An evaluation of source apportionment of fine OC and PM<sub>2.5</sub>by multiple methods: APHH-Beijing campaigns as a case study

Xu, Jingsha; Srivastava, Deepchandra; Wu, Xuefang; Hou, Siqi; Vu, Tuan V.; Liu, Di; Sun, Yele; Vlachou, Athanasia; Moschos, Vaios; Salazar, Gary; Szidat, Sönke; Prévôt, Andrê S. H.; Fu, Pingqing; Harrison, Roy M.; Shi, Zongbo

doi:10.1039/d0fd00095g

Cited by 15 publications

(7 citation statements)

References 54 publications

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“…However, difficulties have been reported when using AMS datasets to separate cooking from other source emissions (Crippa et al, 2014;Mohr et al, 2009;Xu et al, 2015). Therefore, in order to minimise the uncertainties resulting from AMS source apportionment linked to cooking emissions, the development of new source emissions profiles for cooking activities to be used in the CMB method is essential (Dall'Osto et al, 2015;Reyes-Villegas et al, 2018;Xu et al, 2021;Yin et al, 2015). It must be taken into account that the emission profiles obtained with continuous instruments, such as AMS, cannot be used as input to source apportionment models when they are applied to long-term environmental databases based on the collection of PM on filters.…”

Section: Introductionmentioning

confidence: 99%

Fingerprinting and emission rates of particulate organic compounds from typical restaurants in Portugal

Vicente

Rocha

Duarte

et al. 2021

Science of The Total Environment

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Section: Introductionmentioning

confidence: 99%

Fingerprinting and emission rates of particulate organic compounds from typical restaurants in Portugal

Vicente

Rocha

Duarte

et al. 2021

Science of The Total Environment

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“…The time series of CCOC-CMB and CCOC-AMS in Fig. 8 shows a similar trend with a relatively good correlation of R 2 = 0.71, but coal combustion estimated by the CMB model was consistently higher than by AMS-PMF probably because AMS-PMF only resolved the sources of NR-PM 1 , and some coal combustion particles are larger (Xu et al, 2011). The correlation coefficients (R 2 ) of CCOC-AMS with Cl − and NR-Cl − were 0.49 and 0.65, respectively, in the winter data.…”

Section: Comparison With Source Apportionment Results From Ams-pmfmentioning

confidence: 60%

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

Liu

et al. 2021

Atmos. Chem. Phys.

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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.

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“…Six OA factors were identified including fossil-fuel-related OA (FFOA), cooking OA (COA), biomass burning OA (BBOA), oxidized primary OA (OPOA), oxygenated OA (OOA), and aqueous-phase OOA (aqOOA). Detailed information on the processing of HR-AMS data can be found in a related paper during the same campaign (Xu et al, 2019).…”

Section: Ams Data Analysismentioning

confidence: 99%

Persistent residential burning-related primary organic particles during wintertime hazes in North China: insights into their aging and optical changes

Liu

Zhang

et al. 2021

Atmos. Chem. Phys.

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Abstract. Primary organic aerosols (POAs) are a major component of PM2.5 in winter polluted air in the North China Plain (NCP), but our understanding of the atmospheric aging processes of POA particles and the resulting influences on their optical properties is limited. As part of the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-Beijing) program, we collected airborne particles at an urban site (Beijing) and an upwind rural site (Gucheng, Hebei province) in the NCP during 13–27 November 2016 for microscopic analyses. We confirmed that large numbers of light-absorbing spherical POA (i.e., tarball) and irregular POA particles with high viscosity were emitted from domestic coal and biomass burning at the rural site and were further transported to the urban site during regional wintertime hazes. During the heavily polluted period (PM2.5 > 200 µg m−3), more than 60 % of these burning-related POA particles were thickly coated with secondary inorganic aerosols (named as core–shell POA–SIA particles) through the aging process, suggesting that POA particles can provide surfaces for the heterogeneous reactions of SO2 and NOx. As a result, during the heavily polluted period, their average particle-to-core diameter ratios at the rural and urban sites increased to 1.60 and 1.67, respectively. Interestingly, we found that the aging process did not change the morphology and sizes of POA cores, indicating that the burning-related POA particles are quite inert in the atmosphere and can be transported over long distances. Using Mie theory we estimated that the absorption capacity of these POA particles was enhanced by ∼ 1.39 times in the heavily polluted period at the rural and urban sites due to the “lensing effect” of secondary inorganic coatings. We highlight that the lensing effect on burning-related POA particles should be considered in radiative forcing models and authorities should continue to promote clean energy in rural areas to effectively reduce primary emissions.

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An evaluation of source apportionment of fine OC and PM_2.5by multiple methods: APHH-Beijing campaigns as a case study

Abstract: This study aims to critically evaluate the source apportionment of fine particles by multiple receptor modelling approaches, including carbon mass balance modelling of filter-based Radiocarbon (14C) data, Chemical Mass Balance...

Cited by 15 publications

References 54 publications

Fingerprinting and emission rates of particulate organic compounds from typical restaurants in Portugal

Fingerprinting and emission rates of particulate organic compounds from typical restaurants in Portugal

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

Persistent residential burning-related primary organic particles during wintertime hazes in North China: insights into their aging and optical changes

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An evaluation of source apportionment of fine OC and PM2.5by multiple methods: APHH-Beijing campaigns as a case study

Abstract: This study aims to critically evaluate the source apportionment of fine particles by multiple receptor modelling approaches, including carbon mass balance modelling of filter-based Radiocarbon (14C) data, Chemical Mass Balance...

Cited by 15 publications

References 54 publications

Fingerprinting and emission rates of particulate organic compounds from typical restaurants in Portugal

Fingerprinting and emission rates of particulate organic compounds from typical restaurants in Portugal

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

Persistent residential burning-related primary organic particles during wintertime hazes in North China: insights into their aging and optical changes

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An evaluation of source apportionment of fine OC and PM_2.5by multiple methods: APHH-Beijing campaigns as a case study