Yu Yang, Li Yingxia, Li Ben, Shen Zhenyao, Stenstrom Michael K
State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing100875, China; Department of Civil and Environmental Engineering, University of California Los Angeles, Los Angeles, CA 90095, USA.
State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing100875, China.
Ecotoxicol Environ Saf. 2017 Mar;137:281-287. doi: 10.1016/j.ecoenv.2016.11.031. Epub 2016 Dec 19.
Lead (Pb) concentration in urban dust is often higher than background concentrations and can result in a wide range of health risks to local communities. To understand Pb distribution in urban dust and how multi-industrial activity affects Pb concentration, 21 sampling sites within the heavy industry city of Jilin, China, were analyzed for Pb concentration. Pb concentrations of all 21 urban dust samples from the Jilin City Center were higher than the background concentration for soil in Jilin Province. The analyses show that distance to industry is an important parameter determining health risks associated with Pb in urban dust. The Pb concentration showed an exponential decrease, with increasing distance from industry. Both maximum likelihood estimation and Bayesian analysis were used to estimate the exponential relationship between Pb concentration and distance to multi-industry areas. We found that Bayesian analysis was a better method with less uncertainty for estimating Pb dust concentrations based on their distance to multi-industry, and this approach is recommended for further study.
城市灰尘中的铅（Pb）浓度通常高于背景浓度，会给当地社区带来一系列健康风险。为了解城市灰尘中铅的分布情况以及多行业活动如何影响铅浓度，对中国重工业城市吉林的21个采样点的铅浓度进行了分析。吉林市中心所有21个城市灰尘样本的铅浓度均高于吉林省土壤的背景浓度。分析表明，与工业的距离是决定城市灰尘中铅相关健康风险的一个重要参数。随着与工业距离的增加，铅浓度呈指数下降。使用最大似然估计和贝叶斯分析来估计铅浓度与到多行业区域距离之间的指数关系。我们发现，贝叶斯分析是一种更好的方法，基于到多行业的距离估计铅尘浓度时不确定性较小，建议采用这种方法进行进一步研究。
