基于互联网大数据技术的重污染水体识别研究

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• 英文论文题名：The Research of Identification of Heavily Polluted Water Based on Internet Big Data Technology
• 论文作者：石峰 ; 袁钰
• 英文论文作者：SHE Feng ; YUAN Yu ; China-ASEAN Environment Cooperation Center
• 年：2015
• 作者机构：中国-东盟环境保护合作中心;
• 论文关键词：大数据 ; 重污染水体 ; 环境管理
• 英文论文关键词：Big data ; Heavily polluted water ; Environmental management
• 会议召开时间：2015-11-26
• 会议录名称：2015年水资源生态保护与水污染控制研讨会论文集
• 语种：中文
• 分类号：X52;X832
• 学会代码：HJKP
• 会议名称：2015年水资源生态保护与水污染控制研讨会
• 会议地点：中国海南海口
• 主办单位：中国环境科学学会、哈尔滨师范大学
• 学会名称：中国环境科学学会
• 页数：6
• 文件大小：978k
• 原文格式：D
• 会议级别：全国

摘要

国务院近期颁布的《水污染防治行动计划》对重污染水体和黑臭水体治理提出了明确的要求。然而在实际工作中,由于对重污染水体和黑臭水体的判别缺乏明确标准和识别手段,水质监测系统存在着监测能力不足、点位覆盖不够等诸多实际问题,黑臭水体的识别存在较大的困难。本研究首次尝试采用基于互联网开放信息的大数据技术,对互联网媒体曝光最多、群众投诉议论最多的污染水体进行数据搜索和统计分析,得到全国重污染水体和黑臭水体的总体分布情况,其结果可以作为全国重污染水体整治工作的重要参考。分析得出河北漕河等重污染河流因水环境污染问题受到媒体和群众最多关注,通过与现有资料和数据对比,发现此研究结果与各地实际情况基本符合。此方法可拓展到大气、固废、土壤等多个领域,将互联网大数据技术切实作为环境管理转型升级的重要创新领域。
The Action Plan for Water Pollution Prevention and Control, released by the State Council, puts forward clear requirements for the treatment of heavy polluted waters and black-odor waters. But in practice, we lack clear standards and identification methods of heavy polluted waters and black-odor waters. The water quality testing system has some practical problems, such as inadequate monitoring capacity and monitoring points. Therefore, it proves to be much more difficult to identify black-odor water. This research purposes to apply big data techniques in statistical searching and analysis on the polluted waters that received the most media exposure and whistle blowing. It aims to demonstrate the overall layout of highly-polluted and black and odorous waters in China, which would significantly contribute to the national water pollution control and prevention work. Through analysis, this research finds that Caohe River in Hebei Province among others has drawn most attention from the media and the public due to its severe pollution. Meanwhile, through comparing the data with the real situation there, it is confirmed that the results basically match the current condition of Caohe River. The methodology adopted by this paper can also be applied in other relevant pollution studies, such as atmospheric pollution, solid waste treatment, soil contamination and so on. It will practically promote the innovative application of Internet big data technology in facilitating the transformation and upgrading of environment management.

引文

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