Organization:
Pennsylvania State University
Co-Authored Publications:
- Gurney, K., et al. (2021), Under-reporting of greenhouse gas emissions in U.S. cities, Nature, doi:10.1038/s41467-020-20871-0.
- Yang, E. G., et al. (2020), Using Space‐Based Observations and Lagrangian Modeling to Evaluate Urban Carbon Dioxide Emissions in the Middle East, J. Geophys. Res., 125, e2019JD031922, doi:10.1029/2019JD031922.
- Barkley, Z. R., et al. (2019), Estimating Methane Emissions From Underground Coal and Natural Gas Production in Southwestern Pennsylvania, Geophys. Res. Lett., 46, doi:10.1029/2019GL082131.
- Díaz-Isaac, L. I., et al. (2019), Calibration of a multi-physics ensemble for estimating the uncertainty of a greenhouse gas atmospheric transport model, Atmos. Chem. Phys., 19, 5695-5718, doi:10.5194/acp-19-5695-2019.
- Feng, S., et al. (2019), Seasonal characteristics of model uncertainties from biogenic fluxes, transport, and large‐scale boundary inflow in atmospheric CO2 simulations over North America, J. Geophys. Res., 124, 14325-, doi:10.1029/2019JD031165.
- Díaz-Isaac, L. I., T. Lauvaux, and K. J. Davis (2018), Impact of physical parameterizations and initial conditions on simulated atmospheric transport and CO2 mole fractions in the US Midwest, Atmos. Chem. Phys., 18, 14813-14835, doi:10.5194/acp-18-14813-2018.
- Wu, D., et al. (2018), A Lagrangian approach towards extracting signals of urban CO2 emissions from satellite observations of atmospheric column CO2 (XCO2): X-Stochastic Time-Inverted Lagrangian Transport model (“X-STILT v1”), Geosci. Model. Dev., 11, 4843-4871, doi:10.5194/gmd-11-4843-2018.
- Bloom, A., et al. (2016), What are the greenhouse gas observing system requirements for reducing fundamental biogeochemical process uncertainty? Amazon wetland CH4 emissions as a case study, Atmos. Chem. Phys., 16, 15199-15218, doi:10.5194/acp-16-15199-2016.
Note: Only publications that have been uploaded to the
ESD Publications database are listed here.