The Synergistic Role of Sulfuric Acid, Bases, and Oxidized Organics Governing New-Particle Formation in Beijing

Abstract

Intense and frequent new particle formation (NPF) events have been observed in polluted urban environments, yet the dominant mechanisms are still under debate. To understand the key species and governing processes of NPF in polluted urban environments, we conducted comprehensive measurements in downtown Beijing during January–March, 2018. We performed detailed analyses on sulfuric acid cluster composition and budget, as well as the chemical and physical properties of oxidized organic molecules (OOMs). Our results demonstrate that the fast clustering of sulfuric acid (H₂SO₄) and base molecules triggered the NPF events, and OOMs further helped grow the newly formed particles toward climate- and health-relevant sizes. This synergistic role of H₂SO₄, base species, and OOMs in NPF is likely representative of polluted urban environments where abundant H₂SO₄ and base species usually co-exist, and OOMs are with moderately low volatility when produced under high NO_x concentrations.

Key Points

• Process-level understanding of new particle formation (NPF) in wintertime Beijing was obtained based on measurement state-of-the-art instruments

• The analysis of sulfuric acid cluster composition and budget showed that sulfuric acid-base clustering initiated NPF

• Condensable organic vapors were characterized and demonstrated to have a crucial influence on the growth of newly formed particles

Plain Language Summary

Atmospheric new particle formation (NPF) is a dominant source of atmospheric ultrafine particles worldwide. Those particles profoundly influence climate and human health. NPF includes two consecutive processes, that is, the formation of new particles (∼2 nm in diameter) and their subsequent growth to larger sizes. Extensive studies conducted in the laboratory and in forested areas have shown that many gaseous species can participate in NPF, such as sulfuric acid, ammonia, amines, and oxidize organic molecules. However, the actual roles of these vapors may vary significantly from location to location and are largely unclear in urban environments. Here, based on measurements of sulfuric acid, sulfuric acid clusters, and oxidize organic molecules, we demonstrate that sulfuric acid and base molecules were responsible for the initial formation of new particles during a wintertime field campaign in Beijing. The majority of oxidized organic molecules had a minor contribution to the formation of new particles but were crucial for particle growth above 2–3 nm to climate- and health-relevant sizes.

1 Introduction

Atmospheric aerosol particles substantially affect climate and human health (Heal et al., 2012). Most aerosol particles in the Earth's atmosphere, including a large fraction of cloud condensation nuclei (CCN), are thought to originate from formation of atmospheric clusters and their subsequent growth to larger sizes (Gordon et al., 2017; Merikanto et al., 2009; Spracklen et al., 2008). This process is known as new particle formation (NPF). NPF occurs in almost all continental environments with varying frequencies and intensities (Chen et al., 2012; Kalafut-Pettibone et al., 2011; Kerminen et al., 2018; Kulmala et al., 2017; Mönkkönen et al., 2005; Nieminen et al., 2018; Peng et al., 2014; Qi et al., 2015; Wu et al., 2007; Xiao et al., 2015; Yao et al., 2018), and therefore, understanding the underlying mechanisms is an on-going research topic of high importance.

In spite of high primary aerosol emissions, NPF is a major source of ultrafine particles in polluted urban environments (Guo et al., 2014; Kulmala et al., 2016; Wang, Wu, Yue, et al., 2017). Studies have also suggested that NPF in urban environments contributes more to the CCN budget than it does in regional or remote environments (Peng et al., 2014; Wang, Wu, Yue, et al., 2017). In addition, NPF may also lead to haze under stagnant air conditions (Guo et al., 2014; Kulmala et al., 2021). Previous studies have suggested that high aerosol surface concentration is one primary parameter that governs the occurrence of NPF in polluted environments (Cai, Yang, et al., 2017; Deng et al., 2021; McMurry et al., 2005). Another recent study has predicted that little NPF should occur in polluted megacities due to the high condensation sink (CS) (Kulmala et al., 2017); by contrast, observations show that NPF in these areas are frequent and more intense than in clean environments (Deng et al., 2020). This discrepancy underlines an incomplete understanding of NPF in polluted and usually chemically complex environments.

Up to now, the driving mechanisms and key contributing species in both atmospheric clustering and subsequent growth in urban environments remain to be elucidated. For instance, a recent study has shown that clustering of gaseous sulfuric acid (H₂SO₄) and dimethylamine (C₂H₇N) is responsible for the initial steps of NPF in Shanghai (Yao et al., 2018). However, another recent laboratory-based study suggested that low-volatility organic vapors from the oxidation of vehicle-emitted organics, rather than H₂SO₄, can initiate the NPF in some urban environments (Guo et al., 2020). In addition, it was recently suggested that various dicarboxylic acids (diacids) could also cluster with H₂SO₄ and C₂H₇N to initiate NPF (Fang et al., 2020).

Moreover, the contribution of low-volatility organic vapors to the NPF in the polluted urban atmosphere is largely unclear. These vapors form via the atmospheric oxidation of various volatile organic compounds (VOCs). It is widely acknowledged that low-volatility organic vapors are likely dominant contributors to the growth of freshly formed molecular clusters, allowing them to survive the scavenging in the atmosphere (e.g., Riipinen et al., 2011; Smith et al., 2008). Such contribution is controlled by both the concentration and saturation vapor pressures of low-volatility organic vapors (Donahue et al., 2013). Extensive studies that have been conducted in remote forested areas demonstrated that organic vapors, formed via the oxidation of monoterpenes, are able to contribute to the particle growth below 2 nm (Kulmala et al., 2013; Mohr et al., 2017). By contrast, the chemical characteristics of these low-volatility vapors in urban settings are under-studied, and the potential contribution of these vapors to NPF remains to be evaluated.

To advance our understanding of NPF in urban environments, we built a station in downtown Beijing equipped with state-of-the-art instruments. Our measurements cover most of atmospheric species directly contributing to NPF and particle evolution over a wide diameter range (1 nm–10 μm). Our comprehensive measurements allow for molecular-level analyses on NPF, upon which we determine the critical NPF processes and demonstrate the roles of different species in these processes.

2 Methodology

2.1 Measurement Station

The measurement was conducted at the Aerosol and Haze Laboratory/Beijing University of Chemical Technology station (AHL/BUCT station). The station is located in the main teaching building of the west campus of Beijing University of Chemical Technology (Lat. 39º56ʹ31ʺ and Lon. 116º17ʹ52ʺ). The building is surrounded residential and commercial areas. In addition, there are three main roads within 600 m around the station. Therefore, the AHL/BUCT Station is a typical urban observation station affected by heavy traffic and residential emissions. More details about the station can be found elsewhere (Liu et al., 2020).

2.2 Instrumentation

The particle number concentration and size distribution over in the diameter range of 1 nm–10 μm were measured by a diethylene glycol scanning mobility particle spectrometer (DEG-SMPS, 1–7.5 nm) and a particle size distribution system (3 nm–10 μm). Additionally, the number concentration of clusters with a diameter range of 1.3–2.5 nm was measured with a Particle Sizer Magnifier, which showed good agreement with the DEG-SMPS measurements. The particle formation rate (J_1.5) was calculated for all NPF cases based on these data sets using the new-balance formula optimized for polluted environments (Cai & Jiang, 2017). H₂SO₄ and oxidized organic molecule (OOM) concentrations were measured with nitrate ion-based Chemical Ionization Atmospheric Pressure interface Time-of-Flight mass spectrometer (CI-APi-TOF, Aerodyne Research, Inc.). This instrument was calibrated for both the sensitivity to H₂SO₄ and the mass-dependent transmission efficiency. The molecular ion cluster composition was measured with an Atmospheric Pressure interface Time-of-Flight mass spectrometer (APi-TOF, Aerodyne Research, Inc.). The OOM volatility was estimated based on the parameterization by Mohr et al. (2019) and further corrected using the ambient temperature. More details of these instruments and other ancillary measurements are provided in the supporting information.

3 Results and Discussion

3.1 The Frequent Occurrence of NPF Events and the Governing Factors

We extend the mechanistic understanding of NPF in wintertime Beijing based on the results from intensive measurements conducted during January 23–March 31, 2018 at the newly built station in downtown Beijing. In Figure S1, we present the measurement overview, including the particle number concentration and size distribution over a wide size-range from 1 nm to 10 μm, relevant meteorological variables (temperature and UVB radiation intensity), calculated particle formation rate at 1.5 nm (J_1.5), CS, as well as gas-phase concentrations of vapors plausibly contributing to NPF (i.e., H₂SO₄ and OOMs). Details of these measurements and calculations are provided in the supporting information. We classify the whole measurement period into NPF and nonNPF days following the widely used method suggested in previous studies (Dal Maso et al., 2005). During the measurements, we observed NPF events frequently (32 out of 69 days), and during the first five weeks from 23 January to 28 February, NPF occurred on more than 60% of the days. The reduced NPF frequency in March is clearly associated with high CS, which is usually encountered when air masses come from polluted areas located on the south and east of Beijing. This is also consistent with an earlier study conducted at another site in Beijing (Cai, Yang, et al., 2017).

Comparisons of different variables between NPF and nonNPF days are shown in Figure 1. In the present-day continental boundary layer, it is widely accepted that H₂SO₄ and low-volatility organic species are crucial species for NPF (Lehtipalo et al., 2018; Riccobono et al., 2012, 2014; Rose et al., 2018; Yao et al., 2018). However, both H₂SO₄ monomer and total OOM concentrations in our observations were higher on nonNPF days than on NPF days (Figures 1b and 1d), likely due to the higher precursor concentrations (SO₂ and VOCs). Note that this observation should not be interpreted as indicating that H₂SO₄ and OOMs do not participate in NPF, but rather that enhanced clustering can be outcompeted by the simultaneously elevated loss of clusters to the condensation sink (i.e., higher CS, Figure 1e). The competition between H₂SO₄ clustering and CS is reflected in the H₂SO₄ dimer concentration, which is lower on nonNPF days due to the enhanced scavenging (Figure 1c). The close association between H₂SO₄ dimer and NPF occurrence and intensity will be discussed in detail in the next section. Furthermore, the temperature can influence NPF by modifying the formation and volatility of OOMs (Simon et al., 2020; Stolzenburg et al., 2018) and affecting the stability of H₂SO₄ clusters (Almeida et al., 2013). However, the mean temperature in NPF and nonNPF days was almost identical (Figure 1f), suggesting that temperature does not determine the NPF occurrence during our measurement period.

Figure 1

Diurnal variations of particle formation rates as well as relevant species and parameters in new particle formation (NPF) and nonNPF days. Lines are the median values, and shaded areas denote the 25%–75% of the data variation.

3.2 Intense New Particle Formation Driven by Acid-Base Clustering

In addition to the high frequency, NPF also occurred with high intensities, with a median J_1.5 of 86 cm⁻³ s⁻¹ at peak hours (Figure 1a). The high particle formation rates appear to be a common characteristic of NPF in the polluted urban atmosphere, such as Shanghai (Xiao et al., 2015; Yao et al., 2018), Nanjing (Yu et al., 2016), and Barcelona (Brean et al., 2020). These particle formation rates are usually 1–2 orders of magnitude higher than those in relatively clean environments (Kulmala et al., 2013), suggesting the existence of abundant and efficient nucleation species in an urban atmosphere.

In Figure 2a, we show how the particle formation rate J_1.5 changes as a function of H₂SO₄ concentration. Despite an overall weak correlation between J_1.5 and H₂SO₄ monomer concentration, strong correlation becomes visible within narrow ranges of CS. This suggests that while H₂SO₄ drives the initial steps of NPF (i.e., the formation of embryonic clusters), CS plays a crucial role in determining the NPF intensity. For instance, at the same H₂SO₄ monomer concentration, J_1.5 may vary up to 3–4 orders of magnitude when CS ranges from 0.001 to 0.1 s⁻¹. Therefore, such J_1.5-H₂SO₄ relationship should be interpreted with caution when inferring the NPF mechanism, especially when comparing relatively more polluted ambient data with chamber results, because chambers usually have a lower CS (Dada et al., 2020). In our case, the J_1.5-H₂SO₄ relationship at CS < 0.02 s⁻¹ agrees well with the results of the CLOUD chamber experiments using H₂SO₄ and dimethylamine (C₂H₇N) as the nucleating vapors (Kürten et al., 2018), suggesting that H₂SO₄ clustering that proceeds at similar efficiency is driving the initial steps of NPF.

Figure 2

Illustration of the initial acid-base clustering in urban Beijing. (a) Particle formation rate J_1.5 as a function of H₂SO₄ monomer concentration ([H₂SO₄]). Both raw data (dots) and data binned to H₂SO₄ concentration at different condensation sink (CS) ranges (squares) are shown. Data from the CLOUD chamber experiments are shown in gray squares. The R² values are calculated with the raw data in each CS bin. (b) The relationship between sulfuric acid dimer concentration [(H₂SO₄)₂], monomer concentration [H₂SO₄], and the CS. The rate constant of sulfuric acid dimer formation is derived via the slope of a linear fit to the data. (c) Particle formation rate J_1.5 as a function of [(H₂SO₄)₂]. The data are binned in the same way as in (a). Both raw data (dots) and data binned data (squares) are shown. The R² is calculated with raw data. (d) A mass defect plot illustrating the chemical composition of natural ion clusters containing sulfuric acid and a variety of base molecules. Panels (a–c) are color-coded by CS. The size in (d) is logarithmically proportional to the signal intensity. It should be noted that, neutral H₂SO₄ and H₂SO₄ dimer concentrations were measured by the Chemical Ionization Atmospheric Pressure interface Time-of-Flight mass spectrometer (CI-APi-TOF) (a–c), while the H₂SO₄ cluster ion composition was obtained from the APi-TOF (d).

To further confirm the high efficiency of H₂SO₄ cluster formation, we investigate the birth-death processes of H₂SO₄ dimers, that is, clusters containing two H₂SO₄ and also base molecules, which are the only H₂SO₄ clusters that can be reliably quantified. Other larger clusters also form, but they usually fall below the instrumental detection limit due to their low concentration and reduced ionization efficiency (thus low sensitivity) (Jen et al., 2016). As shown in Figure 2b, we found that the H₂SO₄ dimer concentration was in a pseudo steady-state between its formation rate by H₂SO₄ monomer collisions and its loss rate onto pre-existing larger particles by coagulation scavenging. The second-order rate constant between H₂SO₄ monomer collision forming one H₂SO₄ dimer is determined as 3.89 × 10⁻¹⁰ cm³ s⁻¹ (the fitted slope in Figure 2b), which is close to the theoretical molecular collision rate constant. Moreover, we observe a very strong correlation (R² = 0.82) between J_1.5 and H₂SO₄ dimer concentration (Figure 2c), showing that the abundance of H₂SO₄ clusters is directly associated with NPF intensity.

To further understand the high efficiency of H₂SO₄ clustering, we characterize the composition of H₂SO₄ cluster ions measured by the APi-TOF during the NPF events. As shown in Figure 2d, in addition to clusters consisting purely of H₂SO₄ (red dots in Figure 2d), amines (C₂H₇N, C₃H₉N, C₄H₁₁N) start to appear from the H₂SO₄ trimer onwards (magenta and blue dots in Figure 2d). The appearance of C₂H₇N in the H₂SO₄ trimer is consistent with the results in the CLOUD chamber (Almeida et al., 2013). In addition, C₃H₉N and C₄H₁₁N participate in H₂SO₄ clustering at the same step; consistent with an earlier laboratory study with different amines (Jen et al., 2014), this suggests that C₃H₉N and C₄H₁₁N have a similar stabilizing effect on H₂SO₄ clusters. In fact, these amines form stable neutral clusters with one or two H₂SO₄. However, as suggested by our quantum chemical calculations using C₂H₇N as a surrogate, deprotonation of these clusters will result in the loss of the amine moieties (see supporting information Section 3). Thus, large fractions of HSO₄⁻ or H₂SO₄HSO₄⁻ signals in our mass spectra come from (H₂SO₄)_1,2−(C_2–4H_7–11N)_1,2 clusters. Other base molecules, such as CH₅N and NH₃ are involved in the cluster formation at later steps, as they are observed only in larger clusters. Moreover, unlike observations in forested areas and chamber experiments with the presence of both H₂SO₄ and biogenic VOCs (Lehtipalo et al., 2018; Riccobono et al., 2014; Schobesberger et al., 2013), H₂SO₄ clusters containing both base molecules and oxygenated organic molecules are not observed, suggesting little importance of multi-component nucleation. Altogether, we conclude that the initial steps of NPF, that is, the formation of 1.5 nm particles, is predominantly driven by acid-base clustering during the measurement period.

3.3 Characteristics of Oxygenated Organic Molecules and Their Role in NPF

In order to evaluate the role of low-volatility organic vapors in NPF, we measured organic molecules with the nitrate anion CI-APi-TOF (see more details in the supporting information). As we will demonstrate below, according to the latest definition of highly oxygenated organic molecules (HOMs) (Bianchi et al., 2019), most organic vapors that we detected in Beijing do not meet that requirement. Therefore, we use the term “oxygenated organic molecules (OOMs)” to refer to the measured compounds in this study. One should note that this instrument does not detect all OOMs, but it is specifically selective toward more oxidized ones, which are also most relevant for NPF (Ehn et al., 2014). In addition, we found this instrument to be sensitive to various nitrated phenols. However, these nitrated phenols are too volatile to have any noticeable contribution to NPF and are therefore excluded in this study. All identified OOMs together with their concentrations are listed in Table S2.

In Figure 3, we show chemical characteristics of OOMs based on the number of carbon atoms (nC), numbers of nitrogen atoms (nN), and effective oxygen atoms (nO_eff). The nO_eff is calculated by disregarding the two oxygen atoms bonding with each nitrogen atom to reflect better the oxidation state and volatility of OOMs (Yan et al., 2020). These characteristics provide important information for understanding the critical processes in OOM formation.

Figure 3

Chemical characteristics of oxidized organic molecules (OOMs) shown in mass defect plots. (a) Number of carbon (nC), (b) Number of nitrogen (nN). (c) Number of effective oxygen (nO_eff). Lower panels show the fractional distribution of the respective parameters.

Our first observation is that OOMs form through the oxidation of a complex mixture of VOCs. As suggested by the carbon distribution of OOMs that C_5–10 OOMs contribute to a dominant fraction of the total OOM concentration (Figure 3a), isoprene (C₅), alkylbenzenes (C_6–9), and monoterpenes (C₁₀) are likely the most important precursor VOCs. In addition, C_3–4 OOMs might arise from the decomposition during the oxidation of VOCs with larger carbon numbers, and the C_>10 may come from the oxidation of polyaromatic hydrocarbons or from accretion reactions between two peroxy radicals (RO₂). However, it should be noted that, not all identified peaks in this study (Table S2) can be found in previous laboratory studies (Ehn et al., 2014; Krechmer et al., 2015; Molteni et al., 2018; Wang, Wu, Berndt et al., 2017, Wang et al., 2018). The difference in OOM composition may arise from the imperfect mimicking of the VOC oxidation under real atmospheric conditions in previous laboratory experiments, and also possibly results from some important but uncounted OOM sources, such as missing precursor VOCs and the evaporation from particulate phase.

Our second observation is that a major fraction (∼75%) of OOMs are organic nitrates (Figure 3b), suggesting that the reaction of RO₂ + NO_x is the main termination reaction pathway. In Beijing, the concentrations of peroxy radicals (HO₂ and RO₂) and NO_x are in the ranges of 10⁷–10⁸ cm⁻³ and 10¹¹–10¹² cm⁻³, respectively (Tan et al., 2018). Given the fact that the reaction rate coefficient between RO₂ and HO₂/RO₂ is at most one order of magnitude higher than that between RO₂ and NO, the reactions of RO₂ + RO₂ or RO₂ + HO₂ are less important channels than the RO₂ + NO_x channel in OOM formation. In addition to terminating the oxidation, the reaction of RO₂ + NO can also propagate the oxidation by forming alkoxy radicals (RO), which does not lead to the formation of a nitrate group. As a result, it is likely that the actual contribution of the RO₂ + NO_x reaction to the formation of OOMs is even greater than 75%. Furthermore, about 30% of OOMs contains two or three nitrogen atoms (Figure 3b). As indicated by the higher concentration during the day than at the night (Figure S2), the formation of such multiple nitrate groups was associated more with photochemistry than with the dark NO₃ chemistry. Multiple oxidation steps each followed by a RO₂ + NO_x termination reaction could plausibly explain the formation of two or three nitrogen-containing compounds during daytime.

Our third observation is that HOMs in our measurements constituted a minor fraction of all OOMs. This could be explained by high NOx concentrations, which generally suppress RO₂ autoxidation (Figure 3c). From the literature, it is known that the degree of suppression is highly dependent on the precursor VOCs. For isoprene, 5 ppb NO is sufficient to completely shut down the autoxidation at 298 K (Wang et al., 2018). Due to the lower temperature during our measurement, which further slows down autoxidation, and higher NO_x concentration, autoxidation in isoprene oxidation should be fully prevented. For monoterpenes, autoxidation should also be significantly suppressed. This is supported by the comparison of the C₁₀H₁₅O_xN product distribution in Beijing and a boreal forest in southern Finland where the NO_x concentration is much lower (Yan et al., 2016). As shown in Figure S3, relatively less oxygenated products (C₁₀H₁₅O_6-8N, nO_eff = 4–6) are the main products, while highly oxygenated products (C₁₀H₁₅O_8-11N, nO_eff = 6–9) at the boreal forest are dominant ones. For alkylbenzenes, the autoxidation rate of the bicyclic peroxy radicals (BPRs) varies by three orders of magnitude depending to the alkyl substitution group (Wang, Wu, Berndt, et al., 2017). The suggested maximum autoxidation rates of isopropyl-benzene, ethyl-benzene, toluene at 278 K are 9.2, 4.6, and 0.01 s⁻¹, respectively (Wang, Wu, Berndt, et al., 2017). These rates are equivalent to the bimolecular reaction rate with NO of about 38, 18, and 0.04 ppb, respectively, assuming a rate constant of 1 × 10⁻¹¹ cm³ s⁻¹. Therefore, the autoxidation for alkylbenzenes with long-chain substituents (e.g., isopropyl-, ethyl-benzenes) should only be partially suppressed in Beijing, in contrast to the complete suppression of autoxidation for alkylbenzenes with short-chain substituents (e.g., methyl-, dimethyl-benzenes).

The volatility of OOMs is a key variable, linking the formation and chemical composition of OOMs to their potential contribution to the particle growth. We estimate the volatility distribution of the OOMs using a volatility basis set parameterization (see Section 2) (Bianchi et al., 2019; Chuang & Donahue, 2016). The overall binned volatility distribution is shown in Figure 4a. Based on our estimate, ultralow volatility organic compounds (ULVOC, C* ≤ 3 × 10⁻⁹ μg m⁻³) that are capable of nucleating (Schervish & Donahue, 2020) are minor products, with a mean concentration of 2 × 10⁵ cm⁻³ (0.7% of total OOMs). This observation is also consistent with our former conclusion that the main NPF-relevant clustering process is H₂SO₄-base that does not involve OOMs. Also, only a small fraction of OOMs (9%, corresponding to an absolute concentration of 3 × 10⁶ cm⁻³) is extremely low-volatility organic compounds (ELVOC, 3 × 10⁻⁹ < C* ≤ 1 × 10^−4.5 μg m⁻³). Such low concentrations suggest that organic vapors are not the main driver of particle growth at the smallest size (e.g., ∼2 nm). Consistent with this, an independent study based on H₂SO₄ measurement also indicates that H₂SO₄ and its clusters contribute significantly to the particle growth at 1.5–3 nm (Deng et al., 2020). ULVOCs are almost exclusively dimer compounds formed via association reactions between RO₂ radicals, while ELVOCs include both dimer compounds and highly oxygenated monomer compounds. Therefore, their low concentrations can be explained by the dominance of RO₂+NO_x as the termination reaction, as we have discussed above.

Figure 4

Volatility distribution of oxidized organic molecules observed with the nitrate Chemical Ionization Atmospheric Pressure interface Time-of-Flight mass spectrometer (CI-APi-TOF). The volatility is divided into different categories, including ultralow volatility organic compound (ULVOC), extremely low-volatility organic compound (ELVOC), low-volatility organic compound (LVOC), semi-volatile organic compound (SVOC), and intermediate volatile organic compound (IVOC). (a) the mean oxidized organic molecule (OOM) volatility distribution of OOMs during the new particle formation (NPF) periods of the campaign. Both mass saturation concentration (C*) and number saturation concentration (N*) are presented. (b) Mean volatility distributions in two different cases: The ending diameter is above 30 nm (blue) or below 30 nm (yellow). The end size is defined as the maximum diameter that the newly formed particles could reach within the event day.

Even though most OOMs (59%) in Beijing are semi-volatile organic compounds (SVOCs, 10^−0.5 < C* ≤ 10^2.5 μg m⁻³) and intermediate volatile organic compounds (IVOC, 10^2.5 < C* ≤ 10^6.5 μg m⁻³) that do not drive the growth of newly formed particles, a considerable fraction (31%) are low-volatility organic compounds (LVOCs, 10^−4.5 < C* ≤ 10^0.5 μg m⁻³) that can contribute to the growth of particles above ∼2 nm. This contribution is important for the survival of new particles against the scavenging loss. On NPF days, when newly formed particles grew beyond 30 nm, the concentration of OOMs was significantly higher than on days when particles did not reach 30 nm (Figure 4b). This suggests that condensable OOMs are crucial for particle growth from a few nanometers to a few tens of nanometers. It is worth noting that, the OOM volatility distribution in both cases were similar, indicating that the difference of OOMs was mainly caused by the overall VOC oxidation rate rather than a significant change in RO₂ + NO_x chemistry, which can alter the OOM volatility distribution but not the overall concentration (Yan et al., 2020).

4 Conclusion

In summary, with state-of-the-art instruments, we track the particle evolution from molecules to clusters and then to particles. Based on such comprehensive measurements, we depict a complete picture of NPF in wintertime Beijing, including both the initial clustering and the subsequent cluster growth driven by different vapors. The clustering starts with the formation of thermodynamically stable sulfuric acid clusters at around 1–1.5 nm. This process in wintertime Beijing is driven by the acid-base clustering mechanism in the presence of abundant stabilizers, such as amines and NH₃. This is confirmed by our observations from many independent perspectives, including the J-H₂SO₄-CS relationship, the direct observation of molecular ion clusters by APi-TOF, and the low concentrations of ULVOC and ELVOC. This is in contrast to a recent suggestion made based on chamber experimental results that OOMs are solely responsible for NPF in Beijing. Nevertheless, OOMs are crucial for growing the newly formed particles through the very small sizes where they are vulnerable to scavenging loss. We confirm this, by quantifying each OOMs volatility classes. Overall, we clearly demonstrate that H₂SO₄, various bases species, and low-volatility organic vapors synergistically contributed to the intense NPF in wintertime Beijing, and in order to control the aerosol population, those key compounds need to be monitored and regulated.

Acknowledgment

The work is supported by Academy of Finland via the Center of Excellence in Atmospheric Sciences (project no. 272041, 316114, 311932, and 315203) and European Research Council via ATM-GTP 266 (742206), CHAPAs (850614) and BLACARAT (615922), National Natural Science Foundation of China (41730106, 21876094, 91644213, and 92044301), and Samsung PM_2.5 SRP. NMD and MS are supported by the US NSF grant AGS-1801897. LW thanks the National Key R&D Program of China (2017YFC0209505 and 2017YFC0209503).

Conflict of Interest

The authors declare no conflict interest.

Open Research

Data Availability Statement

The measurement data used are available at ZENODO (https://zenodo.org, http://doi.org/10.5281/zenodo.4305410).