This paper presents the estimation of Chinese emissions of HCFC-22 and CFC-11 in 2009 by an inverse modeling method based on in-situ measurement data from the Shangdianzi Global Atmosphere Watch (GAW) Regional Station...This paper presents the estimation of Chinese emissions of HCFC-22 and CFC-11 in 2009 by an inverse modeling method based on in-situ measurement data from the Shangdianzi Global Atmosphere Watch (GAW) Regional Station (SDZ) and atmospheric transport simulations. After inversion (a-posteriori) estimates of the Chinese emissions in 2009 increased by 6.6% for HCFC-22 from 91.7 (± 83.6) to 98.3 (± 47.4) kt/yr and by 22.5% for CFC-11 from 13 (±12.6) to 15.8 (±7.2) kt/yr compared to an a-priori emission. While the model simulation with a-priori emissions already captured the main features of the observed variability at the measurement site, the model performance (in terms of correlation and mean-square-error) improved using a-posteriori emissions. The inversion reduced the root-mean-square (RMS) error by 4% and 10% for HCFC-22 and CFC-11, respectively.展开更多
基金supported by the National Natural Science Foundation of China (41030107)Chinese Ministry of Science and Technology(2010CB950601)+2 种基金EUS & T Cooperative Project 2SMONGS&T Cooperation Project of the MOST and Eu (1015)CAMS Fundamental Research Funds-General Program (2010Y003)
文摘This paper presents the estimation of Chinese emissions of HCFC-22 and CFC-11 in 2009 by an inverse modeling method based on in-situ measurement data from the Shangdianzi Global Atmosphere Watch (GAW) Regional Station (SDZ) and atmospheric transport simulations. After inversion (a-posteriori) estimates of the Chinese emissions in 2009 increased by 6.6% for HCFC-22 from 91.7 (± 83.6) to 98.3 (± 47.4) kt/yr and by 22.5% for CFC-11 from 13 (±12.6) to 15.8 (±7.2) kt/yr compared to an a-priori emission. While the model simulation with a-priori emissions already captured the main features of the observed variability at the measurement site, the model performance (in terms of correlation and mean-square-error) improved using a-posteriori emissions. The inversion reduced the root-mean-square (RMS) error by 4% and 10% for HCFC-22 and CFC-11, respectively.
