生态与农村环境学报 ›› 2023, Vol. 39 ›› Issue (10): 1257-1266.doi: 10.19741/j.issn.1673-4831.2022.0335

• 区域环境与发展 • 上一篇    下一篇

南京北郊冬季PM2.5中重金属的形态、来源及健康风险

赵腾, 孙明洋, 盖鑫磊   

  1. 南京信息工程大学环境科学与工程学院/大气环境与装备技术协同创新中心/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 南京 210044
  • 收稿日期:2022-04-19 出版日期:2023-10-25 发布日期:2023-10-23
  • 通讯作者: 孙明洋,E-mail:qfsmy1216@163.com E-mail:qfsmy1216@163.com
  • 作者简介:赵腾(1996-),男,甘肃庆阳人,研究方向为大气环境化学。E-mail:1424316764@qq.cm
  • 基金资助:
    江苏省自然科学基金(BK20160945);中央高校基本科研业务费专项(2021FZZX002-07)

Chemical Speciation, Source Appointment and Health Risk Assessment of Heavy Metals in PM2.5 in Winter in the North Suburb of Nanjing

ZHAO Teng, SUN Ming-yang, GE Xin-lei   

  1. School of Environmental Science and Engineering/Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET)/Jiangsu Key Laboratory of Atmospheric Environmental Monitoring & Pollution Control, Nanjing University of Information Science and Technology, Nanjing 210044, China
  • Received:2022-04-19 Online:2023-10-25 Published:2023-10-23

摘要: 为探究南京北郊冬季PM2.5重金属的污染特征、来源与健康风险,于2021年1-2月采集PM2.5样品,用BCR连续提取法对11种元素(Al、V、Cr、Mn、Co、Cu、As、Cd、Sr、Ba和Pb)进行连续提取,用电感耦合等离子体原子光谱仪(ICP-OES)测定分析PM2.5中重金属的化学形态和分布特征,利用正定矩阵因子分解模型(PMF)解析其来源,采用基于生物可利用浓度修正的美国国家环境保护局(EPA)健康风险评价模型评估其健康风险,并结合PMF模型、浓度权重轨迹模型(CWT)和后向轨迹模型(HYSPLIT)对特定污染源和区域传输的影响进行评估。结果表明:(1)采样期间PM2.5日均质量浓度为(99.0±18.3)μg·m-3,采样期间有92.3%的天数超过GB 3095-2012《环境空气质量标准》日均浓度限值,11种元素的日均总质量浓度为(1 999.0±307.2)ng·m-3,其中As、Cd日均质量浓度分别为(7.0±3.5)和(22.0±14.0)ng·m-3,均高于GB 3095-2012标准限值。(2)大部分重金属(V、Cr、Mn、As、Sr、Cd、Ba)主要存在于生物可利用性极高的弱酸溶解态(F1),Co、Cu和Pb主要存在于可还原态(F2),Al主要存在于生物可利用性较低的残渣态(F4)。(3)利用PMF模型解析出3类排放源,分别是扬尘源(31.4%)、燃煤源(17.7%)、交通和工业混合源(50.9%)。(4)采样期间重金属的综合非致癌风险指数小于1,非致癌风险可忽略,Cr、Co、As、Cd有潜在致癌风险。结合PMF、CWT和HYSPLIT发现,交通和工业混和源及河南省信阳市和安徽省东部的区域传输对南京北郊健康风险的影响不容忽视,因此不仅要加强对本地工业源排放的管控,也要密切关注区域传输对本地的影响。

关键词: PM2.5, 重金属, 生物可利用性, 来源解析, 特定源健康风险

Abstract: To explore the pollution characteristics, sources, and source-specific health risks of PM2.5-bound heavy metals (HMs) during winter in the north suburb of Nanjing, daily PM2.5 filter samples were collected during January and February 2021. The distribution characteristics and chemical speciation of 11 HMs (Al, V, Cr, Mn, Co, Cu, As, Sr, Cd, Ba and Pb) in PM2.5 were determined by BCR extraction and ICP-OES. Positive matrix factorization (PMF), as well as the modified health risk assessment method was used to analyze the source-specific health risks of HMs, which could find out the major health abuser. The influence of the regional transmission was evaluated using PMF, the concentration-weighted trajectory (CWT) method and Hybrid Single Particle Lagrangian Integrated Trajectories (HYSPLIT), respectively. The results showed that the average daily concentration of PM2.5 was (99.0±18.3) μg·m-3, and 92.3% of the days in the sampling period exceeded the daily average limit of the National Ambient Air Quality Standard (GB 3095-2012). The total contents of HMs was (1 999.0±307.2) ng·m-3, while the average value of As and Cd were (7.0±3.5) and (22.0±14.0) ng·m-3 ,respectively,both higher than the GB 3095-2012 limit value. Most of the studied HMs (V, Cr, Mn, As, Sr, Cd, Ba) were mainly concentrated in acid-soluble fraction (F1) with high bioavailability, a relatively high percentage of Co, Cu and Pb were present in reducible fraction (F2). Al was mostly concentrated in residual fraction (F4) with low bioavailability. Dust sources (31.4%), coal sources (17.7%) and the mixed sources of traffic and industry (50.9%) were the main sources of metal elements. Non-cancer risks of heavy metals were negligible with values under 1, and Cr, Co, As, Cd posed potential cancer risk to child and adults with values between 10-6 and 10-4. It could not be ignored that the impact of the mixed sources of industrial and traffic and regional transmission from Xinyang city of Henan Province and eastern Anhui Province on health risks in the northern suburbs of Nanjing. Therefore, it is not only necessary to strengthen the control of local industrial emissions, but also to pay close attention to the impact of regional transmission.

Key words: PM2.5, heavy metals, bioaccessibility, source apportionment, source-specific health risk

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