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
利用CMAQ（Community Multiscale Air Quality Model）模式预报产品和福州市2007年1月至2010年6月大气污染物的观测资料以及常规地面气象观测资料,根据动力-统计相结合的预报方法,通过多元线性逐步回归,建立不同天气系统下CMAQ模式产品...利用CMAQ（Community Multiscale Air Quality Model）模式预报产品和福州市2007年1月至2010年6月大气污染物的观测资料以及常规地面气象观测资料,根据动力-统计相结合的预报方法,通过多元线性逐步回归,建立不同天气系统下CMAQ模式产品和多类预报因子相结合的日污染物浓度预报模型.结果表明,影响福州市的天气系统共分为大陆高压、副热带高压、切变、暖区辐合、高空槽、台风和热带辐合带7类天气型.在暖区辐合、高空槽和大陆高压控制下,福州市的空气质量较差,而副热带高压和台风系统影响时,福州市的空气质量最好.日污染物浓度预报方程置信度均为P=0.000,模型有统计学意义.利用模型对2010年7~12月福州市各污染物浓度进行预报效果回代检验,模型对PM10的污染指数等级预报正确率达到了71.3%,对SO2和NO2的级别预报正确率达到了100%,日预报综合评分平均达88.8分.展开更多
随着城市化、工业化的快速发展,空气污染已经成为了公众最关注的问题之一。为了提高空气质量预报的准确度,以多尺度空气质量模型(Community Multi-Scale Air Quality,CMAQ)为工具,结合中尺度WRF(Weather Research and Forecast Model)...随着城市化、工业化的快速发展,空气污染已经成为了公众最关注的问题之一。为了提高空气质量预报的准确度,以多尺度空气质量模型(Community Multi-Scale Air Quality,CMAQ)为工具,结合中尺度WRF(Weather Research and Forecast Model)气象预报数据、气象观测数据、污染物浓度观测数据,基于极端随机树方法建立了WRF-CMAQ-MOS(Weather Research and Forecast Model-Community Multi-Scale Air Quality-Model Output Statistics)统计修正模型。结果表明,结合WRF气象预报的CMAQ-MOS方法明显修正了由于模型非客观性产生的模式预报偏差,提高了预报效果。使用线性回归方法不能获得较好的优化效果,选取极端随机树方法和梯度提升回归树方法对模型进行改进和比较,发现极端随机树方法对结合WRF气象要素的CMAQ-MOS模型有较大的提升。针对徐州地区空气质量预报,进一步使用基于极端随机树方法的WRF-CMAQ-MOS模型对2016年1、2、3月的空气质量指数(AQI)及PM_(2.5)、PM_(10)、NO_2、SO_2、O_3、CO六种污染物优化试验进行验证,发现优化效果最为明显的两种污染物分别是NO_2及O_3,2016年1、2、3月整体相关系数NO_2由0.35升至0.63,O_3由0.39升至0.79,均方根误差NO_2由0.0346减至0.0243 mg/m^3,O_3由0.0447减至0.0367 mg/m^3。文中发展的WRFCMAQ-MOS统计修正模型可以有效提升预报精度,在空气质量预报中具有很好的应用前景。展开更多
In this contribution, we present an evaluation of different mitigation plans to improve NO2 levels in Andalusia, a region in the south of Spain. Specifically, we consider four possible mitigation plans: the effects ov...In this contribution, we present an evaluation of different mitigation plans to improve NO2 levels in Andalusia, a region in the south of Spain. Specifically, we consider four possible mitigation plans: the effects over NO2 concentration of apply changes in the distribution of Vehicles Park;the effect of realize traffic restrictions (affecting to the density flow of vehicles) over highways and main roads;the effect of replacement of diesel use by natural gas in urban areas;and the effect of applying new velocity limits to access to urban areas. A sophisticated air quality modelling (AQM) system has been used to evaluate these mitigation plans. AQM implemented is composed on WRF meteorological model, an emission model created by the authors and CMAQ photochemical model. AQM analyzes mitigation plans during fifteen episodes of 2011 where NO2 levels were the highest of the year;so we analyze the effect of mitigation plans in worst conditions. Results provided by the AQM system show that: 1-h maximum daily NO2 is reduced to 10μg.m-3 near circulation roads when traffic restrictions and velocity limits plans are applied (NOx emissions are reduced in 9% - 15%);1-h maximum daily NO2 is reduced to 12 μg.m-3 affecting all municipalities when changes in the distribution of Vehicles Park are applied (NOx emissions are reduced in 25% - 26%);and the replacement of fuel of urban buses does not affect considerably NO2 levels.展开更多
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.
文摘利用CMAQ（Community Multiscale Air Quality Model）模式预报产品和福州市2007年1月至2010年6月大气污染物的观测资料以及常规地面气象观测资料,根据动力-统计相结合的预报方法,通过多元线性逐步回归,建立不同天气系统下CMAQ模式产品和多类预报因子相结合的日污染物浓度预报模型.结果表明,影响福州市的天气系统共分为大陆高压、副热带高压、切变、暖区辐合、高空槽、台风和热带辐合带7类天气型.在暖区辐合、高空槽和大陆高压控制下,福州市的空气质量较差,而副热带高压和台风系统影响时,福州市的空气质量最好.日污染物浓度预报方程置信度均为P=0.000,模型有统计学意义.利用模型对2010年7~12月福州市各污染物浓度进行预报效果回代检验,模型对PM10的污染指数等级预报正确率达到了71.3%,对SO2和NO2的级别预报正确率达到了100%,日预报综合评分平均达88.8分.
文摘随着城市化、工业化的快速发展,空气污染已经成为了公众最关注的问题之一。为了提高空气质量预报的准确度,以多尺度空气质量模型(Community Multi-Scale Air Quality,CMAQ)为工具,结合中尺度WRF(Weather Research and Forecast Model)气象预报数据、气象观测数据、污染物浓度观测数据,基于极端随机树方法建立了WRF-CMAQ-MOS(Weather Research and Forecast Model-Community Multi-Scale Air Quality-Model Output Statistics)统计修正模型。结果表明,结合WRF气象预报的CMAQ-MOS方法明显修正了由于模型非客观性产生的模式预报偏差,提高了预报效果。使用线性回归方法不能获得较好的优化效果,选取极端随机树方法和梯度提升回归树方法对模型进行改进和比较,发现极端随机树方法对结合WRF气象要素的CMAQ-MOS模型有较大的提升。针对徐州地区空气质量预报,进一步使用基于极端随机树方法的WRF-CMAQ-MOS模型对2016年1、2、3月的空气质量指数(AQI)及PM_(2.5)、PM_(10)、NO_2、SO_2、O_3、CO六种污染物优化试验进行验证,发现优化效果最为明显的两种污染物分别是NO_2及O_3,2016年1、2、3月整体相关系数NO_2由0.35升至0.63,O_3由0.39升至0.79,均方根误差NO_2由0.0346减至0.0243 mg/m^3,O_3由0.0447减至0.0367 mg/m^3。文中发展的WRFCMAQ-MOS统计修正模型可以有效提升预报精度,在空气质量预报中具有很好的应用前景。
文摘In this contribution, we present an evaluation of different mitigation plans to improve NO2 levels in Andalusia, a region in the south of Spain. Specifically, we consider four possible mitigation plans: the effects over NO2 concentration of apply changes in the distribution of Vehicles Park;the effect of realize traffic restrictions (affecting to the density flow of vehicles) over highways and main roads;the effect of replacement of diesel use by natural gas in urban areas;and the effect of applying new velocity limits to access to urban areas. A sophisticated air quality modelling (AQM) system has been used to evaluate these mitigation plans. AQM implemented is composed on WRF meteorological model, an emission model created by the authors and CMAQ photochemical model. AQM analyzes mitigation plans during fifteen episodes of 2011 where NO2 levels were the highest of the year;so we analyze the effect of mitigation plans in worst conditions. Results provided by the AQM system show that: 1-h maximum daily NO2 is reduced to 10μg.m-3 near circulation roads when traffic restrictions and velocity limits plans are applied (NOx emissions are reduced in 9% - 15%);1-h maximum daily NO2 is reduced to 12 μg.m-3 affecting all municipalities when changes in the distribution of Vehicles Park are applied (NOx emissions are reduced in 25% - 26%);and the replacement of fuel of urban buses does not affect considerably NO2 levels.
