DOI: 10.1016/j.atmosenv.2017.11.045
Scopus记录号: 2-s2.0-85036501378
论文题名: Estimating representative background PM2.5 concentration in heavily polluted areas using baseline separation technique and chemical mass balance model
作者: Gao S ; , Yang W ; , Zhang H ; , Sun Y ; , Mao J ; , Ma Z ; , Cong Z ; , Zhang X ; , Tian S ; , Azzi M ; , Chen L ; , Bai Z
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2018
卷: 174 起始页码: 180
结束页码: 187
语种: 英语
英文关键词: Air pollutant
; Background concentration
; Baseline separation
; Chemical mass balance model
; PM2.5
; Time-series
Scopus关键词: Digital filters
; Emission control
; Parameter estimation
; Particles (particulate matter)
; Particulate emissions
; Pollution
; Regression analysis
; Separation
; Storms
; Time series
; Air pollutants
; Background concentration
; Baseline separation
; Chemical mass balance model
; PM2.5
; Air pollution
; atmospheric pollution
; background level
; baseline conditions
; chemical mass balance
; concentration (composition)
; estimation method
; numerical model
; particulate matter
; performance assessment
; pollutant source
; regression analysis
; time series
; air pollutant
; air pollution
; air quality
; algorithm
; Article
; combustion
; controlled study
; electric power plant
; heating
; mass
; particle size
; priority journal
; sand
; separation technique
; swamp
; Beijing [China]
; China
; Jinan [Shandong]
; Shandong
; Tianjin
Scopus学科分类: Environmental Science: Water Science and Technology
; Earth and Planetary Sciences: Earth-Surface Processes
; Environmental Science: Environmental Chemistry
英文摘要: The determination of background concentration of PM2.5 is important to understand the contribution of local emission sources to total PM2.5 concentration. The purpose of this study was to exam the performance of baseline separation techniques to estimate PM2.5 background concentration. Five separation methods, which included recursive digital filters (Lyne-Hollick, one-parameter algorithm, and Boughton two-parameter algorithm), sliding interval and smoothed minima, were applied to one-year PM2.5 time-series data in two heavily polluted cities, Tianjin and Jinan. To obtain the proper filter parameters and recession constants for the separation techniques, we conducted regression analysis at a background site during the emission reduction period enforced by the Government for the 2014 Asia-Pacific Economic Cooperation (APEC) meeting in Beijing. Background concentrations in Tianjin and Jinan were then estimated by applying the determined filter parameters and recession constants. The chemical mass balance (CMB) model was also applied to ascertain the effectiveness of the new approach. Our results showed that the contribution of background PM concentration to ambient pollution was at a comparable level to the contribution obtained from the previous study. The best performance was achieved using the Boughton two-parameter algorithm. The background concentrations were estimated at (27 ± 2) μg/m3 for the whole year, (34 ± 4) μg/m3 for the heating period (winter), (21 ± 2) μg/m3 for the non-heating period (summer), and (25 ± 2) μg/m3 for the sandstorm period in Tianjin. The corresponding values in Jinan were (30 ± 3) μg/m3, (40 ± 4) μg/m3, (24 ± 5) μg/m3, and (26 ± 2) μg/m3, respectively. The study revealed that these baseline separation techniques are valid for estimating levels of PM2.5 air pollution, and that our proposed method has great potential for estimating the background level of other air pollutants. © 2017 Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/83059
Appears in Collections: 气候变化事实与影响
There are no files associated with this item.
作者单位: School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin, China; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China; Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China; Commonwealth Scientific and Industrial Research Organization (CSIRO) Energy, North Ryde, Australia
Recommended Citation:
Gao S,, Yang W,, Zhang H,et al. Estimating representative background PM2.5 concentration in heavily polluted areas using baseline separation technique and chemical mass balance model[J]. Atmospheric Environment,2018-01-01,174