资源环境科技发展态势分析平台

A single particle source analysis was conducted for particulate matter and oxalic acid using a single particle aerosol mass spectrometer during a typical biomass burning period in Tianjin, China. The adaptive resonance theory 2 neural network algorithm was applied to analyze mass spectra data and generate 20 particle clusters. Size-resolved time series of the particle classes were put into an advanced three-way model (ABB, multi-size three-way model) for source apportionment. Seven sources were identified, including crustal dust, biomass burning, fossil fuel combustion, secondary organic, secondary nitrate and secondary sulfate. Oxalic acid containing particles accounted for 1.4% of the total detected particles during the overall sampling period, and the fraction increased to 2.6% during the biomass burning period. Oxalic acid was predominantly observed in the Na-K-EC, EC, EC-K, EC-aged, K, Levoglucosan and Fe particle classes. The mixing fraction of oxalic acid in these particle types, and their diurnal variation and size distribution patterns are related to different formation mechanisms. Source contributions to oxalic acid were apportioned, and secondary sulfate (49%), biomass burning (25%), vehicle exhaust (17%), and secondary organic sources (8%) may have contributed to the amount of oxalic acid-containing particles. The contribution of secondary sulfate sources follows the O-3 concentration during the sampling period. This is likely because strong photochemical oxidation activity during the sampling period produces more oxalic acid precursors from Volatile organic compounds. Biomass burning also clearly contributed the number of oxalic acid particles, because precursors emitted by biomass burning can be quickly oxidized into oxalic acid, and more oxalic acid was formed during transportation. Fe particles may also play important role in oxalic acid deposition.