Source apportionment of fine organic carbon at an urban site of Beijing using a chemical mass balance model

Abstract

Abstract. Fine particles were sampled from 9 November to 11 December 2016 and 22 May to 24 June 2017 as part of the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-China) field campaigns in urban Beijing, China. Inorganic ions, trace elements, organic carbon (OC), elemental carbon (EC), and organic compounds, including biomarkers, hopanes, polycyclic aromatic hydrocarbons (PAHs), n-alkanes, and fatty acids, were determined for source apportionment in this study. Carbonaceous components contributed on average 47.2 % and 35.2 % of total reconstructed PM2.5 during the winter and summer campaigns, respectively. Secondary inorganic ions (sulfate, nitrate, ammonium; SNA) accounted for 35.0 % and 45.2 % of total PM2.5 in winter and summer. Other components including inorganic ions (K+, Na+, Cl−), geological minerals, and trace metals only contributed 13.2 % and 12.4 % of PM2.5 during the winter and summer campaigns. Fine OC was explained by seven primary sources (industrial and residential coal burning, biomass burning, gasoline and diesel vehicles, cooking, and vegetative detritus) based on a chemical mass balance (CMB) receptor model. It explained an average of 75.7 % and 56.1 % of fine OC in winter and summer, respectively. Other (unexplained) OC was compared with the secondary OC (SOC) estimated by the EC-tracer method, with correlation coefficients (R2) of 0.58 and 0.73 and slopes of 1.16 and 0.80 in winter and summer, respectively. This suggests that the unexplained OC by the CMB model was mostly associated with SOC. PM2.5 apportioned by the CMB model showed that the SNA and secondary organic matter were the two highest contributors to PM2.5. After these, coal combustion and biomass burning were also significant sources of PM2.5 in winter. The CMB results were also compared with results from the positive matrix factorization (PMF) analysis of co-located aerosol mass spectrometer (AMS) data. The CMB model was found to resolve more primary organic aerosol (OA) sources than AMS-PMF, but the latter could apportion secondary OA sources. The AMS-PMF results for major components, such as coal combustion OC and oxidized OC, correlated well with the results from the CMB model. However, discrepancies and poor agreements were found for other OC sources, such as biomass burning and cooking, some of which were not identified in AMS-PMF factors.

Insight into PM<sub>2.5</sub> sources by applying positive matrix factorization (PMF) at urban and rural sites of Beijing

“…Real-time composition of non-refractory PM 1 particles (NR-PM 1 ) was measured using an Aerodyne aerosol mass spectrometer (AMS) at a time resolution of 2.5 min. The operational details on the AMS measurements have been given elsewhere (Xu et al, 2019). In addition, the measurements of gaseous species such as O 3 , CO, NO, NO 2 , and SO 2 were performed using gas analysers.…”

“…In addition, attempts to improve the PMF results by varying the input species and by analysing data for the IAP and PG sites separately did not offer any advantage. (Sun et al, 2016), 1.38 for cooking organic carbon, 1.58 for biomass burning organic carbon (Xu et al, 2019), and 1.78 for the oxygenated fraction (Huang et al, 2010), and used to evaluate the OC concentrations of relevant OA factors.…”

Source apportionment of carbonaceous aerosols in Beijing with radiocarbon and organic tracers: insight into the differences between urban and rural sites

“…Details of the selection of the organic marker species can be found in Yin et al (2010Yin et al ( , 2015. Experimental details on the AMS and ACSM-PMF method can be found elsewhere (Ng et al, 2011;Sun et al, 2016;Xu et al, 2019). The ACSM data were analysed for the mass concentrations and size distributions of nonrefractory submicron aerosol (NR-PM 1 ) species using the high-resolution data analysis software package PIKA (Sun et al, 2020).…”

“…Positive matrix factorization was performed on high-resolution mass spectra of V mode and W mode to retrieve potential organic aerosol (OA) factors from different sources (Paatero and Tapper, 1994;Ulbrich et al, 2009). The organic matter / organic carbon (OM / OC) factor used for cooking OA (COA) is 1.38 (Xu et al, 2019).…”

Assessment of strict autumn-winter emission controls on air quality in the Beijing-Tianjin-Hebei region

“…The model overestimates total PM2.5 by 10% at the urban site and 34% at the rural site. Components are measured with a semicontinuous analyzer for OC and BC (Han et al, 2014;Kondo et al, 2006) and ion chromatography following particle collection with a Partisol for sulfate, nitrate, and ammonium (Taiwo et al, 2014;Xu et al, 2021). OC is compared instead of organic aerosol (OA), due to uncertainties in conversion of OC to OA (Xing et al, 2013).…”