scholarly journals Potential dual effect of anthropogenic emissions on the formation of biogenic secondary organic aerosol (BSOA)

2019 ◽  
Vol 19 (24) ◽  
pp. 15651-15671 ◽  
Author(s):  
Eetu Kari ◽  
Liqing Hao ◽  
Arttu Ylisirniö ◽  
Angela Buchholz ◽  
Ari Leskinen ◽  
...  

Abstract. The fraction of gasoline direct-injection (GDI) vehicles comprising the total vehicle pool is projected to increase in the future. However, thorough knowledge about the influence of GDI engines on important atmospheric chemistry processes is missing – namely, their contribution to secondary organic aerosol (SOA) precursor emissions, contribution to SOA formation, and potential role in biogenic–anthropogenic interactions. The objectives of this study were to (1) characterize emissions from modern GDI vehicles and investigate their role in SOA formation chemistry and (2) investigate biogenic–anthropogenic interactions related to SOA formation from a mixture of GDI-vehicle emissions and a model biogenic compound, α-pinene. Specifically, we studied SOA formation from modern GDI-vehicle emissions during the constant-load driving. In this study we show that SOA formation from GDI-vehicle emissions was observed in each experiment. Volatile organic compounds (VOCs) measured with the proton-transfer-reaction time-of-flight mass spectrometer (PTR-ToF-MS) could account for 19 %–42 % of total SOA mass generated in each experiment. This suggests that there were lower-volatility intermediate VOCs (IVOCs) and semi-volatile organic compounds (SVOCs) in the GDI-vehicle exhaust that likely contributed to SOA production but were not detected with the instrumentation used in this study. This study also demonstrates that two distinct mechanisms caused by anthropogenic emissions suppress α-pinene SOA mass yield. The first suppressing effect was the presence of NOx. This mechanism is consistent with previous reports demonstrating suppression of biogenic SOA formation in the presence of anthropogenic emissions. Our results indicate a possible second suppressing effect, and we suggest that the presence of anthropogenic gas-phase species may have suppressed biogenic SOA formation by alterations to the gas-phase chemistry of α-pinene. This hypothesized change in oxidation pathways led to the formation of α-pinene oxidation products that most likely did not have vapor pressures low enough to partition into the particle phase. Overall, the presence of gasoline-vehicle exhaust caused a more than 50 % suppression in α-pinene SOA mass yield compared to the α-pinene SOA mass yield measured in the absence of any anthropogenic influence.

2017 ◽  
Vol 17 (17) ◽  
pp. 10743-10752 ◽  
Author(s):  
Jianfei Peng ◽  
Min Hu ◽  
Zhuofei Du ◽  
Yinhui Wang ◽  
Jing Zheng ◽  
...  

Abstract. Gasoline vehicle exhaust is an important contributor to secondary organic aerosol (SOA) formation in urban atmosphere. Fuel composition has a potentially considerable impact on gasoline SOA production, but the link between fuel components and SOA production is still poorly understood. Here, we present chamber experiments to investigate the impacts of gasoline aromatic content on SOA production through chamber oxidation approach. A significant amplification factor of 3–6 for SOA productions from gasoline exhausts is observed as gasoline aromatic content rose from 29 to 37 %. Considerably higher emission of aromatic volatile organic compounds (VOCs) using high-aromatic fuel plays an essential role in the enhancement of SOA production, while semi-volatile organic compounds (e.g., gas-phase PAHs) may also contribute to the higher SOA production. Our findings indicate that gasoline aromatics significantly influence ambient PM2. 5 concentration in urban areas and emphasize that more stringent regulation of gasoline aromatic content will lead to considerable benefits for urban air quality.


2018 ◽  
Vol 18 (19) ◽  
pp. 13813-13838 ◽  
Author(s):  
Sailaja Eluri ◽  
Christopher D. Cappa ◽  
Beth Friedman ◽  
Delphine K. Farmer ◽  
Shantanu H. Jathar

Abstract. Laboratory-based studies have shown that combustion sources emit volatile organic compounds that can be photooxidized in the atmosphere to form secondary organic aerosol (SOA). In some cases, this SOA can exceed direct emissions of primary organic aerosol (POA). Jathar et al. (2017a) recently reported on experiments that used an oxidation flow reactor (OFR) to measure the photochemical production of SOA from a diesel engine operated at two different engine loads (idle, load), two fuel types (diesel, biodiesel), and two aftertreatment configurations (with and without an oxidation catalyst and particle filter). In this work, we used two different SOA models, the Volatility Basis Set (VBS) model and the Statistical Oxidation Model (SOM), to simulate the formation and composition of SOA for those experiments. Leveraging recent laboratory-based parameterizations, both frameworks accounted for a semi-volatile and reactive POA; SOA production from semi-volatile, intermediate-volatility, and volatile organic compounds (SVOC, IVOC and VOC); NOx-dependent parameterizations; multigenerational gas-phase chemistry; and kinetic gas–particle partitioning. Both frameworks demonstrated that for model predictions of SOA mass to agree with measurements across all engine load–fuel–aftertreatment combinations, it was necessary to model the kinetically limited gas–particle partitioning in OFRs and account for SOA formation from IVOCs, which were on average found to account for 70 % of the model-predicted SOA. Accounting for IVOCs, however, resulted in an average underprediction of 28 % for OA atomic O : C ratios. Model predictions of the gas-phase organic compounds (resolved in carbon and oxygen space) from the SOM compared favorably to gas-phase measurements from a chemical ionization mass spectrometer (CIMS), substantiating the semi-explicit chemistry captured by the SOM. Model–measurement comparisons were improved on using SOA parameterizations corrected for vapor wall loss. As OFRs are increasingly used to study SOA formation and evolution in laboratory and field environments, models such as those developed in this work can be used to interpret the OFR data.


2017 ◽  
Author(s):  
Sailaja Eluri ◽  
Christopher D. Cappa ◽  
Beth Friedman ◽  
Delphine K. Farmer ◽  
Shantanu H. Jathar

Abstract. Laboratory-based studies have shown that combustion sources emit volatile organic compounds that can be photo-oxidized in the atmosphere to form secondary organic aerosol (SOA). In some cases, this SOA can exceed direct emissions of primary organic aerosol (POA). Jathar et al. (2017) recently reported on experiments that used an oxidation flow reactor (OFR) to measure the photochemical production of SOA from a diesel engine operated at two different engine loads (idle, load), two fuel types (diesel, biodiesel) and two aftertreatment configurations (with and without an oxidation catalyst and particle filter). In this work, we used two different SOA models, the volatility basis set (VBS) model and the statistical oxidation model (SOM), to simulate the formation and composition of SOA for those experiments. Leveraging recent laboratory-based parameterizations, both frameworks accounted for a semi-volatile and reactive POA; SOA production from semi-volatile, intermediate-volatility and volatile organic compounds (SVOC, IVOC and VOC); multigenerational gas-phase chemistry; and kinetic gas/particle partitioning. Both frameworks demonstrated that for model predictions of SOA mass to agree with measurements across all engine load-fuel-aftertreatment combinations, it was necessary to model the kinetically-limited gas-particle partitioning in OFRs as well as account for SOA formation from IVOCs, which were found to account for more than 90 % of the model-predicted SOA. Accounting for IVOCs however resulted in an underprediction of a factor of two for OA atomic O : C ratios. Model predictions of the gas-phase organic compounds (resolved in carbon and oxygen space) from the SOM compared favorably to gas-phase measurements from a Chemical Ionization Mass Spectrometer (CIMS), substantiating the semi-explicit chemistry captured by the SOM. Model-measurement comparisons were improved on using vapor wall-loss corrected SOA parameterizations. As OFRs are increasingly used to study SOA formation and evolution in laboratory and field environments, models such as those developed in this work can be used to interpret the OFR data.


Author(s):  
Hind A. A. Al-Abadleh

Extensive research has been done on the processes that lead to the formation of secondary organic aerosol (SOA) including atmospheric oxidation of volatile organic compounds (VOCs) from biogenic and anthropogenic...


2019 ◽  
Vol 19 (11) ◽  
pp. 7429-7443 ◽  
Author(s):  
Tian Feng ◽  
Shuyu Zhao ◽  
Naifang Bei ◽  
Jiarui Wu ◽  
Suixin Liu ◽  
...  

Abstract. The implementation of the Air Pollution Prevention and Control Action Plan in China since 2013 has profoundly altered the ambient pollutants in the Beijing–Tianjin–Hebei (BTH) region. Here we show observations of substantially increased O3 concentrations (about 30 %) and a remarkable increase in the ratio of organic carbon (OC) to elemental carbon (EC) in BTH during the autumn from 2013 to 2015, revealing an enhancement in atmospheric oxidizing capacity (AOC) and secondary organic aerosol (SOA) formation. To explore the impacts of increasing AOC on the SOA formation, a severe air pollution episode from 3 to 8 October 2015 with high O3 and PM2.5 concentrations is simulated using the WRF-Chem model. The model performs reasonably well in simulating the spatial distributions of PM2.5 and O3 concentrations over BTH and the temporal variations in PM2.5, O3, NO2, OC, and EC concentrations in Beijing compared to measurements. Sensitivity studies show that the change in AOC substantially influences the SOA formation in BTH. A sensitivity case characterized by a 31 % O3 decrease (or 36 % OH decrease) reduces the SOA level by about 30 % and the SOA fraction in total organic aerosol by 17 % (from 0.52 to 0.43, dimensionless). Spatially, the SOA decrease caused by reduced AOC is ubiquitous in BTH, but the spatial relationship between SOA concentrations and the AOC is dependent on the SOA precursor distribution. Studies on SOA formation pathways further show that when the AOC is reduced, the SOA from oxidation and partitioning of semivolatile primary organic aerosol (POA) and co-emitted intermediate volatile organic compounds (IVOCs) decreases remarkably, followed by those from anthropogenic and biogenic volatile organic compounds (VOCs). Meanwhile, the SOA decrease in the irreversible uptake of glyoxal and methylglyoxal on the aerosol surfaces is negligible.


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