Knowledge of the relative abundance of primary organic aerosol (POA) and secondary organic aerosol (SOA) forms an important scientific basis for formulating particulate matter (PM) control policies. Taking advantage of a comprehensive chemical composition data set of PM2.5 including both POA and SOA tracers (most notably, SOA tracers of a few biogenic voltaic organic compound precursors), we investigate the impact of inclusion of SOA tracers on the source apportionment of organic carbon (OC) and PM2.5 in the Pearl River Delta region of China using positive matrix factorization (PMF). In PMF runs incorporating SOA tracers (PMFw), ten PMF factors were resolved including four secondary factors: (1) SOA I (α-pinene, β-caryophyllene, and naphthalene-derived SOA), (2) SOA II (isoprene-derived SOA), (3) a secondary sulfate factor, and (4) a secondary nitrate factor. In PMF tests without SOA tracers (PMFwo), the SOA I and SOA II factors could not be extracted, but the remaining eight source factors were resolved. Among the eight common source factors, the industrial emission factor, identified by high loadings of Zn and Pb, showed the largest variations between PMFw and PMFwo solutions. The source contributions of SOA I and SOA II resolved in PMFw were largely shifted to the industry emission source in PMFwo. Secondary organic carbon (SOC) summed from the four secondary factors in PMFw contributed ∼40% (4.47 μgC/m3), and the SOC estimate by PMFwo (3.51 μgC/m3) was 21% lower due to the inability to extract SOA I and SOA II. Secondary PM2.5 by PMFwo was 6% lower than that by PMFw (23.7 vs 25.2 μg/m3). The PMFw results indicated that SOC from specific precursors may have different formation pathways than secondary sulfate and nitrate formation processes, and their source contributions could not be properly resolved without the indicative tracers included in PMF. This study demonstrates the utility of biogenic SOA tracers in resolving isoprene-derived SOA and highlights the need for more SOA tracers, especially those specific to anthropogenic precursors, in improving the source apportionment for those broad OA sources such as industrial emissions.

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A group of nonpolar organic compounds (NPOCs) in five compound classes including alkanes, polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes, and 1,3,5‐triphenylbenzene were quantified in samples of particulate matter of aerodynamic diameter less than 2.5 μm collected at four sites in the Pearl River Delta (PRD) region, China, over a 2 year period from 2011 to 2012. The four sites include industrial (Nanhai), urban (Guangzhou), urban outskirt (Dongguan), and suburban (Nansha) locations. Some NPOCs are uniquely emitted from particular combustion sources and thereby serving as markers in source apportionment. Based on this multiyear and multisite NPOC data set, spatial and seasonal variations, correlation analysis, and ratio‐ratio plots were used to investigate the source information and degradation of NPOC tracers. In summer, NPOCs showed distinct local emission characteristics, with urban sites having much higher concentrations than suburban sites. In winter, regional transport was an important influence on NPOC levels, driving up concentrations at all sampling sites and diminishing an urban‐suburban spatial gradient. The lighter NPOCs exhibited more prominent seasonal variations. Such spatiotemporal features suggest that their particle‐phase abundance is more influenced by temperature, which is a critical factor in controlling the extent of semivolatile organics partitioned into the aerosol phase. The heavier NPOCs, especially PAHs, showed negligible correlation among the four sites, suggesting more influence from local emissions. Ratio‐ratio plots indicate photodegradation and mixing of various sources for the NPOCs in the PRD. A positive matrix factorization (PMF) analysis of this large NPOC data set suggests that heavier NPOCs are more suitable source indicators than lighter NPOCs. Incorporating particle‐phase light NPOC concentrations in PMF produces a separate factor, which primarily contains those light NPOCs and likely is not a source factor. Total NPOC concentrations predicted using Pankow partitioning theory were explored as PMF inputs; however, the PMF solution is not able to fully explain the input total concentrations or to give reasonable source profiles, suggesting the need for reliable gas‐phase NPOC data before their use in source apportionment studies. In addition, degradation of NPOCs needs to be considered to avoid misinterpretation of PMF source apportionment results.