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基于多采样点的南京市PM2.5中的水溶性砷分析
引用本文:刘欣,杨孟,李凤英,陈敏东,郑军,黎飞虎,金杰,吴丹.基于多采样点的南京市PM2.5中的水溶性砷分析[J].环境科学学报,2019,39(11):3668-3676.
作者姓名:刘欣  杨孟  李凤英  陈敏东  郑军  黎飞虎  金杰  吴丹
作者单位:南京信息工程大学环境科学与工程学院,江苏省大气环境监测与污染控制高技术研究重点实验室,江苏省大气环境与装备技术协同创新中心,南京210044;南京信息工程大学环境科学与工程学院,江苏省大气环境监测与污染控制高技术研究重点实验室,江苏省大气环境与装备技术协同创新中心,南京210044;南京信息工程大学环境科学与工程学院,江苏省大气环境监测与污染控制高技术研究重点实验室,江苏省大气环境与装备技术协同创新中心,南京210044;南京信息工程大学环境科学与工程学院,江苏省大气环境监测与污染控制高技术研究重点实验室,江苏省大气环境与装备技术协同创新中心,南京210044;南京信息工程大学环境科学与工程学院,江苏省大气环境监测与污染控制高技术研究重点实验室,江苏省大气环境与装备技术协同创新中心,南京210044;南京信息工程大学环境科学与工程学院,江苏省大气环境监测与污染控制高技术研究重点实验室,江苏省大气环境与装备技术协同创新中心,南京210044;南京信息工程大学环境科学与工程学院,江苏省大气环境监测与污染控制高技术研究重点实验室,江苏省大气环境与装备技术协同创新中心,南京210044;南京信息工程大学环境科学与工程学院,江苏省大气环境监测与污染控制高技术研究重点实验室,江苏省大气环境与装备技术协同创新中心,南京210044
基金项目:江苏省自然科学基金项目(No.BK20150915);国家自然科学基金项目(No.41501197)
摘    要:对南京市的18个采样点进行PM_(2.5)样品采集,并利用电感耦合等离子体质谱仪以及液相电感耦合等离子体质谱联用仪分别对样品中的总砷和4种水溶性砷进行测量,在此基础上研究PM_(2.5)中砷的形态及其时空分布特征.结果表明:南京市PM_(2.5)中的砷以无机砷为主,有机砷为辅.无机砷以三价砷(As(III))为主,五价砷(As(V))为辅,As(III)/As(V)的平均值为0.39±0.03.有机砷以二甲基胂酸(DMAs(V))为主,所有样品均未检出甲基胂酸(MMAs(V)).总砷(As_T)、As(III)、As(V)和DMAs(V)的年平均浓度分别为6.90、0.99、3.20和0.03 ng·m~(-3).PM_(2.5)中的砷浓度具有明显季节变化:总砷和As(V)最大浓度出现在冬季,As(III)最大浓度出现在夏季,DMAs(V)只在夏季出现.T检验表明:As(III)、总砷和DMAs(V)年平均浓度在城区和郊区之间存在显著差异.空间变异系数的计算结果表明DMAs(V)的空间变化最大,其空间变异系数为0.6.总砷和3种水溶性砷年平均浓度由大到小排列为:农村郊区城区.道路采样点和城市背景点的总砷年平均浓度比为0.92,说明城区交通源对PM_(2.5)中砷污染的贡献不明显.As(III)和As(V)的主要排放源可能为燃煤电厂和钢铁冶炼厂,而DMAs(V)可能主要来源于生物挥发产物的二次生成.

关 键 词:PM2.5  水溶性砷  空间分布  时间变化
收稿时间:2019/4/23 0:00:00
修稿时间:2019/5/28 0:00:00

Analysis of water extractable arsenic species in PM2.5 in Nanjing based on multiple sampling sites
LIU Xin,YANG Meng,LI Fengying,CHEN Mindong,ZHENG Jun,LI Feihu,JIN Jie and WU Dan.Analysis of water extractable arsenic species in PM2.5 in Nanjing based on multiple sampling sites[J].Acta Scientiae Circumstantiae,2019,39(11):3668-3676.
Authors:LIU Xin  YANG Meng  LI Fengying  CHEN Mindong  ZHENG Jun  LI Feihu  JIN Jie and WU Dan
Institution:Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science&Engineering, Nanjing University of Information Science&Technology, Nanjing 210044,Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science&Engineering, Nanjing University of Information Science&Technology, Nanjing 210044,Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science&Engineering, Nanjing University of Information Science&Technology, Nanjing 210044,Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science&Engineering, Nanjing University of Information Science&Technology, Nanjing 210044,Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science&Engineering, Nanjing University of Information Science&Technology, Nanjing 210044,Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science&Engineering, Nanjing University of Information Science&Technology, Nanjing 210044,Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science&Engineering, Nanjing University of Information Science&Technology, Nanjing 210044 and Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science&Engineering, Nanjing University of Information Science&Technology, Nanjing 210044
Abstract:The PM2.5 samples were collected from 18 sampling sites in Nanjing, and total arsenic (AsT) and four kinds of water extractable As species in the samples were measured by inductively coupled plasma mass spectrometry and liquid phase inductively coupled plasma mass spectrometry respectively. On this basis, the speciation, spatial and temporal distribution characteristics of arsenic in PM2.5 were studied. The results showed that inorganic As, especially arsenate (As(V)), was the dominant species of arsenic in PM2.5, and the ratio of arsenite (As(III)) to As(V) was 0.39±0.03. Organic arsenic was dominated by dimethylarsinic acid (DMAs(V)), and no monomethylarsonic acid (MMAs(V)) was detected in all samples. The average annual concentrations of AsT, As(III), As(V), and DMAs(V) were 6.90, 0.99, 3.20 and 0.03 ng·m-3, respectively. The concentrations of arsenic in PM2.5 have obvious seasonal variation. The highest concentrations of AsT and As(V) were observed during wintertime; the concentrations of As(V) were higher in summer; DMAs(V) was only observed in summer. T tests showed significant difference in concentrations of As(III), AsT and DMAs(V) between urban and suburban areas. The results of spatial variation coefficients (CVs) showed that the spatial variation of DMAs(V), which had a CV value of 0.6, was considerably higher than As(III) and As(V). The concentrations of AsT and the three kinds of arsenic species can be arranged in the following order:rural > suburb > urban. Street and urban background contrasts showed that the ration of street to urban background sites for concentrations of AsT was 0.92, indicating that the contribution of traffic emissions to PM2.5 arsenic pollution in urban areas is not obvious. As (III) and As (V) may be dominantly emitted from coal-fired power plants and steel smelting, while DMAs (V) may be mainly from secondary formation from products of biological volatilization.
Keywords:PM2  5  water extractable arsenic  spatial distribution  temporal variation
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