Speciation of selected redox-active and toxic metals in fine particulate matter (PM2.5): occurrence, seasonal variations, and implication of PM2.5-associated oxidative potential

Epidemiologic studies have shown the relationship between PM2.5-bounded transition metals and the adverse health effects of short-term and long-term exposure to fine particulate matter (PM2.5). Metals, such as iron (Fe), copper (Cu), and manganese (Mn), are redox-active and are key drivers of PM2.5-induced oxidative stress. Moreover, they may interact synergistically/antagonistically with organic species in reactive oxygen species (ROS) production. Arsenic (As), on the other hand, is carcinogenic and has received wide concerns due to its inhalation health risks. The bioaccessibility, toxicity, and redox-activity of metals are primarily determined by their oxidation states and chemical forms in PM2.5. However, given their trace amounts and chemical transformations in the atmosphere, limited studies have been carried out on the speciation of metals in PM2.5 samples, especially for those redox-active ones. Therefore, in this project, we plan to develop analytical techniques to separate and determine the individual species of Fe, Cu, Mn, and As with high sensitivity and specificity using high-performance liquid chromatography coupled to inductively coupled plasma-mass spectrometry (HPLC-ICP-MS). We will investigate the concentration levels and solubility profiles of FeII, FeIII, MnII, MnIII, CuI, CuII, AsIII, AsV, and three organoarsenic species in the whole acid-digested and water-soluble PM2.5 extracts of 24 PM2.5 samples collected in Hong Kong during a 1-yr period. We will also use ICP-MS to determine the amount of total Fe, Mn, Cu, As, and other common transition metals in these two kinds of PM2.5 extracts. The solubility profiles of individual transition metals and the speciation profiles of Fe, Mn, Cu, and As in different seasons and under the influence of varying air mass origins will be examined. Water-soluble PM2.5 associated oxidative potential will be measured. Both Pearson's R analysis and multiple linear regression analysis will be performed to identify the metals species that are significantly related to PM2.5-associated oxidative potential and estimate their contributions. This project will be the first comprehensive study on the speciation of PM2.5-bound Fe, Cu, Mn, and As in Hong Kong. Finding from this study will expand the scientific database of the abundance and solubility of the individual metal species of PM2.5-bound Fe, Cu, Mn, and As and their roles in inducing PM2.5-associated oxidative potential. This information is critical for the mitigation of PM2.5 pollution and the formation of health risk-oriented PM2.5 control policies, which may help better protection of public health from PM2.5 pollution.