应用MM5(Fifth-Generation NCAR/Penn State Mesoscale Model)-Models-3/CMAQ(Community Multi-Scale Air Quality)空气质量模拟系统对京津冀地区进行了模拟,分别采用Brute Force方法和DDM-3D(Decoupled Direct Method in 3 Dimensions...应用MM5(Fifth-Generation NCAR/Penn State Mesoscale Model)-Models-3/CMAQ(Community Multi-Scale Air Quality)空气质量模拟系统对京津冀地区进行了模拟,分别采用Brute Force方法和DDM-3D(Decoupled Direct Method in 3 Dimensions)技术对两个代表性城市石家庄、北京的PM2.5来源进行了分析计算.结果表明,两种方法的计算结果具有显著相关性,相关系数在0.950～0.989之间;其次,在某一地区浓度贡献较低的情况下,两种方法的计算结果非常接近,但随着浓度贡献的增加,Brute Force方法的计算结果逐渐高于DDM-3D方法,直线拟合的斜率在1.14～2.05之间.以石家庄为例,Brute Force和DDM-3D方法估算的河北南部地区排放的浓度贡献分别为54.7%和64.4%,相差10%左右.浓度贡献空间分布的对比表明,Brute Force方法计算出的浓度影响范围更大,出现某些离散的负值点,或某些负值点与很大的正值点相邻,反映了数值计算带来的计算误差;相比之下,DDM-3D方法的计算结果则更为合理.展开更多
We present comparisons of the NO2 regional Chemical Transport Model （CTM） simulations over North-eastern North America during the time period from May to September, 1998 with hourly surface NO2 observations and the ...We present comparisons of the NO2 regional Chemical Transport Model （CTM） simulations over North-eastern North America during the time period from May to September, 1998 with hourly surface NO2 observations and the NO2 columns retrieved from the GOME （Global Ozone Monitoring Experiment） satellite instrument. The model calculations were performed using the Mesoscale Meteorological Model 5 （MM5）, Sparse Matrix Operator Kernal Emissions （SMOKE）, and Community Multiscale Air Quality （CMAQ） modeling systems, using the emission data from the National Emissions Inventory （NEI） databases of 1996 （U.S.） and 1995 （Canada）. The major objectives were to assess the performance of the CMAQ model and the accuracy of the emissions inventories as they affected the simulations of this important short-lived atmospheric species. The modeled （NcMAQ） and measured （NGOME） NO2 column amounts, as well as their temporal variations, agreed reasonably well. The absolute differences （NcMAQ-NGOME） across the domain were between ±3.0×10^15 molecules cm^-2, but they were less than ±1.0×10^15 molecules cm^-2 over the majority （80%） of the domain studied. The overall correlation coefficient between the measurements and the simulations was 0.75. The differences were mainly ascribed to a combination of inaccurate emission data for the CTM and the uncertainties in the GOME retrievals. Of these, the former were the more easily identifiable.展开更多
文摘应用MM5(Fifth-Generation NCAR/Penn State Mesoscale Model)-Models-3/CMAQ(Community Multi-Scale Air Quality)空气质量模拟系统对京津冀地区进行了模拟,分别采用Brute Force方法和DDM-3D(Decoupled Direct Method in 3 Dimensions)技术对两个代表性城市石家庄、北京的PM2.5来源进行了分析计算.结果表明,两种方法的计算结果具有显著相关性,相关系数在0.950～0.989之间;其次,在某一地区浓度贡献较低的情况下,两种方法的计算结果非常接近,但随着浓度贡献的增加,Brute Force方法的计算结果逐渐高于DDM-3D方法,直线拟合的斜率在1.14～2.05之间.以石家庄为例,Brute Force和DDM-3D方法估算的河北南部地区排放的浓度贡献分别为54.7%和64.4%,相差10%左右.浓度贡献空间分布的对比表明,Brute Force方法计算出的浓度影响范围更大,出现某些离散的负值点,或某些负值点与很大的正值点相邻,反映了数值计算带来的计算误差;相比之下,DDM-3D方法的计算结果则更为合理.
文摘We present comparisons of the NO2 regional Chemical Transport Model （CTM） simulations over North-eastern North America during the time period from May to September, 1998 with hourly surface NO2 observations and the NO2 columns retrieved from the GOME （Global Ozone Monitoring Experiment） satellite instrument. The model calculations were performed using the Mesoscale Meteorological Model 5 （MM5）, Sparse Matrix Operator Kernal Emissions （SMOKE）, and Community Multiscale Air Quality （CMAQ） modeling systems, using the emission data from the National Emissions Inventory （NEI） databases of 1996 （U.S.） and 1995 （Canada）. The major objectives were to assess the performance of the CMAQ model and the accuracy of the emissions inventories as they affected the simulations of this important short-lived atmospheric species. The modeled （NcMAQ） and measured （NGOME） NO2 column amounts, as well as their temporal variations, agreed reasonably well. The absolute differences （NcMAQ-NGOME） across the domain were between ±3.0×10^15 molecules cm^-2, but they were less than ±1.0×10^15 molecules cm^-2 over the majority （80%） of the domain studied. The overall correlation coefficient between the measurements and the simulations was 0.75. The differences were mainly ascribed to a combination of inaccurate emission data for the CTM and the uncertainties in the GOME retrievals. Of these, the former were the more easily identifiable.
