SOM‐VBS scheme also including previous work on SOA formation from semi‐ and intermediate volatile organic compounds (S/IVOCs) is implemented in the GEOS‐Chem chemical transport model and applied to simulation of observations from the Korea‐United States Air Quality Study (KORUS‐AQ) field campaign over South Korea in May–June 2016. Our SOM‐VBS scheme can simulate the KORUS‐AQ organic aerosol (OA) observations from aircraft and surface sites better than the default schemes used in GEOS‐Chem including for vertical profiles, diurnal cycle, and partitioning between hydrocarbon‐like OA and oxidized OA. Our results confirm the important contributions of oxidized primary OA and aromatic SOA found in previous analyses of the KORUS‐AQ data and further show a large contribution from S/IVOCs. Model source attribution of OA in surface air over South Korea indicates one third from domestic anthropogenic emissions, with a large contribution from toluene and xylenes, one third from external anthropogenic emissions, and one third from natural emissions.

Why is ozone in South Korea and the Seoul metropolitan area so high and increasing?

Abstract. Surface ozone pollution in South Korea has increased over the past 2 decades, despite efforts to decrease emissions, and is pervasively in exceedance of the maximum daily 8 h average (MDA8) standard of 60 ppb. Here, we investigate the 2015–2019 trends in surface ozone and NO2 concentrations over South Korea and the Seoul metropolitan area (SMA), focusing on the 90th percentile MDA8 ozone as an air quality metric. We use a random forest algorithm to remove the effect of meteorological variability on the 2015–2019 trends and find an ozone increase of up to 1.5 ppb a−1 in April–May, while NO2 decreases by 22 %. Global 3-D atmospheric chemistry model simulations including recent chemical updates can successfully simulate surface ozone over South Korea and China as well as the very high free-tropospheric ozone observed above 2 km altitude (mean 75 ppb in May–June) and can reproduce the observed 2015–2019 emission-driven ozone trend over the SMA including its seasonality. Further investigation of the model trend for May, when meteorology-corrected ozone and its increase are the highest, reveals that a decrease in South Korea NOx emissions is the main driver for the SMA ozone increase. Although this result implies that decreasing volatile organic compound (VOC) emissions is necessary to decrease ozone, we find that ozone would still remain above 80 ppb even if all anthropogenic emissions in South Korea were shut off. China contributes only 8 ppb to this elevated South Korea background, and ship emissions contribute only a few parts per billion. Zeroing out all anthropogenic emissions in East Asia in the model indicates a remarkably high external background of 56 ppb, consistent with the high concentrations observed in the free troposphere, implying that the air quality standard in South Korea is not practically achievable unless this background external to East Asia can be decreased.

Spatiotemporal Analysis of XCO2 and Its Relationship to Urban and Green Areas of China’s Major Southern Cities from Remote Sensing and WRF-Chem Modeling Data from 2010 to 2019

Monitoring CO2 concentrations is believed to be an effective measure for assisting in the control of greenhouse gas emissions. Satellite measurements compensate for the sparse and uneven spatial distribution of ground observation stations, allowing for the collection of a wide range of CO2 concentration data. However, satellite monitoring’s spatial coverage remains limited. This study fills the knowledge gaps of column-averaged dry-air mole fraction of CO2 (XCO2) products retrieved from the Greenhouse Gases Observing Satellite (GOSAT) and Orbiting Carbon Observatory Satellite (OCO-2) based on the normalized output of atmospheric chemical models, WRF-Chem, in Southern China during 2010–2019. Hefei (HF)/Total Carbon Column Observing Network (TCCON), Lulin (LLN)/World Data Centre for Greenhouse Gases (WDCGG) station observations were used to validate the results of void filling with an acceptable accuracy for spatiotemporal analysis (R = 0.96, R2 = 0.92, RMSE = 2.44 ppm). Compared to the IDW (inverse distance weighting) and Kriging (ordinary Kriging) interpolation methods, this method has a higher validation accuracy. In addition, spatiotemporal distributions of CO2, as well as the sensitivity of CO2 concentration to the urban built-up areas and urban green space areas in China’s major southern cities during 2010–2019, are discussed. The approximate annual average concentrations have gradually increased from 388.56 to 414.72 ppm, with an annual growth rate of 6.73%, and the seasonal cycle presents a maximum in spring and a minimum in summer or autumn from 2010 to 2019. CO2 concentrations have a strong positive correlation with the impervious area to city area ratio, while anomaly values of the impervious area to urban green area ratio occurred in individual cities. The experimental findings demonstrate the viability of the study hypothesis that combines remote sensing data with the WRF-Chem model to produce a local area dataset with high spatial resolution and an extracted urban unit from statistical data.

The combined effects of heterogeneous chemistry and aerosol-radiation interaction on severe haze simulation by atmospheric chemistry model in Middle-Eastern China

Heterogeneous chemistry and aerosol-radiation interaction (ARI) are considered two of the key mechanisms affecting haze formation and their reasonable parameterizations in atmospherically chemical models play an important role in accurate haze or air quality prediction. However, until the present, their relative contributions to severe haze have rarely been evaluated. Using the double-way atmospherically chemical model GRAPES_Meso5.1/CUACE CW, the relative contributions of heterogeneous chemistry and ARI to PM2.5 are investigated under different pollution levels in Middle-Eastern China (MEC) during December 2016. Study results show that the combined effects of heterogeneous chemistry and ARI generate 29.7% of total PM2.5 mass in MEC of December 2016, of which ARI contributes 19.7%, much higher than heterogeneous chemistry (6.1%). However, heterogeneous chemistry is important for reasonable reproduction of the proportion of secondary inorganic aerosols (SIA) of PM2.5, especially during heavy haze. Both the contributions of heterogeneous chemistry and ARI to PM2.5 increase with the haze pollution aggravation but to different degrees. The contribution of heterogeneous chemistry to modeled PM2.5 concentration rises from 4.0% on clean days to 6.6% under moderate pollution and 7.8% under heavy haze. And that of ARI increases rapidly from 9.1% on clean days to 21.0% under moderate pollution and 29.1% during heavy pollution. It is worth noticing that there is an additional contribution to PM2.5 caused by the combination of heterogeneous chemistry and ARI except for their respective contributions, which reaches up to 7.3% of PM2.5 mass and 18.5% of SIA generation under heavily polluted conditions. This is because ARI further promotes heterogeneous oxidation of SO2 and NOx by increasing the aerosol surface area concentration (SAC), causing additional SIA production via heterogeneous pathways. This work indicates the contribution of ARI to severe haze formation not only by altering meteorological conditions but also by reforming the chemical processes in the model.

Impacts of emissions policies on future UK mortality burdens associated with air pollution

Air pollution is the greatest environmental risk to public health. Future air pollution concentrations are primarily determined by precursor emissions, which are driven by environmental policies relating to climate and air pollution. Detailed health impact assessments (HIA) are necessary to provide quantitative estimates of the impacts of future air pollution to support decision-makers developing environmental policy and targets. In this study we use high spatial resolution atmospheric chemistry modelling to simulate future air pollution concentrations across the UK for 2030, 2040 and 2050 based on current UK and European policy projections. We combine UK regional population-weighted concentrations with the latest epidemiological relationships to quantify mortality associated with changes in PM2.5 and NO2 air pollution. Our HIA suggests that by 2050, population-weighted exposure to PM2.5 will reduce by 28% to 36%, and for NO2 by 35% to 49%, depending on region. The HIA shows that for present day (2018), annual mortality attributable to the effects of long-term exposure to PM2.5 and NO2 is in the range 26,287 – 42,442, and that mortality burdens in future will be substantially reduced, being lower by 31%, 35%, and 37% in 2030, 2040 and 2050 respectively (relative to 2018) assuming no population changes. Including population projections (increases in all regions for 30+ years age group) slightly offsets these health benefits, resulting in reductions of 25%, 27%, and 26% in mortality burdens for 2030, 2040, 2050 respectively. Significant reductions in future mortality burdens are estimated and, importantly for public health, the majority of benefits are achieved early on in the future timeline simulated, though further efforts are likely needed to reduce impacts of air pollution to health.

Breaking New Ground: Space Agencies and Epidemiologists Partner Up on Particulates

Breaking New Ground: Space Agencies and Epidemiologists Partner Up on Particulates

Low ozone dry deposition rates to sea ice during the MOSAiC field campaign: Implications for the Arctic boundary layer ozone budget

Dry deposition to the surface is one of the main removal pathways of tropospheric ozone (O3). We quantified for the first time the impact of O3 deposition to the Arctic sea ice on the planetary boundary layer (PBL) O3 concentration and budget using year-round flux and concentration observations from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign and simulations with a single-column atmospheric chemistry and meteorological model (SCM). Based on eddy-covariance O3 surface flux observations, we find a median surface resistance on the order of 20,000 s m−1, resulting in a dry deposition velocity of approximately 0.005 cm s−1. This surface resistance is up to an order of magnitude larger than traditionally used values in many atmospheric chemistry and transport models. The SCM is able to accurately represent the yearly cycle, with maxima above 40 ppb in the winter and minima around 15 ppb at the end of summer. However, the observed springtime ozone depletion events are not captured by the SCM. In winter, the modelled PBL O3 budget is governed by dry deposition at the surface mostly compensated by downward turbulent transport of O3 towards the surface. Advection, which is accounted for implicitly by nudging to reanalysis data, poses a substantial, mostly negative, contribution to the simulated PBL O3 budget in summer. During episodes with low wind speed (<5 m s−1) and shallow PBL (<50 m), the 7-day mean dry deposition removal rate can reach up to 1.0 ppb h−1. Our study highlights the importance of an accurate description of dry deposition to Arctic sea ice in models to quantify the current and future O3 sink in the Arctic, impacting the tropospheric O3 budget, which has been modified in the last century largely due to anthropogenic activities.

Impact of changes in refractive indices of secondary organic aerosols on precipitation over China during 1980–2019

Secondary organic aerosols (SOAs), which include both colorless and colored carbonaceous aerosols, represent a major type of aerosol globally. Previous studies have reported that colored aerosols drive the well-known precipitation changes over southern China called the south-flood north-drought (SFND). Considering the highest concentration of SOA in China, SOAs can cause fluctuations in the precipitation system over China. However, studies on the climatic effects of SOAs over East Asia are scarce owing to the chemical complexity of SOAs and high computational cost. Therefore, to investigate the effect of SOAs on the precipitation change over China, we implemented an SOA scheme using empirical parameters in the chemistry-climate model. We performed a control and two sensitivity simulations depending on the difference in refractive indices of SOAs to elucidate the effects of light absorption by SOAs on precipitation. Our results suggest that strong light absorption by SOAs strengthens the convective precipitation over southern China following the enhancement of atmospheric stability with a secondary circulation effect. However, the surface temperature changes caused by SOAs shift the jet core if weak light absorption by SOAs is assumed, causing a strong downdraft in the mid-troposphere and decreasing humidity over south-eastern China. Therefore, precipitation was significantly reduced over southern China. Our results show that light-absorbing SOAs have had a significant impact on precipitation in southern China for the past few decades. Furthermore, the apparent difference in mechanisms of precipitation change between strong and weak light absorption by SOAs suggests the importance of choosing suitable refractive indices for SOAs in the climate–atmospheric chemistry model.

Sensitivity analysis of atmospheric oxidation capacity in Beijing based on the GRAPES-CUACE adjoint model

In this study, based on the evaluation index of atmospheric oxidation capacity (AOIe), the GRAPES-CUACE atmospheric chemistry model was used to simulate and analyze the variation characteristics of atmospheric oxidation capacity (AOC) in Beijing during typical pollution processes in each season in 2017. The sensitivity analysis of the AOIe in Beijing was further conducted using the GRAPES-CUACE adjoint model, and the contribution of precursor emissions in Beijing and surrounding areas to the AOIe in Beijing was quantitatively evaluated. The findings revealed that, on average, Beijing's AOC was strongest in summer, followed by spring and autumn, and weakest in winter. The contribution of oxidation capacity of gaseous-phase oxidation products (AOIe_G) to AOIe was dominant in all seasons, and the oxidation capacity of particle-phase oxidation products (AOIe_P) contributed a relatively larger proportion during PM2.5 pollution periods in winter. Adjoint sensitivity analysis showed that the Beijing peak AOIe value was controlled by both NOx and VOCs in summer, VOCs in winter, and somewhere in between in spring and autumn. Overall, Beijing and Hebei emissions contributed the most to the Beijing peak AOIe value, with a combined contribution of 63–83.6%, while Tianjin, Shanxi, and Shandong emissions also made a non-negligible contribution. In terms of emission source types, VOCs emissions contributed the most to the Beijing peak AOIe value (42.9–79.4%); NOx emissions contributed the most in summer (43.1%) and the least in winter (16.5%); CO emissions contributed a proportion of 4–17.4%. These results further demonstrate that the AOIe index is an appropriate indicator to quantify AOC, laying the foundation for subsequent research based on AOIe. Besides, this study provides more refined results on the sensitivity of AOIe in Beijing to precursor emissions and detects the critical emission sources and their contributions to AOIe in Beijing, which is conducive to a more comprehensive understanding of AOC and improving air quality in Beijing.

An Adaptive Auto‐Reduction Solver for Speeding Up Integration of Chemical Kinetics in Atmospheric Chemistry Models: Implementation and Evaluation in the Kinetic Pre‐Processor (KPP) Version 3.0.0

AbstractKinetic integration of large and stiff chemical mechanisms is a computational bottleneck in models of atmospheric chemistry. It requires implicit solution of the coupled system of kinetic differential equations with time‐consuming construction and inversion of the Jacobian matrix. We present here a new version of the Kinetic Pre‐Processor (KPP 3.0.0) for fast integration of chemical kinetics featuring a range of improvements over previous versions in performance, diagnostics, versatility, and community openness. KPP 3.0.0 includes a new adaptive auto‐reduction solver to decrease the size of any mechanism locally and on the fly under conditions where full complexity is not needed, by partitioning species as “fast” or “slow” based on their local production and loss rates. Previous implementations of this adaptive solver suffered from excessive overhead in the repeated construction of the local Jacobian matrix or were hard‐wired to specific mechanisms. Here we retain the general applicability of the method to any mechanism and avoid overhead by using pre‐computed Jacobian matrix terms for the full mechanism and cropping the matrix locally to remove the slow species with no change in memory allocation. We apply this adaptive solver within KPP 3.0.0 to the GEOS‐Chem global 3‐D model of atmospheric chemistry and demonstrate a 32% reduction in solver time while maintaining a mean error lower than 1% for key species in the troposphere.

Description and evaluation of a newly developed emission inventory processing system (EMIPS)

Commonly available emission inventories are often incompatible with the input requirements of atmospheric chemistry models due to temporal and spatial resolution, pollutant types, etc. We present the Emission Inventory Processing System (EMIPS) version 1, an open-source and multi-scale atmospheric emission modeling framework that prepares specific emissions inputs for atmospheric chemistry models. EMIPS is a multifunctional and user-friendly system, coded in Jython and developed on the MeteoInfo software platform. It allows users to freely combine and process emission inventories to generate model-ready emissions data. The core functions of EMIPS include preprocessing, temporal allocation, spatial allocation, chemical speciation, and vertical allocation. We detail the implementation of each function in the body of this paper, and several examples are provided for illustration. The emission outputs obtained with EMIPS have been evaluated by simulating four pollutants (PM2.5, PM10, NO2, and O3) concentrations in January 2017 using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), and comparison of model results with the observations indicates the model can reproduce the temporal and spatial patterns of pollutants, suggesting that EMIPS is capable of supporting atmospheric chemistry modeling. We expect this work could help to improve air quality research and forecast.

Contribution of biomass burning to black carbon deposition on Andean glaciers: consequences for radiative forcing

Andean glaciers have melted rapidly since the 1960s. While some melting is likely due to anthropogenic climate change driven by increasing greenhouse gases, deposition of light-absorbing particles such as black carbon (BC) may also play a role. We hypothesize that BC from fires in the Amazon Basin and elsewhere may be deposited on Andean glaciers, reducing the surface albedo and inducing further melting. Here we investigate the role of BC deposition on albedo changes in the Andes for 2014–2019 by combining atmospheric chemistry modeling with observations of BC in snow or ice at four mountain sites in Peru (Quelccaya, Huascarán, Yanapaccha, and Shallap) and at one site in Bolivia (Illimani). We find that annual mean ice BC concentrations simulated by the chemical transport model GEOS-Chem for 2014–2019 are roughly consistent with those observed at the site with the longest record, Huascarán, with overestimates of 15%–40%. Smoke from fires account for 20%–70% of total wet and dry deposition fluxes, depending on the site. The rest of BC deposited comes from fossil fuel combustion. Using a snow albedo model, we find that the annual mean radiative forcing from the deposition of smoke BC alone on snow ranges from +0.1 to +3.2 W m−2 under clear-sky conditions, with corresponding average albedo reductions of 0.04%–1.1%. These ranges are dependent on site and snow grain size. This result implies a potentially significant climate impact of biomass burning in the Amazon on radiative forcing in the Andes.

Airborne glyoxal measurements in the marine and continental atmosphere: comparison with TROPOMI observations and EMAC simulations

Abstract. We report on airborne limb and nadir measurements of vertical profiles and total vertical column densities (VCDs) of glyoxal (C2H2O2) in the troposphere, which were performed aboard the German research aircraft HALO (High Altitude and LOng Range) in different regions and seasons around the globe between 2014 and 2019. The airborne nadir and integrated limb profiles agree excellently among each other. Our airborne observations are further compared to collocated glyoxal measurements of the TROPOspheric Monitoring Instrument (TROPOMI), with good agreement between both data sets for glyoxal observations in (1) pristine terrestrial, (2) pristine marine, (3) mixed polluted, and (4) biomass-burning-affected air masses with high glyoxal concentrations. Exceptions to the overall good agreement are observations of (1) faint and aged biomass burning plumes over the oceans and (2) of low-lying biomass burning or anthropogenic plumes in the terrestrial or marine boundary layer, both of which contain elevated glyoxal that is mostly not captured by TROPOMI. These differences in airborne and satellite-detected glyoxal are most likely caused by the overall small contribution of plumes of a limited extent to the total glyoxal absorption in the atmosphere and the difficulty in remotely detecting weak absorbers located close to low reflective surfaces (e.g. the ocean in the visible wavelength range) or within dense aerosol layers. Observations of glyoxal in aged biomass burning plumes (e.g. observed over the tropical Atlantic off the coast of West Africa in summer 2018, off the coast of Brazil by the end of the dry season 2019, and the East China Sea in spring 2018) could be traced back to related wildfires, such as a plume crossing over the Drake Passage that originated from the Australian bushfires in late 2019. Our observations of glyoxal in such aged biomass burning plumes confirm recent findings of enhanced glyoxal and presumably secondary organic aerosol (SOA) formation in aged wildfire plumes from yet-to-be-identified, longer-lived organic precursor molecules (e.g. aromatics, acetylene, or aliphatic compounds) co-emitted in the fires. Furthermore, elevated glyoxal (median 44 ppt – parts per trillion), as compared to other marine regions (median 10–19 ppt), is observed in the boundary layer over the tropical oceans, which is well in agreement with previous reports. The airborne data sets are further compared to glyoxal simulations performed with the global atmosphere chemistry model EMAC (ECHAM/MESSy Atmospheric Chemistry). When using an EMAC set up that resembles recent EMAC studies focusing on complex chemistry, reasonable agreement is found for pristine air masses (e.g. the unperturbed free and upper troposphere), but a notable glyoxal overestimation of the model exists for regions with high emissions of glyoxal and glyoxal-producing volatile organic compounds (VOCs) from the biosphere (e.g. the Amazon). In all other investigated regions, the model underpredicts glyoxal to varying degrees, in particular when probing mixed emissions from anthropogenic activities (e.g. over continental Europe, the Mediterranean, and East China Sea) and potentially from the sea (e.g. the tropical oceans). Also, the model tends to largely underpredict glyoxal in city plumes and aged biomass burning plumes. The potential causes for these differences are likely to be multifaceted, but they all point to missing glyoxal sources from the degradation of the mixture of potentially longer-chained organic compounds emitted from anthropogenic activities, biomass burning, and from the organic microlayer of the sea surface.

Nitrogen oxides in the free troposphere: implications for tropospheric oxidants and the interpretation of satellite NO2 measurements

Abstract. Satellite-based retrievals of tropospheric NO2 columns are widely used to infer NOx (≡ NO + NO2) emissions. These retrievals rely on model information for the vertical distribution of NO2. The free tropospheric background above 2 km is particularly important because the sensitivity of the retrievals increases with altitude. Free tropospheric NOx also has a strong effect on tropospheric OH and ozone concentrations. Here we use observations from three aircraft campaigns (SEAC4RS, DC3, and ATom) and four atmospheric chemistry models (GEOS-Chem, GMI, TM5, and CAMS) to evaluate the model capabilities for simulating NOx in the free troposphere and attribute it to sources. NO2 measurements during the Studies of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS) and Deep Convective Clouds and Chemistry (DC3) campaigns over the southeastern U.S. in summer show increasing concentrations in the upper troposphere above 10 km, which are not replicated by the GEOS-Chem, although the model is consistent with the NO measurements. Using concurrent NO, NO2, and ozone observations from a DC3 flight in a thunderstorm outflow, we show that the NO2 measurements in the upper troposphere are biased high, plausibly due to interference from thermally labile NO2 reservoirs such as peroxynitric acid (HNO4) and methyl peroxy nitrate (MPN). We find that NO2 concentrations calculated from the NO measurements and NO–NO2 photochemical steady state (PSS) are more reliable to evaluate the vertical profiles of NO2 in models. GEOS-Chem reproduces the shape of the PSS-inferred NO2 profiles throughout the troposphere for SEAC4RS and DC3 but overestimates NO2 concentrations by about a factor of 2. The model underestimates MPN and alkyl nitrate concentrations, suggesting missing organic NOx chemistry. On the other hand, the standard GEOS-Chem model underestimates NO observations from the Atmospheric Tomography Mission (ATom) campaigns over the Pacific and Atlantic oceans, indicating a missing NOx source over the oceans. We find that we can account for this missing source by including in the model the photolysis of particulate nitrate on sea salt aerosols at rates inferred from laboratory studies and field observations of nitrous acid (HONO) over the Atlantic. The median PSS-inferred tropospheric NO2 column density for the ATom campaign is 1.7 ± 0.44 × 1014 molec. cm−2, and the NO2 column density simulated by the four models is in the range of 1.4–2.4 × 1014 molec. cm−2, implying that the uncertainty from using modeled NO2 tropospheric columns over clean areas in the retrievals for stratosphere–troposphere separation is about 1 × 1014 molec. cm−2. We find from GEOS-Chem that lightning is the main primary NOx source in the free troposphere over the tropics and southern midlatitudes, but aircraft emissions dominate at northern midlatitudes in winter and in summer over the oceans. Particulate nitrate photolysis increases ozone concentrations by up to 5 ppbv (parts per billion by volume) in the free troposphere in the northern extratropics in the model, which would largely correct the low model bias relative to ozonesonde observations. Global tropospheric OH concentrations increase by 19 %. The contribution of the free tropospheric background to the tropospheric NO2 columns observed by satellites over the contiguous U.S. increases from 25 ± 11 % in winter to 65 ± 9 % in summer, according to the GEOS-Chem vertical profiles. This needs to be accounted for when deriving NOx emissions from satellite NO2 column measurements.

Reconciling the bottom-up and top-down estimates of the methane chemical sink using multiple observations

Abstract. The methane chemical sink estimated by atmospheric chemistry models (bottom-up method) is significantly larger than estimates based on methyl chloroform (MCF) inversions (top-down method). The difference is partly attributable to large uncertainties in hydroxyl radical (OH) concentrations simulated by the atmospheric chemistry models used to derive the bottom-up estimates. In this study, we propose a new approach based on OH precursor observations and a chemical box model. This approach contributes to improving the 3D distributions of tropospheric OH radicals obtained from atmospheric chemistry models and reconciling bottom-up and top-down estimates of the chemical loss of atmospheric methane. By constraining simulated OH precursors with observations, the global mean tropospheric column-averaged air-mass-weighted OH concentration ([OH]trop-M) is ∼10×105 molec. cm−3 (which is 2×105 molec. cm−3 lower than the original model-simulated global [OH]trop-M) and agrees with that obtained by the top-down method based on MCF inversions. With OH constrained by precursor observations, the methane chemical loss is 471–508 Tg yr−1, averaged from 2000 to 2009. The new adjusted estimate is in the range of the latest top-down estimate of the Global Carbon Project (GCP) (459–516 Tg yr−1), contrary to the bottom-up estimates that use the original model-simulated OH fields (577–612 Tg yr−1). The overestimation of global [OH]trop-M and methane chemical loss simulated by the atmospheric chemistry models is caused primarily by the models' underestimation of carbon monoxide and total ozone column, and overestimation of nitrogen dioxide. Our results highlight that constraining the model-simulated OH fields with available OH precursor observations can help improve bottom-up estimates of the global methane sink.

An inversion model based on GEOS-Chem for estimating global and China's terrestrial carbon fluxes in 2019

The 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories added the method of assimilating atmospheric CO2 concentrations to invert carbon sources and sinks; however, many global carbon inversion models are not publicly available. In addition, our regional assimilation inversion system, CCMVS-R (China Carbon Monitoring, Verification and Supporting for Regional), needs a global carbon inversion model with higher assimilation efficiency to provide boundary conditions. Here, an inversion model based on the global atmospheric chemistry model GEOS-Chem and a more accurate and easier-to-implement ensemble square root Kalman filter (EnSRF) algorithm is constructed and used to infer global and China's carbon fluxes in 2019. Atmospheric CO2 concentrations from ObsPack sites and five additional CO2 observational sites from China's Greenhouse Gas Observation Network (CGHGNET) were used for data assimilation to improve the estimate. The inverted annual global terrestrial and oceanic carbon uptake is 2.12 and 2.53 Pg C per year, respectively, accounting for 21.1% and 25.1% of global fossil fuel CO2 emissions. The remaining 5.41 Pg C per year in the atmosphere is consistent with the global atmospheric CO2 growth rates of 5.44 Pg C per year reported by the National Oceanic and Atmospheric Administration (NOAA), showing that the inversion model can provide a reasonable estimate of global-scale natural carbon sinks. The inverted terrestrial carbon sink of China is 0.37 Pg C per year, accounting for approximately 13% of China's fossil CO2 emissions.

Evaluation of reaction between SO2 and CH2OO in MCM mechanism against smog chamber data from ethylene ozonolysis

Environmental context The process of ethylene ozonolysis is an essential source of CH2OO radicals, and the latter is an important oxidant for the atmospheric pollutant SO2. The accuracy of a widely used atmospheric chemistry model (Master Chemical Mechanism, MCM) in quantifying SO2 oxidation has not been evaluated. In this study, this accuracy was evaluated, and optimal parameters underpinned by data from smog chamber experiments. Rationale The oxidation of SO2 by CH2OO radicals in the ethylene-O3 system is one of the important pathways of sulfate aerosol formation, but the accuracy of Master Chemical Mechanism (MCM) simulation for this reaction was not evaluated, although the MCM has been widely used in previous studies. Methodology The oxidation of SO2 in the ethylene-O3 system was performed in detail under different conditions, which were used to evaluate the accuracy of MCM simulation for the reactions in this study. Results The experimental conditions of low RH and high initial SO2 concentration favour the SO2 oxidation in the ethylene ozonolysis, and the yield of CH2OO in the ethylene ozonolysis without irradiations was determined to be 0.43. The n-hexane (C6H14) oxidation intermediates can promote the SO2 oxidation rate by generating sulfur-containing organics in the aerosol water. The original MCM simulated SO2 consumption after 4-h reaction was more than 70% smaller than the measured results. By adjusting the yield of CH2OO and updating the reaction rate constants of CH2OO-related reactions (e.g. with SO2, H2O and organic acid), the difference between experiments and simulations decreased from 70% to 6.6%. Discussion The promotion effects of n-hexane on the oxidation of SO2 suggest that alkanes may be the precursors of sulfur-containing organics in the atmospheric environment. This study further confirms the effect of CH2OO on the oxidation of SO2 in the atmospheric environment and provides information on the performance of MCM simulation.

GIS Atmospheric Chemical Fate Model Simulation of Iron Released from High Intensity Bombing in Northwestern Laos

The atmospheric dispersal of iron fragments ejected from detonated ordnance released within the Nam Souy sub-basin during the secret bombing campaign of Laos from 1965 ~ 1973 was simulated through python integration with ArcGIS. The data for the study was obtained from the US National Archives and shows that of a total of 7,667,619 weapons delivered in Laos (4.5 million tons), 19,005 (5,900 tons) were dropped within the study site. The simulation adapted Gaussian isotropic puff modeling for the dust/grain-sized fragments and explosive force radial release modeling for the larger fragments into python script to produce temporal raster output images of the dispersal patterns of the analyte. The use of code language libraries ArcPy, NumPy, and numba and the logic for their application is discussed and reported along with the script developed. The simulation produced 9 m2 resolution raster images displaying iron material loading at ground level. Loading density is reported at a range between 0 ~ 7.5 g/m2 washable iron load, 0 ~ 0.65 kg/m2 of suspended iron load, and 0 ~ 3.5 kg/m2 of bedded load. The results are intended for use in subsequent studies of surface removal over time with a potential application in exposure risk analysis and for the assessment of impact on natural environments.

Iodine emission from the reactive uptake of ozone to simulated seawater.

The heterogeneous reaction of ozone and iodide is both an important source of atmospheric iodine and dry deposition pathway of ozone in marine environments. While the iodine generated from this reaction is primarily in the form of HOI and I2, there is also evidence of volatile organoiodide compound emissions in the presence of organics without biological activity occuring [M. Martino, G. P. Mills, J. Woeltjen and P. S. Liss, A new source of volatile organoiodine compounds in surface seawater, Geophys. Res. Lett., 2009, 36, L01609, L. Tinel, T. J. Adams, L. D. J. Hollis, A. J. M. Bridger, R. J. Chance, M. W. Ward, S. M. Ball and L. J. Carpenter, Influence of the Sea Surface Microlayer on Oceanic Iodine Emissions, Environ. Sci. Technol., 2020, 54, 13228-13237]. In this study, we evaluate our fundamental understanding of the ozonolysis of iodide which leads to gas-phase iodine emissions. To do this, we compare experimental measurements of ozone-driven gas-phase I2 formation in a flow tube to predictions made with the kinetic multilayer model for surface and bulk chemistry (KM-SUB). The KM-SUB model uses literature rate coefficients used in current atmospheric chemistry models to predict I2(g) formation in pH-buffered solutions of marine composition containing chloride, bromide, and iodide compared to solutions containing only iodide. Experimentally, I2(g) formation was found to be suppressed in solutions containing seawater levels of chloride compared to solutions containing only iodide, but the model does not predict this effect using literature rate constants. However, the model is able to predict this trend upon adjustment of two specific reaction rate constants. To more closely represent true oceanic conditions, we add an organic component to the proxy seawater solutions using material generated from Thalassiosira pseudonana phytoplankton cultures. Whereas the rate of ozone deposition is unaffected, the formation rate of I2(g) is strongly suppressed in the presence of biological organic material, indicative of a sink or reduction of reactive iodine formed during the oxidation process.

Improvement of local ozone phytotoxicity modelling for autochthonous grape cultivars

The grapevine is a key crop for Mediterranean environments and is both sensitive to climate warming and air pollutants, of which ozone is the most damaging to crop yield and quality. Ambient ozone effects on the grapevine have been noticed since the late fifties but risk assessments are still impaired by the lack of information concerning differences in cultivar sensitivity, and adaptation capacity to environmental factors including drought conditions. This study develops a specific parametrization for autochthonous grape cultivars within a leaf-level stomatal flux model, the DO3SE model, coupled with a meteorological and atmospheric chemical transport modelling system, the WRF-CHIMERE, by using a renowned wine producing area, the Douro wine region of Portugal, as case study. The DO3SE model parametrization introduced in this study included phenology, photosynthetic active radiation, air temperature, air vapour pressure deficit, and leaf water potential as a proxy of soil water content. The modelling experiments, which included simulations with the current default Convention on Long-Range Transboundary Air Pollution DO3SE parametrization and with the proposed parametrization, covered a reference grapevine growing season (from April to September 2017), during which a measuring campaign was carried out. Simulation results show that the proposed parametrization succeeded to replicate the observed grapevine leaf-level stomatal flux gradient in the region. Both field and modified DO3SE model values indicate that considerable areas in the Douro wine region of Portugal can exceed critical phytotoxic ozone dose (POD) values, although with a lower and different spatial extent when compared to the default DO3SE parametrization for the grapevine. However, under irrigated conditions, the POD values increase, and the values are close to those obtained with the default parametrization. Overall, the research results indicate that air quality management, in particular the reduction of ozone levels in the ambient air, must also be considered to define sustainable grape and wine production strategies in the context of climate and wine production management change.