Pollution Assessment and Source Analysis of Metals in PM2.5 in Haicang District, Xiamen City, China

Abstract

To determine the spatial-temporal distributions and potential sources of metals in PM2.5 and assess health risks from heavy metals, 348 PM2.5 samples were collected in the Haicang District of Xiamen, China from April 2015 to January 2016. Metals (K, Ca, Na, Mg, Al, Zn, Cu, Fe, Ti, As, V, Mn, Ba, Co) in PM2.5 were detected using an X-ray fluorescence analyzer (XRF). Pollution assessment was performed via enrichment factor calculation and health risk assessment. Potential sources were explored using Pearson's correlation coefficient, principal component analysis, and the HYSPLIT Trajectory Model. Results showed that the total concentration of 14 metal elements contributed to 5.4%-10.6% of PM2.5 during the sampling period. The total concentration of metals was higher in spring and winter than those in summer and autumn. The concentrations were higher in the port and the industrial areas than in residential areas and background locations, in agreement with the seasonal and spatial distribution of PM2.5. The frequency of PM2.5 daily concentrations exceeding the Chinese Ambient Air Quality Standards was higher in the port and residential areas in the summer due to operations at the port and the wind direction. Zn concentration was the highest in the industrial area followed by the background location. Meanwhile, the highest concentration of V was observed in the port area; V concentration in the residential area was high in the summer. These variations in Zn and V indicated that the elements emitted in the polluted areas migrated easily to residential and background areas. K concentrations were the highest in winter and As showed a higher rate of exceeding the standard in winter and spring, indicating that activities, such as biomass burning and coal combustion in the winter severely impacted air quality. The enrichment factors of Cu, Zn, As, Co, Na, and Mn varied considerably, from 67 to 8,449. The total risk level for non-carcinogenic heavy metals (Zn, Cu, Mn) was lower than the average level of risk acceptance (1×10-6 a-1) and Mn contributed 74%-88% of the total risk level of Zn, Cu, and Mn. The combined results of the correlation analysis and the principal component analysis revealed that metals in PM2.5 were mainly came from re-suspension of ground dust, motor vehicle emissions, coal combustion, industrial emissions, and heavy oil combustion, with contributions of 34.5%, 12.5%, 10.6%, and 7.8% respectively. The HYSPLIT Trajectory Model showed that Xiamen was affected by the local air mass in spring, autumn, and winter, but not in summer. Moreover, the rise of PM2.5 in spring and winter was attributed to air masses traveling through the Yangtze River Delta.