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Abstract The impacts of cloud mixing and uptake on wet scavenging are not adequately resolved in global models which can lead to an overestimation of the removal of water‐soluble gases and aerosols from the atmosphere. To address this issue, we develop and implement novel parameterizations to consider the impacts of these processes. Our analysis of vertical profiles of nitric acid, inorganic nitrate, ammonium, and sulfate concentrations during the Atmospheric Tomography Mission periods indicates that air refreshing limitation has a significant impact above 800 hPa, while cloud ice uptake limitation plays an important role above 500 hPa. Incorporating these two processes resulted in a reduction of wet depositions of these species across source regions and a slight increase in their downwind regions. Wet depositions of nitrate, ammonium, and sulfate were reduced in source regions by 22.7%, 8.4%, and 8.3%, respectively and increased in downwind regions by 10.1%, 7.0%, and 4.3%, respectively.

Abstract Marine new particle formation (NPF) can affect cloud condensation nuclei (CCN) in the global atmosphere. Recently, iodic acid (IA) has been identified as a critical driver for marine NPF. However, atmospheric observations of IA cannot be associated with predicted particle formation rates. Given the complexity of atmospheric components, other species may promote IA particle formation. As an efficient stabilizer for acidic precursors, dimethylamine (DMA) has a wide distribution over the oceans. Hence, we investigated the nucleation process of DMA and IA under different atmospheric conditions and uncovered the corresponding nucleating mechanism using a quantum chemical approach and Atmospheric Cluster Dynamics Code (ACDC). The findings show that DMA can structurally stabilize IA via hydrogen and halogen bonds, and the clustering process is energy barrierless. Moreover, DMA can enhance the formation rate of IA clusters by five orders of magnitude, and its efficiency in promoting IA cluster formation is much higher than that of NH3. Compared to the nucleation via sequential addition of IA, the IA-DMA nucleation plays a more dominant role in nucleation kinetic. Thus, the effect of DMA on enhancing IA cluster stability and formation rate cannot be ignored, especially in the regions near the source of IA and DMA emissions. Broadly, the proposed IA-DMA nucleation mechanism may help to explain some missing sources of particles and, thus intensive marine NPF events.

Background: Thermal comfort is essential for human well-being. Consistent exposure to uncomfortable thermal conditions indoors leads to reduced academic performance and adverse health outcomes in schoolchildren. In addition, children are more sensitive to thermal conditions due to physiological differences, yet their exposure to thermal conditions has not been adequately measured.Methods: This cross-sectional study evaluated students' exposure to temperature and relative humidity (RH) using personal air monitors. In this study, we recruited 90 students from 13 classrooms – 60 from 11 NYS primary school classrooms and 30 from two State University of New York at Albany classrooms. Each participant wore an AirBeam air monitor for 48 hours, and their data was transmitted to a cell phone provided by the researchers.Results: Primary school students were routinely exposed to temperatures exceeding ASHRAE standards (winter: 75⁰F, summer: 80.5⁰F), particularly in school in the spring (max=102⁰F, median=82⁰F). At home, temperatures exceeded standards in the evening around dinnertime. However, primary students were routinely exposed to RH below recommended standards in classrooms during all seasons (median=29%). However, the RH was significantly lower in the winter than in any other season (median=17%). Finally, university students were exposed to slightly higher temperatures and significantly lower RH than primary schoolchildren in the spring.Conclusion: These results suggest that students are exposed to uncomfortable thermal conditions, particularly in classrooms when attending class. Teachers should therefore be given more control over classroom ventilation and thermal conditions, while indoor temperature standards should be adjusted for school children.

Background: Mental disorders (MDs) are behavioral or mental patterns that cause significant distress or impairment of personal functioning. Previously, temperature has been linked to MDs, but most studies suffered from exposure misclassification due to limited monitoring sites. We aimed to assess whether multiple meteorological factors could jointly trigger MD-related emergency department (ED) visits in warm season, using a highly dense weather monitoring system. Methods: We conducted a time-stratified, case-crossover study. MDs-related ED visits (primary diagnosis) from May-October 2017–2018 were obtained from New York State (NYS) discharge database. We obtained solar radiation (SR), relative humidity (RH), temperature, heat index (HI), and rainfall from Mesonet, a real-time monitoring system spaced about 17 miles (126 stations) across NYS. We used conditional logistic regression to assess the weather-MD associations. Results: For each interquartile range (IQR) increase, both SR (excess risk (ER): 4.9%, 95% CI: 3.2–6.7%) and RH (ER: 4.0%, 95% CI: 2.6–5.4%) showed the largest risk for MD-related ED visits at lag 0–9 days. While temperature presented a short-term risk (highest ER at lag 0–2 days: 3.7%, 95% CI: 2.5–4.9%), HI increased risk over a two-week period (ER range: 3.7–4.5%), and rainfall hours showed an inverse association with MDs (ER: −0.5%, 95% CI: 0.9-(-0.1)%). Additionally, we observed stronger association of SR, RH, temperature, and HI in September and October. Combination of high SR, RH, and temperature displayed the largest increase in MDs (ER: 7.49%, 95% CI: 3.95–11.15%). The weather-MD association was stronger for psychoactive substance usage, mood disorders, adult behavior disorders, males, Hispanics, African Americans, individuals aged 46–65, or Medicare patients. Conclusions: Hot and humid weather, especially the joint effect of high sun radiation, temperature and relative humidity showed the highest risk of MD diseases. We found stronger weather-MD associations in summer transitional months, males, and minority groups. These findings also need further confirmation.

Ambient fine particulate matter (PM2.5) is one of the most important environmental health risk factors in many regions. Here, the authors present an assessment of PM2.5 emission sources and the related health impacts across global to sub-national scales and find that over 1 million deaths were avoidable in 2017 by eliminating PM2.5 mass associated with fossil fuel combustion emissions.

Satellite-based estimates of radiative forcing by aerosol–cloud interactions are consistently smaller than those from global models, hampering accurate projections of future climate change. Here, the authors show that the discrepancy can be substantially reduced by correcting sampling biases induced by inherent limitations of satellite measurements.

Organic nucleation is an important source of atmospheric aerosol number concentration, especially in pristine continental regions and during the preindustrial period. Here the authors find a 16% reduced radiative forcing associated with anthropogenic aerosols when including organic nucleation together with climate and land use change.

Ammonia (NH3), the most prevalent alkaline gas in the atmosphere, plays a significant role in PM2.5 formation, atmospheric chemistry, and new particle formation. This paper reviews quantification of [NH3] through measurements, satellite-remote-sensing, and modeling reported in over 500 publications towards synthesizing the current knowledge of [NH3], focusing on spatiotemporal variations, controlling processes, and quantification issues. Most measurements are through regional passive sampler networks. [NH3] hotspots are typically over agricultural regions, such as the Midwest US and the North China Plain, with elevated concentrations reaching monthly averages of 20 and 74 ppbv, respectively. Topographical effects dramatically increase [NH3] over the Indo-Gangetic Plains, North India and San Joaquin Valley, US. Measurements are sparse over oceans, where [NH3] ≈ a few tens of pptv, variations of which can affect aerosol formation. Satellite remote-sensing (AIRS, CrIS, IASI, TANSO-FTS, TES) provides global [NH3] quantification in the column and at the surface since 2002. Modeling is crucial for improving understanding of NH3 chemistry and transport, its spatiotemporal variations, source apportionment, exploring physicochemical mechanisms, and predicting future scenarios. GEOS-Chem (global) and FRAME (UK) models are commonly applied for this. A synergistic approach of measurements↔satellite-inference↔modeling is needed towards improved understanding of atmospheric ammonia, which is of concern from the standpoint of human health and the ecosystem.

Long-term satellite climate data records (CDRs) of clouds and aerosols are used to investigate the aerosol indirect effect (AIE) of cirrus clouds over the global oceans from a climatology perspective. Our study focuses on identifying the sensitive regimes and active regions where AIE signatures easily manifest themselves in the sense of the long-term average of cloud and aerosol variables. The aerosol index (AIX) regimes of AIX < 0.18 and 0.18 < AIX < 0.46 are respectively identified as the sensitive regimes for negative and positive aerosol albedos and lifetime effects of cirrus clouds. Relative humidity first decreases (along with upward motions) and then reverses to increase (along with downward motions) in the first regime of negative aerosol albedo and lifetime effects. Relatively wet and strong upward motions are the favorable meteorological conditions for the second regime of positive aerosol albedo and lifetime effects. Two swath regions extending from 15°N to 30°N over the east coastal oceans of China and the USA are the active regions of positive aerosol albedo effects. Positive aerosol lifetime effects are only active or easy to manifest in the regions where a positive aerosol albedo effect is active. The results based on the long-term averaged satellite observations are valuable for the evaluation and improvement of aerosol-cloud interactions for cirrus clouds in global climate models.

Spatiotemporal uncertainty in $\mathrm{NH_{3}}$ emissions in the US hinders prediction of environmental effects of atmospheric $\mathrm{NH_3}$ . We conducted 4D-Var inversions using CrIS remote-sensing observations and GEOS-Chem to estimate monthly $\mathrm{NH_{3}}$ emissions over the contiguous US at the 0.25 ^° × 0.3125 ^° resolution in 2014, finding they are 33% higher than the prior emissions which likely underestimated most agricultural emissions, especially intense springtime fertilizer and livestock sources over the Central US. However, decreases were found in the Central Valley, southern Minnesota, northern Iowa and southeastern North Carolina during warm months. These updates increased the correlation coefficient between modeled monthly mean $\mathrm{NH_3}$ and surface observations from 0.53 to 0.84, and reduced the normalized mean bias of annual mean simulated $\mathrm{NH_3}$ and wet $\mathrm{NH_{4}^{+}}$ by a factor of 1.3 to 12.7. Our satellite-based inversion approach thus holds promise for improving estimates of $\mathrm{PM_{2.5}}$ and reactive nitrogen deposition throughout the world where $\mathrm{NH_3}$ measurements are scarce.

Recent AeroCom phase II experiments showed a large diversity in aerosol optical depth (AOD) among 16 detailed global aerosol models, which contributes to the large uncertainty in the predicted aerosol radiative forcing. The GEOS-Chem-APM, a global size-resolved aerosol model, can be considered as a representative AeroCom II model. In this study, multi-year AOD data (2004–2012) from ground-based Aerosol Robotic Network (AERONET) measurements and Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging SpectroRadiometer (MISR) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) satellite retrievals are used to evaluate the performance of GEOS-Chem-APM in capturing observed seasonal and spatial AOD variations. Compared to the observations, the modelled AOD is overall good over land, but quite low over ocean possibly due to low sea salt emission in the model and/or higher AOD in satellite retrievals, specifically MODIS and MISR. We chose 72 AERONET sites having at least 36 months data available and representative of high spatial domain to compare with the model and satellite data. Comparisons in various representative regions show that the model overall agrees well in the major anthropogenic emission regions, such as Europe, East Asia and North America. Relative to the observations, the modelled AOD is systematically lower in biomass burning regions such as South Africa and South America possibly due to uncertainties in emission inventory, but slightly higher in North Africa likely associated with stronger dust emissions in the model. The model is able to capture the realistic seasonal cycle in all regions, including the peak of AOD in major dust events months and biomass burning seasons. The simulated inter-annual variability is overall consistent with the observations, which is distinctly shown in South Africa and South America with strong inter-annual variability compared to other regions.

Amines, organic derivatives of NH3, are important common trace atmospheric species that can enhance new particle formation in the Earth’s atmosphere under favorable conditions. While methylamine (MA), dimethylamine (DMA) and trimethylamine (TMA) all efficiently enhance binary nucleation, MA may represent the lower limit of the enhancing effect of amines on atmospheric nucleation. In the present paper, we report new thermochemical data concerning MA-enhanced nucleation, which were obtained using the DFT PW91PW91/6-311++G (3df, 3pd) method, and investigate the enhancement in production of stable pre-nucleation clusters due to the MA. We found that the MA ternary nucleation begins to dominate over ternary nucleation of sulfuric acid, water and ammonia at [MA]/[NH3] > ~10−3. This means that under real atmospheric conditions ([MA] ~ 1 ppt, [NH3] ~ 1 ppb) the lower limit of the enhancement due to methylamines is either close to or higher than the typical effect of NH3. A very strong impact of the MA is observed at low RH; however it decreases quickly as the RH grows. Low RH and low ambient temperatures were found to be particularly favorable for the enhancement in production of stable sulfuric acid-water clusters due to the MA.

The impact of organic species which are present in the Earth’s atmosphere on the burst of new particles is critically important for the understanding of the molecular nature of atmospheric nucleation phenomena. Amines have recently been proposed as possible stabilizers of binary pre-nucleation clusters. In order to advance the understanding of atmospheric nucleation phenomena, a quantum-chemical study of hydrogen-bonded complexes of binary sulfuric acid-water clusters with methyl-, dimethyl- and trimethylamines representing common atmospheric organic species, vegetation products and laboratory impurities has been carried out. The thermochemical stability of the sulfuric acid-amines-water complexes was found to be higher than that of the sulfuric acid-ammonia-water complexes, in qualitative agreement with the previous studies. However, the enhancement in stability due to amines appears to not be large enough to overcome the difference in typical atmospheric concentrations of ammonia and amines. Further research is needed in order to address the existing uncertainties and to reach a final conclusion about the importance of amines for the atmospheric nucleation.

A clear understanding of new particle formation processes in remote oceans is critical for properly assessing the role of oceanic dimethyl sulfide (DMS) emission on the Earth’s climate and associated climate feedback processes. Almost free from anthropogenic pollutants and leafed plants, the Antarctic continent and surrounding oceans are unique regions for studying the lifecycle of natural sulfate aerosols. Here we investigate the well-recognized seasonal variations of new particle formation around Antarctic coastal areas with a recently developed global size-resolved aerosol model. Our simulations indicate that enhanced DMS emission and photochemistry during the austral summer season lead to significant new particle formation via ion-mediated nucleation (IMN) and much higher particle number concentrations over Antarctica and surrounding oceans. By comparing predicted condensation nuclei larger than 10 nm (CN10) during a three-year period (2005–2007) with the long-period continuous CN10 measurements at the German Antarctic station Neumayer, we show that the model captures the absolute values of monthly mean CN10 (within a factor 2–3) as well as their seasonal variations. Our simulations confirm that the observed Antarctic CN10 and cloud condensation nuclei (CCN) seasonal variations are due to the formation of secondary particles during the austral summer. From the austral winter to summer, the zonally averaged CN10 and CCN in the lower troposphere over Antarctica increase by a factor of ~4–6 and ~2–4, respectively. This study appears to show that the H2SO4-H2O IMN mechanism is able to account for the new particle formation frequently observed in the Antarctica region during the austral summer.

The sign preference of hydrogen bonded aqueous ionic clusters Χ±(H2O)i (n =1-5, Χ = F; Cl; Br) has been investigated using the Density Functional Theory and ab initio MP2 method. The present study indicates the anomalously large difference in formation free energies between cations and anions of identical chemical composition. The effect of vibrational anharmonicity on stepwise Gibbs free energy changes has been investigated, and possible uncertainties associated with the harmonic treatment of vibrational spectra have been discussed.

Hydration directly affects the mobility, thermodynamic properties, lifetime and nucleation rates of atmospheric ions. In the present study, the role of ammonia on the formation of hydrogen bonded complexes of the common atmospheric hydrogensulfate (HSO4-) ion with water has been investigated using the Density Functional Theory (DFT). Our findings rule out the stabilizing effect of ammonia on the formation of negatively charged cluster hydrates and show clearly that the conventional (classical) treatment of ionic clusters as presumably more stable compared to neutrals may not be applicable to pre-nucleation clusters. These considerations lead us to conclude that not only quantitative but also qualitative assessment of the relative thermodynamic stability of atmospheric clusters requires a quantum-chemical treatment.

The impact of solar variations on particle formation and cloud condensation nuclei (CCN), a critical step for one of the possible solar indirect climate forcing pathways, is studied here with a global aerosol model optimized for simulating detailed particle formation and growth processes. The effect of temperature change in enhancing the solar cycle CCN signal is investigated for the first time. Our global simulations indicate that a decrease in ionization rate associated with galactic cosmic ray flux change from solar minimum to solar maximum reduces annual mean nucleation rates, number concentration of condensation nuclei larger than 10 nm (CN10), and number concentrations of CCN at water supersaturation ratio of 0.8% (CCN0.8) and 0.2% (CCN0.2) in the lower troposphere by 6.8%, 1.36%, 0.74%, and 0.43%, respectively. The inclusion of 0.2 °C temperature increase enhances the CCN solar cycle signals by around 50%. The annual mean solar cycle CCN signals have large spatial and seasonal variations: (1) stronger in the lower troposphere where warm clouds are formed, (2) about 50% larger in the northern hemisphere than in the southern hemisphere, and (3) about a factor of two larger during the corresponding hemispheric summer seasons. The effect of solar cycle perturbation on CCN0.2 based on present study is generally higher than those reported in several previous studies, up to around one order of magnitude.

Atmospheric particles influence the climate indirectly by acting as cloud condensation nuclei (CCN). The first aerosol indirect radiative forcing (FAIRF) constitutes the largest uncertainty among the radiative forcings quantified by the latest IPCC report (IPCC2007) and is a major source of uncertainty in predicting climate change. Here, we investigate the anthropogenic contribution to CCN and associated FAIRF using a state-of-the-art global chemical transport and aerosol model (GEOS-Chem/APM) that contains a number of advanced features (including sectional particle microphysics, online comprehensive chemistry, consideration of all major aerosol species, online aerosol–cloud–radiation calculation, and usage of more accurate assimilated meteorology). The model captures the absolute values and spatial distributions of CCN concentrations measured in situ around the globe. We show that anthropogenic emissions increase the global mean CCN in the lower troposphere by ∼60–80% and cloud droplet number concentration by ∼40%. The global mean FAIRF based on GEOS-Chem/APM is −0.75 W m ^−2 , close to the median values of both IPCC2007 and post-IPCC2007 studies. To the best of our knowledge, this is the first time that a global sectional aerosol model with full online chemistry and considering all major aerosol species (including nitrate, ammonium, and second organic aerosols) has been used used to calculate FAIRF.

The Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) is a six-year (2019-2024) NASA Earth-Venture Suborbital-3 (EVS-3) mission to robustly characterize aerosol-cloud-meteorology interactions over the western North Atlantic Ocean (WNAO) during winter and summer seasons, with a focus on marine boundary layer clouds. This characterization requires understanding the aerosol life cycle (sources and sinks), composition, transport pathways, and distribution in the WNAO region. We use the GEOS-Chem chemical transport model driven by the MERRA-2 reanalysis to simulate tropospheric aerosols that are evaluated against in situ and remote sensing measurements from Falcon and King Air aircraft, respectively, as well as ground-based and satellite observations over the WNAO during the winter (Feb. 14 - Mar. 12) and summer (Aug. 13 - Sep. 30) field deployments of ACTIVATE 2020. Transport of pollution in the boundary layer behind cold fronts is a major mechanism for the North American continental outflow to the WNAO during Feb.-Mar. 2020. While large-scale frontal lifting is a dominant mechanism in winter, convective lifting significantly increases the vertical extent of major continental outflow aerosols in summer. Turbulent mixing is found to be the dominant process responsible for the vertical transport of sea salt within and ventilation out of the boundary layer in winter. The simulated boundary layer aerosol composition and optical depth (AOD) in the ACTIVATE flight domain are dominated by sea salt, followed by organic aerosol and sulfate. Compared to winter, boundary layer sea salt concentrations increased in summer over the WNAO, especially from the ACTIVATE flight areas to Bermuda, because of enhanced surface winds and emissions. Dust concentrations also significantly increased in summer because of long-range transport from North Africa. Comparisons of model and aircraft submicron non-refractory aerosol species (measured by an HR-ToF-AMS) vertical profiles show that intensive measurements of sulfate, nitrate, ammonium, and organic aerosols in the lower troposphere over the WNAO in winter provide useful constraints on model aerosol wet removal by precipitation scavenging. Comparisons of model aerosol extinction (at 550 nm) with the King Air High Spectral Resolution Lidar-2 (HSRL-2) measurements (at 532 nm) and CALIOP/CALIPSO satellite retrievals (at 532 nm) indicate that the model generally captures the continental outflow of aerosols, the land-ocean aerosol extinction gradient, and the mixing of anthropogenic aerosols with sea salt. Large enhancements of aerosol extinction at ~1.5-6.0 km altitudes from long-range transport of the western U.S. fire smoke were observed by HSRL-2 and CALIOP during Aug.-Sep. 2020. Model simulations with biomass burning (BB) emissions injected up to the mid-troposphere (vs. within the BL) better reproduce these remote-sensing observations, Falcon aircraft organic aerosol vertical profiles, as well as AERONET AOD measurements over eastern U.S. coast and Tudor Hill, Bermuda. High aerosol (mostly coarse-mode sea salt) extinction near the top (~1.5-2.0 km) of the marine BL along with high relative humidity and cloud extinction were typically seen over the WNAO (< 35°N) in the CALIOP aerosol extinction profiles and GEOS-Chem simulations, suggesting strong hygroscopic growth of sea salt particles and sea salt seeding of marine boundary layer clouds. Contributions of different emission types (anthropogenic, BB, biogenic, marine, and dust) to the total AOD over the WNAO in the model are also quantified. Future modeling efforts should focus on improving parameterizations for aerosol wet scavenging and sea salt emissions, implementing realistic BB emission injection height, and applying high-resolution models that better resolve vertical transport. [ABSTRACT FROM AUTHOR]

The major bridge linking satellite-derived vertical column densities (VCDs) of nitrogen dioxide (NO2) with ground-level concentration is theoretically the NO2 mixing height (NMH). Various meteorological parameters have been used as a proxy of NMH in existing studies. This study developed a nested machine learning model to convert VCDs of NO2 into ground-level NO2 concentrations across China using Geostationary Environmental Monitoring Spectrometer (GEMS) measurements. This nested model was designed to directly incorporate NMH into the methodological framework and explore its impact on performance. The inner machine learning model predicted the NMH from the meteorological parameters, which were then input into the main machine learning model to predict the ground-level NO2 concentrations from its VCDs. The inclusion of NMH significantly enhanced the accuracy of estimating ground-level NO2 concentration, reducing bias and improving R² values to 0.93 in 10-fold cross-validation and 0.99 in the fully-trained model. Furthermore, NMH was identified as the second most important predictor variable, following the VCDs of NO2. Subsequently, satellite-derived ground-level NO2 data were analyzed across subregions with varying geolocations and urbanization levels. Highly populated areas typically experienced peak NO2 concentrations during early morning rush hours, whereas areas categorized as lightly populated observed a slight increase in NO2 levels one or two hours later, likely due to regional pollutant dispersion from urban sources. This study underscores the importance of incorporating NMH in estimating ground-level NO2 from satellite column measurements and highlights the significant advantages of geostationary satellites in providing detailed air pollution information at an hourly resolution. [ABSTRACT FROM AUTHOR]