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Nucleation is an important source of atmospheric particles and ubiquitous ions in the atmosphere have long been known to promote nucleation. An ion‐mediated nucleation (IMN) mechanism based on a kinetic model is supported by recent measurements of the excess charge on freshly nucleated particles and ion cluster evolution during nucleation events. Here we investigate the dependence of steady state IMN rate (JIMN) on key controlling parameters. We find that sulfuric acid vapor concentration, temperature, relative humidity, ionization rate, and surface area of preexisting particles have profound and nonlinear impacts on JIMN. The sensitivities of JIMN to the changes in these key parameters may imply important physical feedback mechanisms involving climate and emission changes, solar variations, nucleation, aerosol number abundance, and aerosol indirect radiative forcing. We also describe a five‐dimensional JIMN look‐up table derived from the most recent version of the IMN model, with the key parameters covering a wide range of atmospheric conditions. With the look‐up table and a multiple‐variable interpolation subroutine, JIMN and the properties of critical clusters can be determined efficiently and accurately under given atmospheric conditions. The look‐up table reduces the computational costs of the IMN rate calculations significantly (by a factor of around 8000) and can be readily incorporated into multidimensional models to study the secondary particle formation via IMN and associated climatic and health effects.

Satellite-based estimates of radiative forcing by aerosol–cloud interactions (RF aci ) are consistently smaller than those from global models, hampering accurate projections of future climate change. Here we show that the discrepancy can be substantially reduced by correcting sampling biases induced by inherent limitations of satellite measurements, which tend to artificially discard the clouds with high cloud fraction. Those missed clouds exert a stronger cooling effect, and are more sensitive to aerosol perturbations. By accounting for the sampling biases, the magnitude of RFaci (from −0.38 to −0.59 W m −2 ) increases by 55 % globally (133 % over land and 33 % over ocean). Notably, the RF aci further increases to −1.09 W m −2 when switching total aerosol optical depth (AOD) to fine-mode AOD that is a better proxy for CCN than AOD. In contrast to previous weak satellite-based RF aci , the improved one substantially increases (especially over land), resolving a major difference with models. 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.

Ambient fine particulate matter (PM 2.5 ) is the world’s leading environmental health risk factor. Reducing the PM 2.5 disease burden requires specific strategies that target dominant sources across multiple spatial scales. We provide a contemporary and comprehensive evaluation of sector- and fuel-specific contributions to this disease burden across 21 regions, 204 countries, and 200 sub-national areas by integrating 24 global atmospheric chemistry-transport model sensitivity simulations, high-resolution satellite-derived PM 2.5 exposure estimates, and disease-specific concentration response relationships. Globally, 1.05 (95% Confidence Interval: 0.74–1.36) million deaths were avoidable in 2017 by eliminating fossil-fuel combustion (27.3% of the total PM 2.5 burden), with coal contributing to over half. Other dominant global sources included residential (0.74 [0.52–0.95] million deaths; 19.2%), industrial (0.45 [0.32–0.58] million deaths; 11.7%), and energy (0.39 [0.28–0.51] million deaths; 10.2%) sectors. Our results show that regions with large anthropogenic contributions generally had the highest attributable deaths, suggesting substantial health benefits from replacing traditional energy sources. Ambient fine particulate matter (PM 2.5 ) is one of the most important environmental health risk factors in many regions. Here, the authors present an assessment of PM 2.5 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 PM 2.5 mass associated with fossil fuel combustion emissions.

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.

The concentration of fine particulate matter (PM 2.5 ) across China has decreased by 30–50% over the period 2013–2018 due to stringent emission controls. However, the nitrate component of PM 2.5 has not responded effectively to decreasing emissions of nitrogen oxides and has actually increased during winter haze pollution events in the North China Plain. Here, we show that the GEOS-Chem atmospheric chemistry model successfully simulates the nitrate concentrations and trends. We find that winter mean nitrate would have increased over 2013–2018 were it not for favourable meteorology. The principal cause of this nitrate increase is weaker deposition. The fraction of total inorganic nitrate as particulate nitrate instead of gaseous nitric acid over the North China Plain in winter increased from 90% in 2013 to 98% in 2017, as emissions of nitrogen oxides and sulfur dioxide decreased while ammonia emissions remained high. This small increase in the particulate fraction greatly slows down deposition of total inorganic nitrate and hence drives the particulate nitrate increase. Our results suggest that decreasing ammonia emissions would decrease particulate nitrate by driving faster deposition of total inorganic nitrate. Decreasing nitrogen oxide emissions is less effective because it drives faster oxidation of nitrogen oxides and slower deposition of total inorganic nitrate. Reduction of ammonia emissions may be effective in reducing the nitrate component of fine particulate matter air pollution across the North China Plain, according to the simulation of nitrate trends using the GEOS-Chem atmospheric chemistry model.

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. Plain Language Summary Atmospheric species in cloud‐free or rain‐free air need time to be transported and mixed with those in cloudy or rainy air before being influenced by wet scavenging. Additionally, the efficiency of rainout of water‐soluble aerosols for cold clouds is expected to be limited by cloud ice uptake. The removal of water‐soluble aerosols from cold clouds only occurs when they are taken up by ice crystals. However, current models do not adequately address these two processes. In this study, we derived new approaches that consider the effects of air refreshing and cloud ice uptake limitations on wet scavenging. We found that these new approaches have significant impacts on the vertical profiles and wet deposition fluxes of nitrate, ammonium, and sulfate. Key Points Air refreshing and cloud ice uptake limitations are not well resolved in global models Air refreshing limitation impacts vertical concentration profiles <800 hPa, while cloud ice uptake limitation is important above 500 hPa In combination, the two processes reduced wet depositions across source regions and slightly increased wet depositions in downwind regions

Organic nucleation is an important source of atmospheric aerosol number concentration, especially in pristine continental regions and during the preindustrial period. Here, we improve on previous simulations that overestimate boundary layer nucleation in the tropics and add changes to climate and land use to evaluate climate forcing. Our model includes both pure organic nucleation and heteromolecular nucleation of sulfuric acid and organics and reproduces the profile of aerosol number concentration measured in the Amazon. Organic nucleation decreases the sum of the total aerosol direct and indirect radiative forcing by 12.5%. The addition of climate and land use change decreases the direct radiative forcing (−0.38 W m −2 ) by 6.3% and the indirect radiative forcing (−1.68 W m −2 ) by 3.5% due to the size distribution and number concentration change of secondary organic aerosol and sulfate. Overall, the total radiative forcing associated with anthropogenic aerosols is decreased by 16%. 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.

The widely used community model GEOS-Chem 12.0.0 and previous versions have been recognized to significantly overestimate the concentrations of gaseous nitric acid, aerosol nitrate, and aerosol ammonium over the United States. The concentrations of nitric acid are also significantly overpredicted in most global models participating in a recent model intercomparison study. In this study, we show that most or all of this overestimation issue appears to be associated with wet scavenging processes. The replacement of constant in-cloud condensation water (ICCW) assumed in GEOS-Chem standard versions with one varying with location and time from the assimilated meteorology significantly reduces mass loadings of nitrate and ammonium during the wintertime, while the employment of an empirical washout rate for nitric acid significantly decreases mass concentrations of nitric acid and ammonium during the summertime. Compared to the standard version, GEOS-Chem with updated ICCW and washout rate significantly reduces the simulated annual mean mass concentrations of nitric acid, nitrate, and ammonium at surface monitoring network sites in the US from 2.04 to 1.03, 1.89 to 0.88, and 1.09 to 0.68 µg m-3, respectively, in much better agreement with corresponding observed values of 0.83, 0.70, and 0.60 µg m-3, respectively. In addition, the agreement of model-simulated seasonal variations of corresponding species with measurements is also improved. The updated wet scavenging scheme improves the skill of the model in predicting nitric acid, nitrate, and ammonium concentrations, which are important species for air quality and climate.

Wet processes, including aqueous-phase chemistry, wet scavenging, and wet surface uptake during dry deposition, are important for global modeling of aerosols and aerosol precursors. In this study, we improve the treatments of these wet processes in the Goddard Earth Observing System with chemistry (GEOS-Chem) v12.6.0, including pH calculations for cloud, rain, and wet surfaces, the fraction of cloud available for aqueous-phase chemistry, rainout efficiencies for various types of clouds, empirical washout by rain and snow, and wet surface uptake during dry deposition. We compare simulated surface mass concentrations of aerosols and aerosol precursors with surface monitoring networks over the United States, European, Asian, and Arctic regions, and show that model results with updated wet processes agree better with measurements for most species. With the implementation of these updates, normalized mean biases (NMBs) of surface nitric acid, nitrate, and ammonium are reduced from 78 %, 126 %, and 45 % to 0.9 %, 15 %, and 4.1 % over the US sites, from 107 %, 127 %, and 90 % to -0.7 %, 4.2 %, and 16 % over European sites, and from 121 %, 269 %, and 167 % to -21 %, 37 %, and 86 % over Asian remote region sites. Comparison with surface measured SO2, sulfate, and black carbon at four Arctic sites indicated that those species simulated with the updated wet processes match well with observations except for a large underestimate of black carbon at one of the sites. We also compare our model simulation with aircraft measurement of nitric acid and aerosols during the Atmospheric Tomography Mission (ATom)-1 and ATom-2 periods and found a significant improvement of modeling skill of nitric acid, sulfate, and ammonium in the Northern Hemisphere during wintertime. The NMBs of these species are reduced from 163 %, 78 %, and 217 % to -13 %, -1 %, and 10 %, respectively. The investigation of impacts of updated wet process treatments on surface mass concentrations indicated that the updated wet processes have strong impacts on the global means of nitric acid, sulfate, nitrate, and ammonium and relative small impacts on the global means of sulfur dioxide, dust, sea salt, black carbon, and organic carbon.