DOI: 10.1016/j.atmosenv.2017.10.063
Scopus记录号: 2-s2.0-85034626656
论文题名: Understanding the PM2.5 imbalance between a far and near-road location: Results of high temporal frequency source apportionment and parameterization of black carbon
作者: Sofowote U ; M ; , Healy R ; M ; , Su Y ; , Debosz J ; , Noble M ; , Munoz A ; , Jeong C ; -H ; , Wang J ; M ; , Hilker N ; , Evans G ; J ; , Hopke P ; K
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2018
卷: 173 起始页码: 277
结束页码: 288
语种: 英语
英文关键词: Aerosol
; Black carbon
; Machine learning
; Multi-time resolution
; Multilinear engine (ME)
; Nonlinear modelling
; PM2.5
; Receptor modelling
; Source apportionment
Scopus关键词: Aerosols
; Learning systems
; Nonlinear programming
; Optimization
; Roads and streets
; Roadsides
; Transportation
; Black carbon
; Multilinear engine (ME)
; Non-linear modelling
; PM2.5
; Receptor modelling
; Source apportionment
; Time resolution
; Particles (particulate matter)
; black carbon
; diesel fuel
; black carbon
; concentration (composition)
; machine learning
; nonlinearity
; numerical method
; optimization
; parameterization
; particulate matter
; resolution
; road
; road traffic
; roadside environment
; source apportionment
; speciation (chemistry)
; air pollution
; algorithm
; Article
; concentration (parameters)
; environmental policy
; meteorology
; motor vehicle
; particle size
; particulate matter
; priority journal
; traffic
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 differences in PM2.5 concentrations between two relatively close stations, one situated near a major highway and the other much more distant were used to develop a protocol for determining the impact of highway traffic on particulate matter concentrations at the roadside. The roadside station was <15 m away from the edge of a major highway while the other was located ∼170 m away. The roadside station contains a suite of continuous instrumentation capable of near-real-time speciation of PM2.5. The particulate matter difference, formally termed the PM2.5 imbalance was arbitrarily defined as a case wherein |Near-road PM2.5 - Far from road PM2.5|/Near-road PM2.5 ≳50%. Of interest was the variation of multi-time factors based on ME2 analyses of the speciation data from the roadside station during these imbalance events. Of the 7 mass-contributing ME2 factors, a black carbon factor was determined to be the major cause of the PM2.5 imbalance and was especially dominant for the case when PM2.5 concentrations at the roadside station were greater than the farther-station PM2.5. The black carbon concentrations observed during these specific events were further regressed against other traffic-related and meteorological parameters with two nonlinear optimization algorithms (generalized reduced gradient and rules ensemble) in our attempts to model any potential relationships. It was observed that the traffic counts of heavy duty vehicles (predominantly diesel-powered) dominated the relationship with black carbon while contributions from light duty vehicles were negligible during these [PM2.5]Roadside > [PM2.5]Farther events at the roadside station. This work details the most critical ways that highway traffic can contribute to local ambient PM2.5 concentrations that commuters are exposed to and will be important in informing policies and strategies for particulate matter pollution reduction. © 2017 Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/83105
Appears in Collections: 气候变化事实与影响
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作者单位: Environmental Monitoring and Reporting Branch, Ontario Ministry of the Environment and Climate Change, Toronto, Canada; Southern Ontario Centre for Atmospheric Aerosol Research, University of Toronto, Toronto, Canada; Center for Air Resources Engineering and Science, Clarkson University, Potsdam, NY, United States; Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY, United States
Recommended Citation:
Sofowote U,M,, Healy R,et al. Understanding the PM2.5 imbalance between a far and near-road location: Results of high temporal frequency source apportionment and parameterization of black carbon[J]. Atmospheric Environment,2018-01-01,173