Contribution Of Secondary Sources Research Articles

Long‐Emission‐Wavelength Humic‐Like Component (L‐HULIS) as a Secondary Source Tracer of Brown Carbon in the Atmosphere

AbstractThe optical properties of secondary brown carbon (BrC) aerosols are poorly understood, hampering quantitative assessments of their impact. We propose a new method for estimating secondary source of BrC using excitation‐emission matrix (EEM) fluorescence spectroscopy, combined with parallel factor analysis (PARAFAC) and partial least squares regression (PLSR). Experiments were conducted on a collection of PM2.5 samples from urban areas in five Chinese cities during winter and summer. The humic‐like component with long‐emission wavelengths (L‐HULIS) was identified as a secondary source tracer of BrC. This was confirmed by correlating PARAFAC components with secondary organic aerosol tracers and molecular oxidation indices obtained from Fourier transform ion cyclotron resonance mass spectrometry analysis. Using L‐HULIS as a secondary tracer of BrC, it was determined that the contribution of secondary sources to water‐soluble BrC (WS‐BrC) in source emission samples is significantly smaller than in PM2.5 from five Chinese cities, supporting our method. In the five cities, secondary source derived via L‐HULIS contributes a dominant potion (80% ± 3.5%) of WS‐BrC at 365 nm during the summer, which is approximately twice as high as during the winter (45% ± 4.9%). Radiocarbon isotope (14C) analysis provides additional constraints to the sources of L‐HULIS‐derived secondary WS‐BrC in urban PM2.5, suggesting that aged biomass burning is the dominant contributor to secondary WS‐BrC in winter, and biogenic emission is dominant during summer. This study is the first report on identification of secondary sources of BrC using the fluorescence technique. It demonstrates the potential of this method in characterizing non‐fossil source secondary BrC in the atmosphere.

Characteristics, seasonal variations, and dry deposition fluxes of carbonaceous and water-soluble organic components in atmospheric aerosols over China's marginal seas

A total of 37 atmospheric aerosol samples were collected over the Yellow and Bohai Seas (YBS) during four cruises in autumn, winter, spring and summer from 2017 to 2018. The concentrations of organic carbon (OC) and water-soluble organic carbon (WSOC) ranged from 1.04 to 15.43 μg m−3 and 0.77–5.49 μg m−3, respectively, with higher values in autumn and winter than in spring and summer. WSOC contributed 68.49 % to OC in summer and 34.55 % in winter and was affected by temperature and relative humidity. Dicarboxylic acid showed a predominance of oxalic acid followed by malonic and then succinic acids. The contributions of secondary sources to OC and WSOC were 54 % and 65.3 %, respectively, indicating the importance of secondary aging in improving the water solubility of OC. The dry deposition flux of WSOC over the YBS was estimated to be 0.87 mg m−2 d−1, which might play a potential role in the marine carbon cycle.

Seasonal Characteristics of Atmospheric PM2.5 in an Urban Area of Vietnam and the Influence of Regional Fire Activities

This study investigated the seasonal variation and chemical characteristics of atmospheric PM2.5 at an urban site in Hanoi City of Vietnam in summer (July 2020) and winter (January 2021) periods. The study results showed that the average value of daily PM2.5 concentrations observed for the winter period was about 3 times higher than the counterpart for the summer period. The concentrations of major species in atmospheric PM2.5 (SO42−, NH4+, K+, OC and EC) measured during the winter period were also significantly higher than those during the summer period. The contribution of secondary sources to the measured OC (the largest contributor to PM2.5) was larger than that of primary sources during the winter period, compared to those in the summer period. The correlation analysis among anions and cations in PM2.5 suggested that different sources and atmospheric processes could influence the seasonal variations of PM2.5 species. The unfavorable meteorological conditions (lower wind speed and lower boundary layer height) in the winter period were identified as one of the key factors contributing to the high PM2.5 pollution in this period. With the predominance of north and northeast winds during the winter period, the long-range transport of air pollutants which emitted from the highly industrialized areas and the intensive fire regions in the southern part of China and Southeast Asia region were likely other important sources for the highly elevated concentrations of PM2.5 and its chemical species in the study area.

Chemical composition, sources and optical properties of nitrated aromatic compounds in fine particulate matter during winter foggy days in Nanjing, China

Functionalized aromatic compounds are one of the most important light-absorbing organic chromophores – so-called brown carbon (BrC) – in fine particulate matter (PM2.5). In this study, we conducted a wintertime field campaign to measure eight nitrated aromatic compounds (NACs) in PM2.5 with offline analysis techniques, including liquid chromatograph mass spectrometer (LC-MS) and aerodyne high-resolution aerosol mass spectrometer (AMS) measurements, during foggy and nonfoggy days in suburban Nanjing in the Yangtze River Delta region, China. On average, 4-nitrophenol could be one of the most important light absorbing materials in the observed BrC, which accounted for over 40% of the mass concentration of identified chromophores. The mass concentration of 2-methyl-4-nitrophenol and 2,6-dimethyl-4-nitrophenol were evidently increased during foggy days, contribution of which to total NACs were increased by 10% and 5%, respectively. Positive matrix factorization analysis of combining LC-MS and AMS dataset was performed to identify the primary and secondary sources of NACs. Primary sources, e.g., traffic and solid-fuel combustion, accounted for 71% of the sum of 4-nitrophenol, 2,6-dimethyl-4-nitrophenol and 3-nitrosalicylic acid, suggesting important contribution of primary emissions to these NACs. The contribution of secondary sources, associated with two oxygenated organic aerosols, could contribute 66% to 4-nitrophenol, reflecting the link of such nitrated aromatic compounds to secondary organic aerosol source. Together with optical measurements, 4-nitrophenol presented a high contribution (>50%) to the identified BrC absorbance in the light range 250 and 550 nm was observed. This could highlight an important role of such NACs in ambient BrC light absorption, despite its mass contribution to total organic carbon was negligible. Our work could improve the understanding of the links between optical properties and chemical composition of BrC, and the difference between BrC chromophores from nonfoggy days and foggy days under the typical polluted atmospheric conditions.

Quantifying traffic, biomass burning and secondary source contributions to atmospheric particle number concentrations at urban and suburban sites

In this study, we propose a new approach to determine the contributions of primary vehicle exhaust (N1ff), primary biomass burning (N1bb) and secondary (N2) particles to mode segregated particle number concentrations. We used simultaneous measurements of aerosol size distribution in the 12–600 nm size range and black carbon (BC) concentration obtained during winter period at urban and suburban sites influenced by biomass burning (BB) emissions. As expected, larger aerosol number concentrations in the 12–25 and 25–100 nm size ranges are observed at the urban site compared to the suburban site. However, similar concentrations of BC are observed at both sites due to the larger contribution of BB particles to the observed BC at suburban (34%) in comparison to urban site (23%). Due to this influence of BB emissions in our study area, the application of the Rodríguez and Cuevas (2007) method, which was developed for areas mainly influenced by traffic emissions, leads to an overestimation of the primary vehicle exhaust particles concentrations by 18% and 26% in urban and suburban sites, respectively, as compared to our new proposed approach. The results show that (1) N2 is the main contributor in all size ranges at both sites, (2) N1ff is the main contributor to primary particles (>70%) in all size ranges at both sites and (3) N1bb contributes significantly to the primary particles in the 25–100 and 100–600 nm size ranges at the suburban (24% and 28%, respectively) and urban (13% and 20%, respectively) sites. At urban site, the N1ff contribution shows a slight increase with the increase of total particle concentration, reaching a contribution of up to 65% at high ambient aerosol concentrations. New particle formation events are an important aerosol source during summer noon hours but, on average, these events do not implicate a considerable contribution to urban particles.

The characteristics of carbonaceous particles down to the nanoparticle range in Rangsit city in the Bangkok Metropolitan Region, Thailand.

Atmospheric size-classified particles in sizes ranging from small to nanoparticles (PM0.1) are reported for Rangsit City in the Bangkok Metropolitan Region (BMR) of Thailand, for October 2019 (wet season) and January-February 2020 (dry season). The sampling involved the use of a PM0.1 cascade air sampler to determine the mass concentration. The PMs consisted of six stages including TSP-PM10, PM2.5-10, PM1.0-2.5, PM0.5-1.0, PM0.5-1.0 and PM0.1. Elemental carbon (EC) and organic carbon (OC) were evaluated by a carbon analyzer following the IMPROVE_TOR protocol. The average PM0.1 mass concentrations were found to be 13.47±0.79 (wet season) and 18.88±3.99 (dry season) μg/m3, respectively. The average OC/EC ratio for the rainy season was lower than that in the dry season. The char-EC/soot-EC ratios were consistently below 1 for the PM0.1 fraction in both seasons indicating that vehicular traffic appeared to be the main emission source. However, the influence of open biomass burning on fine and coarse PM particles on local air pollution was found to be an important issue during the wet season. In addition, long-range transport from other countries may also contribute to the carbon content in the Bangkok Metropolitan Region (BMR) atmosphere during the dry season. The higher secondary organic carbon to organic carbon (SOC/OC) ratio in the dry season is indicative of the contribution of secondary sources to the formation of PM, especially finer particles. A strong correlation between OC and EC in nanoparticles was found, indicating that they are derived from sources of constant emission, likely the diesel engines. Conversely, the OC and EC correlation for other size-specific PMs decreased during the dry season, indicating that these emission sources were more varied.

Characterization and Source Apportionment of PM2.5 Based on the Online Observation in Tianjin

To study the characterization and source apportionment of PM2.5 in Tianjin, based on high-resolution online monitoring data from 2017 to 2019, the concentrations and its chemical compositions and sources of PM2.5 were analyzed. The results showed that the average concentration of PM2.5 was 61 μg ·m-3. The primary chemical compositions of PM2.5 were nitrate, organic carbon (OC), ammonium, sulfate, elemental carbon (EC), and Cl- and their corresponding mass percentages to PM2.5 were 17.7%, 12.6%, 11.5%, 10.7%, 3.4%, and 3.1%, respectively. From 2017 to 2019, the concentrations of PM2.5 and its main chemical compositions exhibited a decreasing trend; the mass ratios of NO3- and NH4+ to PM2.5 exhibited an increasing trend, while the mass ratios of SO42-, OC, and EC to PM2.5 exhibited a decreasing trend; further, the mass ratio of Cl- exhibited a slight increasing trend. The concentrations of K+, Ca2+, and Na+ and their mass percentages to PM2.5 increased. The concentrations of PM2.5 and its primary components were relatively higher during heating season, and relatively lower during non-heating season. High values of SOR and NOR indicated that the secondary transformation of nitrate and sulfate played an important role during summer and autumn, which resulted in higher mass percentages of secondary inorganic ions (NO3-, SO42-, and NH4+) to PM2.5 during summer and autumn. When the PM2.5 concentrations were at excellent levels, the mass ratios of the secondary inorganic ions to PM2.5 were relatively lower, the mass ratios of OC, Ca2+, and Na+ to PM2.5 were relatively higher, and secondary organic carbon (SOC) was high. When the PM2.5 concentrations were between light pollution to heavy pollution levels, as the pollution levels increased, the mass percentages of secondary inorganic ions, OC, EC, and Cl-, and other components (K+, Ca2+, and Na+) showed a significant increasing trend, relatively stable level, slightly increasing trend, and decreasing trend, respectively. When PM2.5 concentrations were between moderate pollution to heavy pollution levels, the influence of vehicle emission increased significantly. The source apportionment of PM2.5 were analyzed using the positive matrix factorization model. The major sources of PM2.5 in Tianjin were secondary source, vehicle exhaust, industrial and coal combustion emissions, and crustal dust. From 2017 to 2019, the contribution of vehicle exhaust increased, and the contribution of secondary source and crustal dust showed a slight increasing trend, while the contribution of industrial and coal combustion emissions decreased. For Tianjin, vehicle exhaust and industrial and coal combustion emissions were the primary sources of PM2.5. The adjustment of industrial and energy structure and management and control of vehicle exhaust are the main directions for air pollution control in Tianjin.

Characterization of Two Heavy Pollution Episodes in Tianjin in 2020

High-resolution online monitoring data from January to February in 2020 was used to study the characterization of two heavy pollution episodes in Tianjin in 2020; the heavy pollution episode that lasted from January 16 to 18, 2020 (referred to as episode Ⅰ) and that from February 9 to 10, 2020 (referred to as episode Ⅱ) were analyzed. The results showed that two heavy pollution episodes were influenced by regional transportation in the early stage and local adverse meteorological conditions in the later stage. During these episodes, the average wind speed was low, the average relative humidity was close to 70%, and relative humidity approached the saturated, the boundary layer heights were below 300 m, and the horizontal and vertical diffusion conditions were poor. Compared to episode Ⅰ, the concentration of pollutants decreased during episode Ⅱ, especially for the concentration of NO2. During the episode Ⅱ, the concentrations of PM2.5 and CO were higher in the north of Tianjin. The chemical component concentrations and their mass ratios to PM2.5 changed significantly in both episodes; the concentrations of secondary inorganic ions (NO3-, SO42-, and NH4+), elemental carbon (EC) and Ca2+were higher in episode Ⅰ, the concentrations of organic carbon (OC) and Cl- slightly increased in episode Ⅱ; and the concentrations of K+were higher in episode Ⅱ. Compared to episode Ⅰ, because of the increase in the combustion sources and significant reductions in the number of vehicles, the mass ratios of SO42-, OC, and K+ to PM2.5 increased while the mass ratios of NO3- and EC to PM2.5 decreased in episode Ⅱ; the mass ratios of NH4+ and Cl- to PM2.5 were relatively higher due to the continuity of the industrial production processes; the mass ratios of Ca2+ to PM2.5 were lower in two heavy pollution episodes because construction activities were halted. Source apportionment of PM2.5 was performed using the positive matrix factorization (PMF) model. In episode Ⅰ, the major sources of PM2.5 in Tianjin were secondary sources, industrial and coal combustion, vehicle exhaust, crustal dust, fireworks and biomass burning, with contributions of 53.8%, 20.2%, 18.6%, 6.3%, and 1.1%, respectively. In episode Ⅱ, the same sources were identified in the PMF analysis with contributions of 48.3%, 28.2%, 8.7%, 2.6%, and 12.2%, respectively. Compared to episode Ⅰ, the contributions of industrial and coal combustion, fireworks and biomass burning increased, and the contributions of secondary sources, vehicle exhaust, and crustal dust decreased in episode Ⅱ; contributions of vehicle exhaust and crustal dust decreased by 53.2% and 58.7%, respectively.

Chemical Compositions and Sources Contribution of Atmospheric Particles at a Typical Steel Industrial Urban Site

Online monitoring concentrations of PM at five sites were obtained from 01/01/2016 to 31/12/2016 in Laiwu, China, and PM2.5 filters were manually sampled for total 34 days at the same sites in four seasons in 2016. PM pollution sources, including soil dust, urban dust, construction dust, coal-fired power plants dust, steel plant dust and motor vehicle exhaust dust were sampled, respectively. The overall mean PM2.5/PM10 ratio (0.57) in Laiwu was at a relatively lower level compared with that in other Chinese cities, which was higher in winter, indicating fine particulate was the main contributor of atmospheric pollution in this period. NH4+ mainly existed in the form of NH4NO3 and (NH4)2SO4 during the sampling periods. Higher sulfate and NH4+ concentrations were in summer while higher nitrate concentrations prevailed in winter. The annual value of OC/EC was (5.38 ± 1.70), higher in summer and lower in winter, and the calculated SOC/OC value (%) was (43.68 ± 12.98)%. The characteristic components were Si, Fe and Ca in urban dust and soil dust; Ca, Mg, and NH4+ in construction dust; Fe, Ca and SO42− in steel dust; OC, EC and Si in motor vehicle exhaust dust; SO42−, Al and NH4+ in power plant dust. Compared with other cities at home and abroad, it was found that the concentrations of metal elements in Laiwu were significantly higher than those in foreign cities, and at a medium level in China. With the improved CRAESCMB model, the urban dust was regarded as the receptor and the source of PM2.5 and apportioned its secondary sources contributions to PM2.5. The CMB results showed the contributions of secondary sources including sulfate (17%), nitrate (17%) and SOC (13%) to PM2.5 accounted for nearly half of all sources. Therefore, more attentions should be paid on secondary sources from the primary emission sources of the motor vehicle exhaust, coal combustion sources especially.

Significant Contribution of Primary Sources to Water-Soluble Organic Carbon During Spring in Beijing, China

Despite the significant role water-soluble organic carbon (WSOC) plays in climate and human health, sources and formation mechanisms of atmospheric WSOC are still unclear; especially in some heavily polluted areas. In this study, near real-time WSOC measurement was conducted in Beijing for the first time with a particle-into-liquid-sampler coupled to a total organic carbon analyzer during the springtime, together with collocated online measurements of other chemical components in fine particulate matter with a 1 h time resolution, including elemental carbon (EC), organic carbon (OC), multiple metals, and water-soluble ions. Good correlations of WSOC with primary OC, as well as carbon monoxide, indicated that major sources of WSOC were primary instead of secondary during the study period. The positive matrix factorization model-based source apportionment results quantified that 68 ± 19% of WSOC could be attributed to primary sources, with predominant contributions by biomass burning during the study period. This finding was further confirmed by the estimate with the modified EC-tracer method, suggesting significant contribution of primary sources to WSOC. However, the relative contribution of secondary source to WSOC increased during haze episodes. The WSOC/OC ratio exhibited similar diurnal distributions with O3 and correlated well with secondary WSOC, suggesting that the WSOC/OC ratio might act as an indicator of secondary formation when WSOC was dominated by primary sources. This study provided evidence that primary sources could be major sources of WSOC in some polluted megacities, such as Beijing. From this study, it can be seen that WSOC cannot be simply used as a surrogate of secondary organic aerosol, and its major sources could vary by season and location.

Chemical characteristics and source apportionment of PM2.5 using PMF modelling coupled with 1-hr resolution online air pollutant dataset for Linfen, China

The chemical species in PM2.5 and air pollutant concentration data with 1-hr resolution were monitored synchronously between 15 November 2018 and 20 January 2019 in Linfen, China, which were analysed for multiple temporal patterns, and PM2.5 source apportionment using positive matrix factorisation (PMF) modelling coupled with online chemical species data was conducted to obtain the apportionment results of distinct temporal patterns. The mean concentration of PM2.5 was 124 μg/m3 during the heating period, and NO3− and organic carbon (OC) were the dominant species. The concentrations and percentages of NO3−, SO42−, and OC increased notably during the growth periods of haze events, thereby indicating secondary particle formation. Six factors were identified by the PMF model during the heating period, including vehicular emissions (VE: 26.5%), secondary nitrate (SN: 16.5%), coal combustion and industrial emissions (CC&IE: 25.7%), secondary sulfate and secondary organic carbon (SS&SOC: 24.4%), biomass burning (BB: 1.0%), and crustal dust (CD: 5.9%). The primary sources of PM2.5 on clean days were CD (33.3%), VE (23.1%), and SS&SOC (20.6%), while they were CC&IE (32.9%) and SS&SOC (28.3%) during the haze events. The contributions of secondary sources and CC&IE increased rapidly during the growth periods of haze events, while that of CD increased during the dissipation period. Diurnal variations in the contribution of secondary sources were mainly related to the accumulation and transformation of corresponding gaseous precursors. In comparison, contributions of CC&IE and VE varied as a function of the domestic heating load and peak levels occurred during the morning and evening rush hours. High contributions of major sources (CC&IE and SS&SOC) during haze events originated mainly from the north and south, while high contribution of a major source (CD) on clean days was from the northwest.

A refined source apportionment study of atmospheric PM2.5 during winter heating period in Shijiazhuang, China, using a receptor model coupled with a source-oriented model

With the intensification of Chinese source control of air pollution, there is an urgent need for refined and rapid source apportionment techniques. A refined source apportionment method was constructed based on an off-line sampling dataset using a receptor model coupled with a source-oriented model, and the method was implemented in Shijiazhuang during the heating period. The refined results for source apportionment mainly included temporal, spatial, and source-category refinement data. The results indicated that the mean concentration of PM2.5 during the heating period was 96 μg/m3. Organic carbon (OC) and NO3− were found to be the dominant species of PM2.5 during the study. A high correlation was detected between elemental carbon (EC) and NO3− on polluted days, which was suggestive of the stagnant condition that accumulates EC and nitrate simultaneously. Secondary particle formation greatly promoted the occurrence of haze events. Secondary sources (34.9%), vehicle exhaust (18.6%), coal combustion (20.0%), industrial emissions (9.2%), crustal dust (9.7%), and biomass burning (7.6%) were the major sources during the heating period. The contributions of secondary sources and vehicle exhaust increased on polluted days, while those of coal combustion, industrial emissions and crustal dust decreased significantly. The contribution percentage of secondary sources from the southeast direction was basically the highest, while those of vehicle exhaust from the northwest or southeast directions were relatively higher as well, likely due to the distribution of traffic arteries. Based on the refined results for the source-category assessment, we found that the heating boilers (17.0%), non-road mobile (13.8%), diesel vehicles (10.4%), residential combustion (6.7%), road dust (5.5%), and architectural material industry (4.9%) were the major contributors to PM2.5. There was some uncertainty in the distribution proportions of the refined results, which were derived based on the emission inventory and the results of CALPUFF model.

Source directional apportionment of ambient PM2.5 in urban and industrial sites at a megacity in China

Abstract Refined source apportionment plays an important role in precise control of atmospheric particulate matter sources. PM2.5 samples were collected and analysed in Tian'jin from February to October 2016, and directional contribution of individual source category was apportioned by applying a new approach. Results indicated that the mean concentration of PM2.5 was 64 μg/m3 during the studying period. NO3− and OC were dominated species in PM2.5 mass. The concentrations of OC and Cl−, and OC/EC were higher in winter than other seasons. Secondary sources (SS), coal and biomass burning (CBB), vehicle exhaust (VE), crustal dust (CD), and industrial emission (IE), were identified as major sources using the PMF model, their contributions to PM2.5 were 28.6–38.1%, 17.3–20.1%, 21.1–23.5%, 10.9–14.2%, and 4.0–10.3%, respectively. The contributions of dust source and coal combustion in Tian'jin are decreasing, while that of motor vehicles is gradually highlighted. The contribution of secondary sources is maintained at a high level in recent years. Source contributions from the directions 1–3 (SW, NW, NE) for SS (16.8%, 8.5%, 4.0%), CBB (10.1%, 8.5%, 2.0%), VE (8.7%, 7.9%, 3.2%), CD (7.3%, 7.0%, 0.9%), and IE (4.2%, 3.8%, 1.4%), were observed at TG site. Source contributions from the directions1–4 (SW, WNW, NNW, NE) for SS (16.5%, 9.7%, 5.9%, 6.3%), CBB (8.0%, 5.0%, 2.5%, 1.9%), VE (8.5%, 6.8%, 3.5%, 3.3%), CD (5.9%, 3.2%, 2.0%, 1.0%), IE (2.0%, 0.9%, 0.6%, 0.6%), were observed at FK site. The contributions of major sources from SW direction were higher than other directions.

Chemical Composition Characteristics and Source Apportionment of PM2.5 During Winter in Taiyuan

To study the characteristics and sources of PM2.5 pollution in Taiyuan urban area in winter, PM2.5 and its chemical components (water-soluble ions, carbon components, and trace elements) and gaseous pollutants (SO2, NO2) were monitored by online instruments in January 2017. Combined with meteorological data, the characteristics of PM2.5 and its chemical components were analyzed. Also, source apportionment of PM2.5 was conducted by using positive matrix factorization (PMF). The results showed that the mean mass concentration of PM2.5 on polluted days (239.92 μg·m-3) was 5.70 times as much as that on clean days. The concentrations of the main chemical components of PM2.5 on polluted days, SO42-, NO3-, NH4+, Cl-, OC, and EC, were 7.04, 5.76, 6.51, 5.62, 4.06, and 4.70 times their respective values on clean days. The sulfur oxidation ratios (SOR) and the nitrogen oxidation ratios (NOR) on polluted days were 0.12 and 0.19, respectively, which were higher than those in clean days, indicating that secondary transformation was more significant on polluted days. The results of the PMF source apportionment showed that the contributions of secondary sources (35.06%), coal combustion (30.19%), and vehicle emissions (24.25%) were higher on polluted days than on clean days, with increases of 18.03%, 7.39% and 2.10%, respectively. Thus, air pollution control strategies should pay more attention to controlling secondary source precursors on the basis of controlling the primary emission sources on polluted days.

Source Apportionment of PM2.5 in Suburban Area of Beijing-Tianjin-Hebei Region in Autumn and Winter

To identify the main sources of PM2.5 in Beijing-Tianjin-Hebei (BTH) region, PM2.5 samples were collected at four suburban sites in BTH region during autumn and winter in 2014-2015. Source apportionment of PM2.5 was conducted using the chemical mass balance model (CMB). It shows that the main sources of PM2.5 in autumn and winter were secondary aerosols (36%-58%), traffic (8%-26%), residential coal combustion (8%-16%), and biomass burning (5%-16%). Secondary nitrate was the most important source of PM2.5 at most sites during autumn and winter (11%-27%). The source apportionment at different pollution levels indicates that the coherence of the increasing trend of different sources among the four sites were much more obvious in autumn than in winter. Also, the increasing contribution of secondary sources (47.2-115.7 μg·m-3) was much higher than that of primary sources (29.5-43.4 μg·m-3) in autumn, but such trend was not significant in winter. The total contribution of coal combustion at suburban sites was quite similar to that in urban sites, but in suburban areas residential coal combustion dominates the contribution from coal combustion. Thus, it is very necessary for suburban areas of the BTH region to control emissions from residential coal combustion.

Mass Concentrations and Carbonaceous Compositions of PM0.1, PM2.5, and PM10 at Urban Locations of Hanoi, Vietnam

24-hour samples of PM0.1, PM2.5, and PM10 were collected simultaneously for the first time at a roadside site (Vinacomin) and a mixed site (HUST) in Hanoi, Vietnam, during the wet (August) and dry seasons (October to December) in 2015. High levels of PM0.1 (6.06 ± 2.71 µg m–3), PM2.5 (71.06 ± 47.52 µg m–3), and PM10 (106.47 ± 63.95 µg m–3) were observed, especially in the rice straw open burning episode. The influence of some meteorological factors and trajectories on PM0.1 concentrations was negligible compared to larger particles. The average concentrations of organic carbon (OC) and elemental carbon (EC) for PM0.1, PM2.5, and PM10 were 2.77 ± 0.98 µg m–3 and 0.63 ± 0.32 µg m–3, 23.81 ± 21.16 µg m–3 and 6.17 ± 5.87 µg m–3, and 34.93 ± 20.07 µg m–3 and 8.38 ± 4.92 µg m–3, respectively. The total carbon (TC) accounted for 59.19%, 44.65%, and 43.79% of the mass of PM0.1, PM2.5, and PM10, respectively. The OC/EC ratios ranged 3.62–5.68, in which the ratios of PM0.1 were the highest, except for those in the biomass burning period. The char-EC/soot-EC ratios widely fluctuated (0.94–4.61), meaning higher efficiency in the source identification. Strong correlations between the OC and EC in all particle sizes were found (R2 = 0.84–0.99), excluding those of PM0.1 in the dry season at Vinacomin (R2 = 0.61), implying the influence of biomass burning. The concentrations of Secondary Organic Carbon (SOC) were 1.12 ± 0.43 µg m–3, 9.49 ± 8.26 µg m–3, and 9.59 ± 7.72 µg m–3, accounting for 42.7%, 42.3%, and 27.9% of the total OC for PM0.1, PM2.5, and PM10, respectively, indicating the dominant contribution of secondary sources to OC, especially in the finer particles. These results are highly valuable to Vietnam’s database of atmospheric particles.

Quantifying primary and secondary source contributions to ultrafine particles in the UK urban background

Total particle number (TNC, ≥7 nm diameter), particulate matter (PM2.5), equivalent black carbon (eBC) and gaseous pollutants (NO, NO2, NOx, O3, CO) have been measured at an urban background site in Leicester over two years (2014 and 2015). A derived chemical climatology for the pollutants showed maximum concentrations for all pollutants during the cold period except O3 which peaked during spring. Quantification of primary and secondary sources of ultrafine particles (UFPs) was undertaken using eBC as a tracer for the primary particle number concentration in the Leicester urban area. At the urban background site, which is influenced by fresh vehicle exhaust emissions, TNC was segregated into two components, TNC = N1 + N2. The component N1 represents components directly emitted as particles and compounds which nucleate immediately after emission. The component N2 represents the particles formed during the dilution and cooling of vehicle exhaust emissions and by in situ new particle formation (NPF). The values of highest N1 (49%) were recorded during the morning rush hours (07:00–09:00 h), correlating with NOx, while the maximum contribution of N2 to TNC was found at midday (11:00–14:00 h), at around 62%, correlated with O3. Generally, the percentage of N2 (57%) was greater than the percentage of N1 (43%) for all days at the AURN site over the period of the study. For the first time the impact of wind speed and direction on N1 and N2 was explored. The overall data analysis shows that there are two major sources contributing to TNC in Leicester: primary sources (traffic emissions) and secondary sources, with the majority of particles being of secondary origin.

Seasonal behavior of carbonyls and source characterization of formaldehyde (HCHO) in ambient air

Gas-phase formaldehyde (HCHO) is an intermediate and a sensitive indicator for volatile organic compounds (VOCs) oxidation, which drives tropospheric ozone production. Effective photochemical pollution control strategies demand a thorough understanding of photochemical oxidation precursors, making differentiation between sources of primary and secondary generated HCHO inevitable. Spatial and seasonal variations of airborne carbonyls based on two years of measurements (2012–2013), coupled with a correlation-based HCHO source apportionment analysis, were determined for three sampling locations in Hong Kong (denoted HT, TC, and YL). Formaldehyde and acetaldehyde were the two most abundant compounds of the total quantified carbonyls. Pearson's correlation analysis (r > 0.7) implies that formaldehyde and acetaldehyde possibly share similar sources. The total carbonyl concentration trends (HT < TC < YL) reflect location characteristics (urban > rural). A regression analysis further quantifies the relative primary HCHO source contributions at HT (∼13%), TC (∼21%), and YL (∼40%), showing more direct vehicular emissions in urban than rural areas. Relative secondary source contributions at YL (∼36%) and TC (∼31%) resemble each other, implying similar urban source contributions. Relative background source contributions at TC could be due to a closed structure microenvironment that favors the trapping of HCHO. Comparable seasonal differences are observed at all stations. The results of this study will aid in the development of a new regional ozone (O3) control policy, as ambient HCHO can enhance O3 production and also be produced from atmospheric VOCs oxidation (secondary HCHO).

Quantification of long-term primary and secondary source contributions to carbonaceous aerosols

Ambient fine particulate matter samples were collected during 2009–2013 in Chengdu, a megacity in western China, and the samples were speciated into organic carbon (OC), elemental carbon (EC), char-EC, soot-EC, eight carbon fractions, inorganic elements and water-soluble ions. Char-EC and soot-EC contribute to the better understanding of the sources and properties of EC. The highest levels of most carbon fractions were found in winter and May. The higher OC/EC ratio in winter suggests higher SOC fraction in winter, and higher char-EC/soot-EC ratio in May are the direct consequences of straw burning activities. Source contributions to PM2.5 and carbonaceous aerosols were quantified using the ME2 receptor model. Major contributors to OC in PM2.5 are vehicular exhaust (36.5%), coal combustion & straw burning (35.2%) and SOC (27.0%). The first two categories also contributed 51.4% and 49.3% of char-EC in PM2.5. Vehicular exhaust dominated soot-EC, contributing 63.0% to soot-EC in PM2.5. SOC contributed to high OC levels in winter due to the increase of precursor emissions and stable meteorological conditions. Coal combustion & straw burning show higher contributions to OC, char-EC and soot-EC in winter months and in May, which can be explained, in part, by increased coal consumption in winter and straw burning activities in May. Vehicular exhaust contributions are not strongly associated with monthly nor weekday-weekend patterns, resulting in that soot-EC vary insignificantly by month nor by weekday.

A global simulation of brown carbon: implications for photochemistry and direct radiative effect

Abstract. Recent observations suggest that a certain fraction of organic carbon (OC) aerosol effectively absorbs solar radiation, which is also known as brown carbon (BrC) aerosol. Despite much observational evidence of its presence, very few global modelling studies have been conducted because of poor understanding of global BrC emissions. Here we present an explicit global simulation of BrC in a global 3-D chemical transport model (GEOS-Chem), including global BrC emission estimates from primary (3.9 ± 1.7 and 3.0 ± 1.3 TgC yr−1 from biomass burning and biofuel) and secondary (5.7 TgC yr−1 from aromatic oxidation) sources. We evaluate the model by comparing the results with observed absorption by water-soluble OC in surface air in the United States, and with single scattering albedo observations at Aerosol Robotic Network (AERONET) sites all over the globe. The model successfully reproduces the seasonal variations of observed light absorption by water-soluble OC, but underestimates the magnitudes, especially in regions with high secondary source contributions. Our global simulations show that BrC accounts for 21 % of the global mean surface OC concentration, which is typically assumed to be scattering. We find that the global direct radiative effect of BrC is nearly zero at the top of the atmosphere, and consequently decreases the direct radiative cooling effect of OC by 16 %. In addition, the BrC absorption leads to a general reduction of NO2 photolysis rates, whose maximum decreases occur in Asia up to −8 % (−17 %) on an annual (spring) mean basis. The resulting decreases of annual (spring) mean surface ozone concentrations are up to −6 % (−13 %) in Asia, indicating a non-negligible effect of BrC on photochemistry in this region.