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作品数:6 被引量:207H指数:6
相关作者:王跃思辛金元王莉莉朱彬李昕更多>>
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Assessment and comparison of three years of Terra and Aqua MODIS Aerosol Optical Depth Retrieval (C005) in Chinese terrestrial regions
The latest MODIS aerosol optical depth (AOD) retrieval algorithm (C005) for both Terra and Aqua has gradually ...
Lili Wanga, Yuesi Wanga,Jinyuan Xina, Zhanqing Lib, Xiaoyuan Wanga aLAPC, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, PR China bDepartment of Meteorology, The University of Maryland, College Park, MD 20782, USA
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Aerosol Optical Properties Affected by a Strong Dust Storm over Central and Northern China被引量:10
2010年
Aerosol observational data at 8 ground-based observation sites in the Chinese Sun Hazemeter Network (CSHNET) were analyzed to characterize the optical properties of aerosol particles during the strong dust storm of 16-21 April 2005. The observational aerosol optical depth (AOD) increased significantly during this dust storm at sites in Beijing city (86%), Beijing forest (84%), Xianghe (13%), Shapotou (27%), Shenyang (47%), Shanghai (23%), and Jiaozhou Bay (24%). The API (air pollution index) in Beijing and Tianjin also had a similar rise during the dust storm, while the Angstrhm exponent (a) declined evidently at sites in Beijing city (21%), Beijing forest (39%), Xianghe (19%), Ordos (77%), Shapotou (50%), Shanghai (12%), and Jiaozhou Bay (21%), respectively. Furthermore, The observational AOD and a demonstrated contrary trends during M1 storm stages (pre-dust storm, dust storm, and post-dust storm), with the AOD indicating an obvious "Valley Peak-Valley" pattern of variation, while a demonstrated a "Peak-Valley- Peak" pattern. In addition, the dust module in a regional climate model (RegCM3) simulated the dust storm occurrence and track accurately and RegCM3 was able to basically simulate the trends in AOD. The simulation results for the North China stations were the best, and the simulation for dust-source stations was on the high side, while the simulation was on the low side for coastal sites.
辛金元杜吴鹏王跃思高庆先王明星
关键词:REGCM3
沙尘天气对我国北方城市大气环境质量的影响被引量:50
2009年
采用2001—2006年沙尘天气的统计数据以及城市空气污染指数(API),分析了沙尘天气对沙尘源区和影响区代表城市的空气质量影响,并分析了2005—2007年兰州和北京春季沙尘天气与非沙尘天气下气溶胶光学厚度与波长指数的变化特征.结果表明:近些年沙尘天气呈先减少后略微增加但总体呈缓慢下降的趋势;春季沙尘天气加重了城市大气污染,对沙尘源区内代表城市的影响超过了区域本底污染指数的50%,使兰州、银川、呼和浩特和包头的春季非沙尘天气API平均值分别增加了64%,53%,86%和90%;使影响区内代表城市,如北京、天津、太原、石家庄、沈阳、济南、西安和郑州的春季非沙尘天气API平均值分别增加了85%,62%,49%,57%,29%,41%,27%和45%;沙尘天气使城市大气气溶胶光学厚度升高,气溶胶波长指数降低.
杜吴鹏高庆先王跃思辛金元蔺永耀
关键词:沙尘天气空气质量空气污染指数气溶胶
Validation of MODIS aerosol products by CSHNET over China被引量:7
2007年
The Chinese Sun Hazemeter Network (CSHNET) provides the necessary ground-based observation to validate and assess the applicability of MODIS aerosol optical depth (AOD) products over different ecological and geographic regions in China for the first time. The validation results show that the comprehensive utilization ratio and applicability of MODIS products varied very much over different regions and seasons from August 2004 to July 2005. On the Tibetan Plateau, the comprehensive utili- zation ratio of MODIS data was low: MODIS products only accounted for 16% of the ground-based observation; on average, 31% to 45% of MODIS products fell within the retrieval errors issued by NASA. A similar result was found in northern desert areas with the ratio of MODIS to observation ranging from 15% to 55%, with 7% to 39% of MODIS products within errors. In the remote northeast corner of China, low ratios of MODIS to observation were also found ranging from 14% to 46%, with 49% to 69% of MODIS within errors. The forested sites exhibited moderate ratios of MODIS to observation ranging from 46% to 65%, with 30% to 59% of MODIS within errors. This was similar to numbers observed at sites along eastern seashore of China and inland urban sites with the ratio of MODIS to observation between 63% to 75%, with 25% to 67% of MODIS within errors for sites along eastern seashore of China and 43% to 78%, with 35% to 75% of MODIS within errors for inland urban sites. The ratio of MODIS to observation over agricultural areas ranged from 61% to 89%; 59%-88% of MODIS fell within the retrieval errors. At homogeneous and well vegetated areas, the comprehensive utilization ratio of MODIS products was over 80% and above 70% of MODIS products fell within the retrieval errors in growing season.
WANG LiLiXIN JinYuanWANG YueSiLI ZhanQingWANG PuCaiLIU GuangRenWEN TianXue
关键词:气溶胶光学厚度大气科学
天气型对北京地区近地面臭氧的影响被引量:77
2010年
臭氧(O3)是夏秋季北京城市大气光化学污染物中的首要气态污染物,气象因素是影响其浓度水平和变化规律的主要因子之一.2008年7月2008年9月,在北京市4个站点进行了臭氧、氮氧化物(NOx)和一氧化碳(CO)浓度的同步连续观测,并对同期天气型进行了分类比对分析.结果显示,观测期间,北京地区处于低压前部(主要是蒙古气旋)和高压前部的比例分别为42%和20%,分别是造成臭氧浓度高值和低值的主要背景场.处于低压前部控制时,高温、低湿以及局地环流形成的山谷风造成区域臭氧累积,小时最大值(体积分数)高达102.2×10^-9,并随气压的升高以3.4×10^-9Pa^-1的速率降低,山谷风风向的转变决定了臭氧浓度最大值出现时间,峰值出现在14:00左右;处于高压前部控制时,低温、高湿以及系统性北风造成区域臭氧低值,小时最大值(体积分数)仅为49.3×10^-9,系统性北风将臭氧峰值出现时刻推后到16:00左右.北京地区臭氧光化学污染呈现出区域一致性,并与天气型有较好相关,关注天气型结构和演变对预报大气光化学污染具有重要意义.
唐贵谦李昕王效科辛金元胡波王莉莉任玉芬王跃思
关键词:臭氧天气型山谷风光化学污染
北京奥运会期间奥运村站空气质量的观测与研究被引量:28
2010年
为了跟踪研究北京2008年奥运会期间奥运村大气污染物浓度的变化,2008年6月1日─9月30日,利用符合国际标准的在线观测仪器,对奥运村站大气中主要污染物进行加强观测.结果表明:奥运会期间奥运村站大气中φ(NO2),φ(SO2),ρ(PM2.5)和ρ(PM10)分别比奥运会前(7月1日─8月7日)下降了11.2%,46.7%,57.0%和50.0%;比残奥会后时段(9月20─30日)分别下降了41.7%,31.8%,21.6%和28.6%;与2007年同期相比,奥运会时段的φ(NO2),φ(O3),ρ(PM2.5)和ρ(PM10)分别下降了38.8%,37.2%,42.1%和68.0%;残奥会时段分别下降了17.8%,27.5%,44.0%和64.1%.除对污染源严格的控制措施取得了良好的效果外,有利的天气过程也是奥运会期间北京空气质量全面达标的重要原因.
汪伟峰王迎红王莉莉朱彬王跃思
关键词:北京奥运会氮氧化物光化学反应
夏秋季北京及河北三城市的大气污染联合观测研究被引量:38
2011年
为评估北京西南方向城市群对北京大气污染的影响,于2009年夏秋季节(2009年7月16日~10月15日),利用自动在线大气环境观测仪器,对北京及太行山东侧河北省的3个城市涿州、保定和石家庄进行了大气污染物PM10、NOx和O3的联合观测研究.结果表明,夏秋季节4个城市的首要污染物均为可吸入颗粒物(PM10),平均质量浓度分别为(99±88)、(121±74)、(141±92)和(180±107)μg/m3,NOx平均质量浓度分别为(66±48)、(23±14)、(47±35)和(52±32)μg/m3;大气光化学污染物O3浓度小时最高平均值分别达到(107±60)、(128±55)、(164±61)和(120±54)μg/m3.受局地源影响,石家庄颗粒物造成的大气污染最为严重,依次为保定、涿州、北京;受大城市北京和石家庄的双重影响,保定地区大气二次污染物臭氧浓度最高,其次为涿州、石家庄,北京最低.对2009年7月出现的2次典型区域大气污染过程分析表明,太行山东侧河北城市群污染物排放及大气光化学污染对北京及华北区域空气质量有显著影响.
吴莹吉东生宋涛朱彬王跃思
关键词:大气污染PM10O3
Photometric measurements of spring aerosol optical properties in dust and non-dust periods in China
<正>Aerosol observational data spanning three years(2005-2007) from the Chinese Sun Hazemeter Network(CSHN) wer...
Wupeng Du~a,Jinyuan Xin~a,Mingxing Wang~a,Qingxian Gao~b,Zhanqing Li~c,Yuesi Wang~(a,*) a Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,PR China b Chinese Research Academy of Environment Science,Beijing 100012,PR China c Department of Meteorology,The University of Maryland,College Park,MD 20782,USA
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