7 research outputs found

    Methodology of Seawater Quality Assessment Using the Data from Oceanic Automatic Monitoring

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    海洋水质评价方法是水环境保护中不可缺少的一环,它能真实、客观地反映出海水水质的变化情况,有助于保护海洋环境,实现人类同环境的可持续发展。海水水质评价的结果不仅可以使人们充分了解海洋环境质量的情况,还可以为人类科学地管理海洋提供依据,同时也有利于海洋资源可持续地为人类服务。随着自动化技术的发展,越来越多的自动监测设备被广泛应用于水质监测工作中。厦门环境监测站于2004年7月利用海上浮标式水质自动监测站进行海水水质监测。目前,对自动监测数据的处理和应用方法,仅仅使用其最小值、最大值和平均值来进行水质评价,这样对于能连续24小时监测的自动监测站获取的数据来讲,无疑是一种浪费,更不能发挥自动监测站的优...The methods for seawater quality assessment are an essential part of water environment protection. It can reflect the change of seawater quality, give a quantitative description of seawater quality, provide useful information, and make marine resource use toward sustainability. It is very useful for marine environment planning and management. With the development of automatic technology, more and ...学位:理学硕士院系专业:海洋与环境学院环境科学与工程系_环境科学学号:20043405

    自然灾害环境风险评价研究进展

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    总结了国内外关于自然灾害风险评价的研究现状,包括了自然灾害风险的定义、分类以及风险评价的研究进展。在次基础上分析了当前自然灾害风险评价存在的问题,并提出了建议和展望

    水库水源保护区生态补偿机制的探讨

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    本论文提出建立水库水源保护区的生态补偿机制作为长效机制以解决水源保护问题;对生态补偿的定义、建立生态补偿的必要性、定量研究、补偿费分摊率的确定以及资金的来源进行了探讨

    Excel软件在环境监测数据处理中的应用

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    环境监测在环境保护中的作用日益显著,随着自动化监测设备的发展和普及,在我国不少水系、饮用水和污染源等地方广泛使用。自动监测数据较以往的人工监测数据有了新的特点,如数据量大、监测时间长、污染事故的预警预报。如何充分使用监测数据,发挥其在环境保护中的作用?传统的监测数据处理,要通过几个Excel命令操作,本文尝试将Excel功能之一的“数据分析”中的“描述统计”命令对自动监测数据进行分析处理。该命令处理后的结果表明,简单的一个命令就可以分析出数据的特点,可以减少监测数据分析人员的工作量。同时,也便于监测数据的利用,对环境评价具有实用性

    JUNO Sensitivity on Proton Decay pνˉK+p\to \bar\nu K^+ Searches

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    The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in pνˉK+p\to \bar\nu K^+ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via pνˉK+p\to \bar\nu K^+ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is 9.6×10339.6 \times 10^{33} years, competitive with the current best limits on the proton lifetime in this channel

    JUNO sensitivity on proton decay pνK+p → νK^{+} searches

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    JUNO sensitivity on proton decay p → ν K + searches*

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    The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the pνˉK+ p\to \bar{\nu} K^+ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via pνˉK+ p\to \bar{\nu} K^+ is 36.9% ± 4.9% with a background level of 0.2±0.05(syst)±0.2\pm 0.05({\rm syst})\pm 0.2(stat) 0.2({\rm stat}) events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is 9.6×1033 9.6 \times 10^{33} years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies
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