Knowledge Resource Center for Ecological Environment in Arid Area
| 兰州市大气污染物输送特征及污染治理对策的数值模拟研究 | |
| 其他题名 | Numerical simulation of pollutant transport characteristics and air pollution control measures in Lanzhou, Northwestern China |
| 何建军 | |
| 出版年 | 2014 |
| 学位类型 | 博士 |
| 导师 | 余晔 |
| 学位授予单位 | 中国科学院大学 |
| 中文摘要 | 随着社会经济发展和城市化进程加快，城市大气环境问题已成为全球关注的热点问题之一。目前我国正处于经济高速发展期，城市大气污染严重，不仅危害着人的身体健康，也制约着社会经济的可持续发展。兰州地处黄土高原西端，青藏高原东北部，位于黄河峡谷中，属大陆性干旱半干旱地区。大量工业生产排放、机动车尾气排放和燃煤取暖排放加上特殊的山谷地形影响，使兰州成为全国大气污染最严重的城市之一。在前人研究工作的基础上，本文主要针对冬季，采用数值模拟的方法，在改进WRF模式在研究区模拟性能基础上，结合污染物浓度监测资料，明确不同因子对兰州大气污染的影响，并据此建立适合兰州的空气污染预报统计模型，分析兰州局地环流以及大气污染物输送和扩散特征，以及不同部门污染源对兰州大气环境的影响，评估绿化对兰州大气环境的影响，得出如下主要结论： 1）WRF（Weather Research and Forecasting）模式默认的陆面资料精度低，且时效性不好，是制约WRF模式模拟精度的重要因子之一。近地面气温对陆面资料非常敏感，而风场对陆面资料不敏感，WRF模式对气温的模拟效果好于对风场的模拟。采用中国1km分辨率数字高程模型数据集、基于MODIS（MODerate-resolution Imaging Spectroradiometer）植被归一化指数计算的植被覆盖度和MODIS土地利用资料代替模式默认的陆面资料后，WRF模拟的近地面气温准确率显著提高，模拟的夜间气温改进幅度较白天大。陆面资料可影响整个边界层温度场分布，准确的陆面资料对提高WRF模式模拟近地面乃至整个边界层气象场至关重要。尽管风速模拟误差较大，但总体上WRF模式能较准确地模拟出研究区域的风场演变特征。干旱半干旱区冬季数值模拟需要注意土壤湿度初值和模式初始积分时刻的选取。模式水平分辨率也是影响WRF模拟性能的重要因子，提高模式水平分辨率可以更准确的描述陆面信息，改进模式模拟结果。 2）2002～2010年兰州城区SO2和PM10浓度年平均递减率为3.4%和1.5%，NO2年均浓度略有增加。兰州大气污染物浓度呈现明显的季节变化和周末效应。冬季大气污染最为严重，春秋季次之，夏季污染最轻。冬季污染物浓度与气象参数的相关性分析表明，由于周边山体的阻碍，兰州城区污染物浓度变化主要受垂直扩散的影响。考虑局地气象条件、天气形势、排放源变化和湿沉降对污染物浓度的影响，建立了多元线性回归（MLR）和人工神经网络（ANN）空气质量预报模型，并估算了各因子对污染物浓度变化的影响：就污染物浓度逐日变化而言，局地气象条件、天气形势、污染物排放量变化、湿沉降分别可解释SO2浓度变化的60.2%、20.4%、16.9%和0.5%，NO2浓度变化的44.5%、26.0%、31.1%和3.2%，PM10浓度变化的74.7%、35.3%、10.4%和5.2%；就污染物浓度年际变化而言，局地气象条件、天气形势、排放源变化、湿沉降分别可解释SO2浓度变化的53.2%、25.4%、89.3%和15.7%，NO2浓度变化的23.1%、0.2%、91.9%和0.1%，PM10浓度变化的22.4%、40.7%、73.0%和38.2%。 3）兰州局地环流主要表现为山谷风环流特征，白天城市热岛环流抑制谷风环流，山谷上空出现较强的下沉气流，夜间城市热岛环流增强山风环流，山谷中有上升气流。兰州西侧山谷和东南山谷是城区污染物向外界输送的主要通道，其次为东北山谷以及南山西侧地势较低的地区。山谷中9:00～10:00释放的粒子输出山谷的几率高，随后输出山谷的几率减小，22:00左右达到极小值，而后输出山谷的几率缓慢增加。有天气系统经过兰州时，山谷中污染物主要通过西侧山谷向外界输送，部分污染物能直接越过南山西侧向外界输送。弱天气背景时，山谷中污染物通过西侧山谷、东南和东北山谷向外界输送。 4）与1999年相比，2009年南北两山土地利用变化很大，草地、农地和裸地变成闭合灌丛占绿化区域的69.2%，闭合灌丛、草地和农地变成林地占绿化区域的20.6%。绿化改变了地表能量平衡，绿化后南山山坡处白天增温，夜间降温，山谷风环流加强。弱天气背景时，绿化导致东部山谷白天气体交换量增加，最大增幅达10%左右，而夜间气体交换量差异很小。利用ANN统计模型和FLEXPART（FLEXible PARTicle dispersion model）模式计算结果均显示绿化对大气环境的影响是有限的。 5）通用多尺度空气质量模式（CMAQ）基本能模拟出兰州污染物浓度逐日变化和空间分布特征。比较电厂源、生活源、工业源和交通源对兰州大气污染物浓度的贡献发现，工业源是兰州大气污染物的主要来源，其对城区污染物浓度的贡献率超过40%，生活源是兰州大气污染物的第二大来源，对城区污染物浓度的贡献率在10%-40%之间，电厂源和交通源对兰州大气污染物浓度的贡献较小。城区污染源对大气环境的影响并非仅局限于城区，电厂源和工业源影响范围较大，而生活源和交通源影响范围较小。 |
| 英文摘要 | With the soilcal and economic development, and increasing urbanization, atmospheric environment in urban has become one of the hottest issuses in global change. Serious air pollution not only harms human heath, but also restricts the sustainable development of society and economy. Located in the western Loess Plateau and northeastern Tibetan Plateau, Lanzhou is a typical valley city in the Yellow River valley and has a continental aird and semi-arid climate. With the impact of large amount of industrial emissions, vehicle exhausts, coal burning, and the special valley terrain, Lanzhou is one of the most polluted cities in China. Based on previous research, this study investigated the contribution of different factors to air pollutant concentrations in Lanzhou using numerical simulations. Firstly, the WRF model was improved by incorperating updated land surface information, then pollutant concentration data were analyzed with the meteorological field from WRF to find the main factors affecting pollutant concentrations in urban Lanzhou and to build statistical models for air quality forecasting. Characteristics of local circulations and the transport and dispersion of pollutants in the valley were also analyzed and the potential effect of reforestation in the south and the north mountains on atmospheric environment and the contribution of emissions from different sectors on air quality in Lanzhou were investigated. Main conclusions are as follows: 1) The default land surface data released with WRF (Weather Research and Forecasting) model have low resolution and are not up-to-date, which affects its performance obviously. By incorporating high-resolution and up-to-date land surface information (1-km resolution digital elevation model data set of China, MODIS land use and vegetation fraction data in 2006) in WRF, the hit rate of the WRF simulated near surface temperature to observations significantly increased, the improvement was more obvious for night temperature than that for daytime. The impact of surface conditions on temperature extended throughout the boundary layer, which indicates that accurate land surface information is vital for improving near surface and boundary layer simulation of the WRF model. WRF model can accurately capture the evolution of the wind field. The impact of the initial values of soil moisture and initial integration time on the model’s performance is obvious for winter application in arid and semi-arid regions. Model horizontal resolution affected the WRF model performance. Land surface information is better represented with high grid resolution, which improves model’s performance. 2) The annual mean concentrations of SO2 and PM10 decreased by 3.4% and 1.5% per year during 2002 and 2010, however, NO2 concentration increased slightly. Air pollutants in Lanzhou have obvious seasonal and weekly variations. The air quality is the most serious in winter, followed by spring and autum, and it is the best in summer. Vertical diffusion plays an important role in the dispersion of pollutants in valley, i.e., pollutant concentrations correlate better with meteorological parameters related to atmospheric stratifications than those related to wind speed. There is a less than 24 h time lag for local meteorological conditions to have effect on pollutant concentrations. MLR (Multiple Linear Regression) and ANN (Artificial Neural Network) air quality prediction models were established taking local meteorological conditions, weather typse, emission changes and wet deposition into consideration, and it is found that ANN model performed better then MLR. An extimation based on ANN model indicate that local meteorological conditions is the most important factor for daily variations of pollutant concentration, followed by weather types, emissions and wet deposition, while emission is the most important factor in interannual variation of pollutant concentrations, followed by meteorological conditions and wet deposition. 3) |
| 中文关键词 | WRF ; 陆面资料 ; 气象条件 ; 绿化 |
| 英文关键词 | WRF land surface data meteorological condition reforest |
| 语种 | 中文 |
| 国家 | 中国 |
| 来源学科分类 | 大气物理学与大气环境 |
| 来源机构 | 中国科学院西北生态环境资源研究院 |
| 资源类型 | 学位论文 |
| 条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/287403 |
| 推荐引用方式 GB/T 7714 | 何建军. 兰州市大气污染物输送特征及污染治理对策的数值模拟研究[D]. 中国科学院大学,2014. |
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