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 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 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 carbon at an urban site of Beijing using a chemical mass balance model

2021 ◽  
Vol 21 (9) ◽  
pp. 7321-7341
Author(s):  
Jingsha Xu ◽  
Di Liu ◽  
Xuefang Wu ◽  
Tuan V. Vu ◽  
Yanli Zhang ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Mass Balance ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Coal Combustion ◽  
Fine Particles ◽  
Inorganic Ions ◽  
Balance Model ◽  
Urban Site ◽  
Chemical Mass Balance

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.

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

2020 ◽  
Vol 20 (3) ◽  
pp. 1233-1254 ◽  
Author(s):  
Marco Paglione ◽  
Stefania Gilardoni ◽  
Matteo Rinaldi ◽  
Stefano Decesari ◽  
Nicola Zanca ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Organic Aerosol ◽  
Cold Season ◽  
Rural Site ◽  
Urban Site ◽  
Urban Background ◽  
Po Valley ◽  
Rural Sites

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 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 4 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 averages of 45±8 % (ranging from 33 % to 58 %) and 46±7 % (ranging from 36 % to 50 %) of the total non-refractory submicron particle mass (PM1-NR) at the urban and rural sites, 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 concentration 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) contributes to OA mass to a much larger extent than POA at both sites throughout the year (69±16 % and 83±16 % at the urban and rural sites, respectively), with important implications for public health. Within the secondary fraction of OA, the measurements highlight the importance of biomass burning aging 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 the 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 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 Particulate organic nitrates in eastern China: variation characteristics and effects of anthropogenic activities

2019 ◽  
Author(s):  
Jun Zhang ◽  
Xinfeng Wang ◽  
Rui Li ◽  
Shuwei Dong ◽  
Yingnan Zhang ◽  
...  
Keyword(s):  
Oleic Acid ◽  
Biomass Burning ◽  
Coal Combustion ◽  
Urban Areas ◽  
Anthropogenic Activities ◽  
Eastern China ◽  
Rural Site ◽  
Organic Nitrate ◽  
Organic Nitrates ◽  
Variation Characteristics

Abstract. Particulate organic nitrates (PONs) constitute a substantial fraction of secondary organic aerosols and have important effects on the reactive nitrogen budget and air quality. Laboratory studies have revealed the non-negligible influence of the interactions between anthropogenic pollutants and biogenic volatile organic compounds (BVOCs) on the formation of PONs. In this study, the contents of specific PONs, including monoterpene hydroxyl nitrate (MHN215), pinene keto nitrate (PKN229), limonene di-keto nitrate (LDKN247), oleic acid keto nitrate (OAKN359), oleic acid hydroxyl nitrate (OAHN361), and pinene sulfate organic nitrate (PSON295), in fine particulate matters at four rural and urban sites in eastern China were determined, and the variation characteristics of PONs and the impacts of human activities on PONs formation were investigated. The average concentration of PONs ranged from 116 to 548 ng m−3 at these four sites. PONs were present in higher levels in summer than in other seasons, owing to the high emissions of precursors and intensive photochemical activities in this hottest season. Among the six species of PONs, MHN215 was dominant. In addition, the proportion of OAKN359 in PONs in urban areas was much higher than that in the rural site, indicating that OAKN359 primarily originated from anthropogenic activities. Slight diurnal differences existed in the concentration and secondary formation of specific PONs and varied with locations, seasons, and precursor VOCs. The measurement results showed that PONs in North China were clearly influenced by coal combustion and biomass burning, while meteorological conditions and biogenic emissions were the dominant contributing factors in the South China. Biomass burning significantly enhanced the formation of PONs due to the elevated concentrations of ozone and the released BVOCs. Sulfur dioxide (SO2) emitted from coal combustion was able to react rapidly with Criegee intermediates, the reaction products of BVOCs with ozone, to produce PONs at high rates, suggesting that there is a substantially greater role played by SO2 in organic nitrate chemistry than has previously been assumed.

scholarly journals Source Apportionment of Fine Aerosol at an Urban Site of Beijing using a Chemical Mass Balance Model

2020 ◽  
Author(s):  
Jingsha Xu ◽  
Di Liu ◽  
Xuefang Wu ◽  
Tuan V. Vu ◽  
Yanli Zhang ◽  
...  
Keyword(s):  
Mass Balance ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Coal Combustion ◽  
Fine Particles ◽  
Correlation Coefficients ◽  
Inorganic Ions ◽  
Balance Model ◽  
Urban Site ◽  
Chemical Mass Balance

Abstract. Fine particles were sampled from 9th November to 11th December 2016 and 22nd May to 24th 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, OC, EC, and organic compounds including biomarkers, hopanes, 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/residential coal burning, biomass burning, gasoline/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 CMB was mostly associated with SOC. PM2.5 apportioned by CMB showed that the SNA and secondary organic matter were the highest two 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 Positive Matrix Factorization (PMF) analysis of co-located Aerosol Mass Spectrometer (AMS) data. The CMB was found to resolve more primary OA sources than AMS-PMF but the latter apportioned more secondary OA sources. The AMS-PMF results for major components, such as coal combustion OC and oxidized OC correlated well with the results from CMB. 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.

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.

Diurnal variations and source apportionment of ozone at the summit of Mount Huang, a rural site in Eastern China

2020 ◽  
Author(s):  
Jinhui Gao
Keyword(s):  
Boundary Layer ◽  
Diurnal Variation ◽  
Source Apportionment ◽  
Southern China ◽  
Eastern China ◽  
Vertical Mixing ◽  
Diurnal Variations ◽  
Rural Site ◽  
Positive Contribution ◽  
Negative Contribution

&lt;p&gt;Comprehensive measurements were conducted at the summit of Mount (Mt.) Huang, a rural site located in eastern China during the summer of 2011. They observed that ozone showed pronounced diurnal variations with high concentrations at night and low values during daytime. The Weather Research and Forecasting with Chemistry (WRF-Chem) model was applied to simulate the ozone concentrations at Mt. Huang in June 2011. With processes analysis and online ozone tagging method we coupled into the model system, the causes of this diurnal pattern and the contributions from different source regions were investigated. Our results showed that boundary layer diurnal cycle played an important role in driving the ozone diurnal variation. Further analysis showed that the negative contribution of vertical mixing was significant, resulting in the ozone decrease during the daytime. In contrast, ozone increased at night owing to the significant positive contribution of advection. This shifting of major factor between vertical mixing and advection formed this diurnal variation. Ozone source apportionment results indicated that approximately half was provided by inflow effect of ozone from outside the model domain (O&lt;sub&gt;3-INFLOW&lt;/sub&gt;) and the other half was formed by ozone precursors (O&lt;sub&gt;3-PBL&lt;/sub&gt;) emitted in eastern, central, and southern China. In the O&lt;sub&gt;3-PBL&lt;/sub&gt;, 3.0% of the ozone was from Mt. Huang reflecting the small local contribution (O&lt;sub&gt;3-LOC&lt;/sub&gt;) and the non-local contributions (O&lt;sub&gt;3-NLOC&lt;/sub&gt;) accounted for 41.6%, in which ozone from the southerly regions contributed significantly, for example, 9.9% of the ozone originating from Jiangxi, representing the highest geographical contributor. Because the origin and variation of O&lt;sub&gt;3-NLOC&lt;/sub&gt; was highly related to the diurnal movements in boundary layer, the similar diurnal patterns between O&lt;sub&gt;3-NLOC&lt;/sub&gt; and total ozone both indicated the direct influence of O&lt;sub&gt;3-NLOC&lt;/sub&gt; and the importance of boundary layer diurnal variations in the formation of such distinct diurnal ozone variations at Mt. Huang.&lt;/p&gt;

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.

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