Source Characterization and Apportionment of PM10 in Panzhihua, China

Yong-Hua Xue,Jian-Hui Wu,Shi-Bao Tang,Tan Zhu,Li Dai,Xiao-Hui Bi,Mei-Fang Chen,Yin-Chang Feng,Xiang Li

doi:10.4209/aaqr.2010.01.0002

Abstract

ABSTRACTA total of 258 particulate matter (PM10) filter samples and 69 source samples applicable to receptor model source apportionment were collected and chemically analyzed from February to August 2007 in Panzhihua, China. Contributive sources were identified and the chemical profiles were reported for resuspended dust, paved and unpaved road dust, coal-fired power plant exhaust, emissions from coking plants and other industrial sources in Panzhihua. All samples were analyzed for 19 elements (Na-Pb), two ions (NO3– and SO42–) and organic and total carbon. Elevated abundances of geological components (Al, Si, Ca and Fe) from fugitive dust materials and elements (Ti, Cr, Mn, Cu and Zn) from special industry plants were found in the profiles. The contributions to the ambient PM10 levels at six sites in three seasons (spring, summer and winter) were estimated using a chemical mass balance receptor model. The concentration of PM10 was high (150 μg/m3) on winter days and low in summer and spring (133 and 129 μg/m3, respectively). Apportionment results indicate that coal combustion ash, iron and steel industry dust, vehicle exhaust and secondary SO42– were major contributors, accounting for about 70% of PM10. More attention should be paid to particulate matter emitted by iron and steel manufacturing facilities in view of high contribution and potentially toxic metals.

Highlights

Particulate matter is generated by various natural processes and human activities, such as soil dust, resuspended dust, coal combustion fly ash, vehicle exhaust, secondary aerosols and particulate matter produced by other industrial processes (Voutsa et al, 2002; Machemer, 2004; Sun et al, 2004; Han et al, 2005)
Chemical Analysis Procedures Inductively coupled plasma analysis (ICP 9000 N+M, Thermo Fisher Scientific Inc., USA) was employed to determine concentrations of Na, Mg, Al, Si, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Cd, Hg and Pb in samples collected on polypropylene-fiber filters and in dust samples
High PM10 concentrations were observed at most sites in Panzhihua, with the spatially averaged annual concentration being 137.5 μg/m3

Summary

Introduction

Particulate matter is generated by various natural processes and human activities, such as soil dust, resuspended dust, coal combustion fly ash, vehicle exhaust, secondary aerosols and particulate matter produced by other industrial processes (Voutsa et al, 2002; Machemer, 2004; Sun et al, 2004; Han et al, 2005). Source apportionment of ambient particulate matter is widely conducted using chemical mass balance (CMB) model. The CMB model infers source contributions by determining the best-fit combination of emission source chemical composition profiles needed to reconstruct the chemical composition of ambient samples (Waston et al, 1991). The CMB source apportionment have been applied in Panzhihua, a highly industrialized city in southwest China, has poor air quality mainly because of the high concentration of PM10 in the atmosphere. The area has suffered from high particulate matter (PM) and heavy metals. Most power plants were equipped with electrostatic precipitators with high retention efficiency (>99.9%), considerable amounts of fine fly ash particles and heavy metals were emitted to the atmosphere because of the high rate of coal combustion and various metallurgical industries. Source contributions to ambient PM10 were estimated using a CMB receptor model

Methods

Results

Conclusion