A large source of low-volatility secondary organic aerosol

How tiny aerosol particles form and grow from vapours produced by vegetation has been a mystery. The finding that highly oxygenated products form directly from volatile organic compounds may offer the solution. See Letter p.476 Forests emit large quantities of volatile organic compounds to the atmosphere. The condensable oxidation products of volatile organic compounds emitted by forests can form secondary organic aerosols or SOAs that can affect the Earth's radiation balance by scattering solar radiation and by acting as cloud condensation nuclei. But our understanding of the link between biogenic volatile organic compounds and their conversion to aerosol particles remains limited. This study reveals that a direct reaction pathway can lead from volatile organic compounds to low-volatility vapours that can then condense onto aerosol surfaces producing secondary organic aerosol and can significantly enhance the formation and growth of aerosol particles over forested regions.

Secondary organic aerosol formation and source contributions over east China in summertime

Abstract. In order to investigate the variability of the secondary organic aerosol (SOA) distributions and budget and provide a measure for the robustness of the conclusions on human induced changes of SOA, a global 3-dimensional chemistry transport model describing both the gas and the particulate phase chemistry of the troposphere has been applied. The response of the global budget of SOA to temperature and moisture changes as well as to biogenic emission changes over a decade (1984-1993) has been evaluated. The considered emissions of biogenic non-methane volatile organic compounds (VOC) are driven by temperature, light and vegetation. They vary between 756 and 810 Tg Cy-1 and are therefore about 5.5 times higher than the anthropogenic VOC emissions. All secondary aerosols (sulphuric, nitrates and organics) are computed on-line together with the aerosol associated water. Over the studied decade, the computed natural variations (8%) in the chemical SOA production from biogenic VOC oxidation equal the chemical SOA production from anthropogenic VOC oxidation. Maximum values are calculated for 1990 (warmer and drier) and minimum values for 1986 (colder and wetter). The SOA computed variability results from a 7% increase in biogenic VOC emissions from 1986 to 1990 combined with 8.5% and 6% increases in the wet and dry deposition of SOA and leads to about 11.5% increase in the SOA burden of biogenic origin. The present study also demonstrates the importance of the hydrological cycle in determining the built up and fate of SOA in the atmosphere. It also reveals the existence of significant positive and negative feedback mechanisms in the atmosphere responsible for the non linear relationship between emissions of biogenic VOC and SOA burden.

Abstract. The chemical and physical properties of secondary organic aerosol (SOA) formed by the photochemical degradation of biogenic and anthropogenic volatile organic compounds (VOC) are as yet still poorly constrained. The evolution of the complex refractive index (RI) of SOA, formed from purely biogenic VOC and mixtures of biogenic and anthropogenic VOC, was studied over a diurnal cycle in the SAPHIR photochemical outdoor chamber in Jülich, Germany. The correlation of RI with SOA chemical and physical properties such as oxidation level and volatility was examined. The RI was retrieved by a newly developed broadband cavity-enhanced spectrometer for aerosol optical extinction measurements in the UV spectral region (360 to 420 nm). Chemical composition and volatility of the particles were monitored by a high-resolution time-of-flight aerosol mass spectrometer, and a volatility tandem differential mobility analyzer. SOA was formed by ozonolysis of either (i) a mixture of biogenic VOC (α-pinene and limonene), (ii) biogenic VOC mixture with subsequent addition of an anthropogenic VOC (p-xylene-d10), or (iii) a mixture of biogenic and anthropogenic VOC. The SOA aged by ozone/OH reactions up to 29.5 h was found to be non-absorbing in all cases. The SOA with p-xylene-d10 showed an increase of the scattering component of the RI correlated with an increase of the O / C ratio and with an increase in the SOA density. There was a greater increase in the scattering component of the RI when the SOA was produced from the mixture of biogenic VOCs and anthropogenic VOC than from the sequential addition of the VOCs after approximately the same ageing time. The increase of the scattering component was inversely correlated with the SOA volatility. Two RI retrievals determined for the pure biogenic SOA showed a constant RI for up to 5 h of ageing. Mass spectral characterization shows the three types of the SOA formed in this study have a significant amount of semivolatile components. The influence of anthropogenic VOCs on the oxygenated organic aerosol as well as the atmospheric implications are discussed.

Secondary organic aerosol (SOA) particles are formed in the atmosphere from condensable oxidation products of anthropogenic and biogenic volatile organic compounds (VOCs). On a global scale, biogenic VOCs account for about 90% of VOC emissions and of SOA formation (90 billion kilograms of carbon per year). SOA particles can scatter radiation and act as cloud condensation or ice nuclei, and thereby influence the Earth's radiation balance and climate. They consist of a myriad of different compounds with varying physicochemical properties, and little information is available on the phase state of SOA particles. Gas-particle partitioning models usually assume that SOA particles are liquid, but here we present experimental evidence that they can be solid under ambient conditions. We investigated biogenic SOA particles formed from oxidation products of VOCs in plant chamber experiments and in boreal forests within a few hours after atmospheric nucleation events. On the basis of observed particle bouncing in an aerosol impactor and of electron microscopy we conclude that biogenic SOA particles can adopt an amorphous solid-most probably glassy-state. This amorphous solid state should provoke a rethinking of SOA processes because it may influence the partitioning of semi-volatile compounds, reduce the rate of heterogeneous chemical reactions, affect the particles' ability to accommodate water and act as cloud condensation or ice nuclei, and change the atmospheric lifetime of the particles. Thus, the results of this study challenge traditional views of the kinetics and thermodynamics of SOA formation and transformation in the atmosphere and their implications for air quality and climate.

Secondary organic aerosol importance in the future atmosphere

The formation and evolution of secondary organic aerosol during haze events in Beijing in wintertime

Compared to most other forest ecosystems, circumpolar boreal and subarctic forests have few tree species, and are prone to mass outbreaks of herbivorous insects. A short growing season with long days allows rapid plant growth, which will be stimulated by predicted warming of polar areas. Emissions of biogenic volatile organic compounds (BVOC) from soil and vegetation could be substantial on sunny and warm days and biotic stress may accelerate emission rates. In the atmosphere, BVOCs are involved in various gas-phase chemical reactions within and above forest canopies. Importantly, the oxidation of BVOCs leads to secondary organic aerosol (SOA) formation. SOA particles scatter and absorb solar radiation and grow to form cloud condensation nuclei (CCN) and participate in cloud formation. Through BVOC and moisture release and SOA formation and condensation processes, vegetation has the capacity to affect the abiotic environment at the ecosystem scale. Recent BVOC literature indicates that both temperature and herbivory have a major impact on BVOC emissions released by woody species. Boreal conifer forest is the largest terrestrial biome and could be one of the largest sources of biogenic mono- and sesquiterpene emissions due to the capacity of conifer trees to store terpene-rich resins in resin canals above and belowground. Elevated temperature promotes increased diffusion of BVOCs from resin stores. Moreover, insect damage can break resin canals in needles, bark, and xylem and cause distinctive bursts of BVOCs during outbreaks. In the subarctic, mountain birch forests have cyclic outbreaks of Geometrid moths. During outbreaks, trees are often completely defoliated leading to an absence of BVOC-emitting foliage. However, in the years following an outbreak there is extended shoot growth, a greater number of leaves, and greater density of glandular trichomes that store BVOCs. This can lead to a delayed chemical defense response resulting in the highest BVOC emission rates from subarctic forest in the 1–3 years after an insect outbreak. Climate change is expected to increase insect outbreaks at high latitudes due to warmer seasons and arrivals of invasive herbivore species. Increased BVOC emission will affect tropospheric ozone (O3) formation and O3 induced oxidation of BVOCs. Herbivore-induced BVOC emissions from deciduous and coniferous trees are also likely to increase the formation rate of SOA and further growth of the particles in the atmosphere. Field experiments measuring the BVOC emission rates, SOA formation rate and particle concentrations within and above the herbivore attacked forest stands are still urgently needed.

In areas where biogenic emissions are oxidized in the presence of anthropogenic pollutants, it has become increasingly apparent that secondary organic aerosol (SOA) formation from biogenic volatile organic compounds (BVOCs) is substantially enhanced. The Amazon forest is the dominant source of BVOCs globally, and the forest is rapidly being converted to urban and agricultural uses. We participated in a collaborative field study located in the Amazon region around Manaus, Brazil, in 2014 (Green Ocean Amazon; GoAmazon). This study was designed to comprehensively examine how BVOC emissions (specifically, the most highly emitted non-methane hydrocarbon, isoprene, and lesser studied sesquiterpenes) and their interaction with anthropogenic pollution (i.e., nitrogen oxides, sulfur dioxide, and black carbon) alter the atmosphere’s oxidative capacity, influence secondary aerosol formation, atmospheric composition and, ultimately, affect the earth’s radiation balance and climate. We provide the first hourly, in-situ measurement of 30 sesquiterpenes and 4 diterpenes, roughly estimating that sesquiterpene oxidation contributes to 10-14% of ozone reactive loss by terpenes and at least 0.4–5% (median 1 %) of total submicron OA mass. However, this is likely a low-end estimate, as evidence for additional unaccounted sesquiterpenes and their oxidation products clearly exists. We also provide new perspectives on sulfate, NO_x, and particle acidity influencing isoprene-derived SOA, comparing the central Amazon environment with Southeastern U.S.A. summer, representing clean to polluted conditions, respectively. We find that summed concentrations of isoprene-derived SOA tracers correlated with particulate sulfate spanning three orders of magnitude, suggesting that 1 μg m^-3 reduction in sulfate corresponds with at least ~0.5 μg m^-3 reduction in isoprene-derived SOA. We also find that SOA mass derived from isoprene oxidation in the presence of NO_x is primarily comprised of aerosol sulfate bound with isoprene oxidation products (i.e. organosulfates), ~97% in the Amazon and ~55% in the Southeastern U.S. We infer under natural conditions in high isoprene emission regions, preindustrial aerosol sulfate was almost exclusively isoprene-derived organosulfates, which are traditionally thought as representative of anthropogenic influence. We further report the first field observations showing that particle acidity impacts the distribution of isoprene oxidation tracers in the gas and particle phases, providing physicochemical insight into isoprene SOA formation chemistry. Coupled with other co-located measurements by the DOE Atmospheric Radiation Measurement (ARM) team and collaborating PIs at our measurement site (called T3), on the G1 aircraft, and at additional field sites (T0, T1, T2) this data set has been used to understand emission, oxidation, and particle formation pathways at the molecular level, to elucidate how these pathways change when influenced by anthropogenic sources, and to evaluate their importance for the atmospheric budget of aerosols and the earth’s radiation balance on regional scales. Recommendations: Further constraint of the role of sesquiterpenes on ozone (O₃) reactivity and SOA formation is limited by the availability of authentic standards and synthesized compounds of sesquiterpenes and their oxidation products. Future research efforts should focus on making such standards available via custom synthesis to allow for accurate quantification and focused oxidation experiments that will fully elucidate the chemistry of these compounds in the atmosphere. Further, reductions in aerosol sulfate (via SO₂ emissions control) continues to be one of the most effective methods to reduce SOA formation from isoprene, but the concerted role of ammonia (NH₃) gas emissions from (agricultural) industry and other sources requires more investigation to better understand the role of aerosol acidity in SOA formation and potential controls. As GoAmazon particles can be more acidic compared to areas with greater anthropogenic NH₃ emissions, this promotes relatively greater organosulfate (OS) formation from isoprene even in the presence of NO_x. Because OS and inorganic sulfate differ in water uptake properties, this implies preindustrial aerosol sulfate (albeit less abundant) may have been less reflective than current earth system models assume. Further research should investigate the radiative impacts of organic vs inorganic sulfate in aerosols to improve model representation. Finally, future work (currently underway) should include constraint of the contributions of monoterpene (C₁₀H₁₆) BVOCs and biomass burning VOCs as precursors to SOA formation in the region as well as their impacts on radiative forcing in the climate system.

<strong class="journal-contentHeaderColor">Abstract.</strong> Secondary organic aerosols (SOA) are an important component of atmospheric fine particulate matter (PM_2.5) in China, and elsewhere, with contributions from anthropogenic and biogenic volatile organic compounds (AVOC and BVOC) and semi- (SVOC) and intermediate volatility organic compounds (IVOC). Policy makers need to know which SOA precursors are important but accurate simulation of SOA magnitude and contributions remains uncertain. We reviewed SOA modelling studies in the past decade that have reported the relative contributions of different precursors to SOA concentration and the findings have many inconsistencies due to differing emission inventory methodologies/assumptions, air quality model (AQM) algorithms, and other aspects of study methodologies. We investigated the role of different AQM SOA algorithms by applying two commonly used models, CAMx and CMAQ, with consistent emission inventories to simulate SOA concentrations and contributions for July and November 2018 in China. Both models have a volatility basis set (VBS) SOA algorithm but with different parameters and treatments of SOA photochemical aging. BSOA (SOA produced from BVOC) is found to be more important over southern China whereas SOA generated from anthropogenic precursors is more prevalent in the North China Plain (NCP), Yangtze River Delta (YRD), Sichuan Basin and Central China. Both models indicate negligible SOA formation from SVOC emissions as compared to other precursors. In July when BVOC emissions are abundant, SOA is predominantly contributed by BSOA (except for NCP), followed by IVOC-SOA (i.e. SOA produced from IVOC) and ASOA (i.e. SOA produced from anthropogenic VOC). In contrast in November, IVOC becomes the leading SOA contributor for all selected regions except PRD, illustrating the important contribution of IVOC emissions to SOA formation. Therefore, future control policies should aim at reducing IVOC emissions as well as traditional VOC emissions. While both models generally agree in terms of the spatial distributions and seasonal variations of different SOA components, CMAQ tends to predict higher BSOA while CAMx generates higher ASOA concentrations. As a result, CMAQ results suggest that BSOA concentration is always higher than ASOA in November while CAMx emphasizes the importance of ASOA. Utilizing a conceptual model, we found that different treatment of SOA aging between the two models is a major cause of differences in simulated ASOA concentrations. The step-wise SOA aging scheme implemented in CAMx (based on gas-phase reactions with OH radical and similar to other models) exhibits a strong enhancement effect on simulated ASOA concentrations and this effect increases with the ambient OA concentrations. The CMAQ VBS implements a different SOA aging scheme that represents particle-phase oligomerization and has smaller impacts, or no impact, on total OA. A brief literature survey shows that different structure and/or parameters of the SOA aging schemes are being used in current models, which could greatly affect model simulations of OA in ways that are difficult to anticipate. Our results indicate that large uncertainties still exist in the simulation of SOA in current air quality models due to the aging schemes as well as uncertainties of the emission inventory. More sophisticated measurement data and/or chamber experiments are needed to better characterize SOA aging and constrain model parameterizations.

<strong class="journal-contentHeaderColor">Abstract.</strong> Secondary organic aerosols (SOA) are an important component of atmospheric fine particulate matter (PM_2.5) in China, and elsewhere, with contributions from anthropogenic and biogenic volatile organic compounds (AVOC and BVOC) and semi- (SVOC) and intermediate volatility organic compounds (IVOC). Policy makers need to know which SOA precursors are important but accurate simulation of SOA magnitude and contributions remains uncertain. We reviewed SOA modelling studies in the past decade that have reported the relative contributions of different precursors to SOA concentration and the findings have many inconsistencies due to differing emission inventory methodologies/assumptions, air quality model (AQM) algorithms, and other aspects of study methodologies. We investigated the role of different AQM SOA algorithms by applying two commonly used models, CAMx and CMAQ, with consistent emission inventories to simulate SOA concentrations and contributions for July and November 2018 in China. Both models have a volatility basis set (VBS) SOA algorithm but with different parameters and treatments of SOA photochemical aging. BSOA (SOA produced from BVOC) is found to be more important over southern China whereas SOA generated from anthropogenic precursors is more prevalent in the North China Plain (NCP), Yangtze River Delta (YRD), Sichuan Basin and Central China. Both models indicate negligible SOA formation from SVOC emissions as compared to other precursors. In July when BVOC emissions are abundant, SOA is predominantly contributed by BSOA (except for NCP), followed by IVOC-SOA (i.e. SOA produced from IVOC) and ASOA (i.e. SOA produced from anthropogenic VOC). In contrast in November, IVOC becomes the leading SOA contributor for all selected regions except PRD, illustrating the important contribution of IVOC emissions to SOA formation. Therefore, future control policies should aim at reducing IVOC emissions as well as traditional VOC emissions. While both models generally agree in terms of the spatial distributions and seasonal variations of different SOA components, CMAQ tends to predict higher BSOA while CAMx generates higher ASOA concentrations. As a result, CMAQ results suggest that BSOA concentration is always higher than ASOA in November while CAMx emphasizes the importance of ASOA. Utilizing a conceptual model, we found that different treatment of SOA aging between the two models is a major cause of differences in simulated ASOA concentrations. The step-wise SOA aging scheme implemented in CAMx (based on gas-phase reactions with OH radical and similar to other models) exhibits a strong enhancement effect on simulated ASOA concentrations and this effect increases with the ambient OA concentrations. The CMAQ VBS implements a different SOA aging scheme that represents particle-phase oligomerization and has smaller impacts, or no impact, on total OA. A brief literature survey shows that different structure and/or parameters of the SOA aging schemes are being used in current models, which could greatly affect model simulations of OA in ways that are difficult to anticipate. Our results indicate that large uncertainties still exist in the simulation of SOA in current air quality models due to the aging schemes as well as uncertainties of the emission inventory. More sophisticated measurement data and/or chamber experiments are needed to better characterize SOA aging and constrain model parameterizations.

<strong class="journal-contentHeaderColor">Abstract.</strong> Secondary organic aerosols (SOA) are an important component of atmospheric fine particulate matter (PM_2.5) in China, and elsewhere, with contributions from anthropogenic and biogenic volatile organic compounds (AVOC and BVOC) and semi- (SVOC) and intermediate volatility organic compounds (IVOC). Policy makers need to know which SOA precursors are important but accurate simulation of SOA magnitude and contributions remains uncertain. We reviewed SOA modelling studies in the past decade that have reported the relative contributions of different precursors to SOA concentration and the findings have many inconsistencies due to differing emission inventory methodologies/assumptions, air quality model (AQM) algorithms, and other aspects of study methodologies. We investigated the role of different AQM SOA algorithms by applying two commonly used models, CAMx and CMAQ, with consistent emission inventories to simulate SOA concentrations and contributions for July and November 2018 in China. Both models have a volatility basis set (VBS) SOA algorithm but with different parameters and treatments of SOA photochemical aging. BSOA (SOA produced from BVOC) is found to be more important over southern China whereas SOA generated from anthropogenic precursors is more prevalent in the North China Plain (NCP), Yangtze River Delta (YRD), Sichuan Basin and Central China. Both models indicate negligible SOA formation from SVOC emissions as compared to other precursors. In July when BVOC emissions are abundant, SOA is predominantly contributed by BSOA (except for NCP), followed by IVOC-SOA (i.e. SOA produced from IVOC) and ASOA (i.e. SOA produced from anthropogenic VOC). In contrast in November, IVOC becomes the leading SOA contributor for all selected regions except PRD, illustrating the important contribution of IVOC emissions to SOA formation. Therefore, future control policies should aim at reducing IVOC emissions as well as traditional VOC emissions. While both models generally agree in terms of the spatial distributions and seasonal variations of different SOA components, CMAQ tends to predict higher BSOA while CAMx generates higher ASOA concentrations. As a result, CMAQ results suggest that BSOA concentration is always higher than ASOA in November while CAMx emphasizes the importance of ASOA. Utilizing a conceptual model, we found that different treatment of SOA aging between the two models is a major cause of differences in simulated ASOA concentrations. The step-wise SOA aging scheme implemented in CAMx (based on gas-phase reactions with OH radical and similar to other models) exhibits a strong enhancement effect on simulated ASOA concentrations and this effect increases with the ambient OA concentrations. The CMAQ VBS implements a different SOA aging scheme that represents particle-phase oligomerization and has smaller impacts, or no impact, on total OA. A brief literature survey shows that different structure and/or parameters of the SOA aging schemes are being used in current models, which could greatly affect model simulations of OA in ways that are difficult to anticipate. Our results indicate that large uncertainties still exist in the simulation of SOA in current air quality models due to the aging schemes as well as uncertainties of the emission inventory. More sophisticated measurement data and/or chamber experiments are needed to better characterize SOA aging and constrain model parameterizations.

Chemical formation pathways of secondary organic aerosols in the Beijing-Tianjin-Hebei region in wintertime

Modeling of secondary organic aerosols (SOA) based on two commonly used air quality models in China: Consistent S/IVOCs contribution but large differences in SOA aging

Climate models project a further increase in the average global temperature for the following decades, with Alpine regions (and their ecosystems) expected to be over-proportionally more affected. Biogenic volatile organic compounds (BVOCs) comprise the largest, most highly complex, and diverse fraction of the volatile organic compounds (VOCs) emitted into the atmosphere (1). By emitting BVOCs, plants communicate, fight herbivores, and attract pollinators (2). It is well known that biotic stressors (e.g., insects feeding on plants) lead to changes in plants' BVOC emissions: certain compounds can be promoted, and others reduced. Atmospheric oxidation of BVOCs affects the concentration of methane, carbon monoxide, and tropospheric ozone, leading to the formation of Secondary Organic Aerosol (SOA). Atmospheric aerosol load is crucial in defining the radiative balance and negatively impacts air-quality standards (3). Stress-induced changes in plant emissions may thus lead to changes in atmospheric chemistry and SOA properties (e.g., ref. 4). The impact of prolonged changes in abiotic factors and abiotic stress (e.g., heat and drought) on plants' BVOC composition and emissions quantities, and how this may impact atmospheric chemistry and SOA properties, need to be better understood.&amp;#160; Within the experimental project "Acclimation and environmental memory&amp;#8221; (AccliMemo), we study BVOC composition and quantities at basal conditions and under prolonged heat and drought. To this purpose, Scots pine (Pinus Sylvestris) seedlings were grown from seeds collected from selected mother trees from the long-term irrigation experiment Pfynwald. Those mother trees experienced different long-term water availability. This also allows us to examine the consequence of transgenerational memory on BVOC emissions (5).&amp;#160; Our conference contribution will give insight into our findings from plant chamber experiments and address i) gas-phase BVOC samples collected on sorbent tubes and analyzed by Thermal Desorption GC-MS and ii) gas-phase BVOC measurements collected in-situ using a PTR-ToF-MS. These data provide a well-resolved picture of terpene compositions and diurnal trends in emission levels. The BVOC analysis in the gas phase is complemented by a detailed analysis of the secondary metabolites in needle samples. Secondary metabolites are extracted in organic solvents and analyzed by liquid injection GC-FID/MS.&amp;#160; Bibliography&amp;#160; (1) Sindelarova, K., Granier, C., Bouarar, I., Guenther, A., Tilmes, S., Stavrakou, T., M&amp;#252;ller, J.-F., Kuhn, U., Stefani, P., and Knorr, W.: Global data set of biogenic VOC emissions calculated by the MEGAN model over the last 30 years, Atmospheric Chem. Phys., 14, 9317&amp;#8211;9341, https://doi.org/10.5194/acp-14-9317-2014, 2014. (2) Niinemets, &amp;#220;. and Monson, R. K. (Eds.): Biology, Controls and Models of Tree Volatile Organic Compound Emissions, Springer Netherlands, Dordrecht, https://doi.org/10.1007/978-94-007-6606-8, 2013. (3) Seinfeld, John H. and Pandis, Spyros N.: Atmospheric Chemistry and Physics: From Air Pollution to Climate Change, 3rd Edition., Wiley, 1152 pp., 2016. (4) Smith, N. R., et al.: Viscosity and liquid&amp;#8211;liquid phase separation in healthy and stressed plant SOA, Environ. Sci. Atmospheres, 1, 140&amp;#8211;153, https://doi.org/10.1039/D0EA00020E, 2021. (5) Bose, A. K., et al.: Memory of environmental conditions across generations affects the acclimation potential of scots pine, Plant Cell Environ., 43, 1288&amp;#8211;1299, https://doi.org/10.1111/pce.13729, 2020. Funding: Swiss National Science Foundation, Project Numbers 189109, 199317, and, 194390.