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.

Highlights

  • Beijing is the capital of China and a hotspot of particulate matter pollution

  • Six factors in non-refractory (NR)-PM1 from the aerosol mass spectrometer (AMS) were identified based on the mass spectra measured in winter at IAP by applying a positive matrix factorization (PMF) model, including coal combustion organic aerosol (OA) (CCOA-AMS), cooking OA (COA-AMS), biomass burning OA (BBOA-AMS), and three secondary factors of oxidized primary OA (OPOA-AMS), less-oxidized OA (LOOOAAMS), and more-oxidized OA (MOOOA-AMS)

  • chemical mass balance (CMB) modeling showed that in winter 2016, the top three primary contributors to PM2.5-organic carbon (OC) were coal combustion (35 %), biomass burning (17 %), and traffic (12 %); these were in the same order with those at the rural site during the same study period: coal combustion (29 %), biomass burning (18 %), and traffic (17 %) (Wu et al, 2020)

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Summary

Introduction

Beijing is the capital of China and a hotspot of particulate matter pollution. It has been experiencing severe PM2.5 (particulate matter with an aerodynamic diameter of ≤ 2.5 μm) pollution in recent decades as a result of rapid urbanization and industrialization and increasing energy consumption (Wang et al, 2009). High PM2.5 pollution from Beijing could have a significant impact on human health (Song et al, 2006a; Li et al, 2013). A better understanding of PM2.5 sources in Beijing is essential as it can provide important scientific evidence to develop measures to control PM2.5 pollution

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