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Biraud, Sebastien C.

Publications and source records attributed to Biraud, Sebastien C..

Atmospheric Radiation Measurement (ARM) airborne field campaign data products between 2013 and 2018

Airborne measurements are pivotal for providing detailed, spatiotemporally resolved information about atmospheric parameters and aerosol and cloud properties, thereby enhancing our understanding of dynamic atmospheric processes. For 30 years, the US Department of Energy (DOE) Office of Science supported an instrumented Gulfstream 1 (G-1) aircraft for atmospheric field campaigns. Data from the final decade of G-1 operations were archived by the Atmospheric Radiation Measurement (ARM) Data Center and made publicly available at no cost to all registered users. To ensure a consistent data format and to improve the accessibility of the ARM airborne data, an integrated dataset was recently developed covering the final 6 years of G-1 operations (2013 to 2018, https://doi.org/10.5439/1999133; Mei and Gaustad, 2024). The integrated dataset includes data collected from 236 flights (766.4 h), which covered the Arctic, the US Southern Great Plains (SGP), the US West Coast, the eastern North Atlantic (ENA), the Amazon Basin in Brazil, and the Sierras de Córdoba range in Argentina. These comprehensive data streams provide much-needed insight into spatiotemporal variability in the thermodynamic quantities and aerosol and cloud properties for addressing essential science questions in Earth system process studies. This paper describes the DOE ARM merged G-1 datasets, including information on the acquisition, data collection challenges and future potentials, and quality control processes. It further illustrates the usage of this merged dataset to evaluate the Energy Exascale Earth System Model (E3SM) with the Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package.

54 ENVIRONMENTAL SCIENCES↗

AmeriFlux FLUXNET-1F US-RGF Stanislaus County Forage Farm

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-RGF Stanislaus County Forage Farm. This is the FLUXNET version of the carbon flux data for the site US-RGF Stanislaus County Forage Farm produced by applying the standard ONEFlux (1F) software. Site Description - Commercially farmed field in Stanislaus County, California. Part of a multi-year, ground-truthing field study under the DOE ARPA-E SMARTFARM project (https://arpa-e.energy.gov/news-and-media/blog-posts/smartfarm-changing-whats-possible-agriculture). Field is approx. 31.3 ha in size (1,300 ft by 2,600 ft), part of a 176+ acre site in several fields with commercial corn-wheat rotation for silage, in combination with manure application.

Schuppenhauer, Michael R.↗

AmeriFlux FLUXNET-1F US-RGW Desha County Rice Farm

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-RGW Desha County Rice Farm. This is the FLUXNET version of the carbon flux data for the site US-RGW Desha County Rice Farm produced by applying the standard ONEFlux (1F) software. Site Description - Commercially farmed rice variety, field in Desha County, Arkansas. Part of a five-year, ground-truthing field study under the DOE ARPA-E SMARTFARM project.

Schuppenhauer, Michael R.↗

Unlocking Solutions: Innovative Approaches to Identifying and Mitigating the Environmental Impacts of Undocumented Orphan Wells in the United States

In the United States, hundreds of thousands of undocumented orphan wells have been abandoned, leaving the burden of managing environmental hazards to governmental agencies or the public. These wells, a result of over a century of fossil fuel extraction without adequate regulation, lack basic information like location and depth, emit greenhouse gases, and leak toxic substances into groundwater. For most of these wells, basic information such as well location and depth is unknown or unverified. Addressing this issue necessitates innovative and interdisciplinary approaches for locating, characterizing, and mitigating their environmental impacts. Our survey of the United States revealed the need for tools to identify well locations and assess conditions, prompting the development of technologies including machine learning to automatically extract information from old records (95%+ accuracy), remote sensing technologies like aero-magnetometers to find buried wells, and cost-effective methods for estimating methane emissions. Notably, fixed-wing drones equipped with magnetometers have emerged as cost-effective and efficient for discovering unknown wells, offering advantages over helicopters and quadcopters. Efforts also involved leveraging local knowledge through outreach to state and tribal governments as well as citizen science initiatives. These initiatives aim to significantly contribute to environmental sustainability by reducing greenhouse gases and improving air and water quality.

54 ENVIRONMENTAL SCIENCES↗

AmeriFlux FLUXNET-1F US-DS3 Staten Rice 1

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-DS3 Staten Rice 1. This is the FLUXNET version of the carbon flux data for the site US-DS3 Staten Rice 1 produced by applying the standard ONEFlux (1F) software. Site Description - This tower is located in a rice field in the California Delta on Staten Island. The tower is within a few square kilometers of rice fields that comprise the vast majority of the southwestern portion of Staten Island. This is part of a multi-year, ground-truthing field study under the DOE ARPA-E SMARTFARM project.

Schuppenhauer, Michael R.↗

AmeriFlux FLUXNET-1F US-RGA Arkansas Corn Farm

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-RGA Arkansas Corn Farm. This is the FLUXNET version of the carbon flux data for the site US-RGA Arkansas Corn Farm produced by applying the standard ONEFlux (1F) software. Site Description - Commercially farmed corn-soy rotation in Arkansas County, Arkansas. Part of a multi-year, ground-truthing field study under the DOE ARPA-E SMARTFARM project.

Schuppenhauer, Michael R.↗

AmeriFlux FLUXNET-1F US-RGB Butte County Rice Farm

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-RGB Butte County Rice Farm. This is the FLUXNET version of the carbon flux data for the site US-RGB Butte County Rice Farm produced by applying the standard ONEFlux (1F) software. Site Description - Commercially farmed, mid-grain japonica rice variety, field in Butte County, California. Part of a five-year, ground-truthing field study under the DOE ARPA-E SMARTFARM project. Field is approx. 30 ha in size in three checks with commercial rice over rice rotation on silty clay loam.

Schuppenhauer, Michael↗

AmeriFlux FLUXNET-1F US-RGo Glenn County Organic Rice Farm

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-RGo Glenn County Organic Rice Farm. This is the FLUXNET version of the carbon flux data for the site US-RGo Glenn County Organic Rice Farm produced by applying the standard ONEFlux (1F) software. Site Description - Organically farmed medium-grain brown rice field in Glenn County, California. Part of a five-year, ground-truthing field study under the DOE ARPA-E SMARTFARM project. Field check is approx. 7 ha in size (1,250 ft by 250 ft), part of a 75+ acre site in several checks with commercial rice over rice rotation on Tehama silt loam, management practices include winter cover crops and AWD.

Schuppenhauer, Michael R.↗

AmeriFlux US-RGF Stanislaus County Forage Farm

This is the AmeriFlux version of the carbon flux data for the site US-RGF Stanislaus County Forage Farm. Site Description - Commercially farmed field in Stanislaus County, California. Part of a multi-year, ground-truthing field study under the DOE ARPA-E SMARTFARM project (https://arpa-e.energy.gov/news-and-media/blog-posts/smartfarm-changing-whats-possible-agriculture). Field is approx. 31.3 ha in size (1,300 ft by 2,600 ft), part of a 176+ acre site in several fields with commercial corn-wheat rotation for silage, in combination with manure application.

Schuppenhauer, Michael R.↗

How to estimate O&G well leak rates from near field concentration and wind observations?

About 2.3 million orphan oil and gas (O&G) wells exist and are estimated to emit 200G g CH 4 y -1 by EPA/Enverus that implies an average CH 4 leak rate of 10 g CH 4 hr -1 per well. US government has an aggressive plan to plug orphan wells at costs of around $100K/well. In order to manage the costs of plugging millions of wells, quantifying leaks from individual wells is essential for prioritization. Current methods to quantify leaks require costly hardware, labor-intensive protocols and expensive analysis.

02 PETROLEUM↗

AmeriFlux US-DS3 Staten Rice 1

This is the AmeriFlux version of the carbon flux data for the site US-DS3 Staten Rice 1. Site Description - This tower is located in a rice field in the California Delta on Staten Island. The tower is within a few square kilometers of rice fields that comprise the vast majority of the southwestern portion of Staten Island. This is part of a multi-year, ground-truthing field study under the DOE ARPA-E SMARTFARM project.

Schuppenhauer, Michael R.↗

AmeriFlux US-RGA Arkansas Corn Farm

This is the AmeriFlux version of the carbon flux data for the site US-RGA Arkansas Corn Farm. Site Description - Commercially farmed corn-soy rotation in Arkansas County, Arkansas. Part of a multi-year, ground-truthing field study under the DOE ARPA-E SMARTFARM project.

Schuppenhauer, Michael R.↗

AmeriFlux US-RGo Glenn County Organic Rice Farm

This is the AmeriFlux version of the carbon flux data for the site US-RGo Glenn County Organic Rice Farm. Site Description - Organically farmed medium-grain brown rice field in Glenn County, California. Part of a five-year, ground-truthing field study under the DOE ARPA-E SMARTFARM project. Field check is approx. 7 ha in size (1,250 ft by 250 ft), part of a 75+ acre site in several checks with commercial rice over rice rotation on Tehama silt loam, management practices include winter cover crops and AWD.

Schuppenhauer, Michael R.↗

AmeriFlux US-RGW Desha County Rice Farm

This is the AmeriFlux version of the carbon flux data for the site US-RGW Desha County Rice Farm. Site Description - Commercially farmed rice variety, field in Desha County, Arkansas. Part of a five-year, ground-truthing field study under the DOE ARPA-E SMARTFARM project.

Schuppenhauer, Michael R.↗

AmeriFlux US-RGB Butte County Rice Farm

This is the AmeriFlux version of the carbon flux data for the site US-RGB Butte County Rice Farm. Site Description - Commercially farmed, mid-grain japonica rice variety, field in Butte County, California. Part of a five-year, ground-truthing field study under the DOE ARPA-E SMARTFARM project. Field is approx. 30 ha in size in three checks with commercial rice over rice rotation on silty clay loam.

Schuppenhauer, Michael↗

A31N-03: Lower-Tropospheric CO2 from Near-Infrared ACOS-GOSAT Observations

We present two new products from near-infrared GOSAT observations: lower tropospheric (LMT, from 0-2.5 km) and upper tropospheric/stratospheric (U, above 2.5 km) carbon dioxide partial columns. We compare these new products to aircraft profiles and remote surface flask measurements and find that the seasonal and year-to-year variations in the new partial columns significantly improve over the ACOS-GOSAT initial guess/a priori, with distinct patterns in the LMT and U seasonal cycles which match validation data. For land monthly averages, we find errors of 1.9, 0.7, and 0.8 ppm for retrieved GOSAT LMT, U, and XCO2; for ocean monthly averages, we find errors of 0.7, 0.5, and 0.5 ppm for retrieved GOSAT LMT, U, and XCO2. In the southern hemisphere biomass burning season, the new partial columns show similar patterns to MODIS fire maps and MOPITT multispectral CO for both vertical levels, despite a flat ACOS-GOSAT prior, and CO/CO2 emission factor consistent with published values. The difference of LMT and U, useful for evaluation of model transport error, has also been validated with monthly average error of 0.8 (1.4) ppm for ocean (land). The new LMT partial column is more locally influenced than the U partial column, meaning that local fluxes can now be separated from CO2 transported from far away.

Kulawik, Susan S.↗