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2014年9-10月国内生产安全事故统计分析

Statistics of industrial accidents in China during the period from September to October in 2014
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摘要 统计了2014年9—10月国内发生的各种生产安全事故118起,其中包括交通事故、矿业事故、爆炸事故、火灾、毒物泄漏与中毒和其他事故。统计表明,在118起事故中,交通事故占61.86%,矿业事故占5.93%,爆炸事故占3.39%,火灾占3.39%,毒物泄漏与中毒占4.24%,其他事故占21.19%。118起事故共死亡445人,伤270人。死亡人数的百分比分别为交通事故66.29%,矿业事故3.82%,爆炸事故6.07%,火灾2.92%,毒物泄漏与中毒4.49%,其他事故16.40%;受伤人数的百分比分别为交通事故68.89%,矿业事故0.37%,爆炸事故16.67%,火灾2.22%,其他事故11.85%。2014年9-10月生产安全事故发生较多的6个省、自治区分别为黑龙江(10起)、广西(9起)、广东(9起)、云南(7起)、甘肃(7起)、湖北(7起);死亡人数较多的5个省、自治区分别为黑龙江(39人)、广西(35人)、广东(34人)、甘肃(30人)、湖南(28人);受伤人数较多的5个省、直辖市分别为湖南(51人)、云南(35人)、广东(33人)、天津(26人)、江西(18人)。 The present paper reports the statistical data and analysis of industrial accidents in China during the period from September to October in 2014. There are 118 accidents in total, which can be summarized and classified into six categories: traffic, mining indus- try, explosion, fire, leakage and poisoning, and the others. Of all the 118 accidents, the percentages of the six categories can be illus- trated according to their frequency order 61.86%, 5.93%, 3.39%, 3.39%, 4.24%, and 21.19% respectively. The death toll is 445 and the percentages for the six categories are 66.29%, 3.82%, 6.07%, 2.92%, 4.49%, and 16.40% respectively. The injured toll is 270 and the percentages for the six categories are 68.89%, 0.37%, 16.67%, 2.22%, 0, and 11.85% respectively. The analyses of the statistics show that the top six provinces and au- tonomous regions with highest accident number are: Heilongjiang (10 accidents), Guangxi (9), Guangdong (9), Yunnan (7), Gansu (7), and Hubei (7). The top five provinces and autonomous regions with the largest casualty number are: Heilongjiang (39 dead), Guangxi (35), Guangdong (34), Gansu (30), and nunan (28). And the top five provinces and cities with the biggest wounded num- ber are: Hunan (51 wounded), Yunnan (35), Guangdang (33), Tianjin (26) and Jiangxi (18).
作者 李生才 笑蕾
出处 《安全与环境学报》 CAS CSCD 北大核心 2014年第6期346-348,共3页 Journal of Safety and Environment
关键词 安全管理工程 事故数据 统计分析 safety control accident statistical analysis
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