Project No: 16305418

Title: Rapid source apportionment of atmospheric particulate matter using online measurement data of molecular markers and elemental tracers

PI: Prof. Yu, Jianzhen    CI: Dr. Li, Li


Accurate identification of fine particulate matter (PM2.5) primary and secondary sources and quantification of their contributions shapes the scientific basis underlying pollution control policies. Traditional measurement-based source apportionment often relies on daily or sub-daily time series of molecular markers and elemental tracers, coupled with receptor modeling using positive matrix factorization (PMF). However, the off-line nature of filter-based measurements severely limits its utility in addressing episodic pollution events and in developing timely response. The bottleneck for a rapid source analysis is a lack of highly time-resolved data of various source-specific tracers. In this project, this data constrain will be resolved by augmenting existing air quality research supersites with an online X-Ray fluorescence spectrometer for elements and an in-situ thermal desorption aerosol gas chromatography-mass spectrometry analyzer for organic molecular source markers. We will first conduct field campaigns to collect collocated hourly measurements of individual PM2.5 components in months of high pollution borne from photochemical activity or poor dispersion conditions. The online data availability and high-time resolution nature open up an opportunity for rapid source apportionment that is not possible with daily/sub-daily measurements. The second phase of the project will focus on developing rapid source apportionment capability using the array of online molecular and elemental tracer data. In principle, a rapid source diagnosis of an episodic event could be obtained by incorporating the episode measurements into a dataset that has previously been analyzed for source contributions using PMF and subsequently re-running PMF with the expanded dataset. We will characterize stability performance of source apportionment results to achieve the aim of establishing a robust procedure for rapid source apportionment under different pollution conditions. The results from this project will provide policy makers with valuable information to enable a faster response to pollution events and to formulate more timely PM emission control strategies.