Dan is working with David Streets and Zifeng Lu on processing satellite data to better understand the concentrations and trends of several air pollutants including NO2 and fine particulate matter (PM2.5).
He recently published a manuscript on inferring CO2 emissions from satellite-derived NOX estimates:
Goldberg, D. L., Z. Lu, T. Oda, L. N. Lamsal, F. Liu, D. Griffin, C. A. McLinden, N. A. Krotkov, B. N., Duncan, D. G. Streets (2019), Exploiting OMI NO2 satellite observations to infer fossil-fuel CO2 emissions from U.S. megacities, Sci. Tot., Environ., 695, 133805, https://doi.org/10.1016/j.scitotenv.2019.133805.
He also works on developing new strategies to better quantify NO2 and PM2.5 from satellite information. Enhancing NO2 satellite data products will allow scientists to: improve surface level air pollutant estimates used for health assessment studies, evaluate emission inventories on a local scale, and spur the use of satellite data by the air quality policy community.
Goldberg, D. L., P. E. Saide, L. N. Lamsal, B. de Foy, Z. Lu, J.-H. Woo, Y. Kim, J. Kim, M. Gao, G. Carmichael, D. G. Streets (2019), A top-down assessment using OMI NO2 suggests an underestimate in the NOx emissions inventory in Seoul, South Korea, during KORUS-AQ, Atmos. Chem. Phys., 19, 1801-1818, https://doi.org/10.5194/acp-19-1801-2019.
Goldberg, D. L., P. Gupta, K. Wang, C. Jena, Y. Zhang, Z. Lu, D. G. Streets (2019), Using MAIAC AOD and WRF-Chem to estimate daily PM2.5 concentrations at 1 km resolution in the eastern United States, Atmos. Environ, 199, 443-452, https://doi.org/10.1016/j.atmosenv.2018.11.049.
Goldberg, D. L., L. N. Lamsal, C.P. Loughner, W. H. Swartz, Z. Lu, D. G. Streets (2017), A high-resolution and observationally constrained OMI NO2 satellite retrieval, Atmos. Chem. Phys., 17, 11403-11421, https://doi.org/10.5194/acp-17-11403-2017.
All publications in which Dan has contributed to can be found in his CV located in the link to the right.