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Development of WRF/CUACE v1.0 model and its preliminary application in simulating air quality in China

机译:WRF / CUACE V1.0模型的开发及其在模拟中国空气质量的初步应用

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The development of chemical transport models with advanced physics and chemical schemes could improve air-quality forecasts. In this study, the China Meteorological Administration Unified Atmospheric Chemistry Environment (CUACE) model, a comprehensive chemistry module incorporating gaseous chemistry and a size-segregated multicomponent aerosol algorithm, was coupled to the Weather Research and Forecasting (WRF) framework with chemistry (WRF-Chem) using an interface procedure to build the WRF/CUACE v1.0 model. The latest version of CUACE includes an updated aerosol dry deposition scheme and the introduction of heterogeneous chemical reactions on aerosol surfaces. We evaluated the WRF/CUACE v1.0 model by simulating PM 2.5 , O 3 , NO 2 , and SO 2 concentrations for January, April, July, and October (representing winter, spring, summer and autumn, respectively) in 2013, 2015, and 2017 and comparing them with ground-based observations. Secondary inorganic aerosol simulations for the North China Plain (NCP), Yangtze River Delta (YRD), and Sichuan Basin (SCB) were also evaluated. The model captured well the variations of PM 2.5 , O 3 , and NO 2 concentrations in all seasons in eastern China. However, it is difficult to accurately reproduce the variations of air pollutants over SCB, due to its deep basin terrain. The simulations of SO 2 were generally reasonable in the NCP and YRD with the bias at ?15.5 ?% and 24.55?%, respectively, while they were poor in the Pearl River Delta (PRD) and SCB. The sulfate and nitrate simulations were substantially improved by introducing heterogeneous chemical reactions into the CUACE model (e.g., change in bias from ?95.0 ?% to 4.1?% for sulfate and from 124.1?% to 96.0?% for nitrate in the NCP). Additionally, The WRF/CUACE v1.0 model was revealed with better performance in simulating chemical species relative to the coupled Fifth-Generation Penn State/NCAR Mesoscale Model (MM5) and CUACE model. The development of the WRF/CUACE v1.0 model represents an important step towards improving air-quality modeling and forecasts in China.
机译:具有先进物理和化学方案的化学传输模型的发展可以改善空气质量预测。在本研究中,中国气象学统一大气化学环境(CUACE)模型,一种综合化学模块,包括气态化学和尺寸隔离的多组分气溶胶算法,与化学(WRF-)耦合到天气研究和预测(WRF)框架(WRF- Chem)使用接口过程构建WRF / CUACE V1.0模型。最新版本的CUACE包括更新的气溶胶干沉积方案和在气溶胶表面上引入异质化学反应。我们通过模拟2013年1月,4月,7月和10月(分别代表冬季,春季,夏季和秋季)的PM 2.5,O 3,NO 2等浓度来评估WRF / CUACE V1.0模型,以及2017年并将它们与基于地面的观察结果进行比较。还评估了华北平原(NCP),长江三角洲(YRD)和四川盆地(SCB)的二级无机气溶胶模拟。该模型捕获了中国东部所有季节的PM 2.5,O 3和No 2浓度的变化。然而,由于其深度盆地地形,难以准确地再现SCB上的空气污染物的变化。 SO 2的模拟通常在NCP和YRD中具有偏差,分别在偏见,同时在珠江三角洲(PRD)和SCB中差。通过将非均相的化学反应引入CUAGE模型(例如,从硫酸盐的偏差变化至4.1℃的偏差的变化,在NCP中硝酸盐的124.1μm至96.0〜96.0μm)来显着改善硫酸盐和硝酸盐模拟。另外,WRF / CUACE V1.0模型揭示了相对于耦合的第五代PENN状态/ NCAR MESCHE(MM5)和CUACE模型的耦合的第五代PENN状态/ NCAR MEDIES的性能更好的性能。 WRF / CUACE V1.0模型的开发代表了改善中国空气质量建模和预测的重要一步。

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