Time filter

Source Type

Wu Q.,Beijing Normal University | Xu W.,Beijing Municipal Environmental Protection Monitoring Center | Zhao X.,Institute of Urban Meteorology | He Y.,Chinese Research Academy of Environmental Sciences
Huanjing Kexue Xuebao/Acta Scientiae Circumstantiae | Year: 2012

The sparse matrix operator kernel emissions (SMOKE) model is applied to improve the emissions process and provide the high resolution model-ready emissions for the PM 10 simulation of the nested air quality prediction modeling system (NAQPMS). The regional emissions in East Asia from TRACE-P/INTEX-B and the local sources emissions database in North China are included and spatially allocated based on related spatial factor such as the population data and the road length density for the high resolution emissions. The model performance of PM 10 simulation has improved obviously after emission process updated in August 2006. The mean bias (MB) of the simulation on the urban sites reduced greatly from -87.4~-43.2 μg·m -3 to -31.0~13.4 μg·m -3, with the averaged bias from -57.3 μg·m -3 to -5.9 μg·m -3; and the mean error (ME) decreased from 66.6 μg·m -3 to 43.6 μg·m -3. The fraction of prediction within a factor of two of observation (FAC2) increased from 17%~43% to 44%~70%, and the averaged FAC2 of PM 10 on the urban sites reached 74%. Except for the suburban station Dingling, the normalized mean square errors (NMSE) on the urban sites decreased from 1.030~3.447 to 0.370~0.867, with the average from 1.311 to 0.303.

Chen H.,CAS Institute of Atmospheric Physics | Wu Q.,Beijing Normal University | Wang Z.,CAS Institute of Atmospheric Physics | Tang X.,CAS Institute of Atmospheric Physics | Xu W.,Beijing Municipal Environmental Protection Monitoring Center
Huanjing Kexue Xuebao/Acta Scientiae Circumstantiae | Year: 2014

The MM5-CMAQ air quality modeling system was applied to estimate impacts of power plant desulfurization on regional air quality over North China Plain during the Olympic Games. By comparing the difference of two model simulations with and without desulfurization, it can be found that: 1) Power plant desulfurization decreased SO2concentration by 1~10 ppbv in Beijing-Tianjin-Hebei, North Shandong, East Shanxi and Hetao area in Inner Mongolia, and decrease ASO4 concentration by 1 μg · m-3in most regions in North China Plain. 2) The most significant regions of SO2 and ASO4 reduction appeared in Beijing and eastern slope along Taihang Moutains and Moutain Tai, with magnitudes of 50% and 2 μg · m-3, respectively. 3) Power plant desulfurization increased visibility in Beijing, most areas of Hebei, North Shanxi and South Inner Mongolia by more than 0.5 km.

Wu Q.,Beijing Normal University | Xu W.,Beijing Municipal Environmental Protection Monitoring Center | Shi A.,Beijing Municipal Environmental Protection Monitoring Center | Li Y.,Beijing Municipal Environmental Protection Monitoring Center | And 3 more authors.
Geoscientific Model Development | Year: 2014

The MM5-SMOKE-CMAQ model system, which was developed by the United States Environmental Protection Agency (US EPA) as the MODELS-3 system, has been used for daily air quality forecasts in the Beijing Municipal Environmental Monitoring Center (Beijing MEMC), as a part of the Ensemble air quality Modeling forecast System for Beijing (EMS-Beijing) since the 2008 Olympic Games. According to the daily forecast results for the entire duration of 2010, the model shows good performance in the PM10 forecast on most days but clearly underestimates PM10 concentration during some air pollution episodes. A typical air pollution episode from 11-20 January 2010 was chosen, in which the observed air pollution index of particulate matter (PM10-API) reached 180 while the forecast PM10-API was about 100. In this study, three numerical methods are used for model improvement: first, by enhancing the inner domain with 3 km resolution grids, and expanding the coverage from only Beijing to an area including Beijing and its surrounding cities; second, by adding more regional point source emissions located at Baoding, Landfang and Tangshan, to the south and east of Beijing; third, by updating the area source emissions, including the regional area source emissions in Baoding and Tangshan and the local village/town-level area source emissions in Beijing. The last two methods are combined as the updated emissions method. According to the model sensitivity testing results by the CMAQ model, the updated emissions method and expanded model domain method can both improve the model performance separately. But the expanded model domain method has better ability to capture the peak values of PM10 than the updated emissions method due to better reproduction of the pollution transport process in this episode. As a result, the hindcast results ("New(CMAQ)"), which are driven by the updated emissions in the expanded model domain, show a much better model performance in the national standard station-averaged PM10-API. The daily hindcast PM10-API reaches 180 and is much closer to the observed value, and has a high correlation coefficient of 0.93. The correlation coefficient of the PM10-API in all Beijing MEMC stations between the hindcast and observation is 0.82, clearly higher than the forecast 0.54. The FAC2 increases from 56% in the forecast to 84% in the hindcast, and the NMSE decreases from 0.886 to 0.196. The hindcast also has better model performance in PM10 hourly concentrations during the typical air pollution episode. The updated emissions method accompanied by a suitable domain in this study improved the model performance for the Beijing area significantly. © 2014 Author(s).

Huang S.,CAS Institute of Atmospheric Physics | Huang S.,University of Chinese Academy of Sciences | Tang X.,CAS Institute of Atmospheric Physics | Xu W.,Beijing Municipal Environmental Protection Monitoring Center | And 4 more authors.
Huanjing Kexue Xuebao/Acta Scientiae Circumstantiae | Year: 2015

In this study, ensemble forecast combined with linear regression method is used to reduce the uncertainty in air quality models. Firstly, the PM10 forecasts by three models (NAQPMS, CAMx and CMAQ) in EMS-Beijing are evaluated over Beijing areas. In order to improve the forecast performance, the linear regression method (REG) is used to combine the forecast results of the three models and is compared with the ensemble mean method. The results show that for single model forecast, great difference exists among different models and no model performs much better for all statistic indexes than the other two models. Overall, CMAQ performs better in tendency prediction, while NAQPMS has smaller root mean square errors than the other two models. Ensemble mean method presents poor performance in improving the PM10 forecasts from the three models. On the other hand, REG brings significant improvement of the PM10 forecast. When an appropriate training length (36 days) is applied, the root mean square errors of PM10 forecast over 28 stations of Beijing is reduced by 32%~43% when using REG and the bias decreased considerably to 5.8 μg·m-3. This result implies that REG can greatly improve forecast performance than single model and ensemble mean forecast. Furthermore, the REG also greatly improve capturing of pollution episode forecast. ©, 2014, Science Press. All right reserved.

Chen L.,CAS Institute of Remote Sensing | Zhang Y.,CAS Institute of Remote Sensing | Zou M.,CAS Institute of Remote Sensing | Xu Q.,Beijing Municipal Environmental Protection Monitoring Center | And 3 more authors.
Journal of Remote Sensing | Year: 2015

Atmospheric carbon dioxide (CO2) is a primary greenhouse gas, whose concentration and geographic distribution are the key points in global change research. Since 1998, space-based observation has been an important technique for the remote sensing of CO2 concentration. We present an overview of the advances in space-based remote sensing of CO2, including the development of remote sensors and inverse algorithms, as well as the calibration of retrieved results. We analyze the uncertainties in inverse methods from observations of both thermal infrared and shortwave infrared techniques. The potential development of CO2 retrieval is discussed at the end of this paper. ©, 2015, Editorial Board of Chinese Journal of Applied Ecology. All right reserved.

Discover hidden collaborations