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ARS Home » Midwest Area » Urbana, Illinois » Global Change and Photosynthesis Research » Research » Research Project #446964

Research Project: Coordination, Data Collection, and Integration of Midwestern Greenhouse Gas Fluxes Using Tall Tower Instrumentation

Location: Global Change and Photosynthesis Research

Project Number: 5012-21000-032-030-S
Project Type: Non-Assistance Cooperative Agreement

Start Date: Oct 1, 2024
End Date: Sep 30, 2025

Objective:
Contribute oversight of data collection, data quality check and quality assurance, data processing, data sharing, and contribute to data analysis and interpretation of regional-scale agricultural greenhouse gas emissions to improve emission models and track mitigation progress.

Approach:
The research plan will use a television tall tower located in Illinois to quantify and understand regional sources of greenhouse gases (GHGs), specifically nitrous oxide (N2O) and methane (CH4). The objective is to integrate high-precision atmospheric measurements with advanced modeling techniques to derive accurate regional flux estimates, contributing to the USDA-ARS’s broader network understanding of GHG emissions. High-precision analyzers for N2O and CH4 will be installed at the site. Continuous air sampling will be conducted from a height of 100 meters using Teflon tubing, with samples analyzed in a nearby facility equipped with a manifold system designed by the National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Laboratory. This system ensures continuous measurement and frequent calibration for accuracy. Data collected will be logged by a computer and transmitted via cell phone to network headquarters for quality checks and further analysis, with daily monitoring to promptly address any potential issues. To provide accurate bottom-up model estimates of N2O emissions, land cover within the tower's footprint, extending approximately 100 km upwind, will be mapped annually. The Stochastic Inverted Lagrangian Transport (STILT) model, driven by the Weather Research and Forecasting (WRF) system in the Scale Factor Bayesian Inverse (SFBI) method, will be employed to interpret observational data and bottom-up model information, elucidating regional GHG budgets, environmental drivers, and sectoral contributions. The SFBI method will utilize observational data to constrain regional sources, with a priori flux estimates based on emission inventories and biogeochemical modeling. Bayes theorem will be applied to determine optimal a posteriori scaling factors, minimizing a cost function that accounts for both observational and model uncertainties. Comprehensive analyses, including Monte Carlo simulations, will assess the uncertainty and robustness of inversion results, exploring key parameters within land surface schemes to diagnose emission uncertainties. A postdoctoral researcher with expertise in GIS and data management will assist in QA/QC of incoming data and organizing land use data for bottom-up modeling. The post-doctoral scientist will focus on data analysis, with a particular emphasis on inverse modeling and reconciliation of top-down and bottom-up regional flux estimates. The Cooperator’s research team will work in close collaboration with USDA-ARS scientists and other collaborators to produce results that enhance GHG models. The findings from this research will be disseminated to the broader scientific community and relevant stakeholders to improve understanding and mitigation strategies for GHG emissions. This comprehensive and systematic approach leverages advanced technologies and collaborative efforts to address critical questions aligning with the objectives of the IRA and USDA-ARS.