基于极端随机树方法的WRF-CMAQ-MOS模型研究

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、PM₁₀、NO₂、SO₂、O₃、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NO₂及O₃,2016年1、2、3月整体相关系数NO₂由0.35升至0.63,O₃由0.39升至0.79,均方根误差NO₂由0.0346减至0.0243 mg/m3,O₃由0.0447减至0.0367 mg/m3。文中发展的WRF-CMAQ-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。      

A Three-Dimensional Simulation of HO x Concentrations Over East Asia During TRACE-P

The Models-3 Community Multi-scale Air Quality modeling system (CMAQ) coupled with the Regional Atmospheric Modeling System (RAMS) is used to simulate three-dimensional concentration distributions of hydroxyl (OH) and hydroperoxyl (HO₂) radicals over the western Pacific Ocean during the NASA Transport and Chemical Evolution over the Pacific (TRACE-P) field campaign. Modeled values of OH and HO₂ and their closely related chemical species and photolysis rates are compared with observational data collected onboard the DC-8 aircraft. Comparison shows that the model reasonably reproduced these observed values over a broad range of conditions with an overall tendency to overestimate the measured OH and HO₂ by a factor of 1.56 and 1.24, respectively. A case study of OH, HO₂ and their closely related chemical species and photolysis rates along the DC-8 flights 11 and 12 conducted on 17–18 March 2001 shows that the model reproduces the temporal and spatial variations reasonable well, and produces more reliable OH and HO₂ concentrations in the polluted environment than in the clean marine boundary layer.     

2013年1月华北平原重霾成因模拟分析

2013年1月华北平原出现了罕见的重污染天气过程,并引发连续多天大范围重霾现象。利用中华人民共和国环境保护部公布的空气污染指数日值数据和气象常规观测数据,结合区域空气质量模式系统RAMS-CMAQ的模拟结果,对1月10~15日污染过程的气象要素和关键气溶胶物种时空分布特征进行了详细分析,并对灰霾成因进行了探讨。结果表明,受本次污染过程影响的区域主要分布在北京-天津-唐山、河北省中南部和山东省大部。这些地区细颗粒物(即PM2.5)日均质量浓度超过120μg m–3,且基本被灰霾覆盖,日均能见度在5~8 km之间。其中在北京、天津、石家庄和济南市及周边地区细颗粒物日均质量浓度可达250~300μg m–3,部分市区可超过300μg m–3,而日均能见度则可下降至3 km以下,形成重度灰霾。此外,对气象场的分析显示,本次污染过程期间华北平原大部分地区水平风速较多年平均值偏小约20%,且有明显逆温层覆盖,北京-天津-唐山、河北省南部和山东省北部的相对湿度则较多年平均值偏高达10%~40%。这样的气象条件不仅造成污染物易于堆积,而且有利于吸湿性粒子消光效应的快速增长,使能见度明显下降,是引发灰霾的重要因素之一。在北京地区引发灰霾的主要气溶胶物种为硫酸盐、硝酸盐和铵盐,这3种无机盐对近地面的消光贡献比率达到50%以上。其中硝酸盐的消光贡献比率最高,可达总体效应的1/4,表明在这次污染过程中除相关工业源排放外,交通源排放也是北京地区主要的污染源之一。     

Model analysis of influences of aerosol mixing state upon its optical properties in East Asia

The air quality model system RAMS (Regional Atmospheric Modeling System)-CMAQ (Models-3 Community Multi-scale Air Quality) coupled with an aerosol optical/radiative module was applied to investigate the impact of different aerosol mixing states (i.e., externally mixed, half externally and half internally mixed, and internally mixed) on radiative forcing in East Asia. The simulation results show that the aerosol optical depth (AOD) generally increased when the aerosol mixing state changed from externally mixed to internally mixed, while the single scattering albedo (SSA) decreased. Therefore, the scattering and absorption properties of aerosols can be significantly affected by the change of aerosol mixing states. Comparison of simulated and observed SSAs at five AERONET (Aerosol Robotic Network) sites suggests that SSA could be better estimated by considering aerosol particles to be internally mixed. Model analysis indicates that the impact of aerosol mixing state upon aerosol direct radiative forcing (DRF) is complex. Generally, the cooling effect of aerosols over East Asia are enhanced in the northern part of East Asia (Northern China, Korean peninsula, and the surrounding area of Japan) and are reduced in the southern part of East Asia (Sichuan Basin and Southeast China) by internal mixing process, and the variation range can reach 5 W m－2. The analysis shows that the internal mixing between inorganic salt and dust is likely the main reason that the cooling effect strengthens. Conversely, the internal mixture of anthropogenic aerosols, including sulfate, nitrate, ammonium, black carbon, and organic carbon, could obviously weaken the cooling effect.