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Health impacts of domestic coal use in China

机译:中国国内煤炭使用对健康的影响

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Domestic coal combustion has had profound adverse effects on the health of millions of people worldwide. In China alone several hundred million people commonly burn raw coal in unvented stoves that permeate their homes with high levels of toxic metals and organic compounds. At least 3,000 people in Guizhou Province in southwest China are suffering from severe arsenic poisoning. The primary source of the arsenic appears to be consumption of chili peppers dried over fires fueled with high-arsenic coa. Coal samples in the region were found to contain up to 35,000 ppm arsenic. Chili peppers dried over high-arsenic coal fires adsorb 500 ppm arsenic on average. More than 10 million people in Guizhou Province and surrounding areas suffer from dental and skeletal fluorosis. The excess fluorine is caused by eating corn dried over burning briquettes made from high-fluorine coals and high-fluorine clay binders. Polycyclic aromatic hydrocarbons formed during coal combustion are believed to cause or contribute to the high incidence of esophageal and lung cancers in parts of China. Domestic coal combustion also has caused selenium poisoning and possibly mercury poisoning. Better knowledge of coal quality parameters may help to reduce some of these health problems. For example, information on concentrations and distributions of potentially toxic elements in coal may help delineate areas of a coal deposil to be avoided. Information on the modes of occurrence of these elemcnts and the textural relations of the minerals and macerals in coal may help predict the behavior of the potentially t
机译:国内燃煤对全世界数百万人的健康产生了深远的不利影响。仅在中国,就有几亿人通常在未经通风的炉子中燃烧原煤,这些炉子中充满了高含量的有毒金属和有机化合物。在中国西南的贵州省,至少有3,000人患有严重的砷中毒。砷的主要来源似乎是食用以高砷可可为燃料的火烧干的辣椒。发现该地区的煤炭样品中砷含量高达35,000 ppm。在高砷煤火上干燥的辣椒平均吸收500 ppm砷。贵州省及周边地区超过一千万的人患有氟中毒。过量的氟是由于吃掉了用高氟煤和高氟黏土粘合剂制成的燃烧煤块而干燥的玉米引起的。在中国部分地区,煤燃烧过程中形成的多环芳烃被认为是导致食管癌和肺癌高发的原因。国内燃煤还引起了硒中毒甚至汞中毒。更好地了解煤炭质量参数可能有助于减少其中一些健康问题。例如,有关煤中潜在有毒元素的浓度和分布的信息可能有助于勾勒出应避免的煤场区域。有关这些元素发生方式的信息以及煤中矿物和黄石的组织关系的信息可能有助于预测潜在矿物的行为。

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