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APEC会议前后京津冀空气污染物时空变化特征
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科技导报 | 研究论文 2016,34(24): 115-121
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科技导报 |研究论文 2016 , 34 (24) : 115 -121
APEC会议前后京津冀空气污染物时空变化特征
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张媛媛1, 吴立新2, 任传斌1, 项程程1, 李佳乐1, 柴曼1
作者信息
    1. 中国矿业大学(北京)地球科学与测绘工程学院, 北京 100083;
    2. 中南大学地球科学与信息物理学院, 长沙 410083
通讯作者:
吴立新(通信作者),教授,研究方向为空间信息、灾害观测与协同感知,电子信箱:awulixin@263.net
作者简介:
张媛媛,硕士研究生,研究方向为地图学与地理信息系统,电子信箱:13120388205@163.com
On the spatio-temporal features of air pollutants in Beijing-Tianjin-Hebei for the period of APEC summit
  • ZHANG Yuanyuan1, WU Lixin2, REN Chuanbin1, XIANG Chengcheng1, LI Jiale1, CHAI Man1
  • Affiliations
      1. College of Geoscience and Surveying Engineering, China University of Mining and Technology(Beijing), Beijing 100083, China;
      2. School of Geosciences and Infor-Physics, Central South University, Changsha 410083, China
    出版时间: 2016-12-28 doi: 10.3981/j.issn.1000-7857.2016.24.017
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    收藏切换
    以2014年北京APEC会议前后京津冀地区的PM2.5、SO2、NO2监测数据为基础,通过最优空间插值得到该地区空气污染物质量浓度的空间分布变化图,采用空间自相关与核密度分析法研究了污染物分布的空间差异和变化规律。结果表明,京津冀空气污染物质量浓度具有显著的空间正相关与空间集聚特性,城市群空气污染空间关联密切,PM2.5热点集中在北京南部、天津、石家庄和保定等地,SO2热点集中在保定、天津、唐山和石家庄等地,NO2热点集中在北京-天津-唐山片区和保定-石家庄-邢台片区;不同时段空气污染物质量浓度差异显著,APEC会议前及期间,在冷空气活动与减排措施的双重作用下,污染物质量浓度显著降低,高密度热点区均逐渐向中、低密度区转化,而APEC会议后,受冷空气影响良好空气质量得以短期维持,但污染反弹现象较快出现,高密度热点区污染迅速加强并扩展。
    空气污染  /  空间分析  /  时空变化  /  APEC会议  /  京津冀
    Based on air pollutant observations in the period from October to November (related with APEC summit), 2014 from meteorological stations of major cities in Beijing-Tianjin-Hebei (BTH) and the surrounding region, the maps of mean air pollutant concentrations every seven (or five) days are obtained with selected spatial interpolation methods. Global autocorrelation and local autocorrelation analysis methods are used to study the spatial heterogeneities of pollutant concentrations, and the spatio-temporal distribution characteristics of pollutants are explored by using kernel density (KD). The followings are revealed:there were significant positive spatial autocorrelations and spatial aggregating features on the mean concentrations of all pollutants; the hot spots of mean PM2.5 concentrations distributed in Tianjin, Shijiazhuang, Baoding, and south Beijing; the hot spots of mean SO2 concentration concentrated mostly in Baoding, Tianjin, Tangshan and Shijiazhuang, while the hot spots of mean NO2 concentrations distributed mainly along BeijingTianjin-Tangshan and Baoding-Shijiazhuang-Xingtai; variations of air quality were notable at different times. Before and during the APEC summit, the regional control/limiting measures and the cold air activity effectively improved the air quality of Beijing and its surrounds, and the KD high value zones transformed gradually into middle or low KD-value zones. With the help of cold air currents and high wind speeds, nice air quality maintained within the first 5 days after the APEC summit. However, air pollutions rebounded sharply and high KDvalue zones gradually extended to most parts of the BTH region six days after the APEC summit. It is clear that spatial structure adjustment of industry and elimination of high air-pollution enterprises in BTH are imperative, and the regional synergic emission control in condition of poor meteorological period should be normalized.
    air pollution  /  spatial analysis  /  spatio-temporal features  /  APEC summit  /  BTH region
    张媛媛, 吴立新, 任传斌, 项程程, 李佳乐, 柴曼. APEC会议前后京津冀空气污染物时空变化特征. 科技导报, 2016 , 34 (24) : 115 -121 . DOI: 10.3981/j.issn.1000-7857.2016.24.017
    ZHANG Yuanyuan, WU Lixin, REN Chuanbin, XIANG Chengcheng, LI Jiale, CHAI Man. On the spatio-temporal features of air pollutants in Beijing-Tianjin-Hebei for the period of APEC summit[J]. Science & Technology Review, 2016 , 34 (24) : 115 -121 . DOI: 10.3981/j.issn.1000-7857.2016.24.017

      国家重点基础研究发展计划(973计划)项目(2011CB707102);江苏省优势学科(PAPD)及双创团队项目

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    2016年第34卷第24期
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    doi: 10.3981/j.issn.1000-7857.2016.24.017
    • 接收时间:2016-01-16
    • 首发时间:2017-02-07
    • 出版时间:2016-12-28
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    • 收稿日期:2016-01-16
    • 修回日期:2016-11-09
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    通讯作者:

    吴立新(通信作者),教授,研究方向为空间信息、灾害观测与协同感知,电子信箱:awulixin@263.net
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    2种不同金属材料的力学参数

    Family
    属数
    Number of
    genus
    种数
    Number of
    species
    占总种数比例
    Percentage of
    total species (%)

    Genus
    种数
    Number of
    species
    占总种数比例
    Percentage of total
    species (%)
    鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
    小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
    多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
    红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
    小菇属 Mycena 11 5.26
    光柄菇属 Pluteus 5 2.39
    红菇属 Russula 17 8.13
    栓菌属 Trametes 5 2.39
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