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.

Mapping Yearly Fine Resolution Global Surface Ozone through the Bayesian Maximum Entropy Data Fusion of Observations and Model Output for 1990-2017.

Estimates of ground-level ozone concentrations are necessary to determine the human health burden of ozone. To support the Global Burden of Disease Study, we produce yearly fine resolution global surface ozone estimates from 1990 to 2017 through a data fusion of observations and models. As ozone observations are sparse in many populated regions, we use a novel combination of the M3Fusion and Bayesian Maximum Entropy (BME) methods. With M3Fusion, we create a multimodel composite by bias-correcting and weighting nine global atmospheric chemistry models based on their ability to predict observations (8834 sites globally) in each region and year. BME is then used to integrate observations, such that estimates match observations at each monitoring site with the observational influence decreasing smoothly across space and time until the output matches the multimodel composite. After estimating at 0.5° resolution using BME, we add fine spatial detail from an additional model, yielding estimates at 0.1° resolution. Observed ozone is predicted more accurately (R2 = 0.81 at the test point, 0.63 at 0.1°, and 0.62 at 0.5°) than the multimodel mean (R2 = 0.28 at 0.5°). Global ozone exposure is estimated to be increasing, driven by highly populated regions of Asia and Africa, despite decreases in the United States and Russia.

Aircraft observations since the 1990s reveal increases of tropospheric ozone at multiple locations across the Northern Hemisphere.

Tropospheric ozone is an important greenhouse gas, is detrimental to human health and crop and ecosystem productivity, and controls the oxidizing capacity of the troposphere. Because of its high spatial and temporal variability and limited observations, quantifying net tropospheric ozone changes across the Northern Hemisphere on time scales of two decades had not been possible. Here, we show, using newly available observations from an extensive commercial aircraft monitoring network, that tropospheric ozone has increased above 11 regions of the Northern Hemisphere since the mid-1990s, consistent with the OMI/MLS satellite product. The net result of shifting anthropogenic ozone precursor emissions has led to an increase of ozone and its radiative forcing above all 11 study regions of the Northern Hemisphere, despite NO x emission reductions at midlatitudes.

Abrupt decline in tropospheric nitrogen dioxide over China after the outbreak of COVID-19.

China's policy interventions to reduce the spread of the coronavirus disease 2019 have environmental and economic impacts. Tropospheric nitrogen dioxide indicates economic activities, as nitrogen dioxide is primarily emitted from fossil fuel consumption. Satellite measurements show a 48% drop in tropospheric nitrogen dioxide vertical column densities from the 20 days averaged before the 2020 Lunar New Year to the 20 days averaged after. This decline is 21 ± 5% larger than that from 2015 to 2019. We relate this reduction to two of the government's actions: the announcement of the first report in each province and the date of a province's lockdown. Both actions are associated with nearly the same magnitude of reductions. Our analysis offers insights into the unintended environmental and economic consequences through reduced economic activities.

A Cloud-Ozone Data Product from Aura OMI and MLS Satellite Measurements.

Ozone within deep convective clouds is controlled by several factors involving photochemical reactions and transport. Gas-phase photochemical reactions and heterogeneous surface chemical reactions involving ice, water particles, and aerosols inside the clouds all contribute to the distribution and net production and loss of ozone. Ozone in clouds is also dependent on convective transport that carries low troposphere/boundary layer ozone and ozone precursors upward into the clouds. Characterizing ozone in thick clouds is an important step for quantifying relationships of ozone with tropospheric H2O, OH production, and cloud microphysics/transport properties. Although measuring ozone in deep convective clouds from either aircraft or balloon ozonesondes is largely impossible due to extreme meteorological conditions associated with these clouds, it is possible to estimate ozone in thick clouds using backscattered solar UV radiation measured by satellite instruments. Our study combines Aura Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) satellite measurements to generate a new research product of monthly-mean ozone concentrations in deep convective clouds between 30°S to 30°N for October 2004 - April 2016. These measurements represent mean ozone concentration primarily in the upper levels of thick clouds and reveal key features of cloud ozone including: persistent low ozone concentrations in the tropical Pacific of ~10 ppbv or less; concentrations of up to 60 pphv or greater over landmass regions of South America, southern Africa, Australia, and India/east Asia; connections with tropical ENSO events; and intra-seasonal/Madden-Julian Oscillation variability. Analysis of OMI aerosol measurements suggests a cause and effect relation between boundary layer pollution and elevated ozone inside thick clouds over land-mass regions including southern Africa and India/east Asia.

An improved global model for air-sea exchange of mercury: high concentrations over the North Atlantic.

We develop an improved treatment of the surface ocean in the GEOS-Chem global 3-D biogeochemical model for mercury (Hg). We replace the globally uniform subsurface ocean Hg concentrations used in the original model with basin-specific values based on measurements. Updated chemical mechanisms for Hg°/Hg(II) redox reactions in the surface ocean include both photochemical and biological processes, and we improved the parametrization of particle-associated Hg scavenging. Modeled aqueous Hg concentrations are consistent with limited surface water observations. Results more accurately reproduce high-observed MBL concentrations over the North Atlantic (NA) and the associated seasonal trends. High seasonal evasion in the NA is driven by inputs from Hg enriched subsurface waters through entrainment and Ekman pumping. Globally, subsurface waters account for 40% of Hg inputs to the ocean mixed layer, and 60% is from atmospheric deposition. Although globally the ocean is a net sink for 3.8 Mmol Hg y⁻¹, the NA is a net source to the atmosphere, potentially due to enrichment of subsurface waters with legacy Hg from historical anthropogenic sources.

Greenhouse gas emissions from U.S. institutions of higher education.

Greenhouse gas (GHG) emission estimates from signatories of the American College and University Presidents' Climate Commitment (ACUPCC) were compared across Carnegie institutional classifications. Average annual emissions from all institutional classifications are 52,434 metric tons carbon dioxide equivalent (MTCO2E), with emissions from purchased electricity, stationary combustion, and commuting accounting for approximately 88% of total emissions. Average annual emission intensity from all institutional classifications is 19.39 MTCO2E per 1000 gross square feet (GSF) and 7.67 MTCO2E per full-time equivalent (FTE) student. In 2005, U.S. institutions of higher education accounted for approximately 121 million MTCO2E, or nearly 2% of total annual U.S. GHG emissions. For reference, these emissions are comparable to approximately one-quarter of those from the state of California. Because ACUPCC signatories represent over 30% of U.S. higher education enrollment, their long-term commitments to carbon neutrality can result in a measurable reduction (approximately 0.6%) of total annual U.S. GHG emissions.