Abstract. Ice nucleating particles (INPs) are rare aerosols essential for cloud ice formation in the mixed-phase temperature range between -38 °C and 0 °C. Due to measurement challenges and limitations in instrument capabilities, the availability of atmospheric observations of INPs remains scarce in time and space. Consequently, no observation-based global distribution of INPs exists so far. This study applies a machine learning (gradient boosting) algorithm to predict the INP concentration over the mixed-phase temperature range across the globe using aerosol mass concentration reanalysis and observed immersion-mode INPs. This proof-of-concept exercise demonstrates that even with limited measurements, the occurrence of INPs can be estimated, following the spatial pattern of key aerosol species. Point-based evaluation metrics, R2 and log-based RMSE, reach 0.83 and 0.71 for the gradient boosting model, compared to 0.75 and 0.86 for the linear regression benchmark. Regional INP spectra with temperature extracted from the machine learning model agree within one order of magnitude with observations, except over Antarctica (mean bias factor of 150). INPs in continental (oceanic) regions are well predicted within a mean bias of 2.4 (overestimated within a mean bias of 4) by the machine learning model. The prediction is driven by the strong temperature dependence followed by mid-sized dust particles. This approach can resolve a long-standing source of INP prediction uncertainty in regional weather and climate models.

Dimethyl sulfide (DMS; CH3SCH3) from marine phytoplankton is a notable source of atmospheric sulfur1. Its oxidation products include sulfuric acid (SA; H2SO4) and methanesulfonic acid (MSA; CH3SO3H), which has a higher yield than SA below 10 °C (ref. 2). Although SA is known to drive the formation of new particles3, which may subsequently grow and act as cloud condensation nuclei (CCN), the role of MSA remains unclear4. Here, in experiments performed under atmospheric conditions at the CERN CLOUD (Cosmics Leaving OUtdoor Droplets) chamber, we show that MSA nucleates together with ammonia (NH3) below -10 °C, at rates comparable with SA-NH3. Moreover, MSA and SA nucleate synergistically below -10 °C, forming multi-acid molecular clusters with NH3. Even at ultralow NH3 levels, MSA drives particle growth at or near the kinetic limit below 9 °C and above 40% relative humidity (RH). Because MSA and SA generally coexist at similar concentrations in cool marine regions, our findings indicate that nucleation rates may be accelerated up to tenfold and growth rates up to twofold compared with SA-NH3 alone. Our global model simulations indicate that MSA can enhance CCN concentrations, especially in polar regions. We propose that MSA might be an important driver of biogenic particles in cool, pristine marine regions of both the present-day and pre-industrial atmospheres and yet is unaccounted for in global climate models5.

Fine particulate matter (PM2.5) is closely linked to human health, with its sources generally divided into local emissions and regional transport. This study combined concentration-weighted trajectory (CWT) analysis with the HYSPLIT trajectory ensemble to obtain hourly resolution pollutant source results. The Extreme Gradient Boosting (XGBoost) model was then employed to simulate local emissions and ambient PM2.5 in Beijing from 2013 to 2020. The results revealed that clean air masses influencing the Beijing area mainly originated from the north and east regions, exhibiting a strong winter and weak summer pattern. Following the implementation of the Air Pollution Prevention and Control Action Plan (Action Plan) by the Chinese government in 2017, pollution in Beijing decreased significantly, with the most substantial reduction in regional transport pollution events occurring in the west region during summer. Regional transport pollution events were most frequent in spring, up to 1.8 times higher than in winter. Pollutants mainly originated from the west and south regions, while polluted air masses from the east showed the least reduction, and the proportion of pollution sources from this region was gradually increasing. The COVID-19 restrictions might have reduced PM2.5 concentrations in 2020. From 2013 to 2020, local emissions were the main contributors to pollution events in Beijing. The Action Plan has more effectively reduced pollution caused by regional transport, particularly during autumn and winter. This finding underscores the importance of Beijing prioritizing local emission reduction while also considering potential contributions from the east region to effectively mitigate pollution events.

The microphysical properties associated with ice production importantly determine precipitation rates. In this study, the microphysical properties of stratiform clouds with embedded convection during an extratropical cyclone over northern China were characterized in situ. Stages of clouds, including young cells rich in liquid water and developing and mature stages with high number concentrations of ice particles (NIce), were investigated. NIce could reach 300 L-1 in the mature stage, approximately 2 orders of magnitude higher than the primary NIce. The secondary ice production (SIP) rate was 0.005-1.8 L-1 s-1, which was derived from the measured NIce. The SIP rate could be produced using a simplified collision-coalescence model by considering the collection of large droplets by graupel. The collection efficiency between the graupel and the droplet was found to increase when the size of the droplet approached that of the graupel, which may improve the agreement between the measurements and the model. Importantly, the overall NIce was found to be highly related to the distance to the cloud top (DCT). The level with a larger DCT had more rimed graupel falling from the upper levels, which promoted coalescence processes between the graupel and the droplets, producing a greater fraction of smaller ice. This seeder-feeder process extended the avalanche SIP process at lower temperatures to -14 degrees C, beyond the temperature region of the Hallett-Mossop process. The results illustrate the microphysical properties of clouds with convective cells at different stages, which will improve the understanding of the key processes in controlling the cloud glaciation and precipitation processes.

Abstract. The microphysical properties associated with the ice production importantly determine the precipitation rate of clouds. In this study, the microphysical properties including the size distribution and particle morphology of water and ice for stratocumulus during an extratropical cyclone over the northern China were in-situ characterized. Stages of cloud were investigated including young cells rich of liquid water, developing and mature stages with high number concentration of ice particles (Nice). The Nice could reach 300 L-1 at the mature stage, about two orders of magnitudes higher than the primary ice number concentration calculated from ice nucleation. This high Nice occurred at about −5 to −12 °C, spanning the temperature region of Hallett-Mossop process and possible other mechanisms for the secondary ice production (SIP). The Nice was positively associated with the number concentrations of large graupel with diameter (d) > 250 μm and large supercooled droplet (d > 50 μm). The SIP rate was 0.005-1.8 L-1s-1 derived from the measured Nice with known ice growth rate between two sizes. The SIP rate could be produced by a simplified collision-coalescence model within an uncertainty factor of 5, by considering the collection of large droplets by graupel. The collection efficiency between was found to increase when the size of droplet was closer to graupel which may improve the agreement between measurement and model. Importantly, the overall Nice was found to be highly related to the distance to cloud-top (DCT). The level with larger DCT had more abundant rimmed graupels falling from the above level, which promoted the coalescence processes between graupels and droplets, producing a higher fraction of smaller ice through SIP. This seeder-feeder process extended the avalanche SIP at lower temperature up to −14 °C beyond the temperature region of Hallett-Mossop process. The results illustrated the microphysical properties of clouds with convective cells under different stages, which will improve the understanding of the key processes in controlling the cloud glaciation and precipitation process.

Dust storms have great impacts on air quality and climate. Dust can influence cloud microphysical properties and determine their radiative forcing and precipitation. Asian dust storms (ADS) are important sources of global aerosol. However, the physiochemical characteristics of dust from ADS at a single particle level are less understood, and the exact particles that can serve as ice nucleating particles (INPs) remain unclear. Here, we present the physicochemical properties and ice nucleation ability of dust particles collected in Beijing during two major ADS in March 2021. The particles from two ADS were classified into Illite, Kaolinite, Feldspar, Quartz, Chlorite, Mixed-dust, and Non-dust particles, which contributed 28.6% f 3.3 %, 20.0% f 3.9%, 12.3 % f 2.3 %, 11.1% f 2.8%, 9.8% f 0.8%, 13.7% f 1.8%, and 4.4% f 1.7% in number, respectively. On average, the ADS particles formed ice crystals via deposition ice nucleation from relative humidity with respect to ice (RHice) RH ice ) of 112 % f 1 % at 250 K to 154 % f 15 % RH ice at 205 K. Part of the samples also formed ice via immersion freezing between 230 K and 250 K. Among the 149 identified INPs, Clay-like particles (Chlorite, Illite, and Kaolinite) contributed 71.1 % f 6.2 % in number and followed by Mixed-dust-like particles (16.9 % f 8.7 %) and Feldspar-like particles (10.4 % f 6.3 %). Enrichment factor of each particle type in INPs is calculated as the ratio of its number fractions in INPs and the aerosol population. It ranges from 0.6 f 0.7 to 1.3 f 2.2. The contribution of each particle type to INP was correlated with its fraction in the population. These results imply that each particle type can serve as INP. Clay-like particles are the dominant INPs during the ADS. We conducted ice nucleation kinetic analysis and provided parameterizations of heterogeneous ice nucleation rate coefficient and contact angle for ADS. These parameterizations can be used in the modeling study to evaluate the impact of ADS in atmospheric ice crystal formation in clouds.

In this study, joint observations of the airborne Ka-band precipitation radar (KPR) and Himawari-8 were used to investigate the underlying links among cloud macro and microphysical parameters such as cloud top height (CTH), effective particle radius (Re), and cloud top temperature (CTT). Our results indicate that, compared to CTH from the Himawari-8 products (CTH Himawari), CTH detected by KPR (CTHKPR) is mostly lower, with a difference (Delta H) ranging from 0.5 km to 3 km. Statistics of 11 flight observations over North China Plain reveal a non-monotonous dependence of Delta H on Re, while Delta H is well correlated with CTT. In addition, larger particles as observed by Himawari-8 around cloud tops are characterized by more significant size growth than smaller ones, which may be attributed to more efficient aggregation. Two events with small and medium-to-large Re are analyzed, respectively.

Detecting an unambiguous radar reflectivity signature is vital for investigating cloud-seeding impacts. The radar reflectivity change attributed to seeding depends on both the cloud conditions and the concentration of silver iodide (AgI) particles. In this study, the reflectivity change induced by glaciogenic seeding using different AgI particle concentrations is investigated under various cloud conditions using a 1D ice growth model coupled with an AgI nucleation parameterization. In addition, an algorithm is developed to estimate the minimum AgI particle concentration needed for a measurable glaciogenic cloud-seeding signature, assuming there is sufficient supercooled liquid water. The results show that the 1D model captures the ice growth habit compared to available observations and yields an unambiguous reflectivity change that is consistent with 3D model simulations and previous observational studies. Simulations indicate that seeding at a temperature of about -15 degrees C has the highest probability of detecting the radar seeding signature. This finding is consistent with the fact that the seeding temperature was about -15 degrees C or slightly warmer in most documented cases of unambiguous seeding signatures. Using the 1D model, 2500 numerical experiments are conducted, and the outputs are used to develop a parameterization to estimate the AgI particle concentration needed to detect an unambiguous seeding signature. Application of this parameterization to a real case suggests that seeding between -21 and -11 degrees C may possibly produce unambiguous seeding signatures and that seeding at about -15 degrees C requires the lowest AgI particle concentration. Seeding at warmer temperatures in precipitating clouds requires an extremely high amount of AgI and a very high content of supercooled liquid water. The results shown in this study deepen our understanding of the relationship between AgI particle concentration and radar seeding signatures under different cloud conditions. The parameterization can be used in operational seeding-based decision-making regarding the optimal amount of AgI dispersed.

Aerosol particles have an important role in Earth's radiation balance and climate, both directly and indirectly through aerosol-cloud interactions. Most aerosol particles in the atmosphere are weakly charged, affecting both their collision rates with ions and neutral molecules, as well as the rates by which they are scavenged by other aerosol particles and cloud droplets. The rate coefficients between ions and aerosol particles are important since they determine the growth rates and lifetimes of ions and charged aerosol particles, and so they may influence cloud microphysics, dynamics, and aerosol processing. However, despite their importance, very few experimental measurements exist of charged aerosol collision rates under atmospheric conditions, where galactic cosmic rays in the lower troposphere give rise to ion pair concentrations of around 1000 cm(-3). Here we present measurements in the CERN CLOUD chamber of the rate coefficients between ions and small (< 10 nm) aerosol particles containing up to 9 elementary charges, e. We find the rate coefficient of a singly charged ion with an oppositely charged particle increases from 2.0 (0.4-4.4) x 10(-6) cm(3) s(-1) to 30.6 (24.9-45.1) x 10(-6) cm(3) s(-1) for particles with charges of 1 to 9 e, respectively, where the parentheses indicate the +/- 1 sigma uncertainty interval. Our measurements are compatible with theoretical predictions and show excellent agreement with the model of Gatti and Kortshagen (2008).

Volatile organic compounds (VOCs) are precursors for ozone and secondary organic aerosol (SOA) formation, thereby playing a vital role in atmospheric chemistry and urban air quality. To characterize the relationship between VOCs and SOA, organics both in gas and particulate phases were concurrently measured in urban Beijing. The VOCs and organic aerosol (OA) were apportioned into factors with different oxidation levels by applying the factorization analysis on their detailed mass spectra. Six factors of VOCs were identified, including four primary VOCs (PVOC) factors and two secondary VOCs (SVOC) factors. The PVOC factors dominated the total VOCs when the air mass originated in the cleaner northern areas, while SVOC factors dominated for polluted southern air masses. The normalized concentrations of PVOC and primary OA factors showed consistent diurnal variations regardless of air mass directions, owing to the relatively stable local emissions during the experimental period. This contrasted with the secondary factors due to more complex transformation processes. The traffic-related VOCs and solid fuel combustion VOCs negatively correlated with SOA, implying that they may have contributed to the SOA formation through photooxidation. The VOCs in lower oxidation levels were found to have poor correlations with the less oxidized SOA, whereas they correlated strongly to the more oxidized SOA. This implied that the less oxidized SOA may be in a transition state, where its production and loss rates were balanced. These served as products of VOCs oxidation and reactants of more oxidized SOA formation, playing important roles on the VOC to SOA transformation. The identified VOC emission sources and their photochemical production of SOA should be considered in air quality policy planning.

The data of INP concentrations from the CFDC, aerosol size distributions from the APS and mass concentrations of PM10, PM2.5 and PM1 are displayed. The data in episodes are also displayed.

Biogenic organic precursors play an important role in atmospheric new particle formation (NPF). One of the major precursor species is α-pinene, which upon oxidation can form a suite of products covering a wide range of volatilities. Highly oxygenated organic molecules (HOMs) comprise a fraction of the oxidation products formed. While it is known that HOMs contribute to secondary organic aerosol (SOA) formation, including NPF, they have not been well studied in newly formed particles due to their very low mass concentrations. Here we present gas- and particle-phase chemical composition data from experimental studies of α-pinene oxidation, including in the presence of isoprene, at temperatures (−50 and −30 ∘C) and relative humidities (20 % and 60 %) relevant in the upper free troposphere. The measurements took place at the CERN Cosmics Leaving Outdoor Droplets (CLOUD) chamber. The particle chemical composition was analyzed by a thermal desorption differential mobility analyzer (TD-DMA) coupled to a nitrate chemical ionization–atmospheric pressure interface–time-of-flight (CI-APi-TOF) mass spectrometer. CI-APi-TOF was used for particle- and gas-phase measurements, applying the same ionization and detection scheme. Our measurements revealed the presence of C8−10 monomers and C18−20 dimers as the major compounds in the particles (diameter up to ∼ 100 nm). Particularly, for the system with isoprene added, C5 (C5H10O5−7) and C15 compounds (C15H24O5−10) were detected. This observation is consistent with the previously observed formation of such compounds in the gas phase. However, although the C5 and C15 compounds do not easily nucleate, our measurements indicate that they can still contribute to the particle growth at free tropospheric conditions. For the experiments reported here, most likely isoprene oxidation products enhance the growth of particles larger than 15 nm. Additionally, we report on the nucleation rates measured at 1.7 nm (J1.7 nm) and compared with previous studies, we found lower J1.7 nm values, very likely due to the higher α-pinene and ozone mixing ratios used in the present study.

Characterizing vertical profiles of aerosol optical properties is important because relying on only the surface or column-integrated measurements cannot unambiguously constrain the radiative impacts of aerosol. This study presents series of vertical profiles of in situ measured multi-wavelength optical properties of aerosols during three pollution events from November to December 2016 over the Beijing region. For all pollution events, the clean periods (CPs) before pollution initialization showed a higher scattering Ångström exponent (SAE) and a smaller asymmetry parameter (g) with relatively uniform vertical structures. The heavy pollution periods (HPs) showed an increased particle size, causing these parameters to vary in the opposite way. During the transition periods (TPs), regional transport of aged aerosols at higher altitudes was found. The Aerosol Robotic Network (AERONET) aerosol optical depth (AOD) matched the in situ measurements within 10 %; however the AERONET absorption optical depth (AAOD) was 10 %–20 % higher than the in situ measurements, and this positive discrepancy increased to 30 % at shorter wavelengths. The absorption of brown carbon (BrC) was identified by the increased-absorption Ångström exponent (AAE), and the heating rate of black carbon (BC) and BrC was estimated by computing the spectral absorption coefficient and actinic flux calculated by a radiative transfer model. BC and BrC had a heating rate of up to 0.18 and 0.05 K h−1 in the planetary boundary layer (PBL), respectively, during the pollution period. The fraction of BrC absorption increased from 12 % to 40 % in the PBL from the CP to the HP. Notably, a higher contribution of BrC heating was found above the PBL under polluted conditions. This study paints a full picture of shortwave heating impacts of carbonaceous aerosols during different stages of pollution events and highlights the increased contribution of BrC absorption especially at higher altitudes during pollution.

This manuscript presents aerosol optical properties and heating rate along vertical profiles. Due to the several feedbacks triggered by the vertical forcing behaviour I encourage the publication of this work after a serious revision as some parts are not clear enough and other require an improved description. Finally, a comparison with other data available in literature is required. A final improvement of the english is mandatory due to the several typos present along the paper.