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. Identification of various emission sources and quantification of theircontributions comprise an essential step in formulating scientifically soundpollution control strategies. Most previous studies have been based ontraditional offline filter analysis of aerosol major components (usuallyinorganic ions, elemental carbon – EC, organic carbon – OC, and elements).In this study, source apportionment of PM 2.5 using a positive matrixfactorization (PMF) model was conducted for urban Shanghai in the YangtzeRiver Delta region, China, utilizing a large suite of molecular andelemental tracers, together with water-soluble inorganic ions, OC, and ECfrom 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, industrialemission and tire wear, industrial emission II, residual oil combustion, dust,coal combustion, biomass burning, and cooking). The secondary sourcescontributed 62.5 % of the campaign-average PM 2.5 mass, with thesecondary nitrate factor being the leading contributor. Cooking was a minor contributor (2.8 %) to PM 2.5 mass while a significantcontributor (11.4 %) to the OC mass. Traditional PMF analysis relying onmajor components alone (PMF t ) was unable to resolve threeorganics-dominated sources (i.e., biomass burning, cooking, and SOA sourcefactors). Utilizing organic tracers, the MM-PMF analysis determined thatthese three sources combined accounted for 24.4 % of the total PM 2.5 mass. In PMF t , this significant portion of PM mass was apportioned toother 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 andcomposition. It was shown that under all episodes, secondary nitrate and theSOA factor were two major source contributors to the PM 2.5 pollution.Our work has demonstrated that comprehensive hourly data of molecularmarkers and other source tracers, coupled with MM-PMF, enables examinationof detailed pollution source characteristics, especially organics-dominatedsources, at a timescale suitable for monitoring episodic evolution and withfiner source breakdown.

Source apportionment of PM&lt;sub&gt;2.5&lt;/sub&gt; in Shanghai based on hourly organic molecular markers and other source tracers

Source apportionment of PM<sub>2.5</sub> in Shanghai based on hourly organic molecular markers and other source tracers