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Assessment of Regional Human Health Risks from Lead Contamination in Yunnan Province Southwestern China

机译:中国西南云南地区铅污染引起的区域人类健康风险评估

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摘要

Identification and management the 'critical risk areas' where hotspot lead exposures are a potential risk to human health, become a major focus of public health efforts in China. But the knowledge of health risk assessment of lead pollution at regional and national scales is still limited in China. In this paper, under the guidance of 'sources-pathways-receptors' framework, regional human health risk assessment model for lead contamination was developed to calculate the population health risk in Yunnan province. And the cluster and AHP (analytic hierarchy process) analysis was taken to classify and calculate regional health risk and the decomposition of the regional health risk in the greatest health risk region, respectively. The results showed that Yunnan province can be divided into three areas. The highest health risk levels, located in northeastern Yunnan, including Kunming, Qujing, Zhaotong region. In those regions, lead is present at high levels in air, food, water and soil, and high population density which pose a high potential population risk to the public. The current study also reveals that most regional health risk was derived from the child receptors (age above 3 years) 4.3 times than the child receptors (age under 3years), and ingestion of lead-contaminated rice was found to be the most significant contributor to the health risk (accounting for more than 49 % health risk of total). This study can provide a framework for regional risk assessment in China and highlighted some indicators and uncertainties.
机译:识别和管理热点铅暴露可能对人体健康构成威胁的“关键风险领域”,已成为中国公共卫生工作的重点。但是,中国在区域和国家范围内铅污染健康风险评估的知识仍然有限。本文在“源-途径-受体”框架的指导下,建立了铅污染区域人类健康风险评估模型,以计算云南省的人口健康风险。分别采用聚类分析和层次分析法对区域健康风险进行分类和计算,并对最大健康风险区域的区域健康风险进行分解。结果表明,云南省可分为三个区域。健康风险最高的地区位于云南省东北部,包括昆明,曲靖,昭通地区。在那些地区,空气,食物,水和土壤中的铅含量很高,人口密度很高,这给公众带来了巨大的潜在人口风险。当前的研究还表明,大部分区域健康风险来自儿童受体(3岁以上),是儿童受体(3岁以下)的4.3倍,并且发现摄入铅污染的大米是造成这种情况的最重要因素。健康风险(占总健康风险的49%以上)。这项研究可以为中国区域风险评估提供一个框架,并强调了一些指标和不确定性。

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