Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system

Computational Modeling of the Conformation-Dependent Atmospheric Reactivity of Criegee Intermediates

The impacts of Criegee intermediates (CIs) on atmospheric chemistry depend significantly on the CI conformation. In this Perspective, I highlight examples of how electronic structure and statistical rate theory calculations, in conjunction with experiment, have revealed conformation-dependent details of both CI ground-state reactivity and electronic excitation. Calculations using single-reference electronic structure methods and conventional transition state theory have predicted that CIs with syn-alkyl or syn-vinyl substituents isomerize rapidly to vinyl hydroperoxides (VHPs) or dioxoles, both of which can decompose rapidly under atmospheric conditions. Ongoing computational research on hydroxyl radical (OH) roaming initiated by VHP dissociation requires the application of multireference electronic structure methods and variational transition state theory. CIs that lack both syn-alkyl and syn-vinyl substituents undergo either bimolecular reaction or π* ← π electronic excitation in the atmosphere. Accurate predictions of CI ultraviolet-visible spectra require multireference calculations with large active spaces and at least a second-order perturbative treatment of dynamic electron correlation. The extent to which electronic spectra can be diagnostic of the presence of specific CI conformers varies significantly with CI chemical identity.

Single Liquid Aerosol Microparticle Electrochemistry on a Suspended Ionic Liquid Film

Liquid aerosols are ubiquitous in nature, and several tools exist to quantify their physicochemical properties. As a measurement science technique, electrochemistry has not played a large role in aerosol analysis because electrochemistry in air is rather difficult. Here, a remarkably simple method is demonstrated to capture and electroanalyze single liquid aerosol particles with radii on the order of single micrometers. An electrochemical cell is constructed by a microwire (cylindrical working electrode) traversing a film of ionic liquid (1-butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide) that is suspended within a wire loop (reference/counter electrode). An ionic liquid is chosen because the low vapor pressure preserves the film over weeks, vastly improving suspended film electroanalysis. The resultant high surface area allows the suspended ionic liquid cell to act as an aerosol net. Given the hydrophobic nature of the ionic liquid, aqueous aerosol particles do not coalesce into the film. When the liquid aerosols collide with the sufficiently biased microwire (creating a complex boundary: aerosol|wire|ionic liquid|air), the electrochemistry within a single liquid aerosol particle can be interrogated in real-time. The ability to achieve liquid aerosol size distributions for aerosols over 1 µm in radius is demonstrated.

Response of biogenic secondary organic aerosol formation to anthropogenic NOx emission mitigation

This study investigates the effects of anthropogenic nitrogen oxide (NOx) mitigation reduction on secondary organic aerosol (SOA) formation from monoterpene and sesquiterpene precursors across Europe, using the three-dimensional (3-D) Chemical Transport Model (CTM) CHIMERE. Two SOA mechanisms of varying complexity are employed: the GENOA-generated Biogenic Mechanism (GBM) and the Hydrophobic/Hydrophilic Organic mechanism (H2O). GBM is a condensed SOA mechanism generated by automatic reduction from near-explicit chemical mechanisms (i.e., the Master Chemical Mechanism - MCM and the peroxy radical autoxidation mechanism - PRAM) using the GENerator of Reduced Organic Aerosol Mechanisms version 2.0 (GENOA v2.0). Conversely, the H2O mechanism is developed primarily based on experimental data, with simplified chemical pathways and SOA formation yields reflecting those from chamber experiments. In the 3-D simulations conducted for the summer of 2018 over Europe, the implementation of GBM significantly improved the model's performance in comparison to simulations using the H2O mechanism, yielding results more consistent with measured aerosol concentrations extracted from the EBAS database. In response to NOx emission mitigation, simulated SOA concentrations increase with GBM but decrease when using the H2O mechanism, unless a highly oxygenated molecules (HOMs) formation scheme is incorporated. The SOA composition becomes more oxidized and concentrations elevate after NOx reduction, particularly in simulations using GBM. These higher concentrations are likely due to enhanced reaction rates of organic peroxy radicals (RO2) with HO2, resulting in more oxidized products from monoterpene degradation that favors HOM formation. The results suggest that detailed SOA mechanisms including autoxidation are necessary for accurate predictions of SOA concentrations in 3-D modeling.

Hydrated Formic Acid Clusters and their Interaction with Electrons

We investigate ion formation in hydrated formic acid (FA) clusters upon collision with electrons of variable energy, focusing on electron ionization at 70 eV (EI) and low-energy (1.5-15 eV) electron attachment (EA). To uncover details about the composition of neutral clusters, we aim to elucidate the ion formation processes in FAM ⋅ WN clusters initiated by interaction with electrons and determine the extent of cluster fragmentation. EI predominantly produces protonated [FAm+H]+ ions, and in FA-rich clusters, the stable ring structures surrounding H3O+ ions are formed. In contrast, EA leads to a competition between the formation of intact [FAm ⋅ Wn]- and dissociated [FAm ⋅ Wn-H]- fragment ions, influenced by the cluster size, level of hydration, and electron energy. Our findings reveal a predisposition of low-energy EA towards forming [FAm ⋅ Wn]-, while higher electron energies tend to favor the formation of [FAm ⋅ Wn-H]- due to intracluster ion-molecule reactions. The comparison of positive and negative ion spectra suggests that the mass spectra of FA-rich clusters may indicate their actual size and composition. On the other hand, the more weakly bound water evaporation from the clusters depends strongly on the ionization. Thus, for the hydrated clusters, the neutral cluster size can hardly be estimated from the mass spectra.

Application of advanced causal analyses to identify processes governing secondary organic aerosols

Understanding how different physical and chemical atmospheric processes affect the formation of fine particles has been a persistent challenge. Inferring causal relations between the various measured features affecting the formation of secondary organic aerosol (SOA) particles is complicated since correlations between variables do not necessarily imply causality. Here, we apply a state-of-the-art information transfer measure coupled with the Koopman operator framework to infer causal relations between isoprene epoxydiol SOA (IEPOX-SOA) and different chemistry and meteorological variables derived from detailed regional model predictions over the Amazon rainforest. IEPOX-SOA represents one of the most complex SOA formation pathways and is formed by the interactions between natural biogenic isoprene emissions and anthropogenic emissions affecting sulfate, acidity and particle water. Since the regional model captures the known relations of IEPOX-SOA with different chemistry and meteorological features, their simulated time series implicitly include their causal relations. We show that our causal model successfully infers the known major causal relations between total particle phase 2-methyl tetrols (the dominant component of IEPOX-SOA over the Amazon) and input features. We provide the first proof of concept that the application of our causal model better identifies causal relations compared to correlation and random forest analyses performed over the same dataset. Our work has tremendous implications, as our methodology of causal discovery could be used to identify unknown processes and features affecting fine particles and atmospheric chemistry in the Earth's atmosphere.

Exploring the association between long-term MODIS aerosol and air pollutants data across the Northern Great Plains through machine learning analysis

Aerosol optical depth (AOD) and Ångström exponent (AE) are the major environmental indicators to perceive air quality and the impact of aerosol on climate change and health as well as the global atmospheric conditions. In the present study, an average of AOD and AE data from Tera and Aqua satellites of MODIS sensors has been investigated over 7 years i.e., from 2016 to 2022, at four locations over Northern Great Plains. Both temporal and seasonal variations over the study periods have been investigated to understand the behavior of AOD and AE. Over the years, the highest AOD and AE were observed in winter season, varying from 0.75 to 1.17 and 1.30 to 1.63, respectively. During pre-monsoon season, increasing trend of AOD varying from 0.65 to 0.95 was observed from upper (New Delhi) to lower (Kolkata) Gangetic plain, however, during monsoon and post-monsoon a reverse trend varying from 0.85 to 0.65 has been observed. Seasonal and temporal aerosol characteristics have also been analyzed and it has been assessed that biomass burning was found to be the major contributor, followed by desert dust at all the locations except in Lucknow, where the second largest contributor was dust instead of desert dust. During season-wise analysis, biomass burning was also found to be as the major contributor at all the places in all the seasons except New Delhi and Lucknow, where dust was the major contributor during pre-monsoon. A boosting regression algorithm was done using machine learning to explore the relative influence of different atmospheric parameters and pollutants with PM2.5. Water vapor was assessed to have the maximum relative influence i.e., 51.66 % followed by CO (21.81 %). This study aims to help policy makers and decision makers better understand the correlation between different atmospheric components and pollutants and the contribution of different types of aerosols.

Development and evaluation of an online monitoring single-particle optical particle counter with polarization detection

We developed a single-particle optical particle counter with polarization detection (SOPC) for the real-time measurement of the optical size and depolarization ratio (defined as the ratio of the vertical component to the parallel component of backward scattering) of atmospheric particles, the polarization ratio (DR) value can reflect the irregularity of the particles. The SOPC can detect aerosol particles with size larger than 500 nm and the maximum particle count rate reaches ∼1.8 × 105 particles per liter. The SOPC uses a modulated polarization laser to measure the optical size of particles according to forward scattering signal and the DR value of the particles by backward S and P signal components. The sampling rate of the SOPC was 106 #/(sec·channel), and all the raw data were processed online. The calibration curve was obtained by polystyrene latex spheres with sizes of 0.5-10 µm, and the average relative deviation of measurement was 3.96% for sub 3 µm particles. T-matrix method calculations showed that the DR value of backscatter light at 120° could describe the variations in the aspect ratio of particles in the above size range. We performed insitu observations for the evaluation of the SOPC, the mass concentration constructed by the SOPC showed good agreement with the PM2.5 measurements in a nearby state-controlled monitoring site. This instrument could provide useful data for source appointment and regulations against air pollution.

Cloud condensation nuclei activity of internally mixed particle populations at a remote marine free troposphere site in the North Atlantic Ocean

This study reports results from research conducted at the Observatory of Mount Pico (OMP), 2225 m above mean sea level on Pico Island in the Azores archipelago in June and July 2017. We investigated the chemical composition, mixing state, and cloud condensation nuclei (CCN) activities of long-range transported free tropospheric (FT) particles. FLEXible PARTicle Lagrangian particle dispersion model (FLEXPART) simulations reveal that most air masses that arrived at the OMP during the sampling period originated in North America and were highly aged (average plume age > 10 days). We probed size-resolved chemical composition, mixing state, and hygroscopicity parameter (κ) of individual particles using computer-controlled scanning electron microscopy with an energy-dispersive X-ray spectrometer (CCSEM-EDX). Based on the estimated individual particle mass from elemental composition, we calculated the mixing state index, χ. During our study, FT particle populations were internally mixed (χ of samples are between 53 % and 87 %), owing to the long atmospheric aging time. We used data from a miniature Cloud Condensation Nucleus Counter (miniCCNC) to derive the hygroscopicity parameter, κCCNC. Combining κCCNC and FLEXPART, we found that air masses recirculated above the North Atlantic Ocean with lower mean altitude had higher κCCNC due to the higher contribution of sea salt particles. We used CCSEM-EDX and phase state measurements to predict single-particle κ (κCCSEM-EDX) values, which overlap with the lower range of κCCNC measured below 0.15 % SS. Therefore, CCSEM-EDX measurements can be useful in predicting the lower bound of κ, which can be used in climate models to predict CCN activities, especially in remote locations where online CCN measurements are unavailable.

Spatio-temporal evolution of long-range transported mineral desert dust properties over rural and urban sites in Central Europe

An exceptionally strong and very fast (120h) mineral dust inflow from North Africa to Poland was predicted by NMMB/BSC-Dust and NAAPS models on 10-11 June 2019. Simultaneous measurements with two complex lidar systems at the EARLINET-ACTRIS urban site in Warsaw (Central Poland) and the PolWET peatland site in Rzecin (Western Poland) captured the evolution of this dust event. The advected air masses had different source areas in North Africa, they were reaching each station via independent pathways, and thus, were unlikely mixed with each other. The excellent capabilities of the next generation PollyXT lidar and the mobile EMORAL lidar allowed for the derivation of full datasets of aerosol optical properties profiles that enabled comparative study of the advected dust properties evolution. Within a mere 350 km distance between Warsaw and Rzecin, distinctly different dust properties were measured, respectively: dry mineral dust composed mainly of coarse mode dust particles (50 ± 5 % of the total particle backscattering profile) versus the wet mineral dust dominated by fine dust particles (58 ± 4 %). A new parameter fine-to-coarse dust ratio (FCDR) is proposed to describe more intuitively mineral dust composition.

Abundant nitrogenous secondary organic aerosol formation accelerated by cloud processing

Nitrogenous organic (CHON), crucial for secondary organic aerosol (SOA), forms through poorly studied mechanisms in clouds. Our study explores CHON transformation during cloud processes (CPs). These processes play a vital role in enhancing the variety of CHONs, leading to the formation of CHONs with oxygen atom counts ranging from 1 to 10 and double bond equivalent (DBE) values spanning from 2 to 10. We proposed that the CHONs formed during CPs are formed through aqueous phase reactions with CHO compound precursors via nucleophilic attacks by NH3. This scheme can be account for roughly three-quarters of the CHONs by number in cloud water, and near two-thirds of all CHONs are formed through reactions between NH3 and carbonyl-containing biogenic volatile organic compound (BVOC) ozonolysis intermediates. This study provides the first insights into the evolution of CHONs during CPs and reveals the significant roles of CPs in the formation of CHONs.

Plant versus local soil inorganic ionic composition: The relationship to biomass smoke

We examine the relationship between soil and plant inorganic chemical composition as a precursor to biomass smoke aerosol particle (PM2.5) properties in desert landscapes of the Southwestern United States. Past work underscored the importance of plant species and in particular the dependence of smoke PM2.5 water uptake on the water-soluble inorganics important in select plant species (e.g., halophytes) versus absent in other species (e.g., conifers). This study extends this work by looking at a range of soil types and salinity in examining native and invasive species in the Desert Southwest US region. Eighteen plant samples and surrounding soils were taken from four ecosystems in New Mexico, USA. Results here support the conclusion that plant species are the primary controller over the inorganic plant composition that is relevant to biomass smoke and controls its hygroscopicity. The role of soil type is secondary to plant inorganic composition but is found to be important on the ecosystem level in determining what plant species are viable in a given ecosystem. This ultimately affects the smoke properties, including PM2.5 hygroscopicity (water uptake), produced in landscape fires. Knowledge of ecosystem features including plant species distribution and soil salinity may be combined as a first-order predictor of PM2.5 hygroscopicity of the primary smoke emissions. This can be particularly useful when combined with knowledge of burn characteristics such as flame temperature, which also plays a key role in determining PM2.5 water uptake response.

Nonequilibrium Behavior in Isoprene Secondary Organic Aerosol

Recent studies have shown that instantaneous gas-particle equilibrium partitioning assumptions fail to predict SOA formation, even at high relative humidity (∼85%), and photochemical aging seems to be one driving factor. In this study, we probe the minimum aging time scale required to observe nonequilibrium partitioning of semivolatile organic compounds (SVOCs) between the gas and aerosol phase at ∼50% RH. Seed isoprene SOA is generated by photo-oxidation in the presence of effloresced ammonium sulfate seeds at <1 ppbv NOx, aged photochemically or in the dark for 0.3-6 h, and subsequently exposed to fresh isoprene SVOCs. Our results show that the equilibrium partitioning assumption is accurate for fresh isoprene SOA but breaks down after isoprene SOA has been aged for as short as 20 min even in the dark. Modeling results show that a semisolid SOA phase state is necessary to reproduce the observed particle size distribution evolution. The observed nonequilibrium partitioning behavior and inferred semisolid phase state are corroborated by offline mass spectrometric analysis on the bulk aerosol particles showing the formation of organosulfates and oligomers. The unexpected short time scale for the phase transition within isoprene SOA has important implications for the growth of atmospheric ultrafine particles to climate-relevant sizes.

Low-NO-like Oxidation Pathway Makes a Significant Contribution to Secondary Organic Aerosol in Polluted Urban Air

Anthropogenic pollutants can greatly mediate formation pathways and chemical compositions of secondary organic aerosol (SOA) in urban atmospheres. We investigated the molecular tracers for different types of SOA in PM2.5 under varying NO/NO2 conditions in Guangzhou using source analysis of particle-phase speciated organics obtained from an iodide chemical ionization mass spectrometer with a Filter Inlet for Gases and AEROsols (FIGAERO-I-CIMS). Results show that low-NO-like pathways (when NO/NO2 < 0.2) explained ∼75% of the total measured FIGAERO-OA during regional transport periods, which was enriched in more-oxidized C4-C6 non-nitrogenous compounds over ozone accumulation. Daytime high-NO chemistry played larger roles (38%) in local pollution episodes, with organic nitrates (ONs) and nitrophenols increasing with enhanced aerosol water content and nitrate fraction. Nighttime NO3-initiated oxidation, characterized by monoterpene-derived ONs, accounted for comparable percentages (10-12%) of FIGAERO-OA for both two periods. Furthermore, the presence of organosulfates (OSs) improves the understanding of the roles of aqueous-phase processes in SOA production. Carbonyl-derived OSs exhibited a preferential formation under conditions of high aerosol acidity and/or abundant sulfate, which correlated well with low-NO-like SOA. Our results demonstrate the importance of NO/NO2 ratios in controlling SOA compositions, as well as interactions between water content, aerosol acidity, and inorganic salts in gas-to-particle partitioning of condensable organics.

Global Health and Climate Effects of Organic Aerosols from Different Sources

The impact of aerosols on human health and climate is well-recognized, yet many studies have only focused on total PM2.5 or changes from anthropogenic activities. This study quantifies the health and climate effects of organic aerosols (OA) from anthropogenic, biomass burning, and biogenic sources. Using two atmospheric chemistry models, CAM-chem and GEOS-Chem, our findings reveal that anthropogenic primary OA (POA) has the highest efficiency for health effects but the lowest for direct radiative effects due to spatial and temporal variations associated with population and surface albedo. The treatment of POA as nonvolatile or semivolatile also influences these efficiencies through different chemical processes. Biogenic OA shows moderate efficiency for health effects and the highest for direct radiative effects but has the lowest efficiency for indirect effects due to the reduced high cloud, caused by stabilized temperature profiles from aerosol-radiation interactions in biogenic OA-rich regions. Biomass burning OA is important for cloud radiative effect changes in remote atmospheres due to its ability to be transported further than other OAs. This study highlights the importance of not only OA characteristics such as toxicity and refractive index but also atmospheric processes such as transport and chemistry in determining health and climate impact efficiencies.

Formation of nitrogen-containing gas phase products from the heterogeneous (photo)reaction of NO2 with gallic acid

Heterogeneous reaction of gas phase NO2 with atmospheric humic-like substances (HULIS) is potentially an important source of volatile organic compounds (VOCs) including nitrogen (N)-containing compounds, a class of brown carbon of emerging importance. However, the role of ubiquitous water-soluble aerosol components in this multiphase chemistry, namely nitrate and iron ions, remains largely unexplored. Here, we used secondary electrospray ionization ultrahigh-resolution mass spectrometry for real-time measurements of VOCs formed during the heterogeneous reaction of gas phase NO2 with a solution containing gallic acid (GA) as a proxy of HULIS at pH 5 relevant for moderately acidic aerosol particles. Results showed that the number of detected N-containing organic compounds largely increased from 4 during the NO2 reaction with GA in the absence of nitrate and iron ions to 55 in the presence of nitrate and iron ions. The N-containing compounds have reduced nitrogen functional groups, namely amines, imines and imides. These results suggest that the number of N-containing compounds is significantly higher in deliquescent aerosol particles due to the influence of relatively higher ionic strength from nitrate ions and complexation/redox reactivity of iron cations compared to that in the dilute aqueous phase representative of cloud, fog, and rain water.

Heterogeneous Ice Nucleation in Model Crystalline Porous Organic Polymers: Influence of Pore Size on Immersion Freezing

Heterogeneous ice nucleation activity is affected by aerosol particle composition, crystallinity, pore size, and surface area. However, these surface properties are not well understood, regarding how they act to promote ice nucleation and growth to form ice clouds. Therefore, synthesized materials for which surface properties can be tuned were examined in immersion freezing mode in this study. To establish the relationship between particle surface properties and efficiency of ice nucleation, materials, here, covalent organic frameworks (COFs), with different pore diameters and degrees of crystallinity (ordering), were characterized. Results showed that out of all the highly crystalline COFs, the sample with a pore diameter between 2 and 3 nm exhibited the most efficient ice nucleation activity. We posit that the highly crystalline structures with ordered pores have an optimal pore diameter where the ice nucleation activity is maximized and that the not highly crystalline structures with nonordered pores have more sites for ice nucleation. The results were compared and discussed in the context of other synthesized porous particle systems. Such studies give insight into how material features impact ice nucleation activity.

Multi-campaign ship and aircraft observations of marine cloud condensation nuclei and droplet concentrations

In-situ marine cloud droplet number concentrations (CDNCs), cloud condensation nuclei (CCN), and CCN proxies, based on particle sizes and optical properties, are accumulated from seven field campaigns: ACTIVATE; NAAMES; CAMP2EX; ORACLES; SOCRATES; MARCUS; and CAPRICORN2. Each campaign involves aircraft measurements, ship-based measurements, or both. Measurements collected over the North and Central Atlantic, Indo-Pacific, and Southern Oceans, represent a range of clean to polluted conditions in various climate regimes. With the extensive range of environmental conditions sampled, this data collection is ideal for testing satellite remote detection methods of CDNC and CCN in marine environments. Remote measurement methods are vital to expanding the available data in these difficult-to-reach regions of the Earth and improving our understanding of aerosol-cloud interactions. The data collection includes particle composition and continental tracers to identify potential contributing CCN sources. Several of these campaigns include High Spectral Resolution Lidar (HSRL) and polarimetric imaging measurements and retrievals that will be the basis for the next generation of space-based remote sensors and, thus, can be utilized as satellite surrogates.

Spontaneous dark formation of OH radicals at the interface of aqueous atmospheric droplets

Hydroxyl radical (OH) is a key oxidant that triggers atmospheric oxidation chemistry in both gas and aqueous phases. The current understanding of its aqueous sources is mainly based on known bulk (photo)chemical processes, uptake from gaseous OH, or related to interfacial O3 and NO3 radical-driven chemistry. Here, we present experimental evidence that OH radicals are spontaneously produced at the air-water interface of aqueous droplets in the dark and the absence of known precursors, possibly due to the strong electric field that forms at such interfaces. The measured OH production rates in atmospherically relevant droplets are comparable to or significantly higher than those from known aqueous bulk sources, especially in the dark. As aqueous droplets are ubiquitous in the troposphere, this interfacial source of OH radicals should significantly impact atmospheric multiphase oxidation chemistry, with substantial implications on air quality, climate, and health.

Optical trapping and light scattering in atmospheric aerosol science

Aerosol particles are ubiquitous in the atmosphere, and currently contribute a large uncertainty to climate models. Part of the endeavour to reduce this uncertainty takes the form of improving our understanding of aerosol at the microphysical level, thus enabling chemical and physical processes to be more accurately represented in larger scale models. In addition to modeling efforts, there is a need to develop new instruments and methodologies to interrogate the physicochemical properties of aerosol. This perspective presents the development, theory, and application of optical trapping, a powerful tool for single particle investigations of aerosol. After providing an overview of the role of aerosol in Earth's atmosphere and the microphysics of these particles, we present a brief history of optical trapping and a more detailed look at its application to aerosol particles. We also compare optical trapping to other single particle techniques. Understanding the interaction of light with single particles is essential for interpreting experimental measurements. In the final part of this perspective, we provide the relevant formalism for understanding both elastic and inelastic light scattering for single particles. The developments discussed here go beyond Mie theory and include both how particle and beam shape affect spectra. Throughout the entirety of this work, we highlight numerous references and examples, mostly from the last decade, of the application of optical trapping to systems that are relevant to the atmospheric aerosol.

Impact of urban aerosols on the cloud condensation activity using a clustering model

The indirect effect of aerosols on climate through aerosol-cloud-interactions is still highly uncertain and limits our ability to assess anthropogenic climate change. The foundation of this uncertainty is in the number of cloud condensation nuclei (CCN), which itself mainly stems from uncertainty in aerosol sources and how particles evolve to become effective CCN. We analyze particle number size distribution (PNSD) and CCN measurements from an urban site in a two-step method: (1) we use an unsupervised clustering model to classify the main aerosol categories and processes occurring in the urban atmosphere and (2) we explore the influence of the identified aerosol populations on the CCN properties. According to the physical properties of each cluster, its diurnal timing, and additional air quality parameters, the clusters are grouped into five main aerosol categories: nucleation, growth, traffic, aged traffic, and urban background. The results show that, despite aged traffic and urban background categories are those with lower total particle number concentrations (N_tot) these categories are the most efficient sources in terms of contribution to the overall CCN budget with activation fractions (AF) around 0.5 at 0.75 % supersaturation (SS). By contrast, road traffic is an important aerosol source with the highest frequency of occurrence (32 %) and relatively high N_tot, however, its impact in the CCN activity is very limited likely due to lower particle mean diameter and hydrophobic chemical composition. Similarly, nucleation and growth categories, associated to new particle formation (NPF) events, present large N_tot with large frequency of occurrence (22 % and 28 %, respectively) but the CCN concentration for these categories is about half of the CCN concentration observed for the aged traffic category, which is associated with their small size. Overall, our results show that direct influence of traffic emissions on the CCN budget is limited, however, when these particles undergo ageing processes, they have a significant influence on the CCN concentrations and may be an important CCN source. Thus, aged traffic particles could be transported to other environments where clouds form, triggering a plausible indirect effect of traffic emissions on aerosol-cloud interactions and consequently contributing to climate change.

Analysis and Variation of the Maiac Aerosol Optical Depth in Underexplored Urbanized Area of National Capital Region, India

Aerosol monitoring is the emerging application field of satellite remote sensing. As a satellite-based indicator of aerosol concentration, aerosol optical depth (AOD) can aid in assessing the crucial effects of aerosols on the global environment. Among various satellite-based aerosol product, Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 (C6), Multiangle Implementation of Atmospheric Correction (MAIAC) aerosol product (1 km resolution) has still untapped potential in Indian regions. Considering the importance of regional validation of such high-resolution aerosol product, the present study attempts to fill this gap by validating MAIAC aerosol estimates (AODMAIAC) in highly polluted districts (Faridabad, Ghaziabad, Gautam Budh Nagar, Gurugram) of National Capital Region (NCR) with heavy aerosol loading using limited AErosol RObotic NETwork (AERONET) observations obtained from AERONET sites at Amity University (AU) and Gual Pahari (GP). Such evaluation of satellite-retrieved aerosol product with ground data confirms its practicality based on retrieval errors (Expected Error (EE) values (EE = 0.05 + 15 %*AOD) (EE: 78.85 % at AU, 73.58 % at GP), root mean square error (RMSE) values (RMSE: 0.15 at AU, 0.24 at GP), and correlation coefficient (R) values (R: 0.86 at AU, 0.73 at GP). The seasonal variation in AOD over the study area from 2010-2019 reveals increasing trend of AOD in the monsoon and post-monsoon season due to natural and anthropogenic factors. In addition to contributing to a holistic assessment of MAIAC aerosol estimates as a recent, high-resolution aerosol product, present results provide a basis for further research into NCR aerosols.

Quantifying the capacity of tree branches for retaining airborne submicron particles

Human health risks brought by fine atmospheric particles raise scholarly and policy awareness about the role of urban trees as bio-filters of air pollution. While a large number of empirical studies have focused on the characteristics of vegetation leaves and their effects on atmospheric particle retention, the dry deposition of particles on branches, which plays a significant role in capturing and retaining particles during the defoliation period and contributes substantially to total removal of atmospheric particles, is under-investigated. To fill in this knowledge gap, this case study examined the dry deposition velocities (V_d) of submicron particulate matters (PM₁) on the branches of six common deciduous species in Shanghai (China) using laboratory experiments. And the association between V_d and key branch anatomical traits (including surface roughness, perimeter, rind width proportion, lenticel density, peeling, and groove/ridge characteristics) was explored. It was found that surface roughness would increase V_d, as a rougher surface significantly increases turbulence, which is conducive to particle diffusion. By contrast, peeling, branch perimeter, and lenticel density would decrease V_d. Peeling represents the exfoliated remains on the branch surfaces which may flutter considerably with airflow, leading to particle resuspension and low V_d. When branch perimeter increases, the boundary layer of branches thickens and a wake area appears, increasing the difficulty of particles to reach branch surface, and reducing V_d. While lenticels can increase the roughness of branch surface, their pointy shape would uplift airflow and cause a leeward wake area, lowering V_d. This finely wrought study contributes to a better understanding of branch dry deposition during leaf-off seasons and potential of deciduous trees serving as nature-based air filters all year round in urban environments.

Climatology and model prediction of aerosol optical properties over the Indo-Gangetic Basin in north India

The current research focuses on the use of different simulation techniques in the future prediction of the crucial aerosol optical properties over the highly polluted Indo-Gangetic Basin in the northern part of India. The time series model was used to make an accurate forecast of aerosol optical depth (AOD) and angstrom exponent (AE), and the statistical variability of both cases was compared in order to evaluate the effectiveness of the model (training and validation). For this, different models were used to simulate the monthly average AOD and AE over Jaipur, Kanpur and Ballia during the period from 2003 to 2018. Further, the study was aimed to construct a comparative model that will be used for time series statistical analysis of MODIS-derived AOD₅₅₀ and AE_412-470. This will provide a more comprehensive information about the levels of AOD and AE that will exist in the future. To test the validity and applicability of the developed models, root-mean-square error (RMSE), mean absolute error (MAE), mean absolute percent error (MAPE), fractional bias (FB), and Pearson coefficient (r) were used to show adequate accuracy in model performance. From the observation, the monthly mean values of AOD and AE were found to be nearly similar at Kanpur and Ballia (0.62 and 1.26) and different at Jaipur (0.25 and 1.14). Jaipur indicates that during the pre-monsoon season, the AOD mean value was found to be highest (0.32 ± 0.15), while Kanpur and Ballia display higher AOD mean values during the winter season (0.72 ± 0.26 and 0.83 ± 0.32, respectively). Among the different methods, the autoregressive integrated moving average (ARIMA) model was found to be the best-suited model for AOD prediction at Ballia based on fitted error (RMSE (0.22), MAE (0.15), MAPE (24.55), FB (0.05)) and Pearson coefficient r (0.83). However, for AE, best prediction was found at Kanpur based on RMSE (0.24), MAE (0.21), MAPE (22.54), FB (-0.09) and Pearson coefficient r (0.82).

Vertical stratification of aerosols over South Asian cities

This study examines vertically resolved aerosol optical properties retrieved from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard CALIPSO satellite over several cities across South Asia from March 2010 to February 2021. Atmospheric layer-specific stratification of aerosols and dominant aerosol sub-types was recognized over each city with their seasonal trends. A contrasting pattern in aerosol vertical distribution over cities across Indo-Gangetic Plain (IGP) was noted compared to non-IGP cities, with considerable dependency on geographic location of the city itself. In all the cases, total extinction decreased with increasing altitude however, with varying degree of slope. A clear intrusion of transported aerosols at higher altitude (>3 km) was also evident. Extinction coefficient of type-separated aerosols indicate robust contribution of smoke aerosols, urban aerosols/polluted dust, and mineral dust below 3 km height. At higher altitude (>3 km), dust and urban aerosols dominate over majority of the stations. Overall, 51% of total columnar aerosols remained within 0-1 km height over South Asian cities, slightly high over the IGP (57%) against non-IGP cities (39%). Such distribution also has a seasonal pattern with higher fraction of aerosols remaining below 1 km during post-monsoon (October-November, 62%) and winter (December-February, 72%) compared to summer months (March-May, 39%). When partitioned against planetary boundary layer (PBL), 41% (59%) of aerosols remained within the PBL (free troposphere) that too exhibiting strong diurnal variations irrespective of seasons. Dominating aerosol types and their contribution to total aerosol loading was explored by comparing type-based aerosol extinction against total aerosol extinction. Dust, smoke and urban aerosols emerged as three predominating aerosol types, while presence of marine aerosol was noted over the coastal cities. Major fraction of smoke and urban aerosols remained within 2 km height from surface. In contrast, efficient transport of dust aerosol above 2 km height was evident particularly over IGP during summer.

Global reduction in ship-tracks from sulfur regulations for shipping fuel

Ship-tracks are produced by ship-emitted aerosols interacting with low clouds. Here, we apply deep learning models on satellite data to produce the first global climatology map of ship-tracks. We show that ship-tracks are at the nexus of cloud physics, maritime shipping, and fuel regulation. Our map captures major shipping lanes while missing others because of background conditions. Ship-track frequency is more than 10 times higher than a previous survey, and its interannual fluctuations reflect variations in cross-ocean trade, shipping activity, and fuel regulations. Fuel regulation can alter both detected frequency and shipping routes due to cost. The 2020 fuel regulation, together with the coronavirus disease 2019 pandemic, reduced ship-track frequency to its lowest level in recent decades across the globe and may have ushered in an era of low frequency. The regulation reduces the aerosol indirect forcing from ship emissions by 46% or between 0.02 and 0.27 W m^-2 given its current estimates.

Assessment of CALIOP-Derived CCN Concentrations by In Situ Surface Measurements

The satellite-based cloud condensation nuclei (CCN) proxies used to quantify the aerosol-cloud interactions (ACIs) are column integrated and do not guarantee the vertical co-location of aerosols and clouds. This has encouraged the use of height-resolved measurements of spaceborne lidars for ACI studies and led to advancements in lidar-based CCN retrieval algorithms. In this study, we present a comparison between the number concentration of CCN (nCCN) derived from ground-based in situ and spaceborne lidar cloud-aerosol lidar with orthogonal polarization (CALIOP) measurements. On analysing their monthly time series, we found that about 88% of CALIOP nCCN estimates remained within a factor of 1.5 of the in situ measurements. Overall, the CALIOP estimates of monthly nCCN were in good agreement with the in situ measurements with a normalized mean error of 71%, normalized mean bias of 39% and correlation coefficient of 0.68. Based on our comparison results, we point out the necessary measures that should be considered for global nCCN retrieval. Our results show the competence of CALIOP in compiling a global height- and type-resolved nCCN dataset for use in ACI studies.

Vertically Resolved Aerosol Chemistry in the Low Boundary Layer of Beijing in Summer

Air quality in Beijing has been improved significantly in recent years; however, our knowledge of the vertically resolved aerosol chemistry in summer remains poor. Here, we carried out comprehensive measurements of aerosol composition, gaseous species, and aerosol optical properties on a meteorological tower in Beijing in summer and compared with those measured in winter. Our results showed that aerosol liquid water (ALW) contributing approximately 50% of the total mass with higher values aloft played a crucial role in aerosol formation. Particularly, the higher nitrate concentration in city aloft than at the ground level during daytime was mainly due to the enhanced gas-particle partitioning driven by ALW and particle acidity. The vertical profiles of organic aerosol (OA) factors varied more differently in the urban boundary layer. Although the ubiquitous decreases in primary OA with the increase in height were mainly due to the influences of local emissions and vertical convection, the vertical differences in oxygenated OA between summer and winter may be related to the photochemical processing of different biogenic and anthropogenic volatile organic compounds. The single-scattering albedo, brown carbon, and absorption Ångstrom exponent of aerosol particles also presented different vertical profiles between day and night due to the vertical changes in aerosol chemistry.

Role of gas-molecular cluster-aerosol dynamics in atmospheric new-particle formation

New-particle formation from vapors through molecular cluster formation is a central process affecting atmospheric aerosol and cloud condensation nuclei numbers, and a significant source of uncertainty in assessments of aerosol radiative forcing. While advances in experimental and computational methods provide improved assessments of particle formation rates from different species, the standard approach to implement these data in aerosol models rests on highly simplifying assumptions concerning gas-cluster-aerosol dynamics. To quantify the effects of the simplifications, we develop an open-source tool for explicitly simulating the dynamics of the complete particle size spectrum from vapor molecules and molecular clusters to larger aerosols for multi-compound new-particle formation. We demonstrate that the simplified treatment is a reasonable approximation for particle formation from weakly clustering chemical compounds, but results in overprediction of particle numbers and of the contribution of new-particle formation to cloud condensation nuclei for strongly clustering, low-concentration trace gases. The new explicit approach circumvents these issues, thus enabling robust model-measurement comparisons, improved assessment of the importance of different particle formation agents, and construction of optimal simplifications for large-scale models.

Ammonium Chloride Associated Aerosol Liquid Water Enhances Haze in Delhi, India

The interaction between water vapor and atmospheric aerosol leads to enhancement in aerosol water content, which facilitates haze development, but its concentrations, sources, and impacts remain largely unknown in polluted urban environments. Here, we show that the Indian capital, Delhi, which tops the list of polluted capital cities, also experiences the highest aerosol water yet reported worldwide. This high aerosol water promotes secondary formation of aerosols and worsens air pollution. We report that severe pollution events are commonly associated with high aerosol water which enhances light scattering and reduces visibility by 70%. Strong light scattering also suppresses the boundary layer height on winter mornings in Delhi, inhibiting dispersal of pollutants and further exacerbating morning pollution peaks. We provide evidence that ammonium chloride is the largest contributor to aerosol water in Delhi, making up 40% on average, and we highlight that regulation of chlorine-containing precursors should be considered in mitigation strategies.

Anthropogenic Aerosols Effects on Ice Clouds: A Review

Since the ability of anthropogenic aerosols to act as ice nucleation particles has been recognized, the effect of anthropogenic aerosols on ice clouds has attracted increasing attentions. In recent years, some progress has been made in investigating the effects of anthropogenic aerosols on ice clouds. In this paper, we briefly review the study on the impact of anthropogenic aerosols on ice nuclei, properties and radiative forcing of ice clouds. Anthropogenic aerosols can form ice nuclei through homogeneous nucleation and heterogeneous nucleation. Convective strength can modulate the response of ice clouds to anthropogenic aerosols by affecting the nucleation activities. There have been large uncertainties in calculating the radiative forcing of anthropogenic aerosols on ice clouds in climate models. Further studies on the impact of anthropogenic aerosols on ice clouds are imperative to provide better parameterization schemes and reduce the uncertainties of aerosol indirect effects.

Design and Verification of a Double-Grating Spectrometer System (DGSS) for Simultaneous Observation of Aerosols, Water Vapor and Clouds

Simultaneous observation of aerosols, water vapor, and clouds is conducive to the analysis of their interactions, and the consistency of observation equipment, instrument performance, and observation time is crucial. Molecular oxygen A-band (758–778 nm) and water vapor absorption band (758–880 nm) are two bands with similar wavelengths, and the hyperspectral remote sensing information of these two bands can be exploited to invert the vertical profile of aerosol and water vapor. In this paper, a double-grating spectrometer system (DGSS) was developed. DGSS uses a telescope system and fiber to introduce multi-angle, double-band sunlight, and it splits light synchronously (non-sequentially) to different positions of the detector through a slit plate and two gratings. The DGSS was calibrated in the laboratory and observed in the external field. The results indicated that the spectral resolution reached 0.06 nm (molecular oxygen A-band, 758–778 nm) and 0.24 nm (water vapor absorption band, 758–880 nm). Meanwhile, the spectra of the two bands (three angles in each band) are not aliased on the detector. Besides, the multi-angle simultaneous observation of the high-resolution spectra of the two bands is realized, which proves the effectiveness of this method. This study will provide a scientific basis for the observation of aerosol, water vapor, and cloud ground-based networks.

Demonstration of aerosol profile measurement with a dual-wavelength high-spectral-resolution lidar using a scanning interferometer

Simple dual-wavelength high-spectral-resolution lidar at 355 and 532 nm with a scanning interferometer was developed for continuous observations of aerosol profiles. Scanning the interferometer periodically over a range of one fringe at 532 nm (1.5 fringes at 355 nm) enabled recording of range-resolved interference signals at these two wavelengths. Reference signals taken from the transmitted laser were used to correct the interference phase shift due to laser frequency variation for every scan. Profiles of aerosol backscatter and extinction coefficients were retrieved from range-resolved interference data. One month of continuous measurements demonstrated the robustness of the system.

Aerosol Optical Thickness Retrieval in Presence of Cloud: Application to S3A/SLSTR Observations

The Combined Inversion of Surface and AeRosols (CISAR) algorithm for the joint retrieval of surface and aerosol single scattering properties has been further developed in order to extend the retrieval to clouds and overcome the need for an external cloud mask. Pixels located in the transition zone between pure cloud and pure aerosol are often discarded by both aerosol and cloud algorithms, despite being essential for studying aerosol–cloud interactions, which still represent the largest source of uncertainty in climate predictions. The proposed approach aims at filling this gap and deepening the understanding of aerosol properties in cloudy environments. The new CISAR version is applied to Sentinel-3A/SLSTR observations and evaluated against different satellite products and ground measurements. The spatial coverage is greatly improved with respect to algorithms processing only pixels flagged as clear sky by the SLSTR cloud mask. The continuous retrieval of aerosol properties without any safety zone around clouds opens new possibilities for studying aerosol properties in cloudy environments.

Insights about the Sources of PM2.5 in an Urban Area from Measurements of a Low-Cost Sensor Network

PM2.5 measurements using a network of lost-cost sensors were conducted during 2017–2019 in the greater area of Patras, Greece. The average PM2.5 concentration in all sites during the study period was 9.4 μg m−3, varying from 6.2 μg m−3 in the background areas to 12.8 μg m−3 at the city center. The site with the peak PM2.5 levels was not located in an area with high traffic density but rather in a square with pedestrian-only zones and a high restaurant density. The highest PM2.5 concentrations were observed during the colder period (November–March) due to high emissions from residential wood burning for heating purposes. The measurements of the sensors were used to estimate the importance of regional and local PM2.5 sources. During the warm period, regional transport dominated, contributing approximately 80–85% of the PM2.5 in the city center; however, during the colder period, the local sources were responsible for approximately half the PM2.5. The network operated reliably during this multiyear study. Such measurements provide, at a very low cost, valuable insights not only about the temporal and spatial variability of PM2.5 in a city but also about its sources, including the role of regional transport.

Dual-field-of-view high-spectral-resolution lidar: Simultaneous profiling of aerosol and water cloud to study aerosol-cloud interaction

Aerosol–cloud interaction affects the cooling of Earth’s climate, mostly by activation of aerosols as cloud condensation nuclei that can increase the amount of sunlight reflected back to space. But the controlling physical processes remain uncertain in current climate models. We present a lidar-based technique as a unique remote-sensing tool without thermodynamic assumptions for simultaneously profiling diurnal aerosol and water cloud properties with high resolution. Direct lateral observations of cloud properties show that the vertical structure of low-level water clouds can be far from being perfectly adiabatic. Furthermore, our analysis reveals that, instead of an increase of liquid water path (LWP) as proposed by most general circulation models, elevated aerosol loading can cause a net decrease in LWP.

Aerosol–cloud interaction (ACI) is complex and difficult to be well represented in current climate models. Progress on understanding ACI processes, such as the influence of aerosols on water cloud droplet formation, is hampered by inadequate observational capability. Hitherto, high-resolution and simultaneous observations of diurnal aerosol loading and cloud microphysical properties are challenging for current remote-sensing techniques. To overcome this conundrum, we introduce the dual-field-of-view (FOV) high-spectral-resolution lidar (HSRL) for simultaneously profiling aerosol and water cloud properties, especially water cloud microphysical properties. Continuous observations of aerosols and clouds using this instrument, verified by the Monte Carlo simulation and coincident observations of other techniques, were conducted to investigate the interactions between aerosol loading and water cloud microphysical properties. A case study over Beijing highlights the scientific potential of dual-FOV HSRL to become a significant contributor to the ACI investigations. The observed water cloud profiles identify that due to air entrainment its vertical structure is not perfectly adiabatic, as assumed by many current retrieval methods. Our ACI analysis shows increased aerosol loading led to increased droplet number concentration and decreased droplet effective radius—consistent with expectations—but had no discernible increase on liquid water path. This finding supports the hypothesis that aerosol-induced cloud water increase caused by suppressed rain formation can be canceled out by enhanced evaporation. Thus, these observations obtained from the dual-FOV HSRL constitute substantial and significant additions to understanding ACI process. This technique is expected to represent a significant step forward in characterizing ACI.

Machine learning-based estimation of ground-level NO2 concentrations over China

Most current scientific research on NO₂ remote sensing focuses on tropospheric NO₂ column concentrations rather than ground-level NO₂ concentrations; however, ground-level NO₂ concentrations are more related to anthropogenic emissions and human health. This study proposes a machine learning estimation method for retrieving the ground-level NO₂ concentrations throughout China based on the tropospheric NO₂ column concentrations from the TROPOspheric Monitoring Instrument (TROPOMI) and multisource geographic data from 2018 to 2020. This method adopts the XGBoost machine learning model characterized by a strong fitting ability and complex model structure, which can explain the complex nonlinear and high-order relationships between ground-measured NO₂ and its influencing factors. The R² values between the retrievals and the validation and test datasets are 0.67 and 0.73, respectively, which suggests that the proposed method can reliably retrieve the ground-level NO₂ concentrations across China. The distribution characteristics, seasonal variations and interannual differences in ground-level NO₂ concentrations are further analyzed based on the retrieval results, demonstrating that the ground-level NO₂ concentrations exhibit significant geographical and seasonal variations, with high concentrations in winter and low concentrations in summer, and the highly polluted regions are concentrated mainly in Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD), the Pearl River Delta (PRD), Cheng-Yu District (CY) and other urban agglomerations. Finally, the interannual variation in the ground-level NO₂ concentrations indicates that pollution decreased continuously from 2018 to 2020.

Detecting the Causal Nexus between Particulate Matter (PM10) and Rainfall in the Caribbean Area

In this study, we investigate the interactions between particulate matter that have an aerodynamic diameter less than 10 μm diameter (PM10) and rainfall (RR) in entropy framework. Our results showed there is a bidirectional causality between PM10 concentrations and RR values. This means that PM10 concentrations influence RR values while RR induces the wet scavenging process. Rainfall seasonality has a significant impact on the wet scavenging process while African dust seasonality strongly influence RR behavior. Indeed, the wet scavenging process is 5 times higher during the wet season while PM10 impact on RR is 2.5 times higher during the first part of the high dust season. These results revealed two types of causality: a direct causality (RR to PM10) and an indirect causality (PM10 to RR). All these elements showed that entropy is an efficient way to quantify the behavior of atmospheric processes using ground-based measurements.

Rapid growth of anthropogenic organic nanoparticles greatly alters cloud life cycle in the Amazon rainforest

Aerosol-cloud interactions remain uncertain in assessing climate change. While anthropogenic activities produce copious aerosol nanoparticles smaller than 10 nanometers, they are too small to act as efficient cloud condensation nuclei (CCN). The mechanisms responsible for particle growth to CCN-relevant sizes are poorly understood. Here, we present aircraft observations of rapid growth of anthropogenic nanoparticles downwind of an isolated metropolis in the Amazon rainforest. Model analysis reveals that the sustained particle growth to CCN sizes is predominantly caused by particle-phase diffusion-limited partitioning of semivolatile oxidation products of biogenic hydrocarbons. Cloud-resolving numerical simulations show that the enhanced CCN concentrations in the urban plume substantially alter the formation of shallow convective clouds, suppress precipitation, and enhance the transition to deep convective clouds. The proposed nanoparticle growth mechanism, expressly enabled by the abundantly formed semivolatile organics, suggests an appreciable impact of anthropogenic aerosols on cloud life cycle in previously unpolluted forests of the world.

Heterogeneous Ice Growth in Micron-Sized Water Droplets Due to Spontaneous Freezing

Understanding how ice nucleates and grows into larger crystals is of crucial importance for many research fields. The purpose of this study was to shed light on the phase and structure of ice once a nucleus is formed inside a metastable water droplet. Wide-angle X-ray scattering (WAXS) was performed on micron-sized droplets evaporatively cooled to temperatures where homogeneous nucleation occurs. We found that for our weak hits ice grows more cubic compared to the strong hits that are completely hexagonal. Due to efficient heat removal caused by evaporation, we propose that the cubicity of ice at the vicinity of the droplet’s surface is higher than for ice formed within the bulk of the droplet. Moreover, the Bragg peaks were classified based on their geometrical shapes and positions in reciprocal space, which showed that ice grows heterogeneously with a significant population of peaks indicative of truncation rods and crystal defects. Frequent occurrences of the (100) reflection with extended in-planar structure suggested that large planar ice crystals form at the droplet surface, then fracture into smaller domains to accommodate to the curvature of the droplets. Planar faulting due to misaligned domains would explain the increased cubicity close to the droplet surface.

Computational Investigation of the Formation of Peroxide (ROOR) Accretion Products in the OH- and NO3-Initiated Oxidation of α-Pinene

The formation of accretion products (“dimers”) from recombination reactions of peroxyl radicals (RO₂) is a key step in the gas-phase generation of low-volatility vapors, leading to atmospheric aerosol particles. We have recently demonstrated that this recombination reaction very likely proceeds via an intermediate complex of two alkoxy radicals (RO···OR′) and that the accretion product pathway involves an intersystem crossing (ISC) of this complex from the triplet to the singlet surface. However, ISC rates have hitherto not been computed for large and chemically complex RO···OR′ systems actually relevant to atmospheric aerosol formation. Here, we carry out systematic conformational sampling and ISC rate calculations on ³(RO···OR′) clusters formed in the recombination reactions of different diastereomers of the first-generation peroxyl radicals originating in both OH- and NO₃-initiated reactions of α-pinene, a key biogenic hydrocarbon for atmospheric aerosol formation. While we find large differences between the ISC rates of different diastereomer pairs, all systems have ISC rates of at least 10⁶ s^–1, and many have rates exceeding 10¹⁰ s^–1. Especially the latter value demonstrates that accretion product formation via the suggested pathway is a competitive process also for α-pinene-derived RO₂ and likely explains the experimentally observed gas-phase formation of C₂₀ compounds in α-pinene oxidation.

Probing the Water Uptake and Phase State of Individual Sucrose Nanoparticles Using Atomic Force Microscopy

The effects of atmospheric aerosols on the climate and atmosphere of Earth can vary significantly depending upon their properties, including size, morphology, and phase state, all of which are influenced by varying relative humidity (RH) in the atmosphere. A significant fraction of atmospheric aerosols is below 100 nm in size. However, as a result of size limitations of conventional experimental techniques, how the particle-to-particle variability of the phase state of aerosols influences atmospheric processes is poorly understood. To address this issue, the atomic force microscopy (AFM) methodology that was previously established for sub-micrometer aerosols is extended to measure the water uptake and identify the phase state of individual sucrose nanoparticles. Quantified growth factors (GFs) of individual sucrose nanoparticles up to 60% RH were lower than expected values observed on the sub-micrometer sucrose particles. The effect could be attributed to the semisolid sucrose nanoparticle restructuring on a substrate. At RH > 60%, sucrose nanoparticles are liquid and GFs overlap well with the sub-micrometer particles and theoretical predictions. This suggests that quantification of GFs of nanoparticles may be inaccurate for the RH range where particles are semisolid but becomes accurate at elevated RH where particles are liquid. Despite this, however, the identified phase states of the nanoparticles were comparable to their sub-micrometer counterparts. The identified phase transitions between solid and semisolid and between semisolid and liquid for sucrose were at ∼18 and 60% RH, which are equivalent to viscosities of 10^11.2 and 10^2.5 Pa s, respectively. This work demonstrates that measurements of the phase state using AFM are applicable to nanosized particles, even when the substrate alters the shape of semisolid nanoparticles and alters the GF.

Source profiles and emission factors of organic and inorganic species in fine particles emitted from the ultra-low emission power plant and typical industries

Accurate source markers, source profiles and species-based emission factors (EFs) are currently the key limitations for source apportionment and emission inventory researches. Fine particles (PM_2.5) were collected from stack gases of eight types of stationary sources with a dilution sampling system. The mass percentages and EFs of 89 kinds of chemical species in PM_2.5 including water-soluble ions, elements, carbonaceous species and molecular organic species were obtained. Results showed that water-soluble ions (8%-54%) and elements (5%-45%) were the dominant chemical species. Palmitic acid (0.19%-0.62%) and stearic acid (0.21%-0.59%) were the most abundant organic species. PM_2.5 source profiles of the eight sources were different from each other with the coefficient of divergence values all higher than 0.4. The addition of organic species could help to further distinguish them. The indicatory chemical components and specific species ratios were obtained by both a statistical equation and randomForest. These indicatory chemical components (e.g. F^- for glass factory) and species ratios (e.g. K⁺/Mg²⁺ & OC/Mg for pharmaceutical factory) improved the current knowledges of their indicatory performance in source identification of ambient PM_2.5. The EFs of PM_2.5 from the eight stationary sources ranged from 0.019 to 51.6 kg t^-1 of fuel used. The EFs of PM_2.5 from the pharmaceutical factory were about 70-2600 times higher than other seven types of sources due to the lack of dust-removing devices. Certain EFs measured in this study were about 10-36,000 times lower than corresponding EFs estimated in previous studies which didn't perform field measurements, indicating the necessity for improving emission inventories continuously. This study contributes to identifying emission sources of PM_2.5 especially for subtypes of stationary sources and to establishing species-based emission inventories.

Aerosol as a critical factor causing forecast biases of air temperature in global numerical weather prediction models

Weather prediction is essential to the daily life of human beings. Current numerical weather prediction models such as the Global Forecast System (GFS) are still subject to substantial forecast biases and rarely consider the impact of atmospheric aerosol, despite the consensus that aerosol is one of the most important sources of uncertainty in the climate system. Here we demonstrate that atmospheric aerosol is one of the important drivers biasing daily temperature prediction. By comparing observations and the GFS prediction, we find that the monthly-averaged bias in the 24-h temperature forecast varies between ± 1.5 °C in regions influenced by atmospheric aerosol. The biases depend on the properties of aerosol, the underlying land surface, and aerosol-cloud interactions over oceans. It is also revealed that forecast errors are rapidly magnified over time in regions featuring high aerosol loadings. Our study provides direct "observational" evidence of aerosol's impacts on daily weather forecast, and bridges the gaps between the weather forecast and climate science regarding the understanding of the impact of atmospheric aerosol.

Acidity and the multiphase chemistry of atmospheric aqueous particles and clouds

The acidity of aqueous atmospheric solutions is a key parameter driving both the partitioning of semi-volatile acidic and basic trace gases and their aqueous-phase chemistry. In addition, the acidity of atmospheric aqueous phases, e.g., deliquesced aerosol particles, cloud, and fog droplets, is also dictated by aqueous-phase chemistry. These feedbacks between acidity and chemistry have crucial implications for the tropospheric lifetime of air pollutants, atmospheric composition, deposition to terrestrial and oceanic ecosystems, visibility, climate, and human health. Atmospheric research has made substantial progress in understanding feedbacks between acidity and multiphase chemistry during recent decades. This paper reviews the current state of knowledge on these feedbacks with a focus on aerosol and cloud systems, which involve both inorganic and organic aqueous-phase chemistry. Here, we describe the impacts of acidity on the phase partitioning of acidic and basic gases and buffering phenomena. Next, we review feedbacks of different acidity regimes on key chemical reaction mechanisms and kinetics, as well as uncertainties and chemical subsystems with incomplete information. Finally, we discuss atmospheric implications and highlight the need for future investigations, particularly with respect to reducing emissions of key acid precursors in a changing world, and the need for advancements in field and laboratory measurements and model tools.

The Unmanned Systems Research Laboratory (USRL): A New Facility for UAV-Based Atmospheric Observations

The Unmanned Systems Research Laboratory (USRL) of the Cyprus Institute is a new mobile exploratory platform of the EU Research Infrastructure Aerosol, Clouds and Trace Gases Research InfraStructure (ACTRIS). USRL offers exclusive Unmanned Aerial Vehicle (UAV)-sensor solutions that can be deployed anywhere in Europe and beyond, e.g., during intensive field campaigns through a transnational access scheme in compliance with the drone regulation set by the European Union Aviation Safety Agency (EASA) for the research, innovation, and training. UAV sensor systems play a growing role in the portfolio of Earth observation systems. They can provide cost-effective, spatial in-situ atmospheric observations which are complementary to stationary observation networks. They also have strong potential for calibrating and validating remote-sensing sensors and retrieval algorithms, mapping close-to-the-ground emission point sources and dispersion plumes, and evaluating the performance of atmospheric models. They can provide unique information relevant to the short- and long-range transport of gas and aerosol pollutants, radiative forcing, cloud properties, emission factors and a variety of atmospheric parameters. Since its establishment in 2015, USRL is participating in major international research projects dedicated to (1) the better understanding of aerosol-cloud interactions, (2) the profiling of aerosol optical properties in different atmospheric environments, (3) the vertical distribution of air pollutants in and above the planetary boundary layer, (4) the validation of Aeolus satellite dust products by utilizing novel UAV-balloon-sensor systems, and (5) the chemical characterization of ship and stack emissions. A comprehensive overview of the new UAV-sensor systems developed by USRL and their field deployments is presented here. This paper aims to illustrate the strong scientific potential of UAV-borne measurements in the atmospheric sciences and the need for their integration in Earth observation networks.

Estimating PM2.5 concentrations via random forest method using satellite, auxiliary, and ground-level station dataset at multiple temporal scales across China in 2017

Fine particulate matter with aerodynamic diameters less than 2.5 μm (PM_2.5) poses adverse impacts on public health and the environment. It is still a great challenge to estimate high-resolution PM_2.5 concentrations at moderate scales. The current study calibrated PM_2.5 concentrations at a 1 km resolution scale using ground-level monitoring data, Aerosol Optical Depth (AOD), meteorological data, and auxiliary data via Random Forest (RF) model across China in 2017. The three ten-folded cross-validations (CV) methods including sample-based, time-based, and spatial-based validation combined with Coefficient Square (R²), Root-Mean-Square Error (RMSE), and Mean Predictive Error (MPE) have been used for validation at different temporal scales in terms of daily, monthly, heating seasonal, and non-heating seasonal. Finally, the distribution map of PM_2.5 concentrations was illustrated based on the RF model. Some findings were achieved. The RF model performed well, with a relatively high sample-based cross-validation R² of 0.74, a low RMSE of 16.29 μg × m^-3, and a small MPE of -0.282 μg × m^-3. Meanwhile, the performance of the RF model in inferring the PM_2.5 concentrations was well at urban scales except for Chengyu (CY). North China, the CY urban agglomeration, and the northwest of China exhibited relatively high PM_2.5 pollution features, especially in the heating season. The robustness of the RF model in the present study outperformed most statistical regression models for calibrating PM_2.5 concentrations. The outcomes can supply an up-to-date scientific dataset for epidemiological and air pollutants exposure risk studies across China.

Spectroscopic insight into the pH-dependent interactions between atmospheric heavy metals (Cu and Zn) and water-soluble organic compounds in PM2.5

Taking Cu and Zn as examples, the pH-dependent interactions between atmospheric heavy metals (AHMs) and water-soluble organic compounds (WSOCs) in PM_2.5 were analyzed by a combination of UV-vis absorption, Fourier transform infrared (FTIR) spectroscopy and excitation-emission matrix (EEM) fluorescence spectroscopy coupled with parallel factor analysis (PARAFAC). We found metal-H ion exchange, complexation and electrostatic adsorption might occur between AHMs and WSOCs, and were generally enhanced with the increase of pH. Furthermore, these interactions were strengthened with the stepwise addition of [Cu²⁺] (from 0 to 500 μmol·L^-1), but had a relatively slight change with the stepwise addition of [Zn²⁺] (from 0 to 500 μmol·L^-1) generally. This indicated that the above interactions depended on the types and the concentrations of AHMs. Carboxyl, hydroxyl, carbonyl and aromatic structures of WSOCs were the major binding sites with AHMs. Humic acid-like substances were the dominant components of WSOCs binding with AHMs. The ratios of the apparent fluorescence quantum yields of the low and the high conjugation fractions of WSOCs (Q_ExL/H) declined by more than 28% as adding [Cu²⁺], indicating the formers had more strong complexing capacity with AHMs. AHMs might significantly impact the light absorption capacity and the wavelength dependence of WSOCs. The humification index (HIX_em) declined more than 15% as adding [Cu²⁺] at pH 5.6 and 7.5, indicating AHMs might weaken the oxidation capacity of WSOCs. These results implied the interactions between AHMs and WSOCs might play a profound role in atmospheric environment, human health, and global climate change.

Atomic Force Microscopy: An Emerging Tool in Measuring the Phase State and Surface Tension of Individual Aerosol Particles

Atmospheric aerosols are suspended particulate matter of varying composition, size, and mixing state. Challenges remain in understanding the impact of aerosols on the climate, atmosphere, and human health. The effect of aerosols depends on their physicochemical properties, such as their hygroscopicity, phase state, and surface tension. These properties are dynamic with respect to the highly variable relative humidity and temperature of the atmosphere. Thus, experimental approaches that permit the measurement of these dynamic properties are required. Such measurements also need to be performed on individual, submicrometer-, and supermicrometer-sized aerosol particles, as individual atmospheric particles from the same source can exhibit great variability in their form and function. In this context, this review focuses on the recent emergence of atomic force microscopy as an experimental tool in physical, analytical, and atmospheric chemistry that enables such measurements. Remaining challenges are noted and suggestions for future studies are offered.

Impact of Urban Pollution on Organic-Mediated New-Particle Formation and Particle Number Concentration in the Amazon Rainforest

A major challenge in assessing the impact of aerosols on climate change is to understand how human activities change aerosol loading and properties relative to the pristine/preindustrial baseline. Here, we combine chemical transport simulations and field measurements to investigate the effect of anthropogenic pollution from an isolated metropolis on the particle number concentration over the preindustrial-like Amazon rainforest through various new-particle formation (NPF) mechanisms and primary particle emissions. To represent organic-mediated NPF, we employ a state-of-the-art model that systematically simulates the formation chemistry and thermodynamics of extremely low volatility organic compounds, as well as their roles in NPF processes, and further update the model to improve organic NPF simulations under human-influenced conditions. Results show that urban pollution from the metropolis increases the particle number concentration by a factor of 5-25 over the downwind region (within 200 km from the city center) compared to background conditions. Our model indicates that NPF contributes over 70% of the total particle number in the downwind region except immediately adjacent to the sources. Among different NPF mechanisms, the ternary NPF involving organics and sulfuric acid overwhelmingly dominates. The improved understanding of particle formation mechanisms will help better quantify anthropogenic aerosol forcing from preindustrial times to the present day.