LAUSR

Elemental concentrations of ambient aerosols are commonly sampled over 12-24 h, and the low time resolution puts a great limit on current understanding about the temporal variations and source apportionment based on receptor models. In this work, hourly-resolved concentrations of eighteen elements in PM2.5 at an urban site in Nanjing, a megacity in Yangtze River Delta of east China, were obtained by using a Xact 625 ambient metals monitor from 12/12/2016 to 12/31/2017. The influence of traffic activities was clearly reflected by the spikes of crustal elements (e.g., Fe, Ca, and Si) in the morning rush hour, and the firework burning and sandstorm events during the sampling periods were tracked by sharp enrichment of Ba, K and Fe, Ca, Si, Ti in PM2.5, respectively. To evaluate the advantage of hourly-resolved elements data in identifying impacts from specific emission sources, positive matrix factorization (PMF) analysis was performed with the 1-h data set (PMF1-h) and 23-h averaged data (PMF23-h), respectively. The 4- and 6-factor PMF23-h solutions had similar factor profiles and consistent factor contributions as the corresponding PMF1-h solutions. However, due to the limit in inter-sample variability, PMF analysis with 23-h average data misclassified some major (e.g., K, Fe, Zn, Ca, and Si) and trace (e.g., Pb) elements in factor profiles, resulting in different absolute factor contributions between PMF23-h and PMF1-h solutions. These results suggested the use of high time-resolved data to obtain valid and robust source apportionment results.