Abstract. Identification of various emission sources and quantification of their
contributions comprise an essential step in formulating scientifically sound
pollution control strategies. Most previous studies have been based on
traditional offline filter analysis of aerosol major components (usually
inorganic ions, elemental carbon – EC, organic carbon – OC, and elements).
In this study, source apportionment of PM2.5 using a positive matrix
factorization (PMF) model was conducted for urban Shanghai in the Yangtze
River Delta region, China, utilizing a large suite of molecular and
elemental tracers, together with water-soluble inorganic ions, OC, and EC
from measurements conducted at two sites from 9 November to 3 December 2018. The PMF analysis with inclusion of molecular makers (i.e., MM-PMF)
identified 11 pollution sources, including 3 secondary-source factors
(i.e., secondary sulfate; secondary nitrate; and secondary organic aerosol, SOA, factors) and 8 primary sources (i.e., vehicle exhaust, industrial
emission and tire wear, industrial emission II, residual oil combustion, dust,
coal combustion, biomass burning, and cooking). The secondary sources
contributed 62.5 % of the campaign-average PM2.5 mass, with the
secondary nitrate factor being the leading contributor. Cooking was a minor contributor (2.8 %) to PM2.5 mass while a significant
contributor (11.4 %) to the OC mass. Traditional PMF analysis relying on
major components alone (PMFt) was unable to resolve three
organics-dominated sources (i.e., biomass burning, cooking, and SOA source
factors). Utilizing organic tracers, the MM-PMF analysis determined that
these three sources combined accounted for 24.4 % of the total PM2.5
mass. In PMFt, this significant portion of PM mass was apportioned to
other sources and thereby was notably biasing the source apportionment outcome.
Backward trajectory and episodic analysis were performed on the MM-PMF-resolved source factors to examine the variations in source origins and
composition. It was shown that under all episodes, secondary nitrate and the
SOA factor were two major source contributors to the PM2.5 pollution.
Our work has demonstrated that comprehensive hourly data of molecular
markers and other source tracers, coupled with MM-PMF, enables examination
of detailed pollution source characteristics, especially organics-dominated
sources, at a timescale suitable for monitoring episodic evolution and with
finer source breakdown.