"Source Characterization and Apportionment of PM10, PM2.5 and PM0.1 by Using Positive Matrix Factorization"

ABSTRACTAmbient Particulate Matters (PM10, PM2.5 and PM0.1) were investigated at Shinjung station in New Taipei City, Taiwan. Samples were collected simultaneously using a dichotomous sampler (Andersen Model SA-241) and a MOUDI (MSP Model 110) over a 24-h period from May 2011 to November 2011 at Shinjung station. Samples were analyzed for metallic trace elements using ion coupled plasma mass spectroscopy (ICP-MS) and ionic compounds by ion chromatography (IC). The average concentrations of PM10, PM2.5 and PM0.1 were found to be 39.45 ± 11.58, 21.82 ± 7.50 and 1.42 ± 0.56 μg/m3, respectively. Based on the chemical information, positive matrix factorization (PMF) was used to identify PM sources. A total of five source types were identified, soil dust, vehicle emissions, sea salt, industrial emissions and secondary aerosols, and their contributions were estimated using PMF. The crustal enrichment factors (EF) were calculated using Al as a reference for the trace metal species to identify the sources. Conditional probability functions (CPF) were computed using wind profiles and factor contributions. The results of CPF analysis were used to identify local point sources. The results suggest a competitive relationship between anthropogenic and natural source processes over the monitoring station.

[1]  S. Taylor,et al.  The continental crust: Its composition and evolution , 1985 .

[2]  J. Galloway,et al.  Heterogeneous sulfur conversion in sea-salt aerosol particles: the role of aerosol water content and size distribution , 1991 .

[3]  Kenneth L. Rubow,et al.  A Microorifice Uniform Deposit Impactor (MOUDI): Description, Calibration, and Use , 1991 .

[4]  P. Paatero,et al.  Analysis of different modes of factor analysis as least squares fit problems , 1993 .

[5]  P. Paatero,et al.  Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values† , 1994 .

[6]  P. Paatero.  Least squares formulation of robust non-negative factor analysis , 1997 .

[7]  Ronald E. Hester,et al.  Receptor modeling for air quality management , 1997 .

[8]  P. Paatero,et al.  Atmospheric aerosol over Alaska: 2. Elemental composition and sources , 1998 .

[9]  P. Hopke,et al.  Atmospheric aerosol over Alaska: 1. Spatial and seasonal variability , 1998 .

[10]  Philip K. Hopke,et al.  A GUIDE TO POSITIVE MATRIX FACTORIZATION , 2000 .

[11]  Paul J Lioy,et al.  Identification of Sources Contributing to Mid-Atlantic Regional Aerosol , 2002, Journal of the Air & Waste Management Association.

[12]  P. Hopke,et al.  Source Identification of Atlanta Aerosol by Positive Matrix Factorization , 2003, Journal of the Air & Waste Management Association.

[13]  Lianne Sheppard,et al.  Source identification of PM2.5 in an arid Northwest U.S. City by positive matrix factorization , 2003 .

[14]  Philip K. Hopke,et al.  Investigation of sources of atmospheric aerosol at urban and semi-urban areas in Bangladesh , 2004 .

[15]  Philip K Hopke,et al.  Source Apportionment of Fine Particles in Washington, DC, Utilizing Temperature-Resolved Carbon Fractions , 2004, Journal of the Air & Waste Management Association.

[16]  J. Chow,et al.  Spatial and seasonal variations of atmospheric organic carbon and elemental carbon in Pearl River Delta Region, China , 2004 .

[17]  Kenneth L. Demerjian,et al.  Sources of fine particle composition in New York city , 2004 .

[18]  J. Schauer,et al.  Emissions of metals associated with motor vehicle roadways. , 2005, Environmental science & technology.

[19]  Mohammed Khaliquzzaman,et al.  Investigation of Sources of Atmospheric Aerosol at a Hot Spot Area in Dhaka, Bangladesh , 2005, Journal of the Air & Waste Management Association.

[20]  Receptor modeling of source contributions to atmospheric hydrocarbons in urban Kaohsiung, Taiwan , 2005 .

[21]  J. Harkema,et al.  Source identification of ambient PM2.5 during summer inhalation exposure studies in Detroit, MI , 2006 .

[22]  Chien-Lung Chen,et al.  Atmospheric aerosol composition and source apportionments to aerosol in southern Taiwan , 2006 .

[23]  Philip K. Hopke,et al.  Apportioning sources of PM2.5 in St. Louis, MO using speciation trends network data , 2006 .

[24]  Philip K. Hopke,et al.  Source apportionment of Baltimore aerosol from combined size distribution and chemical composition data , 2006 .

[25]  E. Furusjö,et al.  PM(10) source characterization at urban and highway roadside locations. , 2007, The Science of the total environment.

[26]  Peter A. Scheff,et al.  Fine particulate source apportionment using data from the USEPA speciation trends network in Chicago, Illinois: Comparison of two source apportionment models , 2007 .

[27]  Vincent R. Gray.  Climate Change 2007: The Physical Science Basis Summary for Policymakers , 2007 .

[28]  P. Hopke,et al.  Source apportionment of fine particles utilizing partially speciated carbonaceous aerosol data at two rural locations in New York State , 2007 .

[29]  Steven G. Brown,et al.  Analysis and Apportionment of Organic Carbon and Fine Particulate Matter Sources at Multiple Sites in the Midwestern United States , 2007, Journal of the Air & Waste Management Association.

[30]  Myoungwoo Kim,et al.  Source apportionment of fine particulate matter (PM2.5) at a rural Ohio River Valley site , 2007 .

[31]  Chang-Fu Wu,et al.  Source apportionment of PM(2.5) and selected hazardous air pollutants in Seattle. , 2007, The Science of the total environment.

[32]  Philip K. Hopke,et al.  Estimation of source apportionment and potential source locations of PM2.5 at a west coastal IMPROVE site , 2007 .

[33]  G. Golding,et al.  SOURCE APPORTIONMENT OF AMBIENT VOLATILE ORGANIC COMPOUNDS IN MAJOR CITIES IN AUSTRALIA BY POSITIVE MATRIX , 2008 .

[34]  F. Lucarelli,et al.  Quantification of Saharan and local dust impact in an arid Mediterranean area by the positive matrix factorization (PMF) technique , 2008 .

[35]  J. Schauer,et al.  Daily Variations in Sources of Carbonaceous Aerosol in Lahore, Pakistan during a High Pollution Spring Episode , 2008 .

[36]  Kang-Shin Chen,et al.  Characteristics and Receptor Modeling of Atmospheric PM2.5 at Urban and Rural Sites in Pingtung, Taiwan , 2008 .

[37]  P. Lestari,et al.  Source apportionment of particulate matter at urban mixed site in Indonesia using PMF , 2009 .

[38]  Godwin A. Ayoko,et al.  Receptor modeling of source apportionment of Hong Kong aerosols and the implication of urban and regional contribution , 2009 .

[39]  Monica Pandolfi,et al.  Quantifying road dust resuspension in urban environment by Multilinear Engine: A comparison with PMF2 , 2009 .

[40]  P. Siskos,et al.  Assessment of source apportionment by Positive Matrix Factorization analysis on fine and coarse urban aerosol size fractions , 2009 .

[41]  G. Fang,et al.  Atmospheric particulate (PM10 and PM2.5) mass concentration and seasonal variation study in the Taiwan area during 2000–2008 , 2010 .

[42]  S. Masunaga,et al.  Quantifying the sources of hazardous elements of suspended particulate matter aerosol collected in Yokohama, Japan , 2010 .

[43]  Chang-Chuan Chan,et al.  Temporal characteristics from continuous measurements of PM2.5 and speciation at the Taipei Aerosol Supersite from 2002 to 2008 , 2010 .

[44]  Zhi Ning,et al.  Atmospheric Processes Influencing Aerosols Generated by Combustion and the Inference of Their Impact on Public Exposure: A Review , 2010 .

[45]  Gary W. Fuller,et al.  Urban Ambient Particle Metrics and Health: A Time-series Analysis , 2010, Epidemiology.

[46]  Yinchang Feng,et al.  Application of a Combined Model to Study the Source Apportionment of PM10 in Taiyuan, China , 2010 .

[47]  P. Tekasakul,et al.  Workplace Environment and Personal Exposure of PM and PAHs to Workers in Natural Rubber Sheet Factories Contaminated by Wood Burning Smoke , 2010 .

[48]  Yong-Sam Chung,et al.  Source apportionment of PM10 at a small industrial area using Positive Matrix Factorization , 2010 .

[49]  Chuen-Jinn Tsai,et al.  Chemical Mass Closure and Chemical Characteristics of Ambient Ultrafine Particles and other PM Fractions , 2010 .

[50]  C. Kang,et al.  Long-term trend of aerosol composition and direct radiative forcing due to aerosols over Gosan: TSP, PM10, and PM2.5 data between 1992 and 2008 , 2011 .

[51]  Ernie Weijers,et al.  Contrast in air pollution components between major streets and background locations: Particulate matter mass, black carbon, elemental composition, nitrogen oxide and ultrafine particle number , 2011 .

[52]  Gufran Beig,et al.  Emissions inventory of anthropogenic PM2.5 and PM10 in Delhi during Commonwealth Games 2010 , 2011 .

[53]  Atar Singh Pipal,et al.  Characterization and morphological analysis of airborne PM2.5 and PM10 in Agra located in north central India , 2011 .

[54]  I. Barmpadimos,et al.  The weekly cycle of ambient concentrations and traffic emissions of coarse (PM10–PM2.5) atmospheric particles , 2011 .

[55]  L. Neas,et al.  Bayesian hierarchical modeling of cardiac response to particulate matter exposure , 2011, Journal of Exposure Science and Environmental Epidemiology.

[56]  Y. Chan,et al.  Using multiple type composition data and wind data in PMF analysis to apportion and locate sources of air pollutants , 2011 .

[57]  Zong-shuang Wang,et al.  Potential Source Analysis for PM10 and PM2.5 in Autumn in a Northern City in China , 2012 .

[58]  B. Cárdenas,et al.  Chemical composition of PM2.5 particles in Salamanca, Guanajuato Mexico: Source apportionment with receptor models , 2012 .

[59]  Corinne Le Quéré,et al.  Climate Change 2013: The Physical Science Basis , 2013 .