scholarly journals Insight into PM<sub>2.5</sub> Sources by Applying Positive Matrix Factorization (PMF) at an Urban and Rural Site of Beijing

2021 ◽  
Author(s):  
Deepchandra Srivastava ◽  
Jingsha Xu ◽  
Tuan V. Vu ◽  
Di Liu ◽  
Linjie Li ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Biomass Burning ◽  
Coal Combustion ◽  
Road Dust ◽  
Rural Site ◽  
Winter Period ◽  
Soil Dust ◽  
Beijing Area ◽  
Aerosol Mass ◽  
Inorganic Species

Abstract. This study presents the source apportionment of PM2.5 performed by PMF on data collected at an urban (Institute of Atmospheric Physics – IAP) and a rural site (Pinggu-PG) in Beijing as part of the Atmospheric Pollution and Human Health in a Chinese megacity (APHH-Beijing) field campaigns. The campaigns were carried out from 9th November to 11th December 2016 and 22nd May to 24th June 2017. The PMF included both organic and inorganic species, and a seven-factor output provided the most reasonable solution for the PM2.5 source apportionment. These factors are interpreted to be traffic emissions, biomass burning, road dust, soil dust, coal combustion, oil combustion and secondary inorganics. Major contributors to PM2.5 mass were secondary inorganics (22–24 %), biomass burning (30–36 %), and coal combustion (20–21 %) sources during the winter period at both sites. Secondary inorganics (48 %), road dust (20 %) and coal combustion (17 %) showed the highest contribution during summer at PG, while PM2.5 particles were mainly composed of soil dust (35 %) and secondary inorganics (40 %) at IAP. Despite this, factors that were resolved based on metal signatures were not fully resolved and indicate a mixing of two or more sources. PMF results were also compared with sources resolved from another receptor model (i.e. CMB) and PMF performed on other measurements (i.e. online and offline aerosol mass spectrometry (AMS)) and showed a good agreement for some but not all sources. The biomass burning factor in PMF may contain aged aerosols as a good correlation was observed between biomass burning and oxygenated fractions (r2 = 0.6–0.7) from AMS. The PMF failed to resolve some sources identified by the CMB and AMS, and appears to overestimate the dust sources. A comparison with earlier PMF source apportionment studies from the Beijing area highlights the very divergent findings from application of this method.

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

2021 ◽  
Vol 21 (19) ◽  
pp. 14703-14724
Author(s):  
Deepchandra Srivastava ◽  
Jingsha Xu ◽  
Tuan V. Vu ◽  
Di Liu ◽  
Linjie Li ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Biomass Burning ◽  
Matrix Factorization ◽  
Coal Combustion ◽  
Road Dust ◽  
Positive Matrix Factorization ◽  
Winter Period ◽  
Soil Dust ◽  
Positive Matrix ◽  
Inorganic Species

Abstract. This study presents the source apportionment of PM2.5 performed by positive matrix factorization (PMF) on data presented here which were collected at urban (Institute of Atmospheric Physics – IAP) and rural (Pinggu – PG) sites in Beijing as part of the Atmospheric Pollution and Human Health in a Chinese megacity (APHH-Beijing) field campaigns. The campaigns were carried out from 9 November to 11 December 2016 and from 22 May to 24 June 2017. The PMF analysis included both organic and inorganic species, and a seven-factor output provided the most reasonable solution for the PM2.5 source apportionment. These factors are interpreted as traffic emissions, biomass burning, road dust, soil dust, coal combustion, oil combustion, and secondary inorganics. Major contributors to PM2.5 mass were secondary inorganics (IAP: 22 %; PG: 24 %), biomass burning (IAP: 36 %; PG: 30 %), and coal combustion (IAP: 20 %; PG: 21 %) sources during the winter period at both sites. Secondary inorganics (48 %), road dust (20 %), and coal combustion (17 %) showed the highest contribution during summer at PG, while PM2.5 particles were mainly composed of soil dust (35 %) and secondary inorganics (40 %) at IAP. Despite this, factors that were resolved based on metal signatures were not fully resolved and indicate a mixing of two or more sources. PMF results were also compared with sources resolved from another receptor model (i.e. chemical mass balance – CMB) and PMF performed on other measurements (i.e. online and offline aerosol mass spectrometry, AMS) and showed good agreement for some but not all sources. The biomass burning factor in PMF may contain aged aerosols as a good correlation was observed between biomass burning and oxygenated fractions (r2= 0.6–0.7) from AMS. The PMF failed to resolve some sources identified by the CMB and AMS and appears to overestimate the dust sources. A comparison with earlier PMF source apportionment studies from the Beijing area highlights the very divergent findings from application of this method.

scholarly journals Nitrogen isotope fractionation during gas-particle conversion of NO<sub>x</sub> to NO<sub>3</sub><sup>−</sup> in the atmosphere – implications for isotope-based NO<sub>x</sub> source apportionment

2018 ◽  
Author(s):  
Yunhua Chang ◽  
Yanlin Zhang ◽  
Chongguo Tian ◽  
Shichun Zhang ◽  
Xiaoyan Ma ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Isotope Effect ◽  
Biomass Burning ◽  
Coal Combustion ◽  
Isotope Fractionation ◽  
Road Traffic ◽  
Eastern China ◽  
Rural Site ◽  
Urban Site ◽  
Exchange Reactions

Abstract. Atmospheric fine-particle (PM2.5) pollution is frequently associated with the formation of particulate nitrate (pNO3−), the end product of the oxidation of NOx gases (= NO + NO2) in the upper troposphere. The application of stable nitrogen (N) (and oxygen) isotope analyses of pNO3− to constrain NOx source partitioning in the atmosphere requires the knowledge of the isotope fractionation during the reactions leading to NO3− formation. Here we determined the δ15N values of fresh pNO3− (δ15N-pNO3−) in PM2.5 at a rural site in Northern China, where atmospheric pNO3− can be attributed exclusively to biomass burning. The observed δ15N-pNO3− (12.17 ± 1.55 ‰; n = 8) was much higher than the N isotopic source signature of NOx from biomass burning (1.04 ± 4.13 ‰). The large difference between δ15N-pNO3− and δ15N-NOx (Δ(δ15N)) can be reconciled by the net N isotope effect (ԑN) associated with the gas-particle conversion from NOx to NO3−. For the biomass-burning site, a mean ԑN (≈ Δ(δ15N)) of 10.99 ± 0.74 ‰ was assessed through a newly-developed computational quantum chemistry (CQC) module. ԑN depends on the relative importance of the two dominant N isotope exchange reactions involved (NO2 reaction with OH versus hydrolysis of dinitrogen pentoxide (N2O5) with H2O), and varies between regions, and on a diurnal basis. A second, slightly higher CQC-based mean value for ԑN (15.33 ± 4.90 ‰) was estimated for an urban site with intense traffic in Eastern China, and integrated in a Bayesian isotope mixing model to make isotope-based source apportionment estimates for NOx at this site. Based on the δ15N values (10.93 ± 3.32 ‰, n = 43) of ambient pNO3− determined for the urban site, and considering the location-specific estimate for ԑN, our results reveal that the relative contribution of coal combustion and road traffic to urban NOx are 32 ± 11 % and 68 ± 11 %, respectively. This finding agrees well with a regional bottom-up emission inventory of NOx. Moreover, the variation pattern of OH contribution to ambient pNO3− formation calculated by the CQC module is consistent with that simulated by the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), further confirming the robustness of our estimates. Our investigations also show that, without the consideration of the N isotope effect during pNO3− formation, the observed δ15N-pNO3− at the study site would erroneously imply that NOx is derived almost entirely from coal combustion. Similarly, reanalysis of reported δ15N-NO3− data throughout China suggests that, nationwide, NOx emissions from coal combustion may be substantively overestimated (by > 30 %) when the N isotope fractionation during atmospheric pNO3− formation is neglected.

scholarly journals Characteristics of the main primary source profiles of particulate matter across China: from 1987 to 2017

2018 ◽  
Author(s):  
Xiaohui Bi ◽  
Yuan Cheng ◽  
Qili Dai ◽  
Jianhui Wu ◽  
Jiaying Zhang ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Biomass Burning ◽  
Coal Combustion ◽  
Vehicle Emissions ◽  
Sampling Methods ◽  
Road Dust ◽  
Fugitive Dust ◽  
Soil Dust ◽  
Industrial Emissions ◽  
Source Profiles

Abstract. Based on the published literatures and typical profiles from the source library of Nankai University, a total of 3244 chemical profiles of the main primary sources of ambient particulate matter across China from 1987 to 2017, including coal combustion, industrial emissions, vehicle emissions, fugitive dust, biomass burning, and cooking emissions, were investigated and reviewed to trace the evolution of their main components and identify the main influencing factors to the evolution. As a result, the most complicated profiles are likely attributed to coal combustion and industrial emissions, which are evidently influenced by the decontamination processes and sampling techniques as well as the coal nature and the boiler types. The profiles of vehicle emissions are dominated by OC and EC, and varied with the changing standard of sulfur and additives in the gasoline and diesel as well as the sampling methods. The profiles of fugitive dust, such as soil dust and road dust, are dominated by the crustal materials and influenced by the sampling methods to some extent. The profiles of biomass burning is impacted mainly by the biomass categories and sampling methods. As expected, the profiles of cooking emissions is impacted mainly by the cooking types and materials. The uncertainty analysis and cluster analysis of all these source profiles are conducted to reveal the variations of the different source profiles in the same source category and evaluate the differences between source categories. A relatively large variation has been founded in the source profiles of coal combustion, vehicle emissions, industry emissions and biomass burning, indicating that it is necessary to establish the local profiles for these sources due to their high uncertainties. While the profiles of road dust and soil dust present a less variation with the stable chemical characteristics among the different profiles in the same category, suggesting that the profiles of these sources could be referenced for the cities in China when such local profiles are not available. The presented results highlight the need for increased investigation of more specific markers beyond routine measured components (e.g., isotopes, organic compounds and gaseous precursors) to discriminate sources. Additionally, specific focus should be placed on the sub-type of source profiles in the future, especially for local industrial emissions and geographical areas in China, to support the air quality research communities in their efforts to develop high resolution source apportionment for making a more effective control strategies.

scholarly journals Nitrogen isotope fractionation during gas-to-particle conversion of NO<sub><i>x</i></sub> to NO<sub>3</sub><sup>−</sup> in the atmosphere – implications for isotope-based NO<sub><i>x</i></sub> source apportionment

2018 ◽  
Vol 18 (16) ◽  
pp. 11647-11661 ◽  
Author(s):  
Yunhua Chang ◽  
Yanlin Zhang ◽  
Chongguo Tian ◽  
Shichun Zhang ◽  
Xiaoyan Ma ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Isotope Effect ◽  
Biomass Burning ◽  
Coal Combustion ◽  
Isotope Fractionation ◽  
Road Traffic ◽  
Eastern China ◽  
Rural Site ◽  
Urban Site ◽  
Exchange Reactions

Abstract. Atmospheric fine-particle (PM2.5) pollution is frequently associated with the formation of particulate nitrate (pNO3−), the end product of the oxidation of NOx gases (NO + NO2) in the upper troposphere. The application of stable nitrogen (N) (and oxygen) isotope analyses of pNO3− to constrain NOx source partitioning in the atmosphere requires knowledge of the isotope fractionation during the reactions leading to nitrate formation. Here we determined the δ15N values of fresh pNO3− (δ15N–pNO3−) in PM2.5 at a rural site in northern China, where atmospheric pNO3− can be attributed exclusively to biomass burning. The observed δ15N–pNO3− (12.17±1.55 ‰; n = 8) was much higher than the N isotopic source signature of NOx from biomass burning (1.04±4.13 ‰). The large difference between δ15N–pNO3− and δ15N–NOx (Δ(δ15N)) can be reconciled by the net N isotope effect (εN) associated with the gas–particle conversion from NOx to NO3−. For the biomass burning site, a mean εN( ≈ Δ(δ15N)) of 10.99±0.74 ‰ was assessed through a newly developed computational quantum chemistry (CQC) module. εN depends on the relative importance of the two dominant N isotope exchange reactions involved (NO2 reaction with OH versus hydrolysis of dinitrogen pentoxide (N2O5) with H2O) and varies between regions and on a diurnal basis. A second, slightly higher CQC-based mean value for εN (15.33±4.90 ‰) was estimated for an urban site with intense traffic in eastern China and integrated in a Bayesian isotope mixing model to make isotope-based source apportionment estimates for NOx at this site. Based on the δ15N values (10.93±3.32 ‰; n = 43) of ambient pNO3− determined for the urban site, and considering the location-specific estimate for εN, our results reveal that the relative contribution of coal combustion and road traffic to urban NOx is 32 % ± 11 % and 68 %± 11 %, respectively. This finding agrees well with a regional bottom-up emission inventory of NOx. Moreover, the variation pattern of OH contribution to ambient pNO3− formation calculated by the CQC module is consistent with that simulated by the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), further confirming the robustness of our estimates. Our investigations also show that, without the consideration of the N isotope effect during pNO3− formation, the observed δ15N–pNO3− at the study site would erroneously imply that NOx is derived almost entirely from coal combustion. Similarly, reanalysis of reported δ15N–NO3− data throughout China and its neighboring areas suggests that NOx emissions from coal combustion may be substantively overestimated (by  > 30 %) when the N isotope fractionation during atmospheric pNO3− formation is neglected.

scholarly journals Wintertime aerosol chemical composition, volatility, and spatial variability in the greater London area

2016 ◽  
Vol 16 (2) ◽  
pp. 1139-1160 ◽  
Author(s):  
L. Xu ◽  
L. R. Williams ◽  
D. E. Young ◽  
J. D. Allan ◽  
H. Coe ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Solid Fuel ◽  
Field Studies ◽  
Rural Site ◽  
Urban Site ◽  
High Temporal Resolution ◽  
Volatile Organics ◽  
Aerosol Mass ◽  
Rural And Urban ◽  
Wide Range

Abstract. The composition of PM1 (particulate matter with diameter less than 1 µm) in the greater London area was characterized during the Clean Air for London (ClearfLo) project in winter 2012. Two high-resolution time-of-flight aerosol mass spectrometers (HR-ToF-AMS) were deployed at a rural site (Detling, Kent) and an urban site (North Kensington, London). The simultaneous and high-temporal resolution measurements at the two sites provide a unique opportunity to investigate the spatial distribution of PM1. We find that the organic aerosol (OA) concentration is comparable between the rural and urban sites, but the contribution from different sources is distinctly different between the two sites. The concentration of solid fuel OA at the urban site is about twice as high as at the rural site, due to elevated domestic heating in the urban area. While the concentrations of oxygenated OA (OOA) are well-correlated between the two sites, the OOA concentration at the rural site is almost twice that of the urban site. At the rural site, more than 70 % of the carbon in OOA is estimated to be non-fossil, which suggests that OOA is likely related to aged biomass burning considering the small amount of biogenic SOA in winter. Thus, it is possible that the biomass burning OA contributes a larger fraction of ambient OA in wintertime than what previous field studies have suggested. A suite of instruments was deployed downstream of a thermal denuder (TD) to investigate the volatility of PM1 species at the rural Detling site. After heating at 250 °C in the TD, 40 % of the residual mass is OA, indicating the presence of non-volatile organics in the aerosol. Although the OA associated with refractory black carbon (rBC; measured by a soot-particle aerosol mass spectrometer) only accounts for < 10 % of the total OA (measured by a HR-ToF-AMS) at 250 °C, the two measurements are well-correlated, suggesting that the non-volatile organics have similar sources or have undergone similar chemical processing as rBC in the atmosphere. Although the atomic O : C ratio of OOA is substantially larger than that of solid fuel OA and hydrocarbon-like OA, these three factors have similar volatility, which is inferred from the change in mass concentration after heating at 120 °C. Finally, we discuss the relationship between the mass fraction remaining (MFR) of OA after heating in the TD and atomic O : C of OA and find that particles with a wide range of O : C could have similar MFR after heating. This analysis emphasizes the importance of understanding the distribution of volatility and O : C in bulk OA.

scholarly journals The impact of biomass burning and aqueous-phase processing on air quality: a multi-year source apportionment study in the Po Valley, Italy

2019 ◽  
Author(s):  
Marco Paglione ◽  
Stefania Gilardoni ◽  
Matteo Rinaldi ◽  
Stefano Decesari ◽  
Nicola Zanca ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Organic Aerosol ◽  
Cold Season ◽  
World Health ◽  
Rural Site ◽  
Urban Site ◽  
Urban Background ◽  
Po Valley

Abstract. The Po Valley (Italy) is a well-known air quality hotspot characterized by Particulate Matter (PM) levels well above the limit set by the European Air Quality Directive and by the World Health Organization, especially during the colder season. In the framework of the Emilia-Romagna regional project SUPERSITO, the southern Po Valley submicron aerosol chemical composition was characterized by means of High-Resolution Aerosol Mass Spectroscopy (HR-AMS) with the specific aim of organic aerosol (OA) characterization and source apportionment. Eight intensive observation periods (IOPs) were carried out over four years (from 2011 to 2014) at two different sites (Bologna, BO, urban background and San Pietro Capofiume, SPC, rural background), to characterize the spatial variability and seasonality of the OA sources, with a special focus on the cold season. On the multi-year basis of the study, the AMS observations show that OA accounts for an average 45 ± 8 % (ranging 33–58 %) and 46 ± 7 % (ranging 36–50 %) of the total non-refractory submicron particle mass (PM1-NR) at the urban and at the rural site, respectively. Primary organic aerosol (POA) comprises biomass burning (23 ± 13 % of OA) and fossil fuel (12 ± 7 %) contributions with a marked seasonality in concentration. As expected, the biomass burning contribution to POA is more significant at the rural site (urban/rural concentrations ratio of 0.67), but it is also an important source of POA at the urban site during the cold season, with contributions ranging from 14 to 38 % of the total OA mass. Secondary organic aerosol (SOA) contribute to OA mass to a much larger extent than POA at both sites throughout the year (69 ± 16 % and 83 ± 16 % at urban and rural, respectively), with important implications for public health. Within the secondary fraction of OA, the measurements highlight the importance of biomass burning ageing products during the cold season, even at the urban background site. This biomass burning SOA fraction represents 14–44 % of the total OA mass in the cold season, indicating that in this region a major contribution of combustion sources to PM mass is mediated by environmental conditions and atmospheric reactivity. Among the environmental factors controlling the formation of SOA in the Po Valley, the availability of liquid water in the aerosol was shown to play a key role in the cold season. We estimate that organic fraction originating from aqueous reactions of biomass burning products (bb-aqSOA) represents 21 % (14–28 %) and 25 % (14–35 %) of the total OA mass and 44 % (32–56 %) and 61 % (21–100 %) of the SOA mass at the urban and rural sites, respectively.

scholarly journals Source Apportionment of Fine Organic and Inorganic Atmospheric Aerosol in an Urban Background Area in Greece

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 330 ◽  
Author(s):  
Manousos Ioannis Manousakas ◽  
Kalliopi Florou ◽  
Spyros N. Pandis
Keyword(s):  
Source Apportionment ◽  
Biomass Burning ◽  
Fine Particulate Matter ◽  
Organic Aerosols ◽  
Mitigation Strategies ◽  
Traffic Emissions ◽  
Aerosol Mass ◽  
Aerosol Mass Spectrometry ◽  
Five Factors ◽  
Potential Risks

Fine particulate matter (PM) originates from various emission sources and physicochemical processes. Quantification of the sources of PM is an important step during the planning of efficient mitigation strategies and the investigation of the potential risks to human health. Usually, source apportionment studies focus either on the organic or on the inorganic fraction of PM. In this study that took place in Patras, Greece, we address both PM fractions by combining measurements from a range of on- and off-line techniques, including elemental composition, organic and elemental carbon (OC and EC) measurements, and high-resolution Aerosol Mass Spectrometry (AMS) from different techniques. Six fine PM2.5 sources were identified based on the off-line measurements: secondary sulfate (34%), biomass burning (15%), exhaust traffic emissions (13%), nonexhaust traffic emissions (12%), mineral dust (10%), and sea salt (5%). The analysis of the AMS spectra quantified five factors: two oxygenated organic aerosols (OOA) factors (an OOA and a marine-related OOA, 52% of the total organic aerosols (OA)), cooking OA (COA, 11%) and two biomass burning OA (BBOA-I and BBOA-II, 37% in total) factors. The results of the two methods were synthesized, showcasing the complementarity of the two methodologies for fine PM source identification. The synthesis suggests that the contribution of biomass burning is quite robust, but that the exhaust traffic emissions are not due to local sources and may also include secondary OA from other sources.

Geochemistry and Source Apportionment of Atmospheric Particulate Matter in Jiaozuo City

2011 ◽  
Vol 71-78 ◽  
pp. 2867-2872 ◽  
Author(s):  
Dang Yu Song ◽  
Cun Bei Yang
Keyword(s):  
Particulate Matter ◽  
Source Apportionment ◽  
Coal Combustion ◽  
Average Concentration ◽  
Atmospheric Particulate Matter ◽  
Soil Dust ◽  
X Ray Diffraction ◽  
Atmospheric Particulate ◽  
X Ray ◽  
Industrial Action

A total of 28 atmospheric particulate matter samples were collected at Henan Polytechnic University in the southeast of Jiaozuo city during October to December 2010. The daily concentrations of PM10 vary from 190.76 to 670.14 μg/m3, with the average concentration of 359.36 μg/m3. The concentrations of Na, Mg, Al, Si, P, S, Cl, K, Ca, Ti, Fe, Cu, Zn, Mn and Pb in PM10 are determined by Energy Dispersive X-Ray Fluorescence (EDXRF). The result shows that the fifteen elements quality accounts for 17.3%~36.7% of total mass. The X-ray diffraction (XRD) results show that six minerals are identified in the atmospheric particles. They are quartz, gypsum, kaolinite, sal-ammoniac, calcite, and albite, which account for 29%, 29%, 18%, 17%, 4% and 3%, respectively. The principle component analysis (PCA) model is used for source apportionment of PM10. The research results show that there are four sources: architecture/smelting action, coal combustion/traffic action, soil dust and particular industrial action.

scholarly journals Source apportionment of PM<sub>2.5</sub> at a regional background site in North China using PMF linked with radiocarbon analysis: insight into the contribution of biomass burning

2016 ◽  
Vol 16 (17) ◽  
pp. 11249-11265 ◽  
Author(s):  
Zheng Zong ◽  
Xiaoping Wang ◽  
Chongguo Tian ◽  
Yingjun Chen ◽  
Lin Qu ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Biomass Burning ◽  
Coal Combustion ◽  
North China ◽  
Fine Particles ◽  
Vehicle Emission ◽  
Shandong Peninsula ◽  
Air Masses ◽  
Background Site ◽  
Bth Region

Abstract. Source apportionment of fine particles (PM2.5) at a background site in North China in the winter of 2014 was done using statistical analysis, radiocarbon (14C) measurement and positive matrix factorization (PMF) modeling. Results showed that the concentration of PM2.5 was 77.6 ± 59.3 µg m−3, of which sulfate (SO42−) concentration was the highest, followed by nitrate (NO3−), organic carbon (OC), elemental carbon (EC) and ammonium (NH4+). As demonstrated by backward trajectory, more than half of the air masses during the sampling period were from the Beijing–Tianjin–Hebei (BTH) region, followed by Mongolia and the Shandong Peninsula. Cluster analysis of chemical species suggested an obvious signal of biomass burning in the PM2.5 from the Shandong Peninsula, while the PM2.5 from the BTH region showed a vehicle emission pattern. This finding was further confirmed by the 14C measurement of OC and EC in two merged samples. The 14C result indicated that biogenic and biomass burning emission contributed 59 ± 4 and 52 ± 2 % to OC and EC concentrations, respectively, when air masses originated from the Shandong Peninsula, while the contributions fell to 46 ± 4 and 38 ± 1 %, respectively, when the prevailing wind changed and came from the BTH region. The minimum deviation between source apportionment results from PMF and 14C measurement was adopted as the optimal choice of the model exercises. Here, two minor overestimates with the same range (3 %) implied that the PMF result provided a reasonable source apportionment of the regional PM2.5 in this study. Based on the PMF modeling, eight sources were identified; of these, coal combustion, biomass burning and vehicle emission were the main contributors of PM2.5, accounting for 29.6, 19.3 and 15.9 %, respectively. Compared with overall source apportionment, the contributions of vehicle emission, mineral dust, coal combustion and biomass burning increased when air masses came from the BTH region, Mongolia and the Shandong Peninsula, respectively. Since coal combustion and vehicle emission have been considered as the leading emission sources to be controlled for improving air quality, biomass burning was highlighted in the present study.

scholarly journals Simultaneous aerosol mass spectrometry and chemical ionisation mass spectrometry measurements during a biomass burning event in the UK: insights into nitrate chemistry

2018 ◽  
Vol 18 (6) ◽  
pp. 4093-4111 ◽  
Author(s):  
Ernesto Reyes-Villegas ◽  
Michael Priestley ◽  
Yu-Chieh Ting ◽  
Sophie Haslett ◽  
Thomas Bannan ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Organic Aerosol ◽  
Oxides Of Nitrogen ◽  
Night Time ◽  
Aerosol Mass ◽  
Ionisation Mass Spectrometry ◽  
Chemical Ionisation ◽  
Ionisation Mass

Abstract. Over the past decade, there has been an increasing interest in short-term events that negatively affect air quality such as bonfires and fireworks. High aerosol and gas concentrations generated from public bonfires or fireworks were measured in order to understand the night-time chemical processes and their atmospheric implications. Nitrogen chemistry was observed during Bonfire Night with nitrogen containing compounds in both gas and aerosol phases and further N2O5 and ClNO2 concentrations, which depleted early next morning due to photolysis of NO3 radicals and ceasing production. Particulate organic oxides of nitrogen (PONs) concentrations of 2.8 µg m−3 were estimated using the m ∕ z 46 : 30 ratios from aerosol mass spectrometer (AMS) measurements, according to previously published methods. Multilinear engine 2 (ME-2) source apportionment was performed to determine organic aerosol (OA) concentrations from different sources after modifying the fragmentation table and it was possible to identify two PON factors representing primary (pPON_ME2) and secondary (sPON_ME2) contributions. A slight improvement in the agreement between the source apportionment of the AMS and a collocated AE-31 Aethalometer was observed after modifying the prescribed fragmentation in the AMS organic spectrum (the fragmentation table) to determine PON sources, which resulted in an r2 =  0.894 between biomass burning organic aerosol (BBOA) and babs_470wb compared to an r2 =  0.861 obtained without the modification. Correlations between OA sources and measurements made using time-of-flight chemical ionisation mass spectrometry with an iodide adduct ion were performed in order to determine possible gas tracers to be used in future ME-2 analyses to constrain solutions. During Bonfire Night, strong correlations (r2) were observed between BBOA and methacrylic acid (0.92), acrylic acid (0.90), nitrous acid (0.86), propionic acid, (0.85) and hydrogen cyanide (0.76). A series of oxygenated species and chlorine compounds showed good correlations with sPON_ME2 and the low volatility oxygenated organic aerosol (LVOOA) factor during Bonfire Night and an event with low pollutant concentrations. Further analysis of pPON_ME2 and sPON_ME2 was performed in order to determine whether these PON sources absorb light near the UV region using an Aethalometer. This hypothesis was tested by doing multilinear regressions between babs_470wb and BBOA, sPON_ME2 and pPON_ME2. Our results suggest that sPON_ME2 does not absorb light at 470 nm, while pPON_ME2 and LVOOA do absorb light at 470 nm. This may inform black carbon (BC) source apportionment studies from Aethalometer measurements, through investigation of the brown carbon contribution to babs_470wb.

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