Historical Southern Hemisphere biomass burning variability inferred from ice core carbon monoxide records

Biomass burning plays an important role in climate-forcing and atmospheric chemistry. The drivers of fire activity over the past two centuries, however, are hotly debated and fueled by poor constraints on the magnitude and trends of preindustrial fire regimes. As a powerful tracer of biomass burning, reconstructions of paleoatmospheric carbon monoxide (CO) can provide valuable information on the evolution of fire activity across the preindustrial to industrial transition. Here too, however, significant disagreements between existing CO records currently allow for opposing fire histories. In this study, we reconstruct a continuous record of Antarctic ice core CO between 1821 and 1995 CE to overlap with direct atmospheric observations. Our record indicates that the Southern Hemisphere CO burden ([CO]) increased by 50% from a preindustrial mixing ratio of ca. 35 ppb to ca. 53 ppb by 1995 CE with more variability than allowed for by state-of-the-art chemistry-climate models, suggesting that historic CO dynamics have been not fully accounted for. Using a 6-troposphere box model, a 40 to 50% decrease in Southern Hemisphere biomass-burning emissions, coincident with unprecedented rates of early 20th century anthropogenic land-use change, is identified as a strong candidate for this mismatch.

Revisiting regional and seasonal variations in decadal carbon monoxide variability: Global reversal of growth rate

Carbon monoxide (CO) is one of the important trace gases in the atmosphere capturing the evolution of chemical properties of the troposphere. Here we analyze the growth rates of CO during the period of 1991-2020 using in situ measurements from the World Meteorological Organization's (WMO) Global Atmospheric Watch (GAW) program. The analysis of trends has been done on different spatial and temporal scales. Our analysis supports the decline in the overall CO mixing ratios over the globe but inter-decadal and regional trend analysis has shown heterogeneous changes in the given period of study. On average, there has been a decrease of -16.22 ± 1.92 ppb and -4.5 ± 0.64 ppb observed at the sites in the northern hemisphere (NH) and southern hemisphere (SH), respectively. This decline occurred at rates of -0.80 ± 0.12 ppb yr-1 in the NH and - 0.12 ± 0.03 ppb yr-1 in the SH. Bifurcating the annual trends for seasonal analysis reveals the impact of emissions, chemistry and atmospheric transport on CO variation over different regional clusters of stations. Seasonal trend analysis provides further evidence regarding heterogeneous patterns in the South-East Asia region. Our study highlights a slowdown in CO decline during the 2011-2020 decade when compared to the rate of decrease observed in 2001-2010. This is inferred from the variability and much slower decline of CO emissions across different regions, contributing to a weakening in CO trends.

Adoption of cleaner technologies and reduction in fire events in the hotspots lead to global decline in carbon monoxide

Carbon Monoxide (CO) is not a greenhouse gas (GHG), but has the capacity to change atmospheric chemistry of other GHGs such as methane and ozone, and therefore indirectly affects Earth's radiative forcing of the GHGs and surface temperature. Here, we use the CO mixing ratio at 850 hPa from the Tropospheric Emission Spectrometer (TES) reanalysis and the Measurement of Pollution in the Troposphere (MOPITT) satellite measurements for the period 2005-2019 to examine the spatio-temporal changes in CO across the latitudes. We find a substantial decrease in global CO, about 0.21 ± 0.09 ppb/yr (0.23 ± 0.12%/yr) with the TES data and about 0.36 ± 0.07 ppb/yr (0.45 ± 0.08%/yr) with the MOPITT satellite measurements during the study period. The highest CO decreasing trend is observed in Eastern China (2.7 ± 0.37 ppb/yr) followed by Myanmar (2.142 ± 0.59 ppb/yr) and South America (1.08 ± 0.82 ppb/yr). This negative trend in CO is primarily due to the decrease in biomass burning and stringent environmental regulations in the respective regions and countries. The sources including road transport that account for about 33.6% of CO emissions, followed by industries (18.3%) and agricultural waste burning (8.8%), might also be responsible for the reduction in CO due to adaptation of improved emission control technology and regulations in the past decade from 2005 to 2019. Therefore, the study provides new insights on the current trends of global CO distribution and reasons for recent reduction in global CO emissions, which would be useful for future decision-making process to control air pollution.

CO Fluxes in Western Europe during 2017–2020 Winter Seasons Inverted by WRF-Chem/Data Assimilation Research Testbed with MOPITT Observations

The study of anthropogenic carbon monoxide (CO) emissions is crucial to investigate anthropogenic activities. Assuming the anthropogenic CO emissions accounted for the super majority of the winter CO fluxes in western Europe, they could be roughly estimated by the inversion approach. The CO fluxes and concentrations of four consecutive winter seasons (i.e., December–February) in western Europe since 2017 were estimated by a regional CO flux inversion system based on the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and the Data Assimilation Research Testbed (DART). The CO retrievals from the Measurements Of Pollution In The Troposphere instrument (MOPITT) version 8 level 2 multi-spectral Thermal InfraRed (TIR)/Near-InfraRed (NIR) CO retrieval data products were assimilated by the inversion system. The analyses of the MOPITT data used by the inversion system indicated that the mean averaging kernel row sums of the surface level was about 0.25, and the difference percentage of the surface-level retrievals relative to a priori CO-mixing ratios was 14.79%, which was similar to that of the other levels. These results suggested the MOPITT’s surface-level observations contained roughly the same amount of information as the other levels. The inverted CO fluxes of the four winter seasons were 6198.15 kilotons, 4939.72 kilotons, 4697.80 kilotons, and 5456.19 kilotons, respectively. Based on the assumption, the United Nations Framework Convention on Climate Change (UNFCCC) inventories were used to evaluate the accuracy of the inverted CO fluxes. The evaluation results indicated that the differences between the inverted CO fluxes and UNFCCC inventories of the three winter seasons of 2017–2019 were 13.36%, −4.59%, and −4.76%, respectively. Detailed surface-CO concentrations and XCO comparative analyses between the experimental results and the external Community Atmosphere Model with Chemistry (CAM-Chem) results and the MOPITT data were conducted. The comparative analysis results indicated that the experimental results of the winter season of 2017 were obviously affected by high boundary conditions. The CO concentrations results of the experiments were also evaluated by the CO observation data from Integrated Carbon Observation System (ICOS), the average Mean Bias Error (MBE), and the Root Mean Square Error (RMSE) between the CO concentrations results of the inversion system, and the ICOS observations were −22.43 ppb and 57.59 ppb, respectively. The MBE and RMSE of the inversion system were 17.53-ppb and 4.17-ppb better than those of the simulation-only parallel experiments, respectively.

Large uncertainties in global hydroxyl projections tied to fate of reactive nitrogen and carbon

The hydroxyl radical (OH) sets the oxidative capacity of the atmosphere and, thus, profoundly affects the removal rate of pollutants and reactive greenhouse gases. While observationally derived constraints exist for global annual mean present-day OH abundances and interannual variability, OH estimates for past and future periods rely primarily on global atmospheric chemistry models. These models disagree ± 30% in mean OH and in its changes from the preindustrial to late 21st century, even when forced with identical anthropogenic emissions. A simple steady-state relationship that accounts for ozone photolysis frequencies, water vapor, and the ratio of reactive nitrogen to carbon emissions explains temporal variability within most models, but not intermodel differences. Here, we show that departure from the expected relationship reflects the treatment of reactive oxidized nitrogen species (NO y ) and the fraction of emitted carbon that reacts within each chemical mechanism, which remain poorly known due to a lack of observational data. Our findings imply a need for additional observational constraints on NO y partitioning and lifetime, especially in the remote free troposphere, as well as the fate of carbon-containing reaction intermediates to test models, thereby reducing uncertainties in projections of OH and, hence, lifetimes of pollutants and greenhouse gases.

H2 in Antarctic firn air: Atmospheric reconstructions and implications for anthropogenic emissions

The atmospheric history of molecular hydrogen (H₂) from 1852 to 2003 was reconstructed from measurements of firn air collected at Megadunes, Antarctica. The reconstruction shows that H₂ levels in the southern hemisphere were roughly constant near 330 parts per billion (ppb; nmol H₂ mol^-1 air) during the mid to late 1800s. Over the twentieth century, H₂ levels rose by about 70% to 550 ppb. The reconstruction shows good agreement with the H₂ atmospheric history based on firn air measurements from the South Pole. The broad trends in atmospheric H₂ over the twentieth century can be explained by increased methane oxidation and anthropogenic emissions. The H₂ rise shows no evidence of deceleration during the last quarter of the twentieth century despite an expected reduction in automotive emissions following more stringent regulations. During the late twentieth century, atmospheric CO levels decreased due to a reduction in automotive emissions. It is surprising that atmospheric H₂ did not respond similarly as automotive exhaust is thought to be the dominant source of anthropogenic H_2. The monotonic late twentieth century rise in H₂ levels is consistent with late twentieth-century flask air measurements from high southern latitudes. An additional unknown source of H₂ is needed to explain twentieth-century trends in atmospheric H₂ and to resolve the discrepancy between bottom-up and top-down estimates of the anthropogenic source term. The firn air-based atmospheric history of H₂ provides a baseline from which to assess human impact on the H₂ cycle over the last 150 y and validate models that will be used to project future trends in atmospheric composition as H₂ becomes a more common energy source.

Description of the NASA GEOS Composition Forecast Modeling System GEOS-CF v1.0

The Goddard Earth Observing System composition forecast (GEOS-CF) system is a high-resolution (0.25°) global constituent prediction system from NASA's Global Modeling and Assimilation Office (GMAO). GEOS-CF offers a new tool for atmospheric chemistry research, with the goal to supplement NASA's broad range of space-based and in-situ observations. GEOS-CF expands on the GEOS weather and aerosol modeling system by introducing the GEOS-Chem chemistry module to provide hindcasts and 5-days forecasts of atmospheric constituents including ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and fine particulate matter (PM2.5). The chemistry module integrated in GEOS-CF is identical to the offline GEOS-Chem model and readily benefits from the innovations provided by the GEOS-Chem community. Evaluation of GEOS-CF against satellite, ozonesonde and surface observations for years 2018-2019 show realistic simulated concentrations of O3, NO2, and CO, with normalized mean biases of -0.1 to 0.3, normalized root mean square errors between 0.1-0.4, and correlations between 0.3-0.8. Comparisons against surface observations highlight the successful representation of air pollutants in many regions of the world and during all seasons, yet also highlight current limitations, such as a global high bias in SO2 and an overprediction of summertime O3 over the Southeast United States. GEOS-CF v1.0 generally overestimates aerosols by 20%-50% due to known issues in GEOS-Chem v12.0.1 that have been addressed in later versions. The 5-days forecasts have skill scores comparable to the 1-day hindcast. Model skills can be improved significantly by applying a bias-correction to the surface model output using a machine-learning approach.

Correcting model biases of CO in East Asia: impact on oxidant distributions during KORUS-AQ

Global coupled chemistry-climate models underestimate carbon monoxide (CO) in the Northern Hemisphere, exhibiting a pervasive negative bias against measurements peaking in late winter and early spring. While this bias has been commonly attributed to underestimation of direct anthropogenic and biomass burning emissions, chemical production and loss via OH reaction from emissions of anthropogenic and biogenic volatile organic compounds (VOCs) play an important role. Here we investigate the reasons for this underestimation using aircraft measurements taken in May and June 2016 from the Korea-United States Air Quality (KORUS-AQ) experiment in South Korea and the Air Chemistry Research in Asia (ARIAs) in the North China Plain (NCP). For reference, multispectral CO retrievals (V8J) from the Measurements of Pollution in the Troposphere (MOPITT) are jointly assimilated with meteorological observations using an ensemble adjustment Kalman filter (EAKF) within the global Community Atmosphere Model with Chemistry (CAM-Chem) and the Data Assimilation Research Testbed (DART). With regard to KORUS-AQ data, CO is underestimated by 42% in the control run and by 12% with the MOPITT assimilation run. The inversion suggests an underestimation of anthropogenic CO sources in many regions, by up to 80% for northern China, with large increments over the Liaoning Province and the North China Plain (NCP). Yet, an often-overlooked aspect of these inversions is that correcting the underestimation in anthropogenic CO emissions also improves the comparison with observational O₃ datasets and observationally constrained box model simulations of OH and HO₂. Running a CAM-Chem simulation with the updated emissions of anthropogenic CO reduces the bias by 29% for CO, 18% for ozone, 11% for HO₂, and 27% for OH. Longer-lived anthropogenic VOCs whose model errors are correlated with CO are also improved, while short-lived VOCs, including formaldehyde, are difficult to constrain solely by assimilating satellite retrievals of CO. During an anticyclonic episode, better simulation of O₃, with an average underestimation of 5.5 ppbv, and a reduction in the bias of surface formaldehyde and oxygenated VOCs can be achieved by separately increasing by a factor of 2 the modeled biogenic emissions for the plant functional types found in Korea. Results also suggest that controlling VOC and CO emissions, in addition to widespread NO _x controls, can improve ozone pollution over East Asia.

Constraining remote oxidation capacity with ATom observations

The global oxidation capacity, defined as the tropospheric mean concentration of the hydroxyl radical (OH), controls the lifetime of reactive trace gases in the atmosphere such as methane and carbon monoxide (CO). Models tend to underestimate the methane lifetime and CO concentrations throughout the troposphere, which is consistent with excessive OH. Approximately half of the oxidation of methane and non-methane volatile organic compounds (VOCs) is thought to occur over the oceans where oxidant chemistry has received little validation due to a lack of observational constraints. We use observations from the first two deployments of the NASA ATom aircraft campaign during July-August 2016 and January-February 2017 to evaluate the oxidation capacity over the remote oceans and its representation by the GEOS-Chem chemical transport model. The model successfully simulates the magnitude and vertical profile of remote OH within the measurement uncertainties. Comparisons against the drivers of OH production (water vapor, ozone, and NO y concentrations, ozone photolysis frequencies) also show minimal bias, with the exception of wintertime NO y . The severe model overestimate of NO y during this period may indicate insufficient wet scavenging and/or missing loss on sea-salt aerosols. Large uncertainties in these processes require further study to improve simulated NO y partitioning and removal in the troposphere, but preliminary tests suggest that their overall impact could marginally reduce the model bias in tropospheric OH. During the ATom-1 deployment, OH reactivity (OHR) below 3 km is significantly enhanced, and this is not captured by the sum of its measured components (cOHRobs) or by the model (cOHRmod). This enhancement could suggest missing reactive VOCs but cannot be explained by a comprehensive simulation of both biotic and abiotic ocean sources of VOCs. Additional sources of VOC reactivity in this region are difficult to reconcile with the full suite of ATom measurement constraints. The model generally reproduces the magnitude and seasonality of cOHRobs but underestimates the contribution of oxygenated VOCs, mainly acetaldehyde, which is severely underestimated throughout the troposphere despite its calculated lifetime of less than a day. Missing model acetaldehyde in previous studies was attributed to measurement uncertainties that have been largely resolved. Observations of peroxyacetic acid (PAA) provide new support for remote levels of acetaldehyde. The underestimate in both model acetaldehyde and PAA is present throughout the year in both hemispheres and peaks during Northern Hemisphere summer. The addition of ocean sources of VOCs in the model increases cOHRmod by 3% to 9% and improves model-measurement agreement for acetaldehyde, particularly in winter, but cannot resolve the model summertime bias. Doing so would require 100 Tg yr-1 of a long-lived unknown precursor throughout the year with significant additional emissions in the Northern Hemisphere summer. Improving the model bias for remote acetaldehyde and PAA is unlikely to fully resolve previously reported model global biases in OH and methane lifetime, suggesting that future work should examine the sources and sinks of OH over land.

Chemical Mechanisms and Their Applications in the Goddard Earth Observing System (GEOS) Earth System Model

NASA's Goddard Earth Observing System (GEOS) Earth System Model (ESM) is a modular, general circulation model (GCM), and data assimilation system (DAS) that is used to simulate and study the coupled dynamics, physics, chemistry, and biology of our planet. GEOS is developed by the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center. It generates near-real-time analyzed data products, reanalyses, and weather and seasonal forecasts to support research targeted to understanding interactions among Earth System processes. For chemistry, our efforts are focused on ozone and its influence on the state of the atmosphere and oceans, and on trace gas data assimilation and global forecasting at mesoscale discretization. Several chemistry and aerosol modules are coupled to the GCM, which enables GEOS to address topics pertinent to NASA's Earth Science Mission. This paper describes the atmospheric chemistry components of GEOS and provides an overview of its Earth System Modeling Framework (ESMF)-based software infrastructure, which promotes a rich spectrum of feedbacks that influence circulation and climate, and impact human and ecosystem health. We detail how GEOS allows model users to select chemical mechanisms and emission scenarios at run time, establish the extent to which the aerosol and chemical components communicate, and decide whether either or both influence the radiative transfer calculations. A variety of resolutions facilitates research on spatial and temporal scales relevant to problems ranging from hourly changes in air quality to trace gas trends in a changing climate. Samples of recent GEOS chemistry applications are provided.

Global O3-CO Correlations in a Chemistry and Transport Model During July-August: Evaluation with TES Satellite Observations and Sensitivity to Input Meteorological Data and Emissions

We examine the capability of the Global Modeling Initiative (GMI) chemistry and transport model to reproduce global mid-tropospheric (618hPa) O₃-CO correlations determined by the measurements from Tropospheric Emission Spectrometer (TES) aboard NASA's Aura satellite during boreal summer (July-August). The model is driven by three meteorological data sets (fvGCM with sea surface temperature for 1995, GEOS4-DAS for 2005, and MERRA for 2005), allowing us to examine the sensitivity of model O₃-CO correlations to input meteorological data. Model simulations of radionuclide tracers (²²²Rn, ²¹⁰Pb, and ⁷Be) are used to illustrate the differences in transport-related processes among the meteorological data sets. Simulated O₃ values are evaluated with climatological ozone profiles from ozonesonde measurements and satellite tropospheric O₃ columns. Despite the fact that three simulations show significantly different global and regional distributions of O₃ and CO concentrations, all simulations show similar patterns of O₃-CO correlations on a global scale. These patterns are consistent with those derived from TES observations, except in the tropical easterly biomass burning outflow regions. Discrepancies in regional O₃-CO correlation patterns in the three simulations may be attributed to differences in convective transport, stratospheric influence, and subsidence, among other processes. To understand how various emissions drive global O₃-CO correlation patterns, we examine the sensitivity of GMI/MERRA model-calculated O₃ and CO concentrations and their correlations to emission types (fossil fuel, biomass burning, biogenic, and lightning NO_x emissions). Fossil fuel and biomass burning emissions are mainly responsible for the strong positive O₃-CO correlations over continental outflow regions in both hemispheres. Biogenic emissions have a relatively smaller impact on O₃-CO correlations than other emissions, but are largely responsible for the negative correlations over the tropical eastern Pacific, reflecting the fact that O₃ is consumed and CO generated during the atmospheric oxidation process of isoprene under low NO_x conditions. We find that lightning NO_x emissions degrade both positive correlations at mid-/high- latitudes and negative correlations in the tropics because ozone production downwind of lightning NO_x emissions is not directly related to the emission and transport of CO. Our study concludes that O₃-CO correlations may be used effectively to constrain the sources of regional tropospheric O₃ in global 3-D models, especially for those regions where convective transport of pollution plays an important role.

Microbial Electrosynthesis and Anaerobic Fermentation: An Economic Evaluation for Acetic Acid Production from CO2 and CO

Microbial electrosynthesis (MES) and anaerobic fermentation (AF) are two biological processes capable of reducing CO₂, CO, and water into acetic acid, an essential industrial reagent. In this study, we evaluated investment and production costs of acetic acid via MES and AF, and compared them to industrial chemical processes: methanol carbonylation and ethane direct oxidation. Production and investment costs were found high-priced for MES (1.44 £/kg, 1770 £/t) and AF (4.14 £/kg, 1598 £/t) because of variable and fixed costs and low production yields (100 t/y) compared to methanol carbonylation (0.26 £/kg, 261 £/t) and ethane direct oxidation (0.11 £/kg, 258 £/t). However, integrating AF with MES would reduce the release of CO₂, double production rates (200 t/y), and decrease investment costs by 9% (1366 £/t). This resulted into setting the production costs at 0.24 £/kg which is currently market competitive (0.48 £/kg). This economically feasible bioprocess produced molar flow rates of 4550 mol per day from MES and AF independently. Our findings offer a bright opportunity toward the use and scale-up of MES and AF for an economically viable acetic acid production process.

On the feasibility of monitoring carbon monoxide in the lower troposphere from a constellation of Northern Hemisphere geostationary satellites: global scale assimilation experiments (Part II)

This paper describes the second phase of an Observing System Simulation Experiment (OSSE) that utilizes the synthetic measurements from a constellation of satellites measuring atmospheric composition from geostationary (GEO) Earth orbit presented in part I of the study. Our OSSE is focused on carbon monoxide observations over North America, East Asia and Europe where most of the anthropogenic sources are located. Here we assess the impact of a potential GEO constellation on constraining northern hemisphere (NH) carbon monoxide (CO) using data assimilation. We show how cloud cover affects the GEO constellation data density with the largest cloud cover (i.e., lowest data density) occurring during Asian summer. We compare the modeled state of the atmosphere (Control Run), before CO data assimilation, with the known "true" state of the atmosphere (Nature Run) and show that our setup provides realistic atmospheric CO fields and emission budgets. Overall, the Control Run underestimates CO concentrations in the northern hemisphere, especially in areas close to CO sources. Assimilation experiments show that constraining CO close to the main anthropogenic sources significantly reduces errors in NH CO compared to the Control Run. We assess the changes in error reduction when only single satellite instruments are available as compared to the full constellation. We find large differences in how measurements for each continental scale observation system affect the hemispherical improvement in long-range transport patterns, especially due to seasonal cloud cover. A GEO constellation will provide the most efficient constraint on NH CO during winter when CO lifetime is longer and increments from data assimilation associated with source regions are advected further around the globe.