Open Access
Issue
EPJ Web Conf.
Volume 176, 2018
The 28th International Laser Radar Conference (ILRC 28)
Article Number 08013
Number of page(s) 4
Section Synergy of lidars and other sensors
DOI https://doi.org/10.1051/epjconf/201817608013
Published online 13 April 2018
  1. Zhang, X., Hecobian,A., Zheng, M., Frank, N. H., Weber, R. J., 2010: Biomassburning impact on PM2.5 over thesoutheastern US during 2007: integrating chemically speciated FRM filter measurements, MODIS fire counts and PMF analysis, Atmos. Chem. Phys. 10, 6839–6853. [CrossRef] [Google Scholar]
  2. Jacobson, M. Z., 2014: Effects of biomassburning on climate, accounting for heat and moisture fluxes, black and brown carbon, and cloud absorption effects, J. Geophys. Res. Atmos., 119, 8980–9002. [CrossRef] [Google Scholar]
  3. Sigsgaard, T., et al., 2015: Health impacts of anthropogenic biomass burning in the developed world, EurRespir J.,46(6):1577-1588.doi: 10.1183/13993003.01865-2014. [CrossRef] [Google Scholar]
  4. Groß, S., Esselborn, M., Weinzierl, B., Wirth, M., Fix, A., Petzold, A., 2013: Aerosol classification by air borne high spectral resolution lidar observations, Atmos. Chem. Phys., 13, 2487–2505. [CrossRef] [Google Scholar]
  5. Li, H., Liu, C., Burge, L., Southerland, W., 2012: Classification of Protein 3D StructuresUsing Artificial Neural Network, IJMLC,2(6). [Google Scholar]
  6. Nicolae, D., Vasilescu, J., Talianu, C., Dandocsi, A., 2016: Independent retrieval of aerosol type from lidar,EPJ Web of Conferences, http://dx.doi.org/10.1051/epjconf/201611918002. [Google Scholar]
  7. Chaikovsky, A.,et al., 2016: Lidar-Radiometer Inversion Code (LIRIC) for theretrieval of vertical aerosol properties from combined lidar/radiometer data: development and distribution in EARLINET, Atmos. Meas. Tech., 9, 1181–1205. [CrossRef] [Google Scholar]
  8. Lewis,K., Arnott, W.P., MoosMüller, H., Wold, C.E., 2008: Strong spectral variation of biomass smoke light absorption and single scattering albedo observed with a novel dual-wavelength photoacoustic instrument, J. Geophys. Res, 113, D16. [CrossRef] [Google Scholar]
  9. Adler, G.,Flores, J.M., AboRiziq, A., Borrmann, S., Rudich, Y., 2011: Chemical, physical, andopticalevolution of biomassburningaerosols: a case study, Atmos. Chem. Phys., 11, 1491– 1503. [CrossRef] [Google Scholar]
  10. Ng, N.L., Herndon, S. C., Trimborn, A., Canagaratna, M.R., Croteau, P.L., Onasch, T.B., Sueper, D, Worsnop, D.R., Zhang, Q., Sun, Y.L., Jayne, J.T., 2011: An Aerosol Chemical Speciation Monitor (ACSM) for Routine Monitoring of the Composition and Mass Concentrations of Ambient Aerosol, Aerosol Sci. Technol., 45, 780–794. [CrossRef] [Google Scholar]
  11. Stohl, A., Forster, C., Frank, A.,Seibert, P.,Wotawa, G., 2005:Technical note: The Lagrangian particle dispersion model FLEXPART version 6.2, Atmos. Chem. Phys., 5, 2461-2474. [CrossRef] [Google Scholar]
  12. Ichoku, C., and Ellison, L., 2014: Global topdownsmoke-aerosol emissions estimation using satellite fire radiative power measurements, Atmos. Chem. Phys., 14(13), 6643–6667. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.