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@ARTICLE{Marrapu:185522,
      author       = {Marrapu, P. and Cheng, Y. and Beig, G. and Sahu, S. and
                      Srinivas, R. and Carmichael, G. R.},
      title        = {{A}ir quality in {D}elhi during the {C}ommonwealth {G}ames},
      journal      = {Atmospheric chemistry and physics},
      volume       = {14},
      number       = {19},
      issn         = {1680-7324},
      address      = {Katlenburg-Lindau},
      publisher    = {EGU},
      reportid     = {FZJ-2014-06949},
      pages        = {10619 - 10630},
      year         = {2014},
      abstract     = {Air quality during the Commonwealth Games (CWG, held in
                      Delhi in October 2010) is analyzed using a new air quality
                      forecasting system established for the games. The CWG
                      stimulated enhanced efforts to monitor and model air quality
                      in the region. The air quality of Delhi during the CWG had
                      high levels of particles with mean values of PM2.5 and PM10
                      at the venues of 111 and 238 μg m−3, respectively. Black
                      carbon (BC) accounted for ~ $10\%$ of the PM2.5 mass. It is
                      shown that BC, PM2.5 and PM10 concentrations are well
                      predicted, but with positive biases of ~ $25\%.$ The diurnal
                      variations are also well captured, with both the
                      observations and the modeled values showing nighttime maxima
                      and daytime minima. A new emissions inventory, developed as
                      part of this air quality forecasting initiative, is
                      evaluated by comparing the observed and predicted
                      species-species correlations (i.e., BC : CO; BC : PM2.5;
                      PM2.5 : PM10). Assuming that the observations at these sites
                      are representative and that all the model errors are
                      associated with the emissions, then the modeled
                      concentrations and slopes can be made consistent by scaling
                      the emissions by 0.6 for NOx, 2 for CO, and 0.7 for BC,
                      PM2.5, and PM10. The emission estimates for particles are
                      remarkably good considering the uncertainty in the estimates
                      due to the diverse spread of activities and technologies
                      that take place in Delhi and the rapid rates of change.},
      cin          = {IEK-8},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IEK-8-20101013},
      pnm          = {233 - Trace gas and aerosol processes in the troposphere
                      (POF2-233)},
      pid          = {G:(DE-HGF)POF2-233},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000344164800014},
      doi          = {10.5194/acp-14-10619-2014},
      url          = {https://juser.fz-juelich.de/record/185522},
}