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中国京津冀区域大气SO2质量浓度空间分布数据集(2016)

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国家地球系统科学数据中心2019-01-25 更新2024-03-04 收录
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本数据首先由京津冀2016年环保部环境监测站总站公布的各地级城市的地面PM2.5、SO2、O3小时均值计算月平均获得,然后通过克里格方法(Kriging)又称空间局部插值法进行插值计算得到。环保部地面数据采用脉冲荧光法SO2 分析仪原理基于SO2 分子吸收一定波长的UV 光(hν1)后,形成激发态的SO2*,然后激发态SO2*从激发态跃回基态时可发射出另一波长的紫外光(hν2):即SO2 + hν1→SO2*→SO2 + hν2。43C 型SO2分析仪最低检测限:0.5ppb ;零漂:小于1ppb /24h;跨漂:±1%/24h(满度值)响应时间:40s 110s 320s;精度:1ppb 。中国京津冀区域大气SO2质量浓度空间分布数据集(2016);(12个dat 格式文件),文件名中BHT为京津冀首字母缩写,SO2表示数据要素为二氧化硫,Jan, Feb, Mar, Apr, May, Jun, Jul, Aug, Sep, Oct, Nov, Dec为1-12月份缩写。文件包含2016年1月-12月均值0.25度网格分辨率的 SO2的平均浓度记录数据

First, this dataset was obtained by calculating monthly average values from hourly ground-level PM2.5, SO2 and O3 concentrations of prefecture-level cities released by the General Station of Environmental Monitoring of the Ministry of Environmental Protection in the Beijing-Tianjin-Hebei region in 2016, followed by interpolation using the Kriging method, also known as spatial local interpolation. The ground-level data from the Ministry of Environmental Protection were measured with a pulsed fluorescence method SO2 analyzer, whose working principle is: after SO2 molecules absorb UV light (hν1) of a certain wavelength, they form excited-state SO2*, and when the excited-state SO2* transitions back to the ground state, it emits UV light of another wavelength (hν2), i.e., SO2 + hν1 → SO2* → SO2 + hν2. For the Model 43C SO2 analyzer, the performance parameters are as follows: detection limit: 0.5 ppb; zero drift: <1 ppb/24h; span drift: ±1%/24h (full scale); response time: 40s, 110s, 320s; accuracy: 1 ppb. This is the Spatial Distribution Dataset of Atmospheric SO2 Mass Concentration in Beijing-Tianjin-Hebei Region, China (2016), which includes 12 files in DAT format. In the filenames, BHT is the acronym for Beijing-Tianjin-Hebei, SO2 indicates that the data element is sulfur dioxide, and Jan, Feb, Mar, Apr, May, Jun, Jul, Aug, Sep, Oct, Nov, Dec are the abbreviations for January to December respectively. Each file contains the averaged SO2 concentration records at a 0.25-degree grid resolution for each month from January to December 2016.
提供机构:
中国科学院大气物理研究所
创建时间:
2019-01-25
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