关中盆地气象条件与气溶胶变化对霾能见度恶化影响及模拟研究

Fine aerosol particles known to be one of the major contributors to haze pollution in China reducing the transparency of the atmosphere by scattering, reflecting, absorbing solar radiation, Combined with unfavorable meteorological conditions are the main cause of the persistent deterioration of haze visibility. In this project, we plan to investigate the relationship between visual air quality and haze levels based on the U.S. EPA regional haze rule method and standard of observation and forecasting levels of haze from CMA using the manual and automatic horizontal visual range(VR) observation data from meteorological stations, combined with daily/hourly visibility, wind speed / direction, relative humidity, air temperature, air pressure, rainfall and other meteorological parameters and simultaneous measurement of PM1 and PM2.5 concentration during the formation of haze pollution. Methods of detailed partial correlation analysis on short-time scale are employed for establishing the control-respones relationship between critical high-impact meteorological parameters and PM1 and PM2.5 concentration respectively. We will also take PM1 and PM2.5 samples simultaneously at the Guanzhong Basin, China including one populated site(Xi’an) and one intensive industrial site(Baoji), 24-hour integrated PM2.5 samples are collected every day in January, April, July, October, Meanwhile, an intensive sampling campaign is conducted during the heavy haze episodes. All the samples could be classified into several groups by analysis of backward air mass trajectories, optical monitoring parameters for aerosol extinction, absorption and scattering are provided by Climate Center of Shaanxi Meteorological Bureau for free. Carbonaceous species (OC and EC),water-soluble inorganic ions and elements are determined to characterize the chemical composition of PM2.5, IMPROVE equation is used to reveal the aerosol contributions of each chemical composition to the light extinction coefficient, and using WRF-Chem model to simulate the spatial distribution and transmission characteristics of aerosols under different meteorological conditions. These quantitative results obtained could be useful for policy makers to take effective measures to promote visual air quality and control the haze pollution.

颗粒态气溶胶可通过反射、散射太阳辐射等方式降低大气能见度，综合不利的气象条件是造成霾能见度持续恶化的主要原因。为深入认识关中盆地能见度降低的主要因素，量化PM1和PM2.5气溶胶化学组分对能见度的影响，本项目拟在西安（人口聚集）和宝鸡（工业密集）布设采集全年和霾污染天气PM1和PM2.5加密滤膜样品，获取气溶胶消光、散光、吸收等光学参数，依据霾污染等级分别对PM1和PM2.5化学组成（OC/EC、水溶性无机离子、元素等）分析。利用美国EPA和中国气象局标准方法考虑不同天气类型建立能见度与不同污染等级霾气候变化序列，重点运用偏相关分析方法在不同时间尺度上探讨PM1和PM2.5浓度与关键气象因子间的控制响应关系及阈值，比较西安和宝鸡两地PM1和PM2.5差异及对能见度定量贡献，利用WRF-Chem模式模拟不同气象条件下气溶胶的空间与传输特征，为政府制定污染控制与减排措施提供科学依据。

霾污染天气PM2.5细颗粒物当中的碳质气溶胶、水溶性离子和元素组成是造成环境空气质量恶化的主要因素。此外，PM2.5含有的重金属、多环芳烃（PAHs）、邻苯二甲酸酯(PAEs)等化学组分对人体健康存在显著风险。本研究在分析关中盆地典型城市能见度与霾气候变化背景序列基础上，建立了关中城市群主要典型城市空气质量长期变化背景序列，与气象因子的偏相关性分析表明，在一定污染源强度下，温度和气压是影响PM2.5、Cl-、K+、OC、EC、Cu、Zn、As、Pb浓度变化的主要因素。依据环境空气质量污染等级对采样期间PM2.5化学组成（OC/EC、水溶性无机离子、元素等）的分析表明，二次有机碳对碳质气溶胶污染贡献较大，水溶性离子污染水平为硝酸根离子、硫酸根离子、铵根离子、钠离子、钙离子、氯离子、钾离子、镁离子，SNA是水溶性离子的重要组成成分，硝酸铵和硫酸铵是SNA的主要赋存形态；重金属污染水平为Zn>Mn>Pb>Cu>Cr>As>Ni>Co>V，V、Mn主要受自然源的影响，Ni、Co、Cr、Cu来自于自然源和人为源的共同作用；Zn、Pb、As主要受人为源的影响；PM2.5来源主要为机动车尾气排放及制动摩擦、生物质燃烧及二次污染源、燃煤燃烧、冶炼和铸造行业等工业排放、风飏粉尘等途径；在城乡不同区域，LMW-PAHs占比均为最低，HMW-PAHs在城市地区采暖期及非采暖期占比最高，DEHP是PAEs的主要成分。健康风险分析结果表明：Mn元素对儿童具有较大非致癌风险，成年男性致癌风险高于成年女性，Cr、As、Co风险值高于一般可接受水平；重度及以上空气质量PAHs人群暴露风险仅城市地区儿童人群的致癌风险处于可接受水平，其余空气质量级别下城市及农村各人群致癌风险均高于风险阈值，空气质量为良、轻度污染、中度污染时农村地区人群致癌风险高于城市。利用LUR模型对西安NO2浓度进行模拟分析表明大气污染物浓度在旅游景点处最低，工业区大气污染浓度是全市平均的2.81倍，住宅地区的NO2浓度仅次于工业区，在所有功能区中，儿童健康风险最高，婴儿健康风险最低，成年人居中。