@article{155971,
  author = {Mingwei Li and Yuxuan Wang and Weimin Ju},
  title = {Effects of a remotely sensed land cover dataset with high spatial resolution on the simulation of secondary air pollutants over china using the nested-grid GEOS-chem chemical transport model},
  abstract = { A number of remotely sensed land cover datasets with spatial resolutions 1 km have recently become available or are in the process of being mapped. The application of these higher resolution and more up-to-date land cover datasets in chemical transport models (CTMs) is expected to improve the simulation of dry deposition and biogenic emissions of non-methane volatile organic compounds (NMVOCs), which affect ozone and other secondary air pollutants. In the present study, we updated the land cover dataset in the nested-grid GEOS-Chem CTM with the 1 km resolution GLC2000 land cover map and examined the resulting changes in the simulation of surface ozone and sulfate over China in July 2007. Through affecting the dry deposition velocities of ozone and its precursors, using GLC2000 in the dry deposition module can decrease the simulated surface ozone by 3\% (up to 6 ppb) over China. Simulated surface sulfate shows an increase of 3\% in northwestern China and a decrease of 1\% in northern China. Applying GLC2000 in the biogenic emissions of the NMVOC module can lead to a 0.5{\textendash}4.5 ppb increase in simulated surface ozone over East China, mainly driven by the larger coverage of broadleaf trees in East China in the GLC2000 dataset. Our study quantifies the large sensitivity to land cover datasets with different spatial resolutions and time periods of simulated secondary air pollutants over China, supporting ongoing research efforts to produce high resolution and dynamically updated land cover datasets over China, as well as for the globe. },
  year = {2014},
  journal = {Advances in Atmospheric Sciences},
  volume = {31},
  pages = {179{\textendash}187},
  issn = {0256-1530, 1861-9533},
  url = {http://link.springer.com/10.1007/s00376-013-2290-1},
  doi = {10.1007/s00376-013-2290-1},
  language = {eng},
}