GEOS-Chem Chemical Transport Model Research Articles

Interannual variability of summertime formaldehyde (HCHO) vertical column density and its main drivers at northern high latitudes

Abstract. The northern high latitudes (50–90° N, mostly including boreal-forest and tundra ecosystems) have been undergoing rapid climate and ecological changes over recent decades, leading to significant variations in volatile organic compounds (VOC) emissions from biogenic and biomass burning sources. Formaldehyde (HCHO) is an indicator of VOC emissions, but the interannual variability of HCHO and its main drivers over the region remains unclear. In this study, we use the GEOS-Chem chemical transport model and satellite retrievals from the Ozone Monitoring Instrument (OMI) and the Ozone Mapping and Profiler Suite (OMPS) to examine the interannual variability of HCHO vertical column density (VCD) during the summer seasons spanning from 2005 to 2019. Our results show that, in 2005–2019 summers, wildfires contributed 75 %–90 % of the interannual variability of HCHO VCD over Siberia, Alaska and northern Canada, while biogenic emissions and background methane oxidation account for ∼ 90 % of HCHO interannual variability over eastern Europe. We find that monthly solar-induced chlorophyll fluorescence (SIF) from the Orbiting Carbon Observatory-2 (OCO-2), an efficient proxy for plant photosynthesis, shows a good linear relationship (R= 0.6–0.7) with the modeled biogenic HCHO column (dVCDBio,GC) in eastern Europe, Siberia, Alaska and northern Canada, indicating the coupling between SIF and biogenic VOC emissions over the four domains on a monthly scale. In Alaska, Siberia and northern Canada, SIF and dVCDBio,GC both show relatively lower interannual variabilities (SIF: CV = 1 %–9 %, dVCDBio,GC: CV = 1 %–2 %; note that CV stands for coefficient of variation) in comparison to wildfire-induced HCHO (CV = 8 %–13 %), suggesting that the high interannual variabilities of OMI HCHO VCD (CV = 10 %–16 %) in these domains are likely driven by wildfires instead of biogenic emissions.

Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes

Abstract. The newly developed offline land ecosystem model Terrestrial Ecosystem Model in R (TEMIR) version 1.0 is described here. This version of the model simulates plant ecophysiological (e.g., photosynthetic and stomatal) responses to varying meteorological conditions and concentrations of CO2 and ground-level ozone (O3) based on prescribed meteorological and atmospheric chemical inputs from various sources. Driven by the same meteorological data used in the GEOS-Chem chemical transport model, this allows asynchronously coupled experiments with GEOS-Chem simulations with unique coherency for investigating biosphere–atmosphere chemical interactions. TEMIR agrees well with FLUXNET site-level gross primary productivity (GPP) in terms of both the diurnal and monthly cycles (correlation coefficients R2>0.85 and R2>0.8, respectively) for most plant functional types (PFTs). Grass and shrub PFTs have larger biases due to generic model representations. The model performs best when driven by local site-level meteorology rather than reanalyzed gridded meteorology. Simulation using gridded meteorology agrees well for annual GPP in seasonality and spatial distribution with a global average of 134 Pg C yr−1. Application of Monin–Obukhov similarity theory to infer canopy conditions from gridded meteorology does not improve model performance, predicting an increase of +7 % in global GPP. Present-day O3 concentrations simulated by GEOS-Chem and an O3 damage scheme at high sensitivity show a 2 % reduction in global GPP with prominent reductions of up to 15 % in eastern China and the eastern USA. Regional correlations are generally unchanged when O3 is present and biases are reduced, especially for regions with high O3 damage. An increase in atmospheric CO2 concentration of 20 ppmv from the level in 2000 to the level in 2010 modestly decreases O3 damage due to reduced stomatal uptake, consistent with ecophysiological understanding. Our work showcases the utility of this version of TEMIR for evaluating biogeophysical responses of vegetation to changes in atmospheric composition and meteorological conditions.

Improved biomass burning emissions from 1750 to 2010 using ice core records and inverse modeling

Estimating fire emissions prior to the satellite era is challenging because observations are limited, leading to large uncertainties in the calculated aerosol climate forcing following the preindustrial era. This challenge further limits the ability of climate models to accurately project future climate change. Here, we reconstruct a gridded dataset of global biomass burning emissions from 1750 to 2010 using inverse analysis that leveraged a global array of 31 ice core records of black carbon deposition fluxes, two different historical emission inventories as a priori estimates, and emission-deposition sensitivities simulated by the atmospheric chemical transport model GEOS-Chem. The reconstructed emissions exhibit greater temporal variabilities which are more consistent with paleoclimate proxies. Our ice core constrained emissions reduced the uncertainties in simulated cloud condensation nuclei and aerosol radiative forcing associated with the discrepancy in preindustrial biomass burning emissions. The derived emissions can also be used in studies of ocean and terrestrial biogeochemistry.

Urban methane emission monitoring across North America using TROPOMI data: an analytical inversion approach

Monitoring methane emissions is crucial in mitigating climate change as it has a relatively short atmospheric lifetime of about 12 years and a significant radiative forcing impact. To measure the impact of methane-controlling policies and techniques, a deep understanding of methane emissions is of great importance. Remote sensing offers scalable approaches for monitoring methane emissions at various scales, from point-source high-resolution monitoring to regional and global estimates. The TROPOMI satellite instrument provides daily XCH4 data globally, offering the opportunity to monitor methane at a moderate spatial resolution with an acceptable level of sensitivity. To infer emissions from TROPOMI data, we used the prior emission estimates from global and national inventories and the GEOS-Chem chemical transport model to simulate atmospheric methane along with actual observations of TROPOMI. In this study, methane emissions from Toronto, Montreal, New York, Los Angeles, Houston, and Mexico City have been estimated using the analytical solution of Bayesian inversion using the cloud-based Integrated Methane Inversion (IMI) framework. Using the result from ensemble inversions, and city boundaries, the average total emissions were as follows: Toronto 230.52 Gg a−1, Montreal 111.54 Gg a−1, New York 144.38 Gg a−1, Los Angeles 207.03 Gg a−1, Houston 650.16 Gg a−1, and Mexico City 280.81 Gg a−1. The resulting gridded scale factors ranged from 0.22 to 6.2, implying methane prior emission underestimations in most of these cities. As such, this study underscores the key role of remote sensing in accurately assessing urban methane emissions, informing essential climate mitigation efforts.

Exposure to Smoke From Wildfire, Prescribed, and Agricultural Burns Among At-Risk Populations Across Washington, Oregon, and California.

Wildfires, prescribed burns, and agricultural burns all impact ambient air quality across the Western U.S.; however, little is known about how communities across the region are differentially exposed to smoke from each of these fire types. To address this gap, we quantify smoke exposure stemming from wildfire, prescribed, and agricultural burns across Washington, Oregon, and California from 2014 to 2020 using a fire type-specific biomass burning emissions inventory and the GEOS-Chem chemical transport model. We examine fire type-specific PM2.5 concentration by race/ethnicity, socioeconomic status, and in relation to the Center for Disease Control's Social Vulnerability Index. Overall, population-weightedPM2.5 concentrations are greater from wildfires than from prescribed and from agricultural burns. While we found limited evidence of exposure disparities among sub-groups across the full study area, we did observe disproportionately higher exposures to wildfire-specific PM2.5 exposures among Native communities in all three states and, in California, higher agricultural burn-specific PM2.5 exposures among lower socioeconomic groups. We also identified, for all three states, areas of significant spatial clustering of smoke exposures from all fire types and increased social vulnerability. These results provide a first look at the differential contributions of smoke from wildfires, prescribed burns, and agricultural burns to PM2.5 exposures among demographic subgroups, which can be used to inform more tailored exposure reduction strategies across sources.

Contribution of expanded marine sulfur chemistry to the seasonal variability of dimethyl sulfide oxidation products and size-resolved sulfate aerosol

Abstract. Marine emissions of dimethyl sulfide (DMS) and the subsequent formation of its oxidation products methanesulfonic acid (MSA) and sulfuric acid (H2SO4) are well-known natural precursors of atmospheric aerosols, contributing to particle mass and cloud formation over ocean and coastal regions. Despite a long-recognized and well-studied role in the marine troposphere, DMS oxidation chemistry remains a work in progress within many current air quality and climate models, with recent advances exploring heterogeneous chemistry and uncovering previously unknown intermediate species. With the identification of additional DMS oxidation pathways and intermediate species that influence the eventual fate of DMS, it is important to understand the impact of these pathways on the overall sulfate aerosol budget and aerosol size distribution. In this work, we update and evaluate the DMS oxidation mechanism of the chemical transport model GEOS-Chem by implementing expanded DMS oxidation pathways in the model. These updates include gas- and aqueous-phase reactions, the formation of the intermediates dimethyl sulfoxide (DMSO) and methanesulfinic acid (MSIA), and cloud loss and aerosol uptake of the recently quantified intermediate hydroperoxymethyl thioformate (HPMTF). We find that this updated mechanism collectively decreases the global mean surface-layer gas-phase sulfur dioxide (SO2) mixing ratio by 40 % and enhances the sulfate aerosol (SO42-) mixing ratio by 17 %. We further perform sensitivity analyses exploring the contribution of cloud loss and aerosol uptake of HPMTF to the overall sulfur budget. Comparing modeled concentrations to available observations, we find improved biases relative to previous studies. To quantify the impacts of these chemistry updates on global particle size distributions and the mass concentration, we use the TwO-Moment Aerosol Sectional (TOMAS) aerosol microphysics module coupled to GEOS-Chem and find that changes in particle formation and growth affect the size distribution of aerosol. With this new DMS-oxidation scheme, the global annual mean surface-layer number concentration of particles with diameters smaller than 80 nm decreases by 16.8 %, with cloud loss processes related to HPMTF being mostly responsible for this reduction. However, the global annual mean number of particles larger than 80 nm (corresponding to particles capable of acting as cloud condensation nuclei, CCN) increases by 3.8 %, suggesting that the new scheme promotes seasonal particle growth to these sizes.

Long-term spatiotemporal variations of ammonia in the Yangtze River Delta region of China and its driving factors

This study focuses on the spatiotemporal distribution, urban-rural variations, and driving factors of ammonia Vertical Column Densities (VCDs) in China's Yangtze River Delta region (YRD) from 2008 to 2020. Utilizing data from the Infrared Atmospheric Sounding Interferometer (IASI), Generalized Additive Models (GAM), and the GEOS-Chem chemical transport model, we observed a significant increase of NH3 VCDs in the YRD between 2014 and 2020. The spatial distribution analysis revealed higher NH3 concentrations in the northern part of the YRD region, primarily due to lower precipitation, alkaline soil, and intensive agricultural activities. NH3 VCDs in the YRD region increased significantly (65.18%) from 2008 to 2020. The highest growth rate occurs in the summer, with an annual average growth rate of 7.2% during the period from 2014 to 2020. Agricultural emissions dominated NH3 VCDs during spring and summer, with high concentrations primarily located in the agricultural areas adjacent to densely populated urban zones. Regions within several large urban areas have been discovered to exhibit relatively stable variations in NH3 VCDs. The rise in NH3 VCDs within the YRD region was primarily driven by the reduction of acidic gases like SO2, as emphasized by GAM modeling and sensitivity tests using the GEOS-Chem model. The concentration changes of acidic gases contribute to over 80% of the interannual variations in NH3 VCDs. This emphasizes the crucial role of environmental policies targeting the reduction of these acidic gases. Effective emission control is urgent to mitigate environmental hazards and secondary particulate matter, especially in the northern YRD.

Source apportionment of PM2.5 in Montréal, Canada, and health risk assessment for potentially toxic elements

Abstract. Source apportionment of PM2.5 was performed using positive matrix factorization (PMF) based on detailed chemical composition data from 24 h filter samples collected over a 3-month period (August–November 2020) at an urban site in Montréal, a Canadian city with a population of approximately 4×106 people. This source apportionment study, which examined the main contributing sources to PM2.5 using a larger suite of organic molecular markers than other Canadian studies, is the first of its sort in Canada. A focus of this study was on quantifying previously unresolved sources of PM2.5 through the inclusion in the PMF analysis of additional organic molecular markers beyond those measured typically by the Canadian government's National Air Pollution Surveillance Program (NAPS). The organic species included in the PMF model were comprised of six n-alkanes, two fatty acids, one dicarboxylic acid, two biogenic secondary organic aerosol (SOA) tracers, and hopane. Secondary inorganic aerosols (SIAs) and SOAs were the dominant components and constituted 39 % of the measured PM2.5 mass, while the local primary anthropogenic sources, namely traffic exhaust, road dust, industrial, and cooking emissions, contributed 23 %. The chemical transport model GEOS-Chem revealed that ammonium sulfate concentrations in Montréal are strongly influenced by both local sources in Quebec and transboundary input from the United States, with the transboundary input exceeding the local emissions for SOA. Co and Cr(VI) presented an elevated cancer risk, highlighting that more attention should be given to these trace metals, which were associated with industrial emissions by the PMF analysis. Furthermore, the results showed that industrial emissions were minor contributors to the total PM2.5 mass concentration but were the largest contributors to Co and Cr(VI) concentrations. Thus, the health hazards associated with this source cannot be entirely established by the PM2.5 mass concentration alone. This study highlights that, when evaluating air quality in Montréal and other urban regions, the prioritization of sources for mitigation strategies will diverge if one considers total PM2.5 mass concentration or the concentration of individual particulate-bound contaminants. Furthermore, the large transboundary contribution from the United States to total PM2.5 levels suggests that future municipal, provincial, and federal monitoring and regulations would be more effective if they focus on specific high-risk contaminants (e.g., Co and Cr(VI) rather than total PM2.5).

Model Simulations and Predictions of Hydroxymethanesulfonate (HMS) in the Beijing-Tianjin-Hebei Region, China: Roles of Aqueous Aerosols and Atmospheric Acidity.

Hydroxymethanesulfonate (HMS) has been found to be an abundant organosulfur aerosol compound in the Beijing-Tianjin-Hebei (BTH) region with a measured maximum daily mean concentration of up to 10 μg per cubic meter in winter. However, the production medium of HMS in aerosols is controversial, and it is unknown whether chemical transport models are able to capture the variations of HMS during individual haze events. In this work, we modify the parametrization of HMS chemistry in the nested-grid GEOS-Chem chemical transport model, whose simulations provide a good account of the field measurements during winter haze episodes. We find the contribution of the aqueous aerosol pathway to total HMS is about 36% in winter in Beijing, due primarily to the enhancement effect of the ionic strength on the rate constants of the reaction between dissolved formaldehyde and sulfite. Our simulations suggest that the HMS-to-inorganic sulfate ratio will increase from the baseline of 7% to 13% in the near future, given the ambitious clean air and climate mitigation policies for the BTH region. The more rapid reductions in emissions of SO2 and NOx compared to NH3 alter the atmospheric acidity, which is a critical factor leading to the rising importance of HMS in particulate sulfur species.

Simulations of 7Be and 10Be with the GEOS-Chem global model v14.0.2 using state-of-the-art production rates

Abstract. The cosmogenic radionuclides 7Be and 10Be are useful tracers for atmospheric transport studies. Combining 7Be and 10Be measurements with an atmospheric transport model can not only improve our understanding of the radionuclide transport and deposition processes but also provide an evaluation of the transport process in the model. To simulate these aerosol tracers, it is critical to evaluate the influence of radionuclide production uncertainties on simulations. Here we use the GEOS-Chem chemical transport model driven by the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis to simulate 7Be and 10Be with the state-of-the-art production rate from the CRAC:Be (Cosmic Ray Atmospheric Cascade: Beryllium) model considering realistic spatial geomagnetic cutoff rigidities (denoted as P16spa). We also perform two sensitivity simulations: one with the default production rate in GEOS-Chem based on an empirical approach (denoted as LP67) and the other with the production rate from the CRAC:Be but considering only geomagnetic cutoff rigidities for a geocentric axial dipole (denoted as P16). The model results are comprehensively evaluated with a large number of measurements including surface air concentrations and deposition fluxes. The simulation with the P16spa production can reproduce the absolute values and temporal variability of 7Be and 10Be surface concentrations and deposition fluxes on annual and sub-annual scales, as well as the vertical profiles of air concentrations. The simulation with the LP67 production tends to overestimate the absolute values of 7Be and 10Be concentrations. The P16 simulation suggests less than 10 % differences compared to P16spa but a significant positive bias (∼18 %) in the 7Be deposition fluxes over East Asia. We find that the deposition fluxes are more sensitive to the production in the troposphere and downward transport from the stratosphere. Independent of the production models, surface air concentrations and deposition fluxes from all simulations show similar seasonal variations, suggesting a dominant meteorological influence. The model can also reasonably simulate the stratosphere–troposphere exchange process of 7Be and 10Be by producing stratospheric contribution and 10Be/7Be ratio values that agree with measurements. Finally, we illustrate the importance of including the time-varying solar modulations in the production calculation, which significantly improve the agreement between model results and measurements, especially at mid-latitudes and high latitudes. Reduced uncertainties in the production rates, as demonstrated in this study, improve the utility of 7Be and 10Be as aerosol tracers for evaluating and testing transport and scavenging processes in global models. For future GEOS-Chem simulations of 7Be and 10Be, we recommend using the P16spa (versus default LP67) production rate.

Evaluation of the behavior of BTEX at Beijing and Seoul in winter and summer using observations and 3-D modeling

Aromatic volatile organic compounds (VOCs) including benzene, toluene, ethylbenzene, xylene, and trimethylbenzene (BTEX) are known to contribute the most to the formation of ozone and secondary organic aerosols (SOA) in an urban atmosphere and their representation in chemical transport models (CTM) is still uncertain. In this study, we evaluated the model representation of BTEX concentrations and their seasonal difference at Beijing and Seoul using the GEOS-Chem CTM and ground observations from the Fine particle Research Initiative in East Asia considering National Differences (FRIEND) project in winter and summer. The model captured different levels of observed BTEX at Beijing and Seoul, where benzene (BENZ) was comparable and toluene + ethylbenzene (TOLU) and xylenes + trimethylbenzenes (XYLE) were higher at Seoul. The observed seasonal variations of BTEX were similar at both sites, with benzene being higher in winter and TOLU and XYLE being higher in summer. However, the magnitude and seasonal variation of TOLU at Seoul and BENZ at Beijing were not reproduced by the model. TOLU was underestimated in both seasons at Seoul especially in summer due to the underestimation of emission rates and evaporative emission being not included in the current emission inventory. At Beijing, BENZ was underestimated especially in winter and showed no seasonal variation which was different from the observations. Underestimated benzene emission rates or missing sources of it cause discrepancies between observed and modeled benzene concentrations at Beijing.

Exposure to Fine Particulate Matter (PM2.5) Is Associated with Worse Multiple Myeloma Outcomes in a Large, Urban, Multi-Ethnic Cohort

Introduction Outdoor air pollution (OAP) is a complex mixture, primarily consisting of black carbon (BC), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and particulate matter with an aerodynamic diameter of less than 2.5 microns (PM2.5). OAP is typically generated by the combustion process from motor vehicles, fossil fuel burning and industrial waste. The potential impact of air pollutants on cancer outcomes has not been systematically studied in communities of color. Multiple Myeloma (MM) is a hematologic malignancy defined by the clonal expansion of plasma cells leading to subsequent monoclonal protein expression resulting in multiple complications including anemia, renal disease, significant bone pain and increased fracture risk. MM is the second most common hematologic malignancy. The US Surveillance, Epidemiology, and End Results (SEER) registry estimates 34,000 new cases diagnosed and 13,000 deaths annually from MM. Risk factors for multiple myeloma include race, BMI, and occasionally genetic predisposition. Blacks and Hispanics were shown to have a higher incidence of MM that of non-Hispanic whites (Kaur G et al Clin Lymphoma Myeloma Leuk. 2021). There is recent evidence to suggest that environmental exposures, OAP in particular, may play a role in propagating disease progression in multiple myeloma (Landgren O JAMA Oncol 2015). A recent study demonstrated that first responders to the World Trade Center disaster had a higher rate of developing myeloma precursor disease (MGUS) and an earlier age of developing multiple myeloma (Landgren O JAMA Oncol. 2018). Our study seeks to further characterize patterns of exposure to OAP in patients with MM. Methods A retrospective cohort was developed of patients diagnosed with Multiple Myeloma at Montefiore Health System (Bronx, NY) between 1997-2018 (n=1608), using the Montefiore Electronic Data Warehouse. Of those patients, 1525 were identified as having 1 st cancer diagnosis of MM. Patient addresses (n=1514) were then used to geospatially overlay with OAP and Organic Matter from 2000-2018 using land use regression models. Ground-level PM2.5 was estimated by combining Aerosol Optical Depth (AOD) retrievals from the NASA MODIS, MISR, and SeaWIFS instruments with the GEOS-Chem chemical transport model, and subsequently calibrated to regional ground-based observations of both total and compositional mass using Geographically Weighted Regression (Hammer M.S et al Environ. Sci. Technol. 2020). This initial analysis focuses specifically on PM2.5, which was summarized as the number of years each patient was exposed to levels higher than the EPA standard of 12ug/m 3 and if the patient experienced an average PM2.5 >12ug/m 3 across their entire follow-up in the cohort. Additional information regarding demographics, dates of diagnosis and certain clinical parameters (Hgb, Cr, albumin, etc) were extracted. Differences in PM2.5 exposures, and clinical parameters, were compared by race and ethnicity using t-tests and chi-squared tests. Cox proportional hazards regression estimated the risk of death during follow-up associated with PM2.5 exposure, adjusting for confounders. Results Our patient population was highly diverse. Patients were 21% White, 50% Black with 27% having Race classified as Other. Thirty percent were Hispanic. Age at mean diagnosis was 66.24 years. On average, Bronx MM patients had higher exposure to PM2.5 than the EPA safe standard of 12 µg/m 3 from years 2000-2007 and the WHO safe standard of 5 µg/m 3 in all years of follow-up. Improved overall survival among our Multiple Myeloma patients was associated with fewer number of years exposed to PM2.5 >12 µg/m 3 (Hazard Ratio (HR)=1.12, 95% Confidence Interval (CI)=0.99- 1.27), when adjusting for sex and race. Further adjustment for smoking status yielded similar results (HR = 1.13, 95%CI = 0.98-1.30). Conclusion In this large urban, multi-ethnic cohort of MM patients, many patients experienced annual exposures to PM2.5 that were higher than the EPA and WHO safe standards of 12 µg/m 3 and 5 µg/m 3. Overall survival in MM patients was associated with fewer years of exposure to PM2.5, suggesting that reducing exposure to environmental pollutants, particularly OAP for our patients may lead to better outcomes. Additional analyses are needed to better understand the impact of treatment and clinical factors, as well as the other air pollutants in this patient population.

The export of African mineral dust across the Atlantic and its impact over the Amazon Basin

Abstract. The Amazon Basin is frequently influenced by transatlantic transport of African dust plumes during its wet season (January–April), which not only interrupts the near-pristine atmospheric condition in that season, but also provides nutrient inputs to the Amazon rainforest upon deposition. In this study, we use the chemical transport model GEOS-Chem to investigate the impact of the export of African mineral dust to the Amazon Basin during the period of 2013–2017, constrained by multiple datasets obtained from the AErosol RObotic NETwork (AERONET), MODIS, as well as the Cayenne site and the Amazon Tall Tower Observatory (ATTO) site in the Amazon Basin. With an optimized particle mass size distribution (PMSD) of dust aerosols, the model captures observed aerosol optical depth (AOD) well in terms of both the mean value and the decline rate of the logarithm of AOD over the Atlantic Ocean along the transport path (AOaTP), implying consistency with the observed export efficiency of African dust along the transatlantic transport. With an annual emission of 0.73±0.12 Pg yr−1, African dust entering the Amazon Basin during the wet season accounts for 40±4.5 % (up to 70 %) of surface aerosol mass concentrations over the basin. Observed dust peaks over the Amazon Basin are generally associated with relatively higher African dust emissions (including the Sahara and the Sahel) and longer lifetimes of dust along the transatlantic transport, i.e., higher export efficiency of African dust across the Atlantic Ocean. The frequency of dust events during the wet season is around 18 % when averaged over the Amazon Basin, with maxima of over 60 % at the northeastern coast. During the dust events, AOD over most of the Amazon Basin is dominated by dust. Based on dust deposition, we further estimate annual inputs of 52±8.7, 0.97±0.16, and 21±3.6 mg m−2 yr−1 for iron, phosphorus, and magnesium, respectively, into the Amazon rainforest, which may to some extent compensate for the hydrologic losses of nutrients in the forest ecosystem.

CHEEREIO 1.0: a versatile and user-friendly ensemble-based chemical data assimilation and emissions inversion platform for the GEOS-Chem chemical transport model

Abstract. We present a versatile, powerful, and user-friendly chemical data assimilation toolkit for simultaneously optimizing emissions and concentrations of chemical species based on atmospheric observations from satellites or suborbital platforms. The CHemistry and Emissions REanalysis Interface with Observations (CHEEREIO) exploits the GEOS-Chem chemical transport model and a localized ensemble transform Kalman filter algorithm (LETKF) to determine the Bayesian optimal (posterior) emissions and/or concentrations of a set of species based on observations and prior information using an easy-to-modify configuration file with minimal changes to the GEOS-Chem or LETKF code base. The LETKF algorithm readily allows for nonlinear chemistry and produces flow-dependent posterior error covariances from the ensemble simulation spread. The object-oriented Python-based design of CHEEREIO allows users to easily add new observation operators such as for satellites. CHEEREIO takes advantage of the Harmonized Emissions Component (HEMCO) modular structure of input data management in GEOS-Chem to update emissions from the assimilation process independently from the GEOS-Chem code. It can seamlessly support GEOS-Chem version updates and is adaptable to other chemical transport models with similar modular input data structure. A post-processing suite combines ensemble output into consolidated NetCDF files and supports a wide variety of diagnostic data and visualizations. We demonstrate CHEEREIO's capabilities with an out-of-the-box application, assimilating global methane emissions and concentrations at weekly temporal resolution and 2∘ × 2.5∘ spatial resolution for 2019 using TROPOspheric Monitoring Instrument (TROPOMI) satellite observations. CHEEREIO achieves a 50-fold improvement in computational performance compared to the equivalent analytical inversion of TROPOMI observations.

Soil Emissions of Reactive Nitrogen Accelerate Summertime Surface Ozone Increases in the North China Plain.

Summertime surface ozone in China has been increasing since 2013 despite the policy-driven reduction in fuel combustion emissions of nitrogen oxides (NOx). Here we examine the role of soil reactive nitrogen (Nr, including NOx and nitrous acid (HONO)) emissions in the 2013-2019 ozone increase over the North China Plain (NCP), using GEOS-Chem chemical transport model simulations. We update soil NOx emissions and add soil HONO emissions in GEOS-Chem based on observation-constrained parametrization schemes. The model estimates significant daily maximum 8 h average (MDA8) ozone enhancement from soil Nr emissions of 8.0 ppbv over the NCP and 5.5 ppbv over China in June-July 2019. We identify a strong competing effect between combustion and soil Nr sources on ozone production in the NCP region. We find that soil Nr emissions accelerate the 2013-2019 June-July ozone increase over the NCP by 3.0 ppbv. The increase in soil Nr ozone contribution, however, is not primarily driven by weather-induced increases in soil Nr emissions, but by the concurrent decreases in fuel combustion NOx emissions, which enhance ozone production efficiency from soil by pushing ozone production toward a more NOx-sensitive regime. Our results reveal an important indirect effect from fuel combustion NOx emission reduction on ozone trends by increasing ozone production from soil Nr emissions, highlighting the necessity to consider the interaction between anthropogenic and biogenic sources in ozone mitigation in the North China Plain.

Determination of the chemical equator from GEOS-Chem model simulation: a focus on the tropical western Pacific region

Abstract. The tropical western Pacific (TWP) plays an important role in global stratosphere–troposphere exchange and is an active region of the interhemispheric transport (IHT). Common indicators for transport between the hemispheres like the tropical rain belt are too broad or lack precision in the TWP. In this paper, we provide a method to determine the atmospheric chemical equator (CE), which is a boundary for air mass transport between the two hemispheres in the tropics. This method used the model output from an artificial passive tracer simulated by the chemical transport model GEOS-Chem in the troposphere. We investigated the movement of the CE in the tropics, which indicates the migration of atmospheric circulation systems and air mass origins. Our results show the CE on different timescales, suggesting that the different features of the IHT in different regions are highly related to the variation in the circulation systems. We compared the CE with the tropical wind fields, indicating that the region of IHT does not coincide with the convergence of the 10 m wind fields in the tropical land sectors and the TWP region. We compared the CE with the atmospheric composition such as satellite data of CH4 and model simulation of sulfur hexafluoride (SF6). The results show that the CE and north–south gradient of CH4 in the Indian Ocean in January are well consistent with each other, which indicates the CE has good potential to estimate the IHT inferred by observations. We discussed the vertical extent and the meridional extent of the IHT. We find that the vertical structure above 2 km has a slight northern tilt in the Northern Hemisphere (NH) winter season and a southern tilt in the NH summer, meaning the seasonality of the migration of the CE at the lower altitude is larger than that at the higher altitude. The meridional extent of the CE indicates a narrow transition zone where IHT happens throughout the year. We find that the meridional extent above South America is larger compared to other regions. The distribution of the land–sea contrast plays an important role in the meridional extent of IHT. We focus on the TWP region and further compared the tropical rain belt with the CE. There is a broad region of high precipitation occurring in the TWP region, and it is difficult to determine the IHT by the rain belt. In the NH winter, the CE is not consistent with the tropical rain belt in the TWP but is confined to the southern branch of the peak of the rain belt. For the other seasons, both indicators of IHT agree.

Development of an ecophysiology module in the GEOS-Chem chemical transport model version 12.2.0 to represent biosphere–atmosphere fluxes relevant for ozone air quality

Abstract. Ground-level ozone (O3) is a major air pollutant that adversely affects human health and ecosystem productivity. Removal of tropospheric O3 by plant stomatal uptake can in turn cause damage to plant tissues with ramifications for ecosystem and crop health. In many atmospheric and land surface models, the functionality of stomata opening is represented by a bulk stomatal conductance, which is often semi-empirically parameterized and highly fitted to historical observations. A lack of mechanistic linkage to ecophysiological processes such as photosynthesis may render models inadequate to represent plant-mediated responses of atmospheric chemistry to long-term changes in CO2, climate, and short-lived air pollutant concentrations. A new ecophysiology module was thus developed to mechanistically simulate land−atmosphere exchange of important gas species in GEOS-Chem, a chemical transport model widely used in atmospheric chemistry studies. The implementation not only allows for dry deposition to be coupled with plant ecophysiology but also enables plant and crop productivity and functions to respond dynamically to atmospheric chemical changes. We conduct simulations to evaluate the effects of the ecophysiology module on simulated dry deposition velocity and concentration of surface O3 against an observation-derived dataset known as SynFlux. Our estimated stomatal conductance and dry deposition velocity of O3 are close to SynFlux with root-mean-squared errors (RMSEs) below 0.3 cm s−1 across different plant functional types (PFTs), despite an overall positive bias in surface O3 concentration (by up to 16 ppbv). Representing ecophysiology was found to reduce the simulated biases in deposition fluxes from the prior model but worsen the positive biases in simulated O3 concentrations. The increase in positive concentration biases is mostly attributable to the ecophysiology-based stomatal conductance being generally smaller (and closer to SynFlux values) than that estimated by the prior semi-empirical formulation, calling for further improvements in non-stomatal depositional and non-depositional processes relevant for O3 simulations. The estimated global O3 deposition flux is 864 Tg O3 yr−1 with GEOS-Chem, and the new module decreases this estimate by 92 Tg O3 yr−1. Estimated global gross primary production (GPP) without O3 damage is 119 Pg C yr−1. O3-induced reduction in GPP is 4.2 Pg C yr−1 (3.5 %). An elevated CO2 scenario (580 ppm) yields higher global GPP (+16.8 %) and lower global O3 depositional sink (−3.3 %). Global isoprene emission simulated with a photosynthesis-based scheme is 317.9 Tg C yr−1, which is 31.2 Tg C yr−1 (−8.9 %) less than that calculated using the MEGAN (Model of Emissions of Gases and Aerosols from Nature) emission algorithm. This new model development dynamically represents the two-way interactions between vegetation and air pollutants and thus provides a unique capability in evaluating vegetation-mediated processes and feedbacks that can shape atmospheric chemistry and air quality, as well as pollutant impacts on vegetation health, especially for any timescales shorter than the multidecadal timescale.

A Coupled CH4, CO and CO2 Simulation for Improved Chemical Source Modeling

Understanding greenhouse gas–climate processes and feedbacks is a fundamental step in understanding climate variability and its links to greenhouse gas fluxes. Chemical transport models are the primary tool for linking greenhouse gas fluxes to their atmospheric abundances. Hence, accurate simulations of greenhouse gases are essential. Here, we present a new simulation in the GEOS-Chem chemical transport model that couples the two main greenhouse gases—carbon dioxide (CO2) and methane (CH4)—along with the indirect greenhouse gas carbon monoxide (CO) based on their chemistry. Our updates include the online calculation of the chemical production of CO from CH4 and the online production of CO2 from CO, both of which were handled offline in the previous versions of these simulations. In the newly developed coupled (online) simulation, we used consistent hydroxyl radical (OH) fields for all aspects of the simulation, resolving biases introduced by inconsistent OH fields in the currently available uncoupled (offline) CH4, CO and CO2 simulations. We compare our coupled simulation with the existing v12.1.1 GEOS-Chem uncoupled simulations run the way they are currently being used by the community. We discuss differences between the uncoupled and coupled calculation of the chemical terms and compare our results with surface measurements from the NOAA Global Greenhouse Gas Reference Network (NOAA GGGRN), total column measurements from the Total Carbon Column Observing Network (TCCON) and aircraft measurements from the Atmospheric Tomography Mission (ATom). Relative to the standard uncoupled simulations, our coupled results suggest a stronger CO chemical production from CH4, weaker production of CO2 from CO and biases in the OH fields. However, we found a significantly stronger chemical production of CO2 in tropical land regions, especially in the Amazon. The model–measurement differences point to underestimated biomass burning emissions and secondary production for CO. The new self-consistent coupled simulation opens new possibilities when identifying biases in CH4, CO and CO2 source and sink fields, as well as a better understanding of their interannual variability and co-variation.

Wildfire-related PM2.5 and health economic loss of mortality in Brazil

BackgroundWildfire imposes a high mortality burden on Brazil. However, there is a limited assessment of the health economic losses attributable to wildfire-related fine particulate matter (PM2.5). MethodsWe collected daily time-series data on all-cause, cardiovascular, and respiratory mortality from 510 immediate regions in Brazil during 2000–2016. The chemical transport model GEOS-Chem driven with Global Fire Emissions Database (GFED), in combination with ground monitored data and machine learning was used to estimate wildfire-related PM2.5 data at a resolution of 0.25° × 0.25°. A time-series design was applied in each immediate region to assess the association between economic losses due to mortality and wildfire-related PM2.5 and the estimates were pooled at the national level using a random-effect meta-analysis. We used a meta-regression model to explore the modification effect of GDP and its sectors (agriculture, industry, and service) on economic losses. ResultsDuring 2000–2016, a total of US$81.08 billion economic losses (US$5.07 billion per year) due to mortality were attributable to wildfire-related PM2.5 in Brazil, accounting for 0.68% of economic losses and equivalent to approximately 0.14% of Brazil’s GDP. The attributable fraction (AF) of economic losses due to wildfire-related PM2.5 was positively associated with the proportion of GDP from agriculture, while negatively associated with the proportion of GDP from service. ConclusionSubstantial economic losses due to mortality were associated with wildfires, which could be influenced by the agriculture and services share of GDP per capita. Our estimates of the economic losses of mortality could be used to determine optimal levels of investment and resources to mitigate the adverse health impacts of wildfires.

Variable effects of spatial resolution on modeling of nitrogen oxides

Abstract. The lifetime and concentration of nitrogen oxides (NOx) are susceptible to nonlinear production and loss and to the resolution of a chemical transport model (CTM). This is due to the strong spatial gradients of NOx and the dependence of its own chemical loss on such gradients. In this study, we use the GEOS-Chem CTM in its high-performance implementation (GCHP) to investigate NOx simulations over the eastern United States across a wide range of spatial model resolutions (six different horizontal grids from 13 to 181 km). Following increasing grid size, afternoon surface NOx mixing ratios over July 2015 generally decrease over the Great Lakes region (GL) and increase over the southern states of the US region (SS), yielding regional differences (181 km vs. 13 km) of −16 % (in the GL) to 7 % (in the SS); meanwhile, hydrogen oxide radicals (HOx) increase over both regions, consistent with their different chemical regimes (i.e., NOx-saturated in the GL and NOx-limited in the SS). Nighttime titration of ozone by surface nitric oxide (NO) was found to be more efficient at coarser resolutions, leading to longer NOx lifetimes and higher surface mixing ratios of nitrogen dioxide (NO2) over the GL in January 2015. The tropospheric NO2 column density at typical afternoon satellite overpass time has spatially more coherent negative biases (e.g., −8 % over the GL) at coarser resolutions in July, which reversed the positive biases of surface NOx over the SS. The reduced NOx aloft (>1 km altitude) at coarser resolutions was attributable to the enhanced HOx that intrudes into the upper troposphere. Application of coarse-resolution simulations for interpreting satellite NO2 columns will generally underestimate surface NO2 over the GL and overestimate surface NO2 over the SS in summer, but it will uniformly overestimate NOx emissions over both regions. This study significantly broadens understanding of factors contributing to NOx resolution effects and the role of fine-resolution data in accurately simulating and interpreting NOx and its relevance to air quality.