title: Profiles of lead in urban dust and the effect of the distance to multi-industry in an old heavy industry city in China.
abstract: 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.
authors.affiliation: 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.
authors.forename: Yang
authors.initials: Y
authors.lastname: Yu
authors.affiliation: State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing100875, China. Electronic address: yingxia@bnu.edu.cn.
authors.forename: Yingxia
authors.initials: Y
authors.lastname: Li
authors.affiliation: Department of Civil and Environmental Engineering, University of California Los Angeles, Los Angeles, CA 90095, USA.
authors.forename: Ben
authors.initials: B
authors.lastname: Li
authors.affiliation: State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing100875, China.
authors.forename: Zhenyao
authors.initials: Z
authors.lastname: Shen
authors.affiliation: Department of Civil and Environmental Engineering, University of California Los Angeles, Los Angeles, CA 90095, USA.
authors.forename: Michael K
authors.initials: MK
authors.lastname: Stenstrom
mesh_terms: D001499:Bayes Theorem; D002681:China; D002947:Cities; D004391:Dust / Q000032:analysis*; D004784:Environmental Monitoring; D005843:Geography; D007221:Industry / Q000706:statistics & numerical data; D007854:Lead / Q000032:analysis*; D016013:Likelihood Functions; D008669:Metallurgy / Q000706:statistics & numerical data; D019216:Metals, Heavy / Q000032:analysis; D012987:Soil / Q000737:chemistry; D012989:Soil Pollutants / Q000032:analysis*
chemical_list: D004391:Dust; D019216:Metals, Heavy; D012987:Soil; D012989:Soil Pollutants; D007854:Lead
keywords: Bayesian analysis; Health risk assessment; Lead; Maximum likelihood estimation; Monte Carlo simulation; Urban nonpoint source pollution