Determination of Source Contributions to Ambient PM_2.5in Kaohsiung, Taiwan, Using a Receptor Model

Abstract

Ambient particulates of PM 2.5 were sampled at three sites in Kaohsiung, Taiwan, during February and March 1999. In addition, resuspended PM 2.5 collected from traffic tunnels, paved roads, fly ash of a municipal solid waste (MSW) incinerator, and seawater was obtained. All the samples were analyzed for twenty constituents, including watersoluble ions, organic carbon (OC), elemental carbon (EC), and metallic elements. In conjunction with local source profiles and the source profiles in the model library SPECIATE EPA, the receptor model based on chemical mass balance (CMB) was then applied to determine the source contributions to ambient PM 2.5 .The mean concentration of ambient PM 2.5 was 42.69-53.68 µg/m 3 for the sampling period. The abundant species in ambient PM 2.5 in the mass fraction for three sites were OC (12.7-14.2%), SO 4 2-(12.8-15.1%), NO 3 -(8.1-10.3%), NH 4 + (6.7-7.5%), and EC (5.3-8.5%). Results of CMB modeling show that major pollution sources for IMPLICATIONS It is of great importance to identify air pollution sources in the development of air quality control strategies. For about a decade in Taiwan, more efforts have been put into regulation and control of stationary sources. In order to improve the air quality in a serious and cost-effective manner, other sources, such as vehicle emissions and photochemical aerosols, must be reviewed and quantified. The CMB receptor model was used to assess the potential source contributions to ambient PM 2.5 , which is believed to be responsible for visibility deterioration in Kaohsiung. The measurements in this study show that the abundant species in ambient PM 2.5 are OC, secondary aerosols (containing SO 4 2-, NO 3 -, and NH 4 + ), and EC. Assessment with the CMB model suggests that mobile sources should be regulated and controlled more thoroughly in this area than they were previously. ambient PM 2.5 are traffic exhaust (18-54%), secondary aerosols (30-41% from SO 4 2-and NO 3 -

Identification of PM2.5 Sources Affecting a Semi-Arid Coastal Region Using a Chemical Mass Balance Model

“…The correlation coefficients between ammonium vs. sulfur and ammonium vs. sulfates at CAMS 314 were observed to be 0.88 and 0.72, indicating slightly lower influence of local sources such as petrochemical refineries and industrial manufacturing. Similar results were reported in a study conducted by Chen et al (2001). Being located in an industrialized urban area, higher correlation coefficient (0.98) between sulfur and sulfates was observed at CAMS 635 indicating stronger influence of local anthropogenic sources.…”

Influence of environmental conditions on carbonaceous particle concentrations within New Zealand

“…This study investigated the anthropogenic combustion sources and determined the variables that influenced the measured concentrations in the New Zealand environment. Combustion processes predominately produce carbonaceous particulate matter o2.5 mm in diameter (Amato et al, 2009;Chan et al, 1997Chan et al, , 2000Chen, Lin, & Chou, 2001;Davy, 2007;Davy, Markwitz, & Weatherburn, 2007;Fine, Cass, & Simoneit, 2002;Schauer et al, 2006). Therefore the source apportionment results for PM 2.5 presented in Table 1 are representative of the anthropogenic carbonaceous particle contributions to PM 10 .…”

Comparison and Evaluation of Methods to Apportion Ambient PM2.5 to Residential Wood Heating in Fairbanks, AK

“…Over the past several decades the Chemical Mass Balance (CMB) model has been commonly employed for comprehensive source apportionment (Vega et al, 1997;Paode et al, 1999;Chen et al, 2001;Ward, 2001;Li et al, 2003;Ward and Smith, 2005;Olson et al, 2008;Yin et al, 2010;Ward and Lange, 2010;Larson et al, 2011;Herich et al, 2014). CMB requires comprehensive chemical analysis of at least as many constituents of ambient PM 2.5 as there are potential sources, as well as reliable source profiles including the same constituents in PM 2.5 from all potential sources.…”