Sensitivity of a Chemical Mass Balance model for PM2.5 to source profiles for differing styles of cooking

Abdullahi, Karimatu Lami; Delgado-Saborit, Juana María; Harrison, Roy M.

doi:10.1016/j.atmosenv.2018.01.046

Cited by 16 publications

(6 citation statements)

References 25 publications

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“…Although poor agreement of OC ck was found between the EG method and the CMB model, the former correlated better with results from the application of PMF to AMS/ACSM data (slope = 0.74, R 2 = 0.61). It has previously been shown that discrepancies exist between the CMB and PMF model (Reyes-Villegas, et al, 2018;Yin et al, 2015), whereas CMB may not be sensitive enough to the source profile of cooking aerosols (Abdullahi et al, 2018). Overall, the EG method resolves primary and secondary sources of OC well.…”

Section: Cmb Resultsmentioning

confidence: 90%

“…The method of 14 C measurement of carbonaceous aerosols has been described elsewhere (Agrios et al, 2015;Levin et al, 2010;Szidat et al, 2014;Vlachou et al, 2018;Zhang et al, 2012Zhang et al, , 2016Zotter et al, 2014). The 14 C of TC and WINSTC was measured using a one-step protocol under pure O 2 (99.9995 %) at 760 • C for 400 s (Vlachou et al, 2018) using an elemental analyser coupled with the accelerator mass spectrometer Mini Carbon Dating System (MICADAS) at the Laboratory for the Analysis of Radiocarbon (LARA; University of Bern) (Zhang et al, 2012;Szidat et al, 2014).…”

Section: Radiocarbon ( 14 C) Analysismentioning

confidence: 99%

“…The 14 C of TC and WINSTC was measured using a one-step protocol under pure O 2 (99.9995 %) at 760 • C for 400 s (Vlachou et al, 2018) using an elemental analyser coupled with the accelerator mass spectrometer Mini Carbon Dating System (MICADAS) at the Laboratory for the Analysis of Radiocarbon (LARA; University of Bern) (Zhang et al, 2012;Szidat et al, 2014). The EC fraction was separated by an OC/EC analyser (Model 4L, Sunset Laboratory, USA) with the use of the Swiss_4S protocol (Zhang et al, 2012), which was coupled online with the MICADAS (Agrios et al, 2015). Each filter sample was extracted with water before the measurements to minimize the charring effect during the separation of EC from the WINSOC.…”

Section: Radiocarbon ( 14 C) Analysismentioning

confidence: 99%

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

Hou

Liu

et al. 2021

Atmos. Chem. Phys.

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Abstract. Carbonaceous aerosol is a dominant component of fine particles in Beijing. However, it is challenging to apportion its sources. Here, we applied a newly developed method which combined radiocarbon (14C) with organic tracers to apportion the sources of fine carbonaceous particles at an urban (IAP) and a rural (PG) site of Beijing. PM2.5 filter samples (24 h) were collected at both sites from 10 November to 11 December 2016 and from 22 May to 24 June 2017. 14C was determined in 25 aerosol samples (13 at IAP and 12 at PG) representing low pollution to haze conditions. Biomass burning tracers (levoglucosan, mannosan, and galactosan) in the samples were also determined using gas chromatography–mass spectrometry (GC-MS). Higher contributions of fossil-derived OC (OCf) were found at the urban site. The OCf / OC ratio decreased in the summer samples (IAP: 67.8 ± 4.0 % in winter and 54.2 ± 11.7 % in summer; PG: 59.3 ± 5.7 % in winter and 50.0 ± 9.0 % in summer) due to less consumption of coal in the warm season. A novel extended Gelencsér (EG) method incorporating the 14C and organic tracer data was developed to estimate the fossil and non-fossil sources of primary and secondary OC (POC and SOC). It showed that fossil-derived POC was the largest contributor to OC (35.8 ± 10.5 % and 34.1 ± 8.7 % in wintertime for IAP and PG, 28.9 ± 7.4 % and 29.1 ± 9.4 % in summer), regardless of season. SOC contributed 50.0 ± 12.3 % and 47.2 ± 15.5 % at IAP and 42.0 ± 11.7 % and 43.0 ± 13.4 % at PG in the winter and summer sampling periods, respectively, within which the fossil-derived SOC was predominant and contributed more in winter. The non-fossil fractions of SOC increased in summer due to a larger biogenic component. Concentrations of biomass burning OC (OCbb) are resolved by the extended Gelencsér method, with average contributions (to total OC) of 10.6 ± 1.7 % and 10.4 ± 1.5 % in winter at IAP and PG and 6.5 ± 5.2 % and 17.9 ± 3.5 % in summer, respectively. Correlations of water-insoluble OC (WINSOC) and water-soluble OC (WSOC) with POC and SOC showed that although WINSOC was the major contributor to POC, a non-negligible fraction of WINSOC was found in SOC for both fossil and non-fossil sources, especially during winter. In summer, a greater proportion of WSOC from non-fossil sources was found in SOC. Comparisons of the source apportionment results with those obtained from a chemical mass balance model were generally good, except for the cooking aerosol.

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Section: Cmb Resultsmentioning

confidence: 90%

Section: Radiocarbon ( 14 C) Analysismentioning

confidence: 99%

Section: Radiocarbon ( 14 C) Analysismentioning

confidence: 99%

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

Hou

Liu

et al. 2021

Atmos. Chem. Phys.

Self Cite

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“…It had previously been shown that discrepancies existed between CMB and PMF model in the quantification of OCck. ACSM-PMF may overestimate OCck by approximately 2 times (Reyes-Villegas, et al, 2018;Yin et al, 2015), whereas, CMB may not be sensitive enough to the source profile of cooking aerosols (Abdullahi et al, 2018). Overall, the EG method resolves primary and secondary sources of OC well.…”

Section: Other Sources Of Oc and Consistency With Cmb And Ascm-pmf Momentioning

confidence: 96%

Source Apportionment of Carbonaceous Aerosols in Beijing with Radiocarbon and Organic Tracers: Insight into the Differences between Urban and Rural Sites

Hou¹,

Liu²,

Xu³

et al. 2020

Preprint

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Abstract. Carbonaceous aerosol is the dominant component of fine particles in Beijing. However, it is challenging to apportion its sources. Here, we applied a newly developed method which combined radiocarbon (14C) with organic tracers to apportion the sources of fine carbonaceous particles at an urban (IAP) and a rural (PG) site of Beijing. PM2.5 filter samples (24-h) were collected at both sites from 10 November to 11 December 2016 and from 22 May to 24 June 2017. 14C was determined in 25 aerosol samples (13 at IAP and 12 at PG) representing low pollution to haze conditions. Biomass burning tracers (levoglucosan, mannosan and galactosan) in the samples were also determined using GC-MS. Higher contributions of fossil-derived OC (OCf) were found at the urban site. OCf to OC ratio decreased in the summer samples (IAP: 67.8 ± 4.0 % in winter and 54.2 ± 11.7 % in summer; PG: 59.3 ± 5.7 % in winter and 50.0 ± 9.0 % in summer) due to less consumption of coal in the warm season. A novel extended Gelencsér method incorporating the 14C and organic tracer data was developed to estimate the fossil and non-fossil sources of primary and secondary OC (POC and SOC). It showed that fossil-derived POC was the largest contributor to OC (35.8 ± 10.5 % and 34.1 ± 8.7 % in winter time for IAP and PG, 28.9 ± 7.4 % and 28.9 ± 9.6 % in summer), regardless of season. SOC contributed 50.0 ± 12.3 % and 47.2 ± 15.5 % at IAP, and 42.0 ± 11.7 % and 43.0 ± 13.4 % at PG in the winter and summer sampling periods respectively, within which the fossil-derived SOC was predominant and contributed more in winter. The non-fossil fractions of SOC increased in summer due to a larger biogenic component. Concentrations of biomass burning OC (OCbb) are resolved by the extended Gelencsér method with average contributions (to total OC) of 10.6 ± 1.7 % and 10.4 ± 1.5 % in winter at IAP and PG, and 6.5 ± 5.2 % and 17.9 ± 3.5 % in summer, respectively. Correlations of water-insoluble OC (WINSOC), water-soluble OC (WSOC) with POC and SOC showed that although WINSOC was the major contributor to POC, a non-negligible fraction of WINSOC was found in SOC for both fossil and non-fossil sources especially during winter. In summer, a greater proportion of WSOC from non-fossil sources was found in SOC. Comparisons of the source apportionment results with those obtained from a Chemical Mass Balance model were generally good, except for the cooking aerosol.

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“…In other cases, the combination of remote sensing and hydrological characteristics provides a new approach to calculate the annual load of pollution sources [ 24 ]. Among the above methods, the CMB model requires a complete spectrum of emission source components, which is difficult to ascertain in reality, and the isotope method is limited to some extent by its high equipment requirements and complex analysis process [ 25 ]. Numerical modeling requires a comprehensive understanding of the transportation and transformation mechanisms of the pollutants, as well as a large amount of data to support it [ 26 ].…”

Section: Introductionmentioning

confidence: 99%

Pollution Source Apportionment and Water Quality Risk Evaluation of a Drinking Water Reservoir during Flood Seasons

Qin

Liu

et al. 2021

IJERPH

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Reservoirs play an important role in the urban water supply, yet reservoirs receive an influx of large amounts of pollutants from the upper watershed during flood seasons, causing a decline in water quality and threatening the water supply. Identifying major pollution sources and assessing water quality risks are important for the environmental protection of reservoirs. In this paper, the principal component/factor analysis-multiple linear regression (PCA/FA-MLR) model and Bayesian networks (BNs) are integrated to identify water pollution sources and assess the water quality risk in different precipitation conditions, which provides an effective framework for water quality management during flood seasons. The deterioration of the water quality of rivers in the flood season is found to be the main reason for the deterioration in the reservoir water quality. The nonpoint source pollution is the major pollution source of the reservoir, which contributes 53.20%, 48.41%, 72.69%, and 68.06% of the total nitrogen (TN), phosphorus (TP), fecal coliforms (F.coli), and turbidity (TUB), respectively. The risk of the water quality parameters exceeding the surface water standard under different hydrological conditions is assessed. The results show that the probability of the exceedance rate of TN, TP, and F.coli increases from 91.13%, 3.40%, and 3.34%, to 95.75%, 25.77%, and 12.76% as the monthly rainfall increases from ≤68.25 mm to >190.18 mm. The risk to the water quality of the Biliuhe River reservoir is found to increase with the rising rainfall intensity, the water quality risk at the inlet during the flood season is found to be much greater than that at the dam site, and the increasing trend of TP and turbidity is greater than that of TN and F.coli. The risk of five-day biochemical oxygen demand (BOD5) does not increase with increasing precipitation, indicating that it is less affected by nonpoint source pollution. The results of this study can provide a research basis for water environment management during flood seasons.

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Sensitivity of a Chemical Mass Balance model for PM2.5 to source profiles for differing styles of cooking

Cited by 16 publications

References 25 publications

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

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

Source Apportionment of Carbonaceous Aerosols in Beijing with Radiocarbon and Organic Tracers: Insight into the Differences between Urban and Rural Sites

Pollution Source Apportionment and Water Quality Risk Evaluation of a Drinking Water Reservoir during Flood Seasons

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