JP

Background nitrogen dioxide (NO2) over the United States and its implications for satellite observations and trends: roles of aircraft, wildfires, and nitrate photolysis

Abstract: Tropospheric nitrogen dioxide (NO2) measured from satellites has been widely used to track anthropogenic NOx emissions, but its retrieval and interpretation can be complicated by the free tropospheric background to which satellite measurements are particularly sensitive. Observations from the OMI satellite instrument over the contiguous US (CONUS) shows no trend after 2009, despite sustained decreases in anthropogenic NOx emissions, implying an important and rising contribution from the free tropospheric background. Here we use the GEOS-Chem chemical transport model applied to simulation of OMI NO2 to better understand the sources and trends of background NOx over CONUS. Previous model underestimate of the background is largely corrected by the consideration of aerosol nitrate photolysis and by using a new aircraft emission inventory. The increase in aircraft emissions over the past decades not only increases the background NO2 but also affects the satellite retrieval by altering the NO2 vertical profile. Increasing wildfire emissions also contributed to the post-2009 increase in the NO2 background over the western US.

Advances in Simulating the Global Spatial Heterogeneity of Air Quality and Source Sector Contributions: Insights into the Global South

Abstract: High-resolution simulations are essential to resolve fine-scale air pollution patterns due to localized emissions, nonlinear chemical feedbacks, and complex meteorology. However, high-resolution global simulations of air quality remain rare, especially of the Global South. Here, we exploit recent developments to the GEOS-Chem community model in its high performance implementation (GCHP) to conduct one-year simulations in 2015 at cubed-sphere C360 (~ 25km) and C48 (~ 200km) resolutions. We investigate the resolution dependence of population exposure and sectoral contributions to surface PM2.5 and NO2 focusing on understudied regions. Our results indicate pronounced spatial heterogeneity with global mean population-weighted normalized root mean square error (PW-NRMSE) at C48 of for primary (50% - 105%) and secondary (26% - 36%) PM2.5 species. Under-represented regions are more sensitive to spatial resolution resulting from sparse pollution hotspots, with PW-NRMSE for PM2.5 in the Global South (34%) 1.3 times higher than globally (25%). The spatial heterogeneity in southern cities (50%) is substantially higher than the more typically clustered northern cities (27%). High-resolution simulations also change the relative importance of emission sectors for both black carbon and NO2 in the Global South. Overall, spatial gradients of population exposure and sectoral contributions are artificially reduced with coarse simulations, especially in the Global South.

Quantifying the impact of terrestrial carbon and nutrient discharge on the global-ocean carbon cycle over seasonal-to-interannual timescales

Abstract: Large amounts of carbon and nutrients are delivered to the coastal and pelagic ocean by the Land-Ocean Aquatic Continuum (LOAC). The LOAC refers to the major biogeochemical pathway whereby river and groundwater discharge is connected to coastal systems. Terrestrial loads fluxed through the LOAC system likely play a key role in the carbon cycle of the global ocean. For example, riverine carbon export may be responsible for global-ocean outgassing of roughly 0.45 Pg C yr-1. While the significance of terrestrial exports is commonly accepted in the community, quantification of these fluxes over seasonal-to-interannual timescales is still lacking. To address this deficiency, we parameterize contemporary terrestrial carbon and nutrient export in the ECCO-Darwin global-ocean biogeochemistry state estimate and evaluate the subsequent sensitivity of air-sea CO2 fluxes at regional and global scales from 1995 to 2017. We compute daily riverine export by combining the GlobalNEWS2.0 watershed model with point-source freshwater discharge from the JRA55-do atmospheric reanalysis. Additionally, we derive carbon exports from coastal wetlands (i.e., mangroves and marshes) from ecosystem primary production and the associated soil organic carbon. We evaluate our simulated ocean biogeochemistry and air-sea CO2 fluxes using in-situ and remotely-sensed observations in the coastal ocean. We quantify the impact of terrestrial exports to the global ocean by comparing our new simulation with a baseline simulation that does not include terrestrial carbon and nutrient export. Our study highlights the importance of improving the representation of terrestrial fluxes in global-ocean biogeochemistry models for the accurate simulation of ocean carbon cycling, biogeochemistry, and ecology.

Increase in global and East Asia Nitrogen trifluoride (NF3) emissions inferred from atmospheric observations

Abstract: Nitrogen trifluoride (NF3) is a very powerful long-lived greenhouse gas (GHG), with a global warming potential on a 100-year timescale of ∼16,600. NF3 is widely used in the manufacture of semiconductors, photovoltaic (PV) cells, and flat panel displays. Here we investigate global and regional NF3 emission rates in East Asia, using atmospheric observations from five AGAGE background monitoring stations (Mace Head, Ireland Trinidad Head, California, Ragged Point, Barbados, Cape Grim, Tasmania, Cape Matatula, Samoa) and Gosan, South Korea combined with an inverse modeling approach based on the global 3-D atmospheric chemical transport model (GEOS-Chem). We find that global NF3 emissions have grown from 1.73 0.13 Gg yr-1 ( one standard deviation) in 2014 to 2.91 0.23 Gg yr-1 in 2020, with an average annual increase of 8% yr-1. This rise in global emission is mainly attributable to East Asia (South China, Northeast China, Japan, and South Korea), where emissions increased from 1.4 0.86 Gg yr-1 to 1.49 Gg yr-1. Due to increasing demand for electronic device manufacture, especially flat panel displays, NF3 emissions are expected to increase further in the future.

The Climate Consensus Network - Creating Capacity for Climate Outreach Within our Universities

Abstract: Many scientists desire to create a more informed public on the topic of anthropogenic climate change but have limited time and energy to contribute to this cause. The Climate Consensus is a new 501(c)(3) nonprofit organization that seeks to create capacity for such work through scholarship and stipend awards, and by creating a formal network across academic institutions and departments for resource sharing. We are a group of concerned students, faculty, and staff from 12 teaching- and research-focused universities who are promoting a culture shift toward the prioritization of public outreach on the topic of climate change. We are encouraging upcoming and established scientists to engage in dialog with their local communities while garnering philanthropic and grant support for these efforts. By building capacity for the next generation of scientists to speak up for science and our future, we have an immense opportunity to shape public opinion on this topic and to motivate real action.

Sensitivity Analysis and Uncertainty Quantification of E3SM Methane model using Machine Learning

Abstract: Methane (CH4) is the second most important Greenhouse gas after carbon dioxide, accounting for 16-25% of atmospheric warming to date. However, large uncertainty exists in methane emissions estimates using biogeochemistry models. This uncertainty arises largely because CH4 dynamics depend on multiple physical, biological, and chemical processes and a large number of uncertain model parameters. Sensitivity analysis (SA) can help not only identify important parameters for methane emission, but also achieve reduced biases and uncertainties in future projections. In this study, SA is performed for the pre-selected critical parameters of methane biogeochemistry module within the Energy Exascale Earth System Model (E3SM) land model (ELM). Considering the large number of model simulations typically required for the variance-based SA, we employ a machine learning algorithm, namely, Gaussian process regression, to construct a surrogate model that enables emulating the behaviour of ELM methane biogeochemistry and conducting a full variance-based SA with much reduced computational costs but barely any loss in accuracy. We examine the sensitivity of CH4 emission to a large set of parameters at multiple FLUXNET-CH4 sites of different vegetation types. Our results will provide useful insights into the key parameters and processes that drive the uncertainty in methane emissions at different sites and the consistency of parametric uncertainties across vegetation types, soil types, climatic zones, and seasons.

When and How to Use Economy-Wide Models for Environmental Policy Analysis

Abstract: We describe the factors researchers should consider in deciding when and how to use computational general equilibrium (CGE) models for environmental policy analysis instead of partial equilibrium or engineering models. Special attention is given to modeling the social costs and benefits of regulations and the role played by labor markets. CGE models excel at quantifying interactions across different sectors of the economy, factor-market outcomes, and the distributional consequences of policy, all using a comprehensive set of the resource constraints faced by agents. The ceteris paribus nature of these experiments allows a skilled modeler to develop a systematic understanding of the connection between model assumptions and policy outcomes. Using CGE models to address environmental policy questions involves challenges, including the representation of narrow and technology-specific regulatory designs, data and aggregation issues, and the development of methods to improve model transparency and validity.

A nutrient relay sustains subtropical ocean productivity

Significance

The vast subtropical oceans play a leading role in the global storage of organic carbon into the deep ocean. There, biological production is limited by the availability of surface nutrients due to the large-scale ocean circulation pushing nutrient-rich waters at depth. The transfer of nutrients into the sunlit layer is achieved by fine-scale vertical motions, at the expense of the layers beneath. We show that subsurface layers are substantially replenished by the lateral turbulent transport of nutrients along density surfaces, on 10 to 100 km scales. This nutrient relay, involving both vertical and lateral transport, ultimately fuels biological production and sustains an associated sequestration of carbon in the subtropics.

Abstract

The expansive gyres of the subtropical ocean account for a significant fraction of global organic carbon export from the upper ocean. In the gyre interior, vertical mixing and the heaving of nutrient-rich waters into the euphotic layer sustain local productivity, in turn depleting the layers below. However, the nutrient pathways by which these subeuphotic layers are themselves replenished remain unclear. Using a global, eddy-permitting simulation of ocean physics and biogeochemistry, we quantify nutrient resupply mechanisms along and across density surfaces, including the contribution of eddy-scale motions that are challenging to observe. We find that mesoscale eddies (10 to 100 km) flux nutrients from the shallow flanks of the gyre into the recirculating interior, through time-varying motions along density surfaces. The subeuphotic layers are ultimately replenished in approximately equal contributions by this mesoscale eddy transport and the remineralization of sinking particles. The mesoscale eddy resupply is most important in the lower thermocline for the whole subtropical region but is dominant at all depths within the gyre interior. Subtropical gyre productivity may therefore be sustained by a nutrient relay, where the lateral transport resupplies nutrients to the thermocline and allows vertical exchanges to maintain surface biological production and carbon export.

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