新疆博斯腾湖沉积岩心的~(210)Pb、~(228)Th、~(239,240)Pu和~3H的分布及意义

作者测定了博斯腾湖沉积岩心~(210)Pb、~(228)Th和核试验释放核素~(239,240)Pu、~3H的分布,并据~(210)Pb、~(228)Th、~(239,240)Pu的结果估算湖泊的沉积速率,分别为0.31cm/a,0.26cm/a和0.33cm/a。它表明该湖泊近百年来沉积环境十分稳定。沉积物岩心极好地保存了人类大气核试验的历史记录。~(239,240)Pu分布在1963±2出现峰值,与60年代核试验高峰期相当吻合。沉积物孔隙水~3H分布的峰值出现在1969年,与湖水的混合过程有关。     

The Statistical Analysis of Migration of Strong Earthquakes-Taking the North China Region asan Example

The migration of strong earthquakes is an important research topic because the migration phenomena reflect partly the seismic mechanism and involve the prediction of tendency of seismic activity. Research on migration of strong earthquakes has mostly focused on finding the phenomena. Some attempts on getting regularity were comparatively subjective. This paper suggests that there should be indices of migration in earthquake dataset and the indexes should have statistical meaning if there is regularity in the migration of strong earthquakes. In this study, three derivative attributes of migration, i.e., migration orientation, migration distance and migration time interval, were statistically analyzed. Results in the North China region show that the migration of strong earthquakes has statistical meaning. There is a dominant migration orientation (W by S to E by N), a dominant distance ( ≤ 100kin and on the confines of 300 ～ 700km), and a dominant time interval ( ≤ la and on the confines of 3 - 4a). The results also show that the migration will differ slightly with different magnitude range or earthquake activity phase.     

ARGOS LUT运行软件的分析与改进：（一）数据收集模块的分析与改进

我国在1986年引进的ARGOS系统地面站(VHF LuT)只能接收 NOAA—10及其前卫星转发的信息,无法接收1988年秋发射的、改变了传输格式的 NOAA—11转发的信息。为了解决这个问题,本文对 LUT 原有软件的“数据收集模块”进行了深入的分析,比较了 NOAA—10与 NOAA—11传输的数据,找出了其中的规律,并据之改进了原来的机器语言代码程序,使现有的 LUT 也能接收 NOAh—11转发的信息.这项成果不仅可供目前国内其它 LUT 工作人员参考,而且为今后分析 NOAA 系列卫星新的数据传输格式摸索了路子。     

基于荧光原理的叶绿素a传感器校准方法研究

利用传感器对水体叶绿素a 浓度进行原位测量是获取实时、连续、长时间序列数据的重要手段。本文在对RBR 传感器和ECO（Environmental Characterization Optics）传感器进行原理分析和线性度、稳定性、重复性等基本性能测试的基础上，利用单一藻种培养液和2020年南海北部海域现场数据校准传感器，并对新的传感器校准系数进行验证。结果表明：两台传感器使用新系数比原出厂系数的叶绿素a 浓度测量准确度有明显提高。RBR 传感器现场数据校准系数的计算结果与叶绿素a 标准值误差最小，平均绝对误差从1.93 μg/L 减小到0.35 μg/L，平均相对误差从55.1%减小到10.9%；ECO 传感器藻液系数明显优于出厂系数和现场数据校准系数的计算结果，平均绝对误差从1.76 μg/L 减小到0.59 μg/L，平均相对误差从50.3%减小到15.1%。传感器测量准确度的提高，可为海洋环境监测、海洋生态灾害预警等工作获取真实可靠数据提供支撑。