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Research Integrated Research on Energy, Environment and Society | IREES Research

Regional inversion studies of methane fluxes using CTDAS-WRF | Mengrong Lu

Mengrong Lu
Mengrong Lu

Field | Discipline

  • Environmental Sciences
  • Greenhouse Gas Emissions
  • Sustainable Methane Emission Development


  • Inversion & Atmospheric Modeling
  • Methane Emission Analysis


Methane, a major greenhouse gas, is key to climate change mitigation. Accurately measuring urban methane emissions is crucial for crafting effective strategies. Our work focuses on high-resolution regional inversion studies validated by observations to assess emissions and pinpoint sources. We use the CTDAS-WRF system, which integrates the CarbonTracker Data Assimilation Shell (CTDAS), the Weather Research and Forecasting model (WRF), and GHG modules (WRF-GHG). This system assimilates data from satellites (TROPOMI, GOSAT) and ICOS observations to estimate methane emissions regionally. Enhancements to CTDAS-WRF will contribute to understanding the methane budget globally and regionally. Our analysis will offer well-founded recommendations for international policy development and the rational distribution of economic industries.

Initial steps include testing the CTDAS-WRF system with pseudo-data to identify and correct biases and discrepancies. Additionally, conducting sensitivity tests will help quantify the uncertainties in the emission fluxes estimated by the system. Subsequent steps include selecting urban study areas that meet specific criteria: (1) comprehensive emission inventories, and (2) advanced urban observation networks or satellite data availability. By running the CTDAS-WRF with real observational data, we will examine the spatial and temporal patterns of methane emissions in urban areas and accurately pinpoint emission sources based on these findings.

Following the completion of several case studies, we will evaluate and enhance the CTDAS-WRF system, aiming to reduce errors when compared to actual observations. Our approach includes optimizing the model to foster a continuous cycle of emissions monitoring, optimization, and adjustment based on ongoing observations. By incorporating existing economic models and studies on methane variability, we aim to deepen our understanding of the factors influencing methane emissions.

Supervision by

More information and contact details can be found on the personal profile of Mengrong Lu.

Last modified:27 February 2024 09.08 a.m.