DOI: 10.1016/j.atmosenv.2014.07.051
Scopus记录号: 2-s2.0-84905662165
论文题名: A review of receptor modelling of industrially emitted particulate matter
作者: Taiwo A ; M ; , Harrison R ; M ; , Shi Z
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2014
卷: 97 起始页码: 109
结束页码: 120
语种: 英语
英文关键词: Industrial emissions
; Metals
; Particulate matter
; Receptor modelling
; Source apportionment
; Steel industry
Scopus关键词: Data handling
; Fog
; Iron and steel industry
; Metals
; Multivariant analysis
; Organic carbon
; Particles (particulate matter)
; Principal component analysis
; Steelmaking
; Urban growth
; Iron and steel industry
; Metals
; Chemical mass balance
; Fine particulate matter
; Multivariate statistical models
; Organic and elemental carbon
; Particulate Matter
; Positive Matrix Factorization
; Receptor modelling
; Source apportionment
; Industrial emissions
; Industrial emissions
; carbon
; element carbon
; organic carbon
; polycyclic aromatic hydrocarbon
; trace element
; unclassified drug
; receptor
; trace metal
; chemical composition
; classification
; flow modeling
; industrial emission
; particulate matter
; site investigation
; urban atmosphere
; atmospheric pollution
; literature review
; metal
; metals industry
; urban site
; aerosol
; atmosphere
; industrial area
; industry
; model
; particulate matter
; pollutant
; priority journal
; receptor model
; review
; traffic and transport
; urban area
; Article
; controlled study
; principal component analysis
; receptor modelling
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: This review summarizes the different receptor models that have been adopted at industrial and urban sites to apportion the sources of particulate matter (PM) from industries. Industrial processes and those associated with industry (such as transportation) are an important source of airborne PM which includes trace elements, organic and elemental carbon, and PAHs. Industry also emits gaseous pollutants which form secondary aerosol in the atmosphere. Most published studies have employed chemical mass balance (CMB), positive matrix factorization (PMF) and/or principal component analysis (PCA) models as source apportionment tools. These receptor models were mostly applied to fine particulate matter (PM2.5) and PM10 compositional data, particularly the inorganic constituents. Some studies have combined two or more of these receptor models, which provides useful information on the uncertainties associated with different models. Industry has been reported to contribute from 0 to 70% of PM mass at industrial sites. It appears that some studies are unsuccessful in apportioning PM from industry, e.g., unable to distinguish industrial emissions from other sources. A critical evaluation of the literature data also showed that the choice of appropriate tracers for industry, both generically and for specific industries, varies between different PM source apportionment studies. This is not surprising considering the significant difference in source profiles of PM from different types of industry, which may compromise source apportionment of industrial emissions using CMB with non-local source profiles. It may also affect the attribution of industrial emissions in multivariate statistical models (e.g. PMF and PCA). It is concluded that a general classification of the source "industry" is rarely appropriate for PM source apportionment. Indeed, such studies may even need to consider the different processes within a particular industry, such as a steelworks, which emit PM with significantly different chemical signatures. It is suggested that future source apportionment studies should make every effort to measure source profiles of PM from different industrial processes, and where possible, use multiple models in order to more accurately apportion the source emissions from industry. © 2014 Elsevier Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/81307
Appears in Collections: 气候变化事实与影响
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作者单位: Division of Environmental Health and Risk Management, School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
Recommended Citation:
Taiwo A,M,, Harrison R,et al. A review of receptor modelling of industrially emitted particulate matter[J]. Atmospheric Environment,2014-01-01,97