Nitrate radicals suppress biogenic new particle formation from monoterpene oxidation

doi:10.21203/rs.3.rs-2722087/v1

Download PDF

Article

Nitrate radicals suppress biogenic new particle formation from monoterpene oxidation

https://doi.org/10.21203/rs.3.rs-2722087/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Highly oxygenated organic molecules (HOMs) are a major source of new particles affecting Earth’s climate^1,2. HOM production from the oxidation of volatile organic compounds (VOCs) occurs during both day and night, and can lead to new particle formation (NPF)^3,4. However, NPF involving organic vapors has been reported much more often during daytime^3-6 than during nighttime^7,8. Here, we show that the nitrate radicals (NO₃) - which arise predominantly at night – inhibit NPF during the oxidation of monoterpenes based on three lines of observational evidence: NPF experiments in the CLOUD chamber at CERN; radical chemistry experiments using an oxidation flow reactor; and field observations in a wetland that occasionally exhibits nocturnal NPF. Nitrooxy-peroxy radicals formed from NO₃ chemistry suppress the production of ultra-low volatility organic compounds (ULVOCs) responsible for biogenic NPF, which are covalently bound RO₂ dimer association products. The ULVOC yield of α-pinene in the presence of NO3 is one-fifth of that resulting from ozone chemistry alone. Even trace amounts of NO₃ radicals, at sub parts per trillion level, suppress the NPF rate by a factor of 4. Ambient observations further confirm that when NO₃ chemistry is involved, monoterpene NPF is completely turned off. Our results explain the frequent absence of nocturnal biogenic NPF in monoterpene-rich environments.

Earth and environmental sciences/Climate sciences/Atmospheric science/Atmospheric chemistry

Earth and environmental sciences/Environmental sciences/Environmental chemistry/Atmospheric chemistry

More than half of cloud condensation nuclei (CCN) are formed through gas-to-particle conversion of oxidation products, a process called new particle formation (NPF)^6,9. Gaseous species responsible for atmospheric NPF include sulfuric acid, nitric acid, iodine oxoacids, and highly oxygenated organic molecules (HOMs)^5,10−13. HOMs are formed from the gas-phase oxidation of biogenic and anthropogenic volatile organic compounds (VOCs) through multiple autoxidation reactions of peroxy radicals (RO₂)^1,3,14. It is well established that HOMs play an important role both in nucleation itself and in particle growth, either alone or by stabilizing sulfuric acid clusters^4,15,16.

Pure organic nucleation appears to be driven by highly functionalized accretion products, which are of ultralow- or extremely low volatility and are thought to be peroxides (ROOR) formed via rapid RO₂ self/cross-reactions^4,17−20. Daytime VOC oxidation is usually initiated by reactions with hydroxyl radicals (OH) and ozone (O₃)^21,22, whereas nocturnal VOC oxidation is often initiated by nitrate radicals (NO₃) in addition to O₃^23–25. Although dimers are mainly formed during nighttime, notably from ozone chemistry, NPF involving organic species at night is rarely reported^5,26,27. The mechanism suppressing biogenic NPF at night remains uncertain, although it is suspected that NO₃ chemistry may play a role^28,29. For example, it has been suggested that NO₃ oxidation of α-pinene, the most abundant monoterpene globally, is a less efficient source of SOA than oxidation by either OH or O₃^30,31. However, a recent study has shown a higher SOA yield from the α-pinene + NO₃ system depending on different RO₂ fates³². It is important to note that involvement in nucleation and growth is a subset of SOA formation, and therefore it stands to reason that NO₃ oxidation might also be an inefficient source of particles. As a result, the exact role of NO₃ radicals on the formation and growth of particles remains highly uncertain.

Here we examine the reactivity of α-pinene with varying levels of NO₃ radicals and the influence of different HOM composition on NPF. We draw on three datasets: experiments conducted in the CLOUD chamber (Cosmics Leaving OUtdoor Droplets) at CERN (European Organization for Nuclear Research); laboratory oxidation flow reactor (OFR) experiments; and field measurements in a wetland surrounded by boreal forests (Siikaneva, Finland) (see Methods for experimental details). Controlled laboratory experiments were performed using α-pinene, as it is one of the most abundant biogenic VOCs in the atmosphere³³ and one of the key precursors for the production of HOMs⁴. We oxidized α-pinene in the presence of O₃ and NO₃ radicals produced from the reaction of NO₂ with O₃. Various mass spectrometers equipped with chemical ionization inlets using different reagent ions (i.e., NH₄⁺, NO₃^–) were deployed to determine the chemical composition of neutral gas-phase oxygenated VOCs (OVOCs), including HOMs.

NPF with different oxidants

Figure 1 shows the evolution of reactant and reaction product concentrations together with the resulting particle formation rates measured in the CLOUD chamber. We broke the experiment into three stages to examine different radical chemistry under otherwise identical conditions, including approximately 1000 parts per billion (ppbv) of carbon monoxide to scavenge the OH radicals formed from the ozonolysis of α-pinene and homogeneous illumination from four Hg-Xe arc lamps (UVH, Supplementary Fig. 1). We first examined the reaction of α-pinene with O₃. At t = 0 min, nitrogen dioxide (NO₂) was continuously injected to form NO₃. The production rate of NO₃ was 0.3 ppbv h^− 1, similar to that observed in the atmosphere³⁴, and the NO₃ concentration was estimated using a 0-D box model (F0AM)³⁵. Finally, at t = 80 min, LEDs at 385 nm (LS3) were switched on to form nitrogen monoxide (NO) via NO₂ photolysis and convert NO₃ into NO₂. The three conditions were thus: pure ozonolysis; ozonolysis perturbed by NO₃; and ozonolysis perturbed by NO_x.

Non-nitrogen containing OVOCs (CHO) formed through the ozonolysis of α-pinene comprise monomers C_9,10H_12,14,16,18O_≥2 (CHO monomers) and dimers C_19,20H_28,30,32O_≥4 (CHO dimers), which predominated during its ozonolysis. NO₂ injection and NO₃ formation resulted in a sharp decrease in the concentrations of CHO dimers (Fig. 1B). Ultimately, CHO dimers were completely suppressed as NO₃ radicals rose toward a concentration of only 0.6 pptv, even though measured O₃ and α-pinene concentrations remained constant (Fig. 1A). Meanwhile, we observed a large formation of nitrogen-containing species (CHON), including monomers C_9,10H_13,15,17O_≥4N (CHON monomers) and two classes of dimers (CHON dimers): C_19,20H_29,31,33O_≥5N (CHON₁ dimers) and C₂₀H₃₂O_≥ 8N₂ (CHON₂ dimers), with the concentrations of CHON dimers being higher those of CHO dimers during pure ozonolysis (~ 1.4-fold) (Fig. 1B). Good agreement between NH₄⁺-Orbitrap and NO₃^–-LTOF (a nitrate CI atmospheric pressure interface long time of flight mass spectrometer)³⁶ for the detection of CHO and CHON species indicates similar sensitivity for the different mass spectrometers (Supplementary Fig. 2).

Added NO₃ increased the overall concentration of dimers due to the greater formation of CHON dimers. During this stark change in dimer composition, the net formation rate of particles at 1.7 nm (J_1.7) decreased by a factor of 4, implying that NO₃ chemistry strongly suppresses α-pinene NPF (Fig. 1C). After switching on the lights at t = 80 min, the NO₃ radicals were scavenged mainly by reaction with NO as well as by photolysis; subsequently, oxidation proceeded via ozonolysis under high NO_x conditions. The presence of NO_x terminated the bimolecular reactions of RO₂ generated from the O₃ + α-pinene (CHO RO₂) and formed CHON monomers (Fig. 1B and Supplementary Fig. 3), whereas the formation pathway of CHON dimers was cut off due to the absence of nitrooxy peroxy radicals, which are generated from the NO₃ radical addition to α-pinene (CHON RO₂). As Fig. 1C shows, the particle formation rates did not change even at higher CHO concentrations when the lights were turned on, which is consistent with previously observed lower J values at higher NO_x³⁷. This indicates that NO₃ chemistry suppresses particle formation to a similar extent as NO does³⁷, even though NO₃ initiated oxidation of α-pinene yields a large concentration of dimeric compounds, unlike NO.

The evolution of the α-pinene reacted in the NO₃ chemistry stage is shown in Fig. 1D. The same amount of α-pinene reacted with O₃ in the presence of NO₃ radicals, while the total reacted α-pinene increased by 10%. NO₃ chemistry suppression of NPF occurred even though most of the α-pinene oxidation was still driven by O₃ (Fig. 1D and Supplementary Fig. 4), and even though the overall concentration of dimers produced with NO₃ present was substantially higher than that during the pure ozonolysis³⁸. Our F0AM simulations show that, almost all CHO RO₂ radicals predominantly undergo self-/cross-reactions and also reactions with HO₂ pathway, indicating the presence of NO₃ and NO_x did not fundamentally modify the dimer branching ratios of RO₂ radicals (Supplementary Fig. 5). The results suggest that CHON RO₂ produced from NO₃ oxidation are highly reactive and dimers formed through NO₃ chemistry must be significantly more volatile than dimers formed from O₃ chemistry. This is similar to isoprene suppression of biogenic NPF where the resulting oxidation products (i.e., C₁₄-C₁₅ dimers) are more volatile than those from monoterpenes alone^39,40.

Importantly, the sharp decrease in particle formation rates occurred at very low NO₃ concentrations relative to O₃, even though the reaction with O₃ remained the dominant α-pinene oxidation process (Fig. 1D and Supplementary Fig. 4). Thus, NO₃ chemistry fundamentally alters the product distributions and volatility, even when it represents only a small fraction of the total α-pinene reactivity, i.e., less than 30% (Supplementary Fig. 4).

HOM distribution at different NO₃ levels

To further investigate the influence of different steady-state concentrations of NO₃ radicals on α-pinene oxidation, we performed extensive OFR experiments in the presence of O₃, OH, and NO₃ radicals. In addition to an experiment without any NO₂ addition, we also investigated eight NO₂ to O₃ ratios between 0.03:1 (close to the ratio of 0.023:1 for the CLOUD experiments) and 1.5:1 (Supplementary Fig. 6). Over this range, no NPF occurred due to the short residence time inside OFR, and the simulation shows that the rate of the α-pinene reaction with O₃ remained constant, but the total α-pinene reactivity increased by a factor of 3 relative to O₃/OH chemistry (Supplementary Fig. 7a). Ultimately up to ~ 80% of the α-pinene loss was from NO₃ oxidation at the highest NO₂:O₃ (Supplementary Fig. 7b). Meanwhile, fraction of α-pinene oxidized by OH radicals decreased from 44–6% because NO₂ scavenged the OH. Similarly, other than reaction with NO₂ (resulting in approximately 50 to 2000 pptv of N₂O₅ in the OFR), NO₃ radicals were almost completely consumed by α-pinene, and the reactions of CHO RO₂ + NO₃ and CHO RO₂ + NO₂ did not play a significant role in modifying the product distribution (Supplementary Fig. 8).

Like the CLOUD observations, the presence of NO₃ radicals fundamentally alters the product distribution (Supplementary Fig. 9). All CHON dimers identified in the CLOUD chamber were found in OFR, but more CHON monomers and OH-initiated species were observed in OFR due to its short residence time and the absence of OH scavenger (Supplementary Fig. 10). Figure 2 shows the sensitivity of oxidation products generated from α-pinene and the fraction reacting with NO₃ vs. O₃/OH. Specifically, at maximal NO₃ concentrations, CHO dimers intensity is ~ 10 times lower compared to experiments performed without NO₃ (Fig. 2A). CHO monomers are much less sensitive to the increasing level of NO₃ radicals in α-pinene oxidation, with only a 2.3-fold decrease, which is probably due to the cross reactions of CHO RO₂ and CHON RO₂. This is consistent with our F0AM simulation, which shows a 1.4-fold decrease for the less oxidized CHO monomers (i.e., O_2 − 5) concentrations (Supplementary Fig. 11). However, the sharper reduction of the most oxidized CHO (i.e., O_> 6) as the NO₃ contribution increases (up to 10-fold decrease) indicates that the suppression of ozonolysis products by NO₃ is most important for the most highly oxygenated monomer and dimer products (Fig. 2, A and B, and Supplementary Fig. 12).

In contrast to CHO dimers (10-folds decrease), the concentrations of products identified as CHO RO₂ (with an odd number of H atoms, including C₁₀H₁₅O_4 − 10 and C₁₀H₁₇O_3 − 7) do not differ much in the presence of NO₃ versus O₃/OH chemistry, with slight fluctuations across all different NO₃ reactivities (Fig. 2B). In contrast to a 20% reduction in simulated C₁₀H₁₅O_x radicals, the measured C₁₀H₁₅O_x rose with NO₃ radicals, likely due to the additional C₁₀H₁₅O_x produced by the H-abstraction pathway from the reaction of NO₃ radicals with α-pinene which was not included in the model (Supplementary Fig. 11, 12e, and 13). Concentrations of C₁₀H₁₇O_5,7 radicals from OH chemistry decreased by a factor of 9 due to the lowered reactivity of α-pinene with OH and more loss via bimolecular reactions (Supplementary Figs. 7 and 12f). CHON RO₂ (including C₁₀H₁₆O_5,6,7,9N) started to play an important or even dominant role as soon as NO₃ radicals were produced (Supplementary Fig. 13, and 14e).

Unlike O₃/OH chemistry, NO₃ chemistry yields a solitary RO₂ species (i.e., C₁₀H₁₆NO₅), the autoxidation of which is very limited. This is shown by comparing the signal of a “parent” RO₂ to its more oxygenated autoxidation products (Supplementary Fig. 13). Although uncertainties remained in the quantification of RO₂ radical concentrations, chemical ionizations were reported to exhibit the same sensitivity for the O₃-derived RO₂ radicals⁴¹, and NH₄⁺-Orbitrap did not show any distinct sensitivity to CHON species compared to CHO species (Supplementary Fig. 2). The average ratio of C₁₀H₁₅O₄ to (C₁₀H₁₅O₆ + C₁₀H₁₅O₈), which are ozonolysis products, was 4.0 ± 0.3. In contrast, the ratio of C₁₀H₁₆NO₅ to (C₁₀H₁₆NO₇ + C₁₀H₁₆NO₉), from NO₃ oxidation, was 72 ± 14 (Supplementary Fig. 13). Such a large difference is likely caused by the ring-retaining structure of C₁₀H₁₆NO₅ preventing the H-shift isomerization involved in the autoxidation of peroxy radicals^41,42. The concentrations of CHON RO₂, CHON₁ dimers, and CHON monomers seemed to be constant when the α-pinene reactivity by NO₃ reached ~ 40%, indicating that newly formed CHON RO₂ proceed immediately via a propagation cycle to form RO radicals or via an accretion reaction to form CHON₂ dimers at higher NO₃ levels (Supplementary Fig. 14).

The contribution to total dimers of CHON₁ dimers generated from the cross reaction between CHON RO₂ and CHO RO₂ increased with an increasing contribution of NO₃ to α-pinene reactivity and peaked (67%) when the α-pinene reaction rate with NO₃ radicals was greater than 5 ppbv h^− 1, corresponding to ~ 40% of total α-pinene reactivity, after which its dominance was gradually replaced by CHON₂ dimers produced from CHON RO₂ self/cross-reactions (Fig. 2C, and Supplementary Fig. 7). The proportion of CHON monomers to total monomers also reached its highest value (60%) at this α-pinene reaction rate (i.e., 5 ppbv h^− 1), and then remained constant (Fig. 2D). Results obtained with the CI-Orbitrap operated in negative mode (NO₃^–) further support the role of CHON RO₂ in the distribution of OVOCs (Supplementary Fig. 15). However, it should be mentioned that the nitrate reagent ion is selective towards HOMs, i.e., n_O > 6 for CHO monomers and n_O > 8 for CHON monomers, which explains the general decreasing trend of OVOCs (i.e., monomers and dimers) measured by the CI-(NO₃^–)-Orbitrap. Overall, the OFR results indicate that the presence of CHON RO₂ competes against autoxidation and CHO dimers formation, two mechanisms responsible for monoterpene NPF, resulting in a net reduction of CHO species formed from O₃/OH oxidation.

Change of HOM volatility distribution by NO₃

Higher volatilities of CHON dimers than CHO dimers in the particle phase are confirmed by thermal desorption measurements performed by a FIGAERO-CIMS (Filter Inlet for Gases and AEROsols coupled to a chemical ionization time of flight mass spectrometer)⁴³ (Fig. 3A). It is worth mentioning that unlike monomers, thermal fragmentation contributions are negligible for larger compounds like dimers during particle desorption within the FIGAERO^44,45. The maximum desorption temperatures (T_max) of particulate CHON dimers were much lower (40-85°C) than T_max of particulate CHO dimers (~ 110°C), corresponding to saturation vapor concentrations (C_sat) of 10^− 3 to 10¹ µg m^− 3 for CHON dimers and 10^− 5 to 10^− 7 µg m^− 3 for CHO dimers⁴⁶. The saturation vapor concentrations of particulate OVOCs in the CLOUD chamber experiments are predicted using the volatility basis set (VBS) parameterizations^47,48 (see Methods). Parameterized log₁₀C_sat agree well with the measured log₁₀C_sat for particulate CHO species (Supplementary Fig. 16a). In addition, measured log₁₀C_sat of particulate dimers show a good correlation (R² = 0.85) with their estimated log₁₀C_sat using the modified Li et al. approach⁴⁸ accounting for nitrate functionalities (Supplementary Fig. 16b).

Therefore, we estimated the volatility distribution of the full-range OVOCs measured by CI-(NH₄⁺)-Orbitrap in the CLOUD chamber (Fig. 3B, and Supplementary Fig. 17) using the modified Li et al. approach⁴⁸. As shown in Fig. 3B, we grouped monomers C_9 − 10 and dimers C_{18 − 20} measured in the CLOUD chamber into five volatility regimes based on their log₁₀C_sat values^49,50; ultra-low volatility (ULVOCs), extremely low-volatility (ELVOCs), low-volatility (LVOCs), semi-volatile (SVOCs), and intermediate-volatility organic compounds (IVOCs). Only the ULVOCs and some ELVOCs initiate cluster growth and form new particles^50,51. In each volatility bin, we show the signal of the sum of OVOCs that fall in this volatility range. Due to the negligible CHON RO₂ autoxidation, the volatility distribution of OVOCs shifts towards relatively higher volatility in the presence of NO₃ radicals compared to the distribution from pure O₃ chemistry (Fig. 3B). The resulting average signal-weighted C_sat value is 2 times higher in the presence of NO₃ radicals. However, the effect is most dramatic in the tail, for compounds directly involved in NPF. The contribution of ELVOCs drops by a factor of 2 (i.e., from 1.7–0.8%), and the ULVOCs, which contribute most efficiently to pure biogenic nucleation⁵¹, comprise 0.6% of the total measured OVOCs in the pure O₃ system but decrease to 0.1% in the presence of NO₃ radicals (Fig. 3C). The lowest volatility bins of the ULVOC range (log₁₀C_sat<-13 µg m^− 3) vanish entirely. A 5-fold reduction of the ULVOC yield was also quantified using the NO₃^–-LTOF.

As the OVOC composition changed during the experiment, the decrease of the measured particle formation rates at 1.7 nm by a factor of 4 (see also Fig. 1C) is likely driven by the decreasing concentration of ULVOCs caused by an increase in the NO₃ radical concentration, although the a-pinene O₃ reactivity remained constant (Fig. 1D and 3D). Overall, the results demonstrate that NO₃ radicals inhibit the production of the least volatile compounds and ultimately impede the formation of new particles.

Nocturnal NPF in a wetland. We further investigated the role of NO₃ radicals in suppressing NPF from the ozonolysis of monoterpenes by conducting nighttime observations in a wetland surrounded by boreal forests in Siikaneva, Finland. At this location, we did observe rare nocturnal NPF events (Supplementary Fig. 18), which were found to be accompanied with a decoupled layer formation capturing the emissions from the wetland inside this stable surface layer and nearly no mixing with the rest of the atmosphere⁵². More details for the characteristics of these nocturnal NPF events can be found in Junninen et al.⁵² and Huang et al.⁵³. Similar OVOC species as in the CLOUD chamber were detected in this ambient environment (Supplementary Fig. 19). Monoterpenes were found to be the dominating VOCs at this site (Supplementary Fig. 20), and the most abundant monoterpene species there were found to be α-pinene and Δ³-carene⁵⁴. These species were thus used to calculate the reactivity of different monoterpene isomers in wetland, in order to represent the reactivity range in Siikaneva by assuming the total monoterpene concentration is that of one monoterpene. The resulting reactivity of ozonolysis with these two monoterpenes and the generated concentrations of CHO dimer were on average 3 times and 2 times higher during the nighttime NPF event compared to nonevent night, respectively, with the dominating monoterpene ozonolysis reactivity in Siikaneva from α-pinene (Fig. 4, and Supplementary Fig. 21a). Further, concentrations of CHO monomer and CHO dimer were 4 and 10 times higher than those of CHON monomer and CHON dimer during the NPF event, respectively, with total CHO species representing 80% of total OVOCs. In contrast, sharp increases of CHON monomer and CHON dimer were observed only during the nonevent when no decoupling process occurred but in well-mixed conditions with the rest of the atmosphere⁵². The presence of CHON dimer, which are markers for NO₃ chemistry, indicates the presence of NO₃ during the nonevent night^29,52, which was estimated at nearly 1 ppqv, resulting in a reactivity of monoterpene 0.2 pptv h^− 1 during the nonevent night (NO₂:O₃ ≈ 0.007:1) with the reactivity of monoterpenes by NO₃ radicals in Siikaneva mainly coming from α-pinene (Supplementary Fig. 21b). These were associated with a corresponding drop in ULVOC and ELVOC concentration both by a factor of 6 (Fig. 4G). Consistent with the CLOUD experiments, the particle number concentration is up to one order of magnitude (3-fold in median) lower during the nonevent night compared to event night (Fig. 4A).

Taken together, these results form the basis of a molecular understanding of why biogenic NPF is not commonly observed at night, especially in monoterpene-dominated environments. The NO₃-derived RO₂ radicals formed from monoterpene oxidations not only yield higher volatility dimers but also completely alter the fate of RO₂ radicals from other oxidants and thus the capacity to form new particles. The nitrogen-containing organic vapors formed from NO₃ chemistry are not of sufficiently low volatility to initiate the formation and growth of particles. When only 20–30% of the α-pinene reactivity is driven by NO₃, ULVOC yields are reduced by a factor of 5 and particle formation rates by a factor of 4. In the ambient atmosphere, particle number is cut by up to an order of magnitude in monoterpene-dominated environments when NO₃ chemistry is involved.

In general, the quantity and volatility distribution of HOMs, HOM-RO₂, and RO₂ produced from concurrent complex chemical reactions can substantially alter the formation of new particles in the atmosphere. This is especially important for organic NPF governed by covalently bound dimers, where cross-reactions between different RO₂ control the ULVOC tail of the volatility distribution, and exact NPF rates depend even on the volatility distribution within that tail. In some cases, such as for isoprene suppression of monoterpene nucleation, it is the mixture of organic precursors that influences the outcome^39,40. In others, such as for NO_x suppression, it is inhibition of dimer formation that affects the outcome³⁷. Here, for NO₃ suppression, it is the oxidant that influences the outcome. Our results highlight a need for more realistic consideration of NPF processes in the atmosphere, especially when multiple oxidants/processes are involved. In addition, the influence of NO₃ derived from NO_x represents an anthropogenic perturbation on a biogenic system, which have broader implications for the understanding of aerosol sources and CCN in the modern atmosphere.

Kinetic and product characterization in the oxidation flow reactor. The oxidation of α-pinene initiated by ozone and nitrate radical (NO₃) was conducted in an 18-liter Pyrex glass oxidation flow reactor (OFR, 12 cm i.d. × 158 cm length) under dry conditions, at room temperature of 296 ± 1 K and atmospheric pressure ⁵⁵. The total flow rate was kept at 16 standard litres per minute (slpm) using synthetic air (N₂/O₂ 80:20) and the residence time was 67.5 s. The volatile organic compound (VOC) precursors, (+)-α-pinene (Sigma-Aldrich, ≥ 99%), ozone, and NO₂ were injected continuously using mass flow controllers (MFC, Bronkhorst). Input VOC concentration was fixed at approximately 8 ± 1 ppbv and retrieved using a quadrupole mass spectrometer (IONICON, PTR-QMS 300). NO₃ radicals were generated from the oxidation of NO₂ with O₃ in an external 1-liter pre-reactor at atmospheric pressure and room temperature. The pre-reactor was dimmed to prevent the photolysis of NO₃ by room lights. 500 standard cm³ min^− 1 (sccm) of O₂ was passed through a stable ozone generator (Fisher Scientific, SOG-1) to generate ~ 900 ppbv of O₃ within the pre-reactor (corresponding to ~ 50 ± 5 ppbv after dilution in the flow tube). O₃ is mixed with a variable NO₂ flow in the pre-reactor to produce different NO₃ radical concentrations. The total flow in pre-reactor was fixed at 1 slpm, giving a reaction time of 60 s. Then the mixture of NO₃, O_3, and excess NO₂ enters OFR and reacts with α-pinene. The concentrations of O₃ and NO₂ in OFR outflow (ranging from 1.9 to 75 ± 2 ppbv in the flow tube) were retrieved using a Thermo 49C, and a Ecophysics CLD 88p equipped with a photolytic converter PLC 860, respectively. The particle formation was measured by a condensation particle counter (TSI CPC 3772) and remained negligible (< 100 cm^− 3) during all flow tube experiments. A chemical ionization coupled to a Q-Exactive Orbitrap mass spectrometer (CI-Orbitrap, Thermo Scientific) monitored the oxidation products.

Particle formation in CLOUD chamber. New particle formation experiments were performed at CERN in the CLOUD (Cosmics Leaving OUtdoor Droplets) chamber, a 3-m-diameter electropolished stainless steel vessel of 26.1 m³. This chamber enables to achieve a high standard of cleanliness and discussed in detail by Kirkby et al.⁴. The evaporation of cryogenic liquid nitrogen (N₂) and liquid oxygen (O₂) was blended at a ratio of 79:21 to produce pure synthetic air, which flushed the chamber constantly. Variable amounts of trace gases, for example, O₃, VOCs, NOx, SO₂, and CO were precisely injected into the system as needed and monitored. 250 optical fiber-optic systems installed on top of the chamber are utilized to initiate photolytic reactions, including Hg-Xe UV lamps, and UV excimer laser. The CLOUD chamber is cleaned by irrigating the walls with ultra-pure water, heating to 373 K, and flushing with humidified pure air and the high ozone concentration, declining the contaminant levels such as VOCs to less 1 ppbv. The particles were wiped out under a high voltage electric field. During the CLOUD 14 campaign, the total flow was kept at 250 slpm with an average residence time of 105 mins. With mounting in a thermal housing, the CLOUD chamber temperature was maintained at 264 ± 0.1 K and relative humidity at 20% for the NO₃ run. The contents of the chamber were ceaselessly detected and analyzed by a wide range of external instruments connected to the sampling probes ~ 1 m protruding into the chamber. The chamber instrumentation for the results reported here comprised an atmospheric pressure chemical ionization inlet coupled to an ultrahigh-resolution Orbitrap mass spectrometer (CI-Orbitrap) for retrieving the chemical composition of gaseous (highly) oxygenated volatile organic compounds (OVOC)⁵⁶, a nitrate chemical ionization atmospheric pressure interface long time of flight mass spectrometer (CI-(NO₃^–)-APi-LTOF, Aerodyne Research Inc. and Tofwerk AG) from the University of Frankfurt³⁶ for providing the reference of highly oxygenated molecules (HOMs) concentration, an iodide-adduct chemical ionization time of flight mass spectrometer equipped with a Filter Inlet for Gases and AEROsols (FIGAERO-CIMS) for the composition of particle phase, a proton transfer reaction time-of-flight (PTR-TOF) mass spectrometer for organic precursors concentrations⁵⁷, a CPC battery at 2.5–12 nm thresholds (mobility diameters), a di-ethylene glycol CPC (DEG-CPC) at 2.0 nm threshold⁵⁸, a nano-scanning electrical mobility spectrometer (nSEMS) for 1.5–25 nm particle size⁵⁹, trace gas analyzers to measure ozone (O₃, Thermo Fisher Scientific Inc. 42i-TLE), nitric oxide (NO, ECO Physics, CLD 780TR) and nitrogen dioxide monitor (CAPS NO₂, Aerodyne Research Inc.) and dew point mirrors (EdgeTech) for RH of the chamber.

Field campaign in Siikaneva, Finland. The ambient observation was conducted between March 10 and June 15, 2016 in a wetland, Siikaneva, southern Finland (61° 49’ 59.4”N, 24°92 11’ 32.4”E). It is located ~ 5 km west of the Station for Measuring Ecosystem – Atmosphere Relations (SMEAR) II station, which is located in a boreal forest at Hyytiälä. Air temperature was measured with Rotronic HC2 sensor (Rotronic 88 AG, Switzerland). Global radiation was measured by a Kipp & Zonen CNR4 radiometer (OTT HydroMet B.V., The Netherlands). A proton transfer reaction time-of-flight mass spectrometer (PTR-TOF, Ionicon Analytik GmbH) using H₃O⁺ as the ion source was used to measure VOC concentrations. A chemical ionization atmospheric pressure interface time-of-flight mass spectrometers (CI-APi-TOF, Aerodyne Research Inc.) using NO₃^– as the reagent ion was deployed to measure the molecular composition of ambient neutral clusters. Number concentrations of particles with a mobility diameter larger than 2.5 nm were recorded with a condensation particle counter (CPC3776, TSI Inc). Number concentration and size distribution of atmospheric ions and neutral particles with a mobility diameter of 0.8–42 nm were measured with a neutral cluster and air ion spectrometer (NAIS, Airel Ltd.).

Orbitrap technology. CI-Orbitrap technology has been described elsewhere and prior studies have reported its capabilities to study atmospheric reactive organic species successfully^56,60. For this study, ammonium and nitrate ions (NH₄⁺ / NO₃^–) were used as reagent ion of CI-Orbitrap for the detection of an extensive range of OVOCs. NO₃^– ionization has been described elsewhere⁵⁶, and NH₄⁺ adduct ion chemistry has already been utilized with PTR-MS as discussed by Lindinger et al.⁶¹ and with the novel PTR3-TOF by Hansel et al.⁶² or Berndt et al.¹⁸ and shown excellent sensitivity to detect OVOCs. Therefore, for this study, OVOCs refer to oxidized organic compounds that can be detected, including HOMs (O > 6) and the lower oxidized molecules (O = 2-5) in positive mode.

NH₃ was added to the ion source taking 5 sccm from the headspace of a 1% of liquid ammonium hydroxide solution (25% NH₃ basis, ACS reagent, Sigma-Aldrich). The product molecules (prod) were softly charged by binding to ammonium ions, forming (prod)-NH₄⁺ adduct ions or protonated products (prod)-H⁺, following equations (1) and (2).

NH₄⁺ + prod → (prod)-NH₄⁺ (1)

NH₄⁺ + prod → (prod)-H⁺ + NH₃ (2)

The Orbitrap was externally mass-calibrated using a 2 mM sodium acetate solution (Aldrich, > 99%

purity) in an electrospray ionization source. The drift in mass accuracy remained within 2 ppm throughout the experiments. The formula assignment of measured ions was constrained by known oxidation chemistry and elemental composition, i.e., ions are assumed to contain only carbon, hydrogen, oxygen, and nitrogen atoms (up to three N atoms to account for adduction of NH₄⁺).

Volatility of HOMs. Since HOM are difficult to synthesis and their vapor pressures are too low for the methods currently used to detect volatility, direct measurements of the volatilities of individual HOM are very challenging. Numerous model calculations, such as so-called group contribution approaches⁶³ or parameterizations based on the oxidation state^64,65. We use a volatility parameterization to calculate effective saturation mass concentration (C_sat) of individual organic compounds according to their structure-based estimations and formula-based estimations using the modified Li et al. approach^48,65 as in Eq. (3):

$${log}_{10}{C}_{sat}\left(298K\right)=\left({n}_{C}^{0}-{n}_{C}\right){b}_{C}-{n}_{O}{b}_{O}-2\frac{{n}_{C}{n}_{O}}{({n}_{C}+{n}_{O})}{b}_{CO}-{n}_{N}{b}_{N}-{n}_{S}{b}_{S}$$

where ${n}_{C}$, ${n}_{O}$, ${n}_{N}$, and ${n}_{S}$ are the number of carbon, oxygen, nitrogen, and sulfur atoms of the specific molecule, separately; ${n}_{C}^{0}$ is the reference carbon number; ${b}_{C}$, ${b}_{O}$, ${b}_{N}$, and ${b}_{S}$ are the contribution of each atom to ${log}_{10}{C}_{sat}$, separately; ${b}_{CO}$ is the carbon-oxygen nonideality⁶⁴. Values of b coefficient can be found in Li et al.⁶⁵. The formula used to estimate the vapor pressure is amended to convert all NO₃ groups into OH groups to reduce the bias from the compounds containing nitrates^48,66.

Due to the different temperatures in the CLOUD 14 experiments, we adjusted the ${C}_{sat}\left(298K\right)$ to the measured experimental temperature in equations (4) and (5):

$${log}_{10}{C}_{sat}\left(T\right)={log}_{10}{C}_{sat}\left(298K\right)+\frac{\varDelta {H}_{vap}}{Rln\left(10\right)}\times (\frac{1}{298}-\frac{1}{T})$$

$$\varDelta {H}_{vap}\left(kJ {mol}^{-1}\right)= -11\bullet {log}_{10}{C}_{sat}\left(298K\right)+129$$

where $T$ is the temperature in kelvin; ${C}_{sat}\left(298K\right)$ is the saturation mass concentration at 298 K; $\varDelta {H}_{vap}$ is the evaporation enthalpy and R is the gas constant (8.3134 J K^− 1 mol^− 1). The potential presence of isomers may result in uncertainty in this method since the only input is molecular formula.

In this study, all oxidation products were grouped into six volatility regimes; ultralow-volatility (ULVOCs), ${C}_{sat}$ < 10^−8.5 µg m⁻³, extremely low volatility (ELVOCs), 10^−8.5 < ${C}_{sat}$ < 10^−4.5 µg m⁻³, low-volatility (LVOCs), 10^−4.5 < ${C}_{sat}$ < 10^−0.5 µg m^− 3, semi-volatile (SVOCs), 10^−0.5 < ${C}_{sat}$ < 10^2.5 µg m⁻³, intermediate-volatility organic compounds (IVOC), 10^2.5 < ${C}_{sat}$ < 10^6.5 µg m⁻³, and VOC, 10^6.5 < ${C}_{sat}$µg m⁻³ based on VBS.

Kinetic model simulations. The behaviors of NO₃, N₂O₅, RO₂ (C₁₀H₁₅O₄, C₁₀H₁₇O₃ and C₁₀H₁₆NO₅), the corresponding less oxidized monomers formed from the oxidation reaction of α-pinene by O₃/OH and NO₃ radicals under typical experimental conditions were simulated simply using the F0AM v3.1³⁵ box model employing MCM v3.3.1⁶⁷. The RO₂ autoxidation reactions and NO₃ chemistry-related packages were not considered in the model.

Acknowledgements: We thank the European Organization for Nuclear Research (CERN) for supporting CLOUD with important technical and financial resources. We thank the Orbitool team for developing the tools to analyze mass spectra and the F0AM people for developing systems to simulate atmospheric chemistry.

Funding: This work was financially supported by the French National program LEFE (Les Enveloppes Fluides et l’Environnement), the European Research Council (ERC-StG MAARvEL; no. 852161 and ERC-StG CHAPAs; no. 850614), the European Union’s Horizon 2020 Research and Innovation programme (Marie Sklodowska-Curie Grant Agreement no.764991), the Swiss National Science Foundation (nos. 200020_172602 and 20FI20_172622), and the US National Science Foundation (nos. AGS-1801574, AGS-1801897, AGS-2132089 and AGS-1801280). The PSI team thanks the European Commission Horizon 2020 Research and Innovation Framework Program, ATMO-ACCESS Integrating Activity (grant agreement No 101008004). D.D.L. thanks the China Scholarship Council of P. R. China for the Ph.D. grant and supports by State Environment Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex (No. CX2020080582). J.A.T. was supported with a grant from the U.S. Department of Energy Atmospheric System Research Program (DE-SC0021097). H.J. thanks European Regional Development Fund (project MOBTT42), Estonian Research Council (project PRG714). W.S. thanks the University of Innsbruck for her doctoral scholarship (2021/1). X.C.H. thanks Jenny and Antti Wihuri Foundation for providing funding for this research.

Author Contributions: D.D.L., D.Y.W., M.Y.W., L.C., B.R., R.M., W.S., H.F., G.M., D.M.B., Z.B., J.C., L.D., J.D., X.D.G., A.H., X.-C.H., V.H., H.J., J.E.K., A.K., H.L., K.L., B.L., N.G.A.M., H.E.M., B.M., S.P., J.P., M.P., M.S., S.S., J.L.S., M.S., S.T., R.V., X.K.W., S.K.W., A.W., D.R.W., Y.S.W., M.Z.-W., M.K., J.K., N.M.D., C.G., I.E.-H., and M.R. prepared the CLOUD facility or measuring instruments. D.D.L., D.Y.W., M.Y.W., L.C., B.R., R.M., W.S., H.F., G.M., D.M.B., J.D., X.D.G., X.-C.H., V.H., H.L., B.L., N.G.A.M., B.M., M.S., J.L.S., M.S., S.K.W., Y.S.W., M.Z.-W., J.K., and M.R. collected the CLOUD data. D.D.L., W.H., D.Y.W., M.Y.W., L.C., B.R., R.M., W.S., H.F., G.M., H.L., S.K.W., and M.R. analysed the data. D.D.L., D.Y.W., S.P., C.G., I.E.-H., and M.R. planned the flow tube experiments. W.H., H.J., T.P., M.K., and F.B. planned the field campaign and/or data analysis. D.D.L., J.A.T., and M.R. provided model calculations. D.D.L., W.H., D.Y.W., M.Y.W., J.A.T., L.C., B.R., R.M., W.S., H.F., U.B., X.D.G., A.H., H.J., K.L., Y.G.M., B.M., S.P., T.P., S.T., R.V., X.K.W., C.Y., J.K., N.M.D., C.G., I.E.-H., F.B., and M.R. contributed to the scientific discussion. D.D.L., W.H., D.Y.W., M.Y.W., J.A.T., U.B., N.M.D., C.G., I.E.-H., F.B., and M.R. wrote the manuscript. All authors discussed the results and commented on the paper.

Bianchi, F. et al. Highly Oxygenated Organic Molecules (HOM) from Gas-Phase Autoxidation Involving Peroxy Radicals: A Key Contributor to Atmospheric Aerosol. Chemical reviews 119, 3472-3509, doi:10.1021/acs.chemrev.8b00395 (2019).
Trostl, J. et al. The role of low-volatility organic compounds in initial particle growth in the atmosphere. Nature 533, 527-531, doi:10.1038/nature18271 (2016).
Ehn, M. et al. A large source of low-volatility secondary organic aerosol. Nature 506, 476-479, doi:10.1038/nature13032 (2014).
Kirkby, J. et al. Ion-induced nucleation of pure biogenic particles. Nature 533, 521, doi:10.1038/nature17953 (2016).
Bianchi, F. et al. New particle formation in the free troposphere: A question of chemistry and timing. Science 352, 1109-1112, doi:10.1126/science.aad5456 (2016).
Kulmala, M. et al. Formation and growth rates of ultrafine atmospheric particles: a review of observations. Journal of Aerosol Science 35, 143-176 (2004).
Kürten, A. et al. Observation of new particle formation and measurement of sulfuric acid, ammonia, amines and highly oxidized organic molecules at a rural site in central Germany. Atmospheric Chemistry and Physics 16, 12793-12813, doi:10.5194/acp-16-12793-2016 (2016).
Rose, C. et al. Observations of biogenic ion-induced cluster formation in the atmosphere. Science Advances 4, eaar5218, doi:doi:10.1126/sciadv.aar5218 (2018).
Kerminen, V. M. et al. Atmospheric nucleation: highlights of the EUCAARI project and future directions. Atmospheric Chemistry and Physics 10, 10829-10848, doi:10.5194/acp-10-10829-2010 (2010).
Almeida, J. et al. Molecular understanding of sulphuric acid-amine particle nucleation in the atmosphere. Nature 502, 359-363, doi:10.1038/nature12663 (2013).
Wang, M. et al. Rapid growth of new atmospheric particles by nitric acid and ammonia condensation. Nature 581, 184-189, doi:10.1038/s41586-020-2270-4 (2020).
He, X. C. et al. Role of iodine oxoacids in atmospheric aerosol nucleation. Science 371, 589-595, doi:10.1126/science.abe0298 (2021).
Wang, M. et al. Synergistic H NO₃-H₂SO₄-NH₃ upper tropospheric particle formation. Nature 605, 483-489, doi:10.1038/s41586-022-04605-4 (2022).
Jimenez, J. L. et al. Evolution of Organic Aerosols in the Atmosphere. Science 326, 1525-1529, doi:doi:10.1126/science.1180353 (2009).
Gordon, H. et al. Reduced anthropogenic aerosol radiative forcing caused by biogenic new particle formation. Proceedings of the National Academy of Sciences of the United States of America 113, 12053-12058, doi:10.1073/pnas.1602360113 (2016).
Gordon, H. et al. Causes and importance of new particle formation in the present-day and preindustrial atmospheres. Journal of Geophysical Research: Atmospheres 122, 8739-8760, doi:10.1002/2017jd026844 (2017).
Molteni, U. et al. Formation of highly oxygenated organic molecules from aromatic compounds. Atmospheric Chemistry and Physics 18, 1909-1921, doi:10.5194/acp-18-1909-2018 (2018).
Berndt, T. et al. Accretion Product Formation from Self- and Cross-Reactions of RO₂ Radicals in the Atmosphere. Angewandte Chemie 57, 3820-3824, doi:10.1002/anie.201710989 (2018).
Zhao, Y., Thornton, J. A. & Pye, H. O. T. Quantitative constraints on autoxidation and dimer formation from direct probing of monoterpene-derived peroxy radical chemistry. Proceedings of the National Academy of Sciences of the United States of America 115, 12142-12147, doi:10.1073/pnas.1812147115 (2018).
Tomaz, S. et al. Structures and reactivity of peroxy radicals and dimeric products revealed by online tandem mass spectrometry. Nature communications 12, 300, doi:10.1038/s41467-020-20532-2 (2021).
Jokinen, T. et al. Production of extremely low volatile organic compounds from biogenic emissions: Measured yields and atmospheric implications. Proceedings of the National Academy of Sciences of the United States of America 112, 7123-7128, doi:10.1073/pnas.1423977112 (2015).
Lim, Y. B. & Ziemann, P. J. Products and Mechanism of Secondary Organic Aerosol Formation from Reactions of n-Alkanes with OH Radicals in the Presence of NOx. Environmental science & technology 39, 9229-9236, doi:10.1021/es051447g (2005).
Kurtenbach, R. et al. Verification of the Contribution of Vehicular Traffic to the Total NMVOC Emissions in Germany and the Importance of the NO₃ Chemistry in the City Air. Journal of Atmospheric Chemistry 42, 395-411, doi:10.1023/A:1015778616796 (2002).
Asaf, D. et al. Long-Term Measurements of NO₃ Radical at a Semiarid Urban Site: 1. Extreme Concentration Events and Their Oxidation Capacity. Environmental science & technology 43, 9117-9123, doi:10.1021/es900798b (2009).
Geyer, A. et al. Chemistry and oxidation capacity of the nitrate radical in the continental boundary layer near Berlin. Journal of Geophysical Research: Atmospheres 106, 8013-8025, doi:10.1029/2000jd900681 (2001).
Kulmala, M. et al. Overview of the international project on biogenic aerosol formation in the boreal forest (BIOFOR). Tellus B: Chemical and Physical Meteorology 53, 324-343, doi:10.3402/tellusb.v53i4.16601 (2001).
Junninen, H. et al. Observations on nocturnal growth of atmospheric clusters. Tellus B: Chemical and Physical Meteorology 60, 365-371, doi:10.1111/j.1600-0889.2008.00356.x (2017).
Bonn, B. & Moorgat, G. K. New particle formation during α- and β pinene oxidation by O₃, OH and NO₃, and the influence of water vapour: particle size distribution studies. Atmospheric Chemistry and Physics 2, 183-196, doi:10.5194/acp-2-183-2002 (2002).
Yan, C. et al. Source characterization of highly oxidized multifunctional compounds in a boreal forest environment using positive matrix factorization. Atmospheric Chemistry and Physics 16, 12715-12731, doi:10.5194/acp-16-12715-2016 (2016).
Fry, J. L. et al. Secondary organic aerosol formation and organic nitrate yield from NO₃ oxidation of biogenic hydrocarbons. Environmental science & technology 48, 11944-11953, doi:10.1021/es502204x (2014).
Ng, N. L. et al. Nitrate radicals and biogenic volatile organic compounds: oxidation, mechanisms, and organic aerosol. Atmospheric Chemistry and Physics 17, 2103-2162, doi:10.5194/acp-17-2103-2017 (2017).
Bates, K. H., Burke, G. J. P., Cope, J. D. & Nguyen, T. B. Secondary organic aerosol and organic nitrogen yields from the nitrate radical (NO₃) oxidation of alpha-pinene from various RO₂ fates. Atmospheric Chemistry and Physics 22, 1467-1482, doi:10.5194/acp-22-1467-2022 (2022).
Kanakidou, M. et al. Organic aerosol and global climate modelling: a review. Atmospheric Chemistry and Physics 5, 1053-1123, doi:10.5194/acp-5-1053-2005 (2005).
Liebmann, J. et al. Direct measurement of NO₃ radical reactivity in a boreal forest. Atmospheric Chemistry and Physics 18, 3799-3815, doi:10.5194/acp-18-3799-2018 (2018).
Wolfe, G. M., Marvin, M. R., Roberts, S. J., Travis, K. R. & Liao, J. The Framework for 0-D Atmospheric Modeling (F0AM) v3.1. Geoscitific Model Development 9, 3309-3319, doi:10.5194/gmd-9-3309-2016 (2016).
Kurten, A. et al. Neutral molecular cluster formation of sulfuric acid-dimethylamine observed in real time under atmospheric conditions. Proceedings of the National Academy of Sciences of the United States of America 111, 15019-15024, doi:10.1073/pnas.1404853111 (2014).
Yan, C. et al. Size-dependent influence of NOx on the growth rates of organic aerosol particles. Science Advances 6, eaay4945, doi:doi:10.1126/sciadv.aay4945 (2020).
Lehtipalo, K. et al. Multicomponent new particle formation from sulfuric acid, ammonia, and biogenic vapors. Science Advances 4, eaau5363, doi:10.1126/sciadv.aau5363 (2018).
McFiggans, G. et al. Secondary organic aerosol reduced by mixture of atmospheric vapours. Nature 565, 587-593, doi:10.1038/s41586-018-0871-y (2019).
Heinritzi, M. et al. Molecular understanding of the suppression of new-particle formation by isoprene. Atmospheric Chemistry and Physics 20, 11809-11821, doi:10.5194/acp-20-11809-2020 (2020).
Berndt, T. et al. Hydroxyl radical-induced formation of highly oxidized organic compounds. Nature communications 7, 13677, doi:10.1038/ncomms13677 (2016).
Kurten, T. et al. Alkoxy Radical Bond Scissions Explain the Anomalously Low Secondary Organic Aerosol and Organonitrate Yields From alpha-Pinene + NO₃. Journal of Physical Chemistry Letters 8, 2826-2834, doi:10.1021/acs.jpclett.7b01038 (2017).
Lopez-Hilfiker, F. D. et al. A novel method for online analysis of gas and particle composition: description and evaluation of a Filter Inlet for Gases and AEROsols (FIGAERO). Atmospheric Measurement Techniques 7, 983-1001, doi:10.5194/amt-7-983-2014 (2014).
Huang, W. et al. α-Pinene secondary organic aerosol at low temperature: chemical composition and implications for particle viscosity. Atmospheric Chemistry and Physics 18, 2883-2898, doi:10.5194/acp-18-2883-2018 (2018).
Wang, D. S. & Hildebrandt Ruiz, L. Chlorine-initiated oxidation of n-alkanes under high-NOx conditions: insights into secondary organic aerosol composition and volatility using a FIGAERO–CIMS. Atmospheric Chemistry and Physics 18, 15535-15553, doi:10.5194/acp-18-15535-2018 (2018).
Wang, M. et al. Photo-oxidation of Aromatic Hydrocarbons Produces Low-Volatility Organic Compounds. Environmental science & technology 54, 7911-7921, doi:10.1021/acs.est.0c02100 (2020).
Stolzenburg, D. et al. Rapid growth of organic aerosol nanoparticles over a wide tropospheric temperature range. Proceedings of the National Academy of Sciences 115, 9122-9127, doi:doi:10.1073/pnas.1807604115 (2018).
Isaacman-VanWertz, G. & Aumont, B. Impact of organic molecular structure on the estimation of atmospherically relevant physicochemical parameters. Atmospheric Chemistry and Physics 21, 6541-6563, doi:10.5194/acp-21-6541-2021 (2021).
Donahue, N. M., Kroll, J. H., Pandis, S. N. & Robinson, A. L. A two-dimensional volatility basis set – Part 2: Diagnostics of organic-aerosol evolution. Atmospheric Chemistry and Physics 12, 615-634, doi:10.5194/acp-12-615-2012 (2012).
Schervish, M. & Donahue, N. M. Peroxy radical chemistry and the volatility basis set. Atmospheric Chemistry and Physics 20, 1183-1199, doi:10.5194/acp-20-1183-2020 (2020).
Simon, M. et al. Molecular understanding of new-particle formation from α-pinene between −50 and +25 °C. Atmospheric Chemistry and Physics 20, 9183-9207, doi:10.5194/acp-20-9183-2020 (2020).
Junninen, H. et al. Terpene emissions from boreal wetlands can initiate stronger atmospheric new particle formation than boreal forests. Communications Earth & Environment 3, 93, doi:10.1038/s43247-022-00406-9 (2022).
Huang, W. et al. Potential Pre-Industrial New Particle Formation Hidden In The Air Pocket Of Finnish Peatland, submitted, 2023.
Vettikkat, L. et al. High emission rates and strong temperature response make boreal wetlands a large source of isoprene and terpenes. Atmospheric Chemistry and Physics. 23, 2683-2698, doi:10.5194/acp-23-2683-2023 (2023).
Aregahegn, K. Z., Nozière, B. & George, C. Organic aerosol formation photo-enhanced by the formation of secondary photosensitizers in aerosols. Faraday discussions 165, 123, doi:10.1039/c3fd00044c (2013).
Riva, M. et al. CI-Orbitrap: An Analytical Instrument To Study Atmospheric Reactive Organic Species. Analytical chemistry 91, 9419-9423, doi:10.1021/acs.analchem.9b02093 (2019).
Breitenlechner, M. et al. PTR3: An Instrument for Studying the Lifecycle of Reactive Organic Carbon in the Atmosphere. Analytical chemistry 89, 5824-5831, doi:10.1021/acs.analchem.6b05110 (2017).
Dada, L. et al. Formation and growth of sub-3-nm aerosol particles in experimental chambers. Nature protocols 15, 1013-1040, doi:10.1038/s41596-019-0274-z (2020).
Mai, H. & Flagan, R. C. Scanning DMA Data Analysis I. Classification Transfer Function. Aerosol Science and Technology 52, 1382-1399, doi:10.1080/02786826.2018.1528005 (2018).
Riva, M. et al. Capability of CI-Orbitrap for Gas-Phase Analysis in Atmospheric Chemistry: A Comparison with the CI-APi-TOF Technique. Analytical chemistry 92, 8142-8150, doi:10.1021/acs.analchem.0c00111 (2020).
Lindinger, W., Hansel, A. & Jordan, A. On-line monitoring of volatile organic compounds at pptv levels by means of proton-transfer-reaction mass spectrometry (PTR-MS) medical applications, food control and environmental research. International Journal of Mass Spectrometry and Ion Processes 173, 191-241, doi:https://doi.org/10.1016/S0168-1176(97)00281-4 (1998).
Hansel, A., Scholz, W., Mentler, B., Fischer, L. & Berndt, T. Detection of RO₂ radicals and other products from cyclohexene ozonolysis with NH₄⁺ and acetate chemical ionization mass spectrometry. Atmospheric Environment 186, 248-255, doi:10.1016/j.atmosenv.2018.04.023 (2018).
Pankow, J. F. & Asher, W. E. SIMPOL.1: a simple group contribution method for predicting vapor pressures and enthalpies of vaporization of multifunctional organic compounds. Atmospheric Chemistry and Physics 8, 2773-2796, doi:10.5194/acp-8-2773-2008 (2008).
Donahue, N. M., Epstein, S. A., Pandis, S. N. & Robinson, A. L. A two-dimensional volatility basis set: 1. organic-aerosol mixing thermodynamics. Atmospheric Chemistry and Physics 11, 3303-3318, doi:10.5194/acp-11-3303-2011 (2011).
Li, Y., Pöschl, U. & Shiraiwa, M. Molecular corridors and parameterizations of volatility in the chemical evolution of organic aerosols. Atmospheric Chemistry and Physics 16, 3327-3344, doi:10.5194/acp-16-3327-2016 (2016).
Daumit, K. E., Kessler, S. H. & Kroll, J. H. Average chemical properties and potential formation pathways of highly oxidized organic aerosol. Faraday discussions 165, 181-202, doi:10.1039/c3fd00045a (2013).
Jenkin, M. E., Saunders, S. M. & Pilling, M. J. The tropospheric degradation of volatile organic compounds: a protocol for mechanism development. Atmospheric Environment 31, 81-104, doi:https://doi.org/10.1016/S1352-2310(96)00105-7 (1997).

There is NO Competing Interest.

NO3chemistrySIncv2.docx

Download PDF

Version 1

posted

You are reading this latest preprint version

Nitrate radicals suppress biogenic new particle formation from monoterpene oxidation

Status:

Version 1

Abstract

Figures

Introduction

Results

NPF with different oxidants

HOM distribution at different NO₃ levels

Change of HOM volatility distribution by NO₃

Discussion

Methods

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1

Nitrate radicals suppress biogenic new particle formation from monoterpene oxidation

Status:

Version 1

Abstract

Figures

Introduction

Results

NPF with different oxidants

HOM distribution at different NO3 levels

Change of HOM volatility distribution by NO3

Discussion

Methods

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1

HOM distribution at different NO₃ levels

Change of HOM volatility distribution by NO₃