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北京地区大气氨时空变化特征
引用本文:刘湘雪,蒲维维,马志强,林伟立,韩婷婷,李颖若,周礼岩,石庆峰.北京地区大气氨时空变化特征[J].中国环境科学,2021,41(8):3473-3483.
作者姓名:刘湘雪  蒲维维  马志强  林伟立  韩婷婷  李颖若  周礼岩  石庆峰
作者单位:1. 京津冀环境气象预报预警中心, 北京 100089;2. 中国气象局北京城市气象研究院, 北京 100089;3. 上甸子国家大气本底站, 北京 101507;4. 中央民族大学生命与环境科学学院, 北京 100081
基金项目:国家重点研发计划项目(2016YFC0201902);国家自然科学基金资助项目(42005094);北京市科委项目(Z181100005418016)
摘    要:在北京城区和上甸子本底地区分别开展了为期3a和1a的NH3在线观测,并结合风向、风速、温度、相对湿度等气象因素的变化特征,分析了北京地区NH3浓度水平、年季特征及影响因素.结果发现,北京城区和本底地区的NH3年均浓度分别为(32.5±20.8)×10-9V/V和(11.6±10.3)×10-9V/V,北京城区的NH3浓度高于大多数国内外主要城市和地区的NH3浓度水平.城区和本底地区NH3浓度年变化特征为夏季高,分别为(34.1±6.8)×10-9V/V和(11.1±2.2)×10-9V/V,冬季低,分别为(19.7±9.3)×10-9V/V和(2.4±0.6)×10-9V/V.NH3的日变化特征受气象因素影响明显,其结果表明,春季城区NH3浓度峰值出现在15:00,而本底地区受西南风影响在20:00达到峰值;夏季城区NH3浓度最高值在7:00出现,本底地区则呈现双峰值(分别在09:00和22:00);秋季城区和本底地区的日变化规律一致,均在22:00出现峰值;冬季城区的峰值出现时间晚于本底地区,峰值分别出现在23:00和20:00.西南风是造成本底地区NH3浓度升高的主要原因,春季和夏季,随着西南向风速的增大,NH3浓度显著升高.城区的NH3浓度则主要受到局地排放的影响.浓度权重轨迹法的研究结果发现,北京、天津、河北及河南北部地区是影响北京地区大气NH3的主要源区.

关 键 词:NH3  上甸子本底站  区域输送  拉格朗日综合单粒子轨道(HYSPLIT)模型  浓度权重轨迹(CWT)  
收稿时间:2021-01-28

Study on the temporal and spatial variation of atmospheric ammonia in Beijing
LIU Xiang-xue,PU Wei-wei,MA Zhi-qiang,LIN Wei-li,HAN Ting-ting,LI Ying-ruo,ZHOU Li-yan,SHI Qing-feng.Study on the temporal and spatial variation of atmospheric ammonia in Beijing[J].China Environmental Science,2021,41(8):3473-3483.
Authors:LIU Xiang-xue  PU Wei-wei  MA Zhi-qiang  LIN Wei-li  HAN Ting-ting  LI Ying-ruo  ZHOU Li-yan  SHI Qing-feng
Institution:1. Environmental Meteorology Forecast Center of Beijing-Tianjin-Hebei, Beijing 100089, China;2. Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China;3. Shangdianzi Regional Air Background Station, Beijing 101507, China;4. College of Life & Environmental Science, Minzu University of China, Beijing 100081, China
Abstract:Considering the variables in meteorological characterizations including wind direction, wind speed, temperature and relative humidity, a three-year and one-year online observation of ammonia was conducted at Beijing urban sites and Shangdianzi background station separately, for analyzing the temporal and spatial changes of NH3 concentration and influencing factors in Beijing. The average annual NH3 concentration in Beijing urban was (32.5±20.8)×10-9V/V, which was significantly higher than that in background station(11.6±10.3)×10-9V/V] and many major cities and regions both in China and foreign countries. The seasonal variation characteristics exhibited that the average concentrations of NH3 were higher in summer than those of in winter, with giving (34.1±6.8)×10-9V/V and (11.1±2.2)×10-9V/V in summer, and (19.7±9.3)×10-9V/V and (2.4±0.6)×10-9V/V in winter, in terms of Beijing urban and background area, respectively. Moreover, the effect of meteorological factors on daily variation of NH3 is significant. In spring, the peak value of NH3 concentration in urban appeared at 15:00, which was earlier than that at 20:00 in background area under the influence of southwest wind. In contrast, the time for reaching highest concentration in urban area delayed in winter and was slightly later than that of background area, with cresting at 23:00 and 20:00 respectively. During summer, the NH3 concentration in urban area peaked at 7:00, whereas dual crest value of NH3 concentration in background area occurred twice at 09:00 and 22:00. In autumn, urban and background area had presented the same diurnal variation with peaking approximately at 22:00. The southwest wind was the main reason that leads to the changes of NH3 concentration in the background area, where the concentration rise remarkably with the increase of southwest wind speed in spring and summer. However, concentration weighted trajectory analysis (CWT) drove that surrounding areas involving Beijing, Tianjin, Hebei and northern Henan contributed to the varying concentrations in Beijing urban areas, were the main sources of NH3 affecting Beijing urban areas and background stations.
Keywords:NH3  Shangdianzi background station  regional transportation  hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model  concentration weighted trajectory(CWT)  
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