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Compound specific carbon isotopic measurements (δ

Receptor model source apportionment has been facilitated by the availability of particulate matter (PM) speciation networks that measure elements, ions, and carbon fractions, and the availability of effective variance (EV)- and positive matrix factorization (PMF)-chemical mass balance (CMB) solutions to identify and quantify source contributions. However, receptor modeling software is too often applied without a thorough evaluation of the results. Quantitative source contribution estimates derived from these solutions must be challenged as part of a larger modeling and data analysis effort that supplies a “weight of evidence” for the major contributors. PMF-derived source factors should be compared with measured source profiles to identify potential source mixing within a factor and collinearities among factors. EV-CMB solutions should justify the use of measured profiles from other areas as representing those in the study area. Cost-effective methods exist to obtain more relevant source profiles that better represent the potential contributors. As pollution controls reduce primary emissions, elemental source markers and elemental carbon are becoming less useful for distinguishing among source types. Much more information can be obtained from speciation network filters at minimal additional cost to provide more specific markers related to important source types, such as solid fuel combustion for heating and cooking and secondary organic aerosol contributions. Receptor models have been productive for identifying sources, quantifying their contributions, and justifying regulations for residential wood combustion and cooking emission reduction strategies. When used as complements to source-oriented models and emission inventory development, air quality management practices can more accurately allocate pollution control resources.

Biomass burning, the largest global source of elemental carbon (EC) and primary organic carbon (OC), is strongly associated with many subjects of great scientific concern, such as secondary organic aerosol and brown carbon which exert important effects on the environment and on climate in particular. This study investigated the relationships between levoglucosan and other biomass burning tracers (i.e. water soluble potassium and mannosan) based on both ambient samples collected in Beijing and source samples. Compared with North America and Europe, Beijing was characterized by high ambient levoglucosan concentrations and low winter to summer ratios of levoglucosan, indicating significant impact of biomass burning activities throughout the year in Beijing. Comparison of levoglucosan and water soluble potassium (K+) levels suggested that it was acceptable to use K+ as a biomass burning tracer during summer in Beijing, while the contribution of fireworks to K+ could be significant during winter. Moreover, the levoglucosan to K+ ratio was found to be lower during the typical summer period (0.21±0.16) compared with the typical winter period (0.51±0.15). On the other hand, levoglucosan correlated strongly with mannosan (R2=0.97) throughout the winter and the levoglucosan to mannosan ratio averaged 9.49±1.63, whereas levoglucosan and mannosan exhibited relatively weak correlation (R2=0.73) during the typical summer period when the levoglucosan to mannosan ratio averaged 12.65±3.38. Results from PMF model analysis showed that about 50% of the OC and EC in Beijing were associated with biomass burning processes. In addition, a new source-identification method was developed based on the comparison of the levoglucosan to K+ ratio and the levoglucosan to mannosan ratio among different types of biomass. Using this method, the major source of biomass burning aerosol in Beijing was suggested to be the combustion of crop residuals, while the contribution from softwood burning was also non-negligible, especially in winter.