Comparison of PM2.5 Exposure in Hazy and Non-Hazy Days in Nanjing, China

被引:26
|
作者
Zhang, Ting [1 ,2 ]
Chillrud, Steven N. [2 ]
Ji, Junfeng [1 ]
Chen, Yang [1 ]
Pitiranggon, Masha [2 ]
Li, Wenqing [3 ]
Liu, Zhenyang [1 ]
Yan, Beizhan [2 ]
机构
[1] Nanjing Univ, Minist Educ, Key Lab Surficial Geochem, Nanjing 210023, Jiangsu, Peoples R China
[2] Columbia Univ, Lamont Doherty Earth Observ, Palisades, NY 10964 USA
[3] Nanjing Municipal Inst Environm Protect, Nanjing 210093, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
PM2.5; Micro-environment; Haze; Personal exposure; Subway; PARTICULATE MATTER PM2.5; SHORT-TERM EXPOSURE; PERSONAL EXPOSURE; FINE PARTICLES; AIR-POLLUTION; MICROENVIRONMENTAL EXPOSURE; CHEMICAL CHARACTERISTICS; PUBLIC TRANSPORTATION; ELEMENTAL COMPOSITION; INDOOR;
D O I
10.4209/aaqr.2016.07.0301
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Fine particulate matter (PM2.5), levels of which are about 6 times the 2014 WHO air quality guidelines for 190 cities in China, has been found to be associated with various adverse health outcomes. In this study, personal PM2.5 exposures were monitored along a fixed routine that included 19 types of non-residential micro-environments (MEs) on 4 hazy days (ambient PM2.5 292 +/- 70 mu g m(-3)) and 2 non-hazy days (55 +/- 16 mu g m(-3)) in Nanjing, China using miniaturized real-time portable particulate sensors that also collect integrated filters of PM2.5 (MicroPEMs, Research Triangle Institute (RTI), NC). Gravimetric correction is necessary for nephelometer devices in calculating real-time PM levels. During both hazy and non-hazy days, personal PM2.5 levels were generally higher in MEs with noticeable PM2.5 sources than MEs serving as receptor sites, higher in open MEs than indoor MEs, and higher in densely populated MEs than MEs with few people. Personal PM2.5 levels measured during hazy and non-hazy days were 242 +/- 91 mu g m(-3) and 103 +/- 147 mu g m(-3), respectively. The ratio of personal exposure to ambient PM2.5 levels (r(p/a)) was less than 1.0 and less variable on hazy days (0.85 +/- 0.31); while it was larger than 1.0 and more variable on non-hazy days (1.71 +/- 1.93), confirming the importance of local sources other than ambient during non-hazy days. Air handling methods (e.g., ventilation/filtration) impacted personal exposures in enclosed locations on both types of days. Street food vendors with cooking emissions were MEs with the highest personal PM2.5 levels while subway cars in Nanjing were relatively clean due to good air filtration on both hazy and nonhazy days. In summary, on hazy days, personal exposure was mainly affected by the regional ambient levels, while on non-hazy days, local sources together with ambient levels determined personal exposure levels.
引用
收藏
页码:2235 / 2246
页数:12
相关论文
共 50 条
  • [31] Sources of emission and their impacts on PM2.5 in Nanjing and Shanghai
    Gao Song
    Zhang Long
    Hu Yanan
    Ma Xiaoyan
    Sha Tong
    Guan Qikun
    Li Ruolin
    Fu Zeyu
    PROCEEDINGS OF THE 2017 3RD INTERNATIONAL FORUM ON ENERGY, ENVIRONMENT SCIENCE AND MATERIALS (IFEESM 2017), 2017, 120 : 1132 - 1137
  • [32] Nonmethane Hydrocarbons in Ambient Air of Hazy and Normal Days in Foshan, South China
    Guo, Songjun
    Yang, Fumo
    Tan, Jihua
    Duan, Jingchun
    ENVIRONMENTAL ENGINEERING SCIENCE, 2012, 29 (04) : 262 - 269
  • [33] Comparison of PM2.5 Chemical Compositions during Haze and Non-haze Days in a Heavy Industrial City in North China
    Li, Menghui
    Wu, Liping
    Zhang, Xiangyan
    Wang, Xinwu
    Bai, Wenyu
    Ming, Jing
    Geng, Chunmei
    Yang, Wen
    AEROSOL AND AIR QUALITY RESEARCH, 2020, 20 (09) : 1950 - 1960
  • [34] PM2.5 exposure and anxiety in China: evidence from the prefectures
    Buwei Chen
    Wen Ma
    Yu Pan
    Wei Guo
    Yunsong Chen
    BMC Public Health, 21
  • [35] Reduced inequality in ambient and household PM2.5 exposure in China
    Luo, Zhihan
    Shen, Guofeng
    Men, Yatai
    Zhang, Wenxiao
    Meng, Wenjun
    Zhu, Wenyuan
    Meng, Jing
    Liu, Xinlei
    Cheng, Qin
    Jiang, Ke
    Yun, Xiao
    Cheng, Hefa
    Xue, Tao
    Shen, Huizhong
    Tao, Shu
    ENVIRONMENT INTERNATIONAL, 2022, 170
  • [36] PM2.5 exposure and anxiety in China: evidence from the prefectures
    Chen, Buwei
    Ma, Wen
    Pan, Yu
    Guo, Wei
    Chen, Yunsong
    BMC PUBLIC HEALTH, 2021, 21 (01)
  • [37] A Study on Distance Transport of PM2.5 to Xianlin in Nanjing, China and its Source Areas
    Cheng, Feng
    Zha, Yong
    Zhang, Jiahua
    He, Junliang
    Yan, Shiyong
    AEROSOL AND AIR QUALITY RESEARCH, 2017, 17 (07) : 1772 - 1783
  • [38] Population Exposure to Ambient PM2.5 at the Subdistrict Level in China
    Long, Ying
    Wang, Jianghao
    Wu, Kang
    Zhang, Junjie
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2018, 15 (12)
  • [39] Estimating adult mortality attributable to PM2.5 exposure in China with assimilated PM2.5 concentrations based on a ground monitoring network
    Liu, Jun
    Han, Yiqun
    Tang, Xiao
    Zhu, Jiang
    Zhu, Tong
    SCIENCE OF THE TOTAL ENVIRONMENT, 2016, 568 : 1253 - 1262
  • [40] Characterization and source apportionment of oxidative potential of ambient PM2.5 in Nanjing, a megacity of Eastern China
    Zhang, Lu
    Hu, Xin
    Chen, Sisi
    Chen, Yijun
    Lian, Hong-Zhen
    ENVIRONMENTAL POLLUTANTS AND BIOAVAILABILITY, 2023, 35 (01)