Aerosol-driven droplet concentrations dominate coverage and water of oceanic low-level clouds

Bionic dual-scale structured films for efficient passive radiative cooling accompanied by robust durability

Passive radiative cooling (PRC), as an energy-free cooling approach, is ingeniously harnessed for certain natural organisms to withstand extreme high-temperature climates, which has inspired numerous bionic designs. However, it is a great challenge to enhance the durability of the designed materials in practical scenarios while inheriting the natural biological principles. We demonstrate bionic dual-scale structured (BDSS) films for efficient passive radiative cooling accompanied by robust durability after discovering the excellent thermoregulatory properties of the inner surface of Hawaiian scallop shell. We found that the inner surface of the shell consists of large-scale triangular ridges scattered with small-scale terrace steps. This dual-scale structure can enhance the reflectivity of sunlight by efficient Mie scattering and increase the emissivity in the mid-infrared range by lengthening the propagation of photons, thereby decreasing the surface temperature. Underpinned by this finding, we developed a BDSS film that features a strong solar spectrum reflectivity of 0.95 and a high mid-infrared emissivity of 0.98, achieving a sub-ambient cooling of 10.8 °C under direct sunlight. Additionally, the designed films possess robust durability including excellent self-cleaning, flexibility, mechanical strength, chemical stability, and anti-ultraviolet radiation, which is promising for thermal thermoregulation in various harsh scenarios.

Long-term relationships between summer clouds and aerosols over mid-high latitudes of the Northern Hemisphere

While the short-term relationship between clouds and aerosols is well known, no adequate data is available to verify the longer-term, annual to decadal, relationship. It is important to quantify the aerosol-cloud interaction (ACI) for mitigating uncertainty in climate prediction. Here the long-term ACI over the mid-to-high latitudes of the Northern Hemisphere was analyzed by using seasonally-resolved ion fluxes reconstructed from a southeastern Greenland ice core (SE-Dome ice core) as aerosol proxies, and satellite-based summer cloud amount between 1982 and 2014. As a result, SO42- flux in the ice core shows significant positive correlation with total cloud amounts (CC T ) and cloud droplet concentration ( N d ) in the summer over the southeastern Greenland Sea, implying that the sulfate aerosols may contribute to the variability ofCC T via microphysical cloud processes. Significant positive correlations are persistent even under the constrained conditions when cloud formation factors such as relative humidity, air temperature at cloud height, and summer North Atlantic Oscillation are limited within ± 1σ variability. Hence sulfate aerosols should control the interannual variability of summerCC T In terms of decadal changes,CC T was approximately 3-5% higher in the 1960s-1970s than in the 1990s-2000s, which can be explained by changes in the,SO 4 2 - flux preserved in the SE-Dome ice core.

Observational evidence of strong forcing from aerosol effect on low cloud coverage

Aerosols cool Earth's climate indirectly by increasing low cloud brightness and their coverage (Cf), constituting the aerosol indirect forcing (AIF). The forcing partially offsets the greenhouse warming and positively correlates with the climate sensitivity. However, it remains highly uncertain. Here, we show direct observational evidence for strong forcing from Cf adjustment to increased aerosols and weak forcing from cloud liquid water path adjustment. We estimate that the Cf adjustment drives between 52% and 300% of additional forcing to the Twomey effect over the ocean and a total AIF of -1.1 ± 0.8 W m-2. The Cf adjustment follows a power law as a function of background cloud droplet number concentration, Nd. It thus depends on time and location and is stronger when Nd is low. Cf only increases substantially when background clouds start to drizzle, suggesting a role for aerosol-precipitation interactions. Our findings highlight the Cf adjustment as the key process for reducing the uncertainty of AIF and thus future climate projections.

The occurrence of lower-than-expected bulk NCCN values over the marginal seas of China - Implications for competitive activation of marine aerosols

In this study, we combined the measured bulk particle number concentration (N_CN), particle number size distribution (PNSD) and bulk cloud condensation nuclei concentration (N_CCN) at various supersaturation (SS) levels to investigate competitive activation of aerosols in the marine atmospheres over the marginal seas of China during two winter campaigns Campaign A (December 9-19, 2019) and Campaign B (December 28, 2019-January 16, 2020). During the two campaigns, we observed various categories of aerosols, i.e., long-range transport continental aerosols, clean marine aerosols, grown new particles ranging from nucleation mode to larger sizes, and grown pre-existing particles ranging from Aitken mode to accumulation mode size, etc. We found that the measured N_CCN increased by only approximately 30 % with increases in SS levels from 0.2 % to 1.0 %, e.g., (1.8 ± 1.4) × 10³ cm^-3 at SS = 0.2 % and (2.4 ± 1.4) × 10³ cm^-3 at SS = 1.0 % during Campaign A. We further calculated the hygroscopicity parameter kappa (κ) by combining simultaneously measured PNSD and bulk N_CCN to explore the causes. The calculated κ values were below 0.1 at SS = 0.4 % during the 72 % (or 88 %) period of Campaign A (or Campaign B). When κ values below 0.1 (or 0.2) were excluded, the remaining κ values were apparently reasonable, with an average of 0.22 (or 0.36) and a standard deviation of 0.10 (or 0.21) at SS = 0.4 % during Campaign A (or Campaign B). The unexpectedly lower κ values were discussed in terms of competitive activation of aerosols in marine atmospheres together with its net contribution to lowering the measured bulk N_CCN below the expected value.

Enrichment of short-chain organic acids transferred to submicron sea spray aerosols

Organic acids, considered to be a substantial component of the marine carbon cycle, can enter the atmosphere through sea spray aerosol (SSA) and further affect the climate. Despite their importance, the distribution and mixing state of organic acids in SSA over the marine boundary layer are poorly understood and therefore need more investigation. Here, we have used ion chromatography (IC) in anion mode to measure short-chain organic acids concentrations in SSA collected throughout a custom-made SSA simulation chamber. The enrichment behavior and morphology of monocarboxylic acids (MAs, C_1-8) and dicarboxylic acids (DAs) in submicron SSA were studied in seawater. We found that with MAs addition, the number concentration and mass concentration of SSA particles decreased gradually for C_5-8 MAs, whereas they weakly varied with DAs addition due to the fact that carboxyl groups at both ends of DAs increased the surface tension of seawater. Moreover, the target compounds in submicron SSA displayed a surface activity-dependent enrichment behavior, where seawater with stronger surface activity, such as that containing MAs with >5 carbons, was more enriched in SSA in comparison to seawater with weaker surface activity. MAs with chain length <5 carbons were slightly enriched in SSA, whereas the enrichment factor (EF) of C_5-8 MAs further increased with increasing chain length. These findings are of utmost importance in further understanding and quantifying the contribution of organic matter to SSA, which is crucial for assessing the atmosphere feedback of the marine carbon cycle. MAIN FINDING OF THE WORK: Surface tension of seawater is the key factor affecting the enrichment of short-chain organic acids in SSA.

Establishing a non-hydrostatic global atmospheric modeling system at 3-km horizontal resolution with aerosol feedbacks on the Sunway supercomputer of China

During the era of global warming and highly urbanized development, extreme and high impact weather as well as air pollution incidents influence everyday life and might even cause the incalculable loss of life and property. Despite the vast development of atmospheric models, there still exist substantial numerical forecast biases objectively. To accurately predict extreme weather, severe air pollution, and abrupt climate change, numerical atmospheric model requires not only to simulate meteorology and atmospheric compositions simultaneously involving many sophisticated physical and chemical processes but also at high spatiotemporal resolution. Global integrated atmospheric simulation at spatial resolutions of a few kilometers remains challenging due to its intensive computational and input/output (I/O) requirement. Through multi-dimension-parallelism structuring, aggressive and finer-grained optimizing, manual vectorizing, and parallelized I/O fragmenting, an integrated Atmospheric Model Across Scales (iAMAS) was established on the new Sunway supercomputer platform to significantly increase the computational efficiency and reduce the I/O cost. The global 3-km atmospheric simulation for meteorology with online integrated aerosol feedbacks with iAMAS was scaled to 39,000,000 processor cores and achieved the speed of 0.82 simulation day per hour (SDPH) with routine I/O, which enabled us to perform 5-day global weather forecast at 3-km horizontal resolution with online natural aerosol impacts. The results demonstrate the promising future that the increasing of spatial resolution to a few kilometers with online integrated aerosol feedbacks may significantly improve the global weather forecast.

Phytoplankton Impact on Marine Cloud Microphysical Properties Over the Northeast Atlantic Ocean

The current understanding of the impact of natural cloud condensation nuclei (CCN) variability on cloud properties in marine air is low, thus contributing to climate prediction uncertainty. By analyzing cloud remote sensing observations (2009-2015) at Mace Head (west coast of Ireland), we show the oceanic biota impact on the microphysical properties of stratiform clouds over the Northeast Atlantic Ocean. During spring to summer (seasons of enhanced oceanic biological activity), clouds typically host a higher number of smaller droplets resulting from increased aerosol number concentration in the CCN relevant-size range. The induced increase in cloud droplet number concentration (+100%) and decrease in their radius (-14%) are comparable in magnitude to that generated by the advection of anthropogenically influenced air masses over the background marine boundary layer. Cloud water content and albedo respond to marine CCN perturbations with positive adjustments, making clouds brighter as the number of droplets increases. Cloud susceptibility to marine aerosols overlaps with a large variability of cloud macrophysical and optical properties primarily affected by the meteorological conditions. The above findings suggest the existence of a potential feedback mechanism between marine biota and the marine cloud-climate system.

Long-term ecological research and the COVID-19 anthropause: A window to understanding social-ecological disturbance

The period of disrupted human activity caused by the COVID-19 pandemic, coined the "anthropause," altered the nature of interactions between humans and ecosystems. It is uncertain how the anthropause has changed ecosystem states, functions, and feedback to human systems through shifts in ecosystem services. Here, we used an existing disturbance framework to propose new investigation pathways for coordinated studies of distributed, long-term social-ecological research to capture effects of the anthropause. Although it is still too early to comprehensively evaluate effects due to pandemic-related delays in data availability and ecological response lags, we detail three case studies that show how long-term data can be used to document and interpret changes in air and water quality and wildlife populations and behavior coinciding with the anthropause. These early findings may guide interpretations of effects of the anthropause as it interacts with other ongoing environmental changes in the future, particularly highlighting the importance of long-term data in separating disturbance impacts from natural variation and long-term trends. Effects of this global disturbance have local to global effects on ecosystems with feedback to social systems that may be detectable at spatial scales captured by nationally to globally distributed research networks.

Climatological Characteristics and Aerosol Loading Trends from 2001 to 2020 Based on MODIS MAIAC Data for Tianjin, North China Plain

The North China Plain (NCP) in East Asia has a severe air pollution problem. In this study, the long-term spatial distribution and interannual trends of aerosol optical depth (AOD) were investigated using the MODIS MAIAC (multiangle implementation of the atmospheric correction) dataset from 2001 to 2020 for Tianjin, a city on the NCP. The annual AOD in Tianjin was 0.59 from 2001 to 2020. The average AOD of Tianjin was the highest in summer (0.96), followed by spring (0.58) and autumn (0.51). The annual AOD in Tianjin increased significantly in 2008 (approximately 0.77), and the minimum annual AOD was observed in 2020 (0.41). In summer, AOD in the 11 districts of Tianjin significantly increased from 2001 to 2010 and gradually decreased from 2011 to 2020. The occurrence frequency of AOD in the range of 0.2–0.5 was high in Tianjin accounting for almost 40% of the total proportion. In Tianjin, AOD exhibited a positive trend from 2001 to 2008 and an obvious negative growth trend from 2009 to 2020 due to anthropogenic emission. The findings are valuable for analyzing the climatological characteristics of aerosol loading and their optical properties at the district level of cities on the NCP.

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.

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.

Significance of the organic aerosol driven climate feedback in the boreal area

Aerosol particles cool the climate by scattering solar radiation and by acting as cloud condensation nuclei. Higher temperatures resulting from increased greenhouse gas levels have been suggested to lead to increased biogenic secondary organic aerosol and cloud condensation nuclei concentrations creating a negative climate feedback mechanism. Here, we present direct observations on this feedback mechanism utilizing collocated long term aerosol chemical composition measurements and remote sensing observations on aerosol and cloud properties. Summer time organic aerosol loadings showed a clear increase with temperature, with simultaneous increase in cloud condensation nuclei concentration in a boreal forest environment. Remote sensing observations revealed a change in cloud properties with an increase in cloud reflectivity in concert with increasing organic aerosol loadings in the area. The results provide direct observational evidence on the significance of this negative climate feedback mechanism.

CALIOP retrieval of droplet effective radius accounting for cloud vertical homogeneity

Monitoring cloud droplet effective radius (re) is of great significance for studying aerosol-cloud interactions (ACI). Passive satellite retrieval, e.g., MODIS (Moderate Resolution Imaging Spectroradiometer), requires sunlight. This requirement prompted developing re retrieval using active sensors, e.g., CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization). Given the highest sensitivity of vertically homogeneous clouds to aerosols that feed to cloud base, here CALIOP profile measurements were used for the first time to quantify cloud vertical homogeneity and estimate cloud re during both day and night. Comparison using simultaneous Aqua-MODIS measurements demonstrates that CALIOP retrieval has the highest accuracy for vertically homogeneous clouds, with R² (MAE, RMSE) of 0.72 (1.75 µm, 2.25 µm), while the accuracy is lowest for non-homogeneous clouds, with R² (MAE, RMSE) of 0.60 (2.90 µm, 3.70 µm). The improved re retrieval in vertically homogeneous clouds provides a basis for possible breakthrough insights in ACI by CALIOP since re in such clouds reflects most directly aerosol effects on cloud properties. Global day-night maps of cloud vertical homogeneity and respective re are presented.

Significant underestimation of radiative forcing by aerosol-cloud interactions derived from satellite-based methods

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.

Historical Changes in Seasonal Aerosol Acidity in the Po Valley (Italy) as Inferred from Fog Water and Aerosol Measurements

Acidity profoundly affects almost every aspect that shapes the composition of ambient particles and their environmental impact. Thermodynamic analysis of gas-particle composition datasets offers robust estimates of acidity, but they are not available for long periods of time. Fog composition datasets, however, are available for many decades; we develop a thermodynamic analysis to estimate the ammonia in equilibrium with fog water and to infer the pre-fog aerosol pH starting from fog chemical composition and pH. The acidity values from the new method agree with the results of thermodynamic analysis of the available gas-particle composition data. Applying the new method to historical (25 years) fog water composition at the rural station of San Pietro Capofiume (SPC) in the Po Valley (Italy) suggests that the aerosol has been mildly acidic, with its pH decreasing by 0.5-1.5 pH units over the last decades. The observed pH of the fog water also increased 1 unit over the same period. Analysis of the simulated aerosol pH reveals that the aerosol acidity trend is driven by a decrease in aerosol precursor concentrations, and changes in temperature and relative humidity. Currently, NO_x controls would be most effective for PM_2.5 reduction in the Po valley both during summer and winter. In the future, however, seasonal transitions to the NH₃-sensitive region may occur, meaning that the NH₃ reduction policy may become increasingly necessary.

Exploring the spatial heterogeneity and temporal homogeneity of ambient PM10 in nine core cities of China

We focus on the causes of fluctuations in wintertime PM₁₀ in nine regional core cities of China using two machine learning models, Random Forest (RF) and Recurrent Neural Network (RNN). RF and RNN both show high performance in predicting hourly PM₁₀ using only gaseous air pollutants (SO₂, NO₂ and CO) as inputs, showing the predominance of the secondary inorganic aerosol and implying the existence of thermodynamic equilibrium between gaseous air pollutants and PM₁₀. Also, we find the following results. The correlation of gaseous air pollutants and PM₁₀ were more relevant than that of meteorological conditions and PM₁₀. CO was the predominant factor for PM₁₀ in the Beijing-Tianjin-Hebei Plain and the Yangtze River Delta while SO₂ and NO₂ were also important features for PM₁₀ in the Pearl River Delta and Sichuan Basin. The spatial heterogeneity and temporal homogeneity of PM₁₀ in China are revealed. The long-range transported PM₁₀ was substantiated to be insignificant, except in the sandstorms. The severity of PM₁₀ was attributable to the lopsided shift of thermodynamic equilibrium and the phenology of indigenous flora.

Simulation study on the indirect effect of sulfate on the summer climate over the eastern China monsoon region

In this study, we designed a sensitivity test using the half number concentration of sulfate in the nucleation calculation process to study the aerosol-cloud interaction (ACI) of sulfate on clouds, precipitation, and monsoon intensity in the summer over the eastern China monsoon region (ECMR) with the National Center for Atmospheric Research Community Atmosphere Model version 5. Numerical experiments show that the ACI of sulfate led to an approximately 30% and 34% increase in the cloud condensation nuclei and cloud droplet number concentrations, respectively. Cloud droplet effective radius below 850 hPa decreased by approximately 4% in the southern ECMR, while the total liquid water path increased by 11%. The change in the indirect radiative forcing due to sulfate at the top of the atmosphere in the ECMR during summer was − 3.74 W·m⁻². The decreased radiative forcing caused a surface cooling of 0.32 K and atmospheric cooling of approximately 0.3 K, as well as a 0.17 hPa increase in sea level pressure. These changes decreased the thermal difference between the land and sea and the gradient of the sea-land pressure, leading to a weakening in the East Asian summer monsoon (EASM) and a decrease in the total precipitation rate in the southern ECMR. The cloud lifetime effect has a relatively weaker contribution to summer precipitation, which is dominated by convection. The results show that the ACI of sulfate was one possible reason for the weakening of the EASM in the late 1970s.

City-level air quality improvement in the Beijing-Tianjin-Hebei region from 2016/17 to 2017/18 heating seasons: Attributions and process analysis

With the implementation of clean air strategies, PM_2.5 pollution abatement has been observed in the "2 + 26" cities in the Beijing-Tianjin-Hebei (BTH) region (referred to as the BTH2+26) and their surrounding areas. To identify the drivers for PM_2.5 concentration decreases in the BTH2+26 cites from the 2016/17 heating season (HS1617) to the 2017/18 heating season (HS1718), we investigated the contributions of meteorological conditions and emission-reduction measures by Community Multi-Scale Air Quality (CMAQ) model simulations. The source apportionments of five sector sources (i.e., agriculture, industry, power plants, traffic and residential), and regional sources (i.e., local, within-BTH: other cities within the BTH2+26 cities, outside-BTH, and boundary conditions (BCON)) to the PM_2.5 decreases in the BTH2+26 cities were estimated with the Integrated Source Apportionment Method (ISAM). Mean PM_2.5 concentrations in the BTH2+26 cities substantially decreased from 77.4 to 152.5 μg m^-3 in HS1617 to 52.9-101.9 μg m^-3 in HS1718, with the numbers of heavy haze (daily PM_2.5 ≥150 μg m^-3) days decreasing from 17-77 to 5-30 days. The model simulation results indicated that the PM_2.5 concentration decreases in most of the BTH2+26 cities were attributed to emission reductions (0.4-55.0 μg m^-3, 2.3-81.6% of total), but the favorable meteorological conditions also played important roles (1.9-25.4 μg m^-3, 18.4-97.7%). Residential sources dominated the PM_2.5 reductions, leading to decreases in average PM_2.5 concentrations by more than 30 μg m^-3 in severely polluted cities (i.e., Shijiazhuang, Baoding, Xingtai, and Beijing). Regional source analyses showed that both local and within-BTH sources were significant contributors to PM_2.5 concentrations for most cities. Emission controls in local and within-BTH sources in HS1718 decreased the average PM_2.5 concentrations by 0.1-47.2 μg m^-3 and 0.3-22.1 μg m^-3, respectively, relative to those in HS1617. Here we demonstrate that a combination of favorable meteorological conditions and anthropogenic emission reductions contributed to the improvement of air quality from HS1617 to HS1718 in the BTH2+26 cities.

Aerosol-cloud-climate cooling overestimated by ship-track data

The effect of anthropogenic aerosol on the reflectivity of stratocumulus cloud decks through changes in cloud amount is a major uncertainty in climate projections. In frequently occurring nonprecipitating stratocumulus, cloud amount can decrease through aerosol-enhanced cloud-top mixing. The climatological relevance of this effect is debated because ship exhaust only marginally reduces stratocumulus amount. By comparing detailed numerical simulations with satellite analyses, we show that ship-track studies cannot be generalized to estimate the climatological forcing of anthropogenic aerosol. The ship track-derived sensitivity of the radiative effect of nonprecipitating stratocumulus to aerosol overestimates their cooling effect by up to 200%. The offsetting warming effect of decreasing stratocumulus amount needs to be taken into account if we are to constrain the cloud-mediated radiative forcing of anthropogenic aerosol.

New particle formation in the remote marine boundary layer

Marine low clouds play an important role in the climate system, and their properties are sensitive to cloud condensation nuclei concentrations. While new particle formation represents a major source of cloud condensation nuclei globally, the prevailing view is that new particle formation rarely occurs in remote marine boundary layer over open oceans. Here we present evidence of the regular and frequent occurrence of new particle formation in the upper part of remote marine boundary layer following cold front passages. The new particle formation is facilitated by a combination of efficient removal of existing particles by precipitation, cold air temperatures, vertical transport of reactive gases from the ocean surface, and high actinic fluxes in a broken cloud field. The newly formed particles subsequently grow and contribute substantially to cloud condensation nuclei in the remote marine boundary layer and thereby impact marine low clouds.

A Global Climatology of Dust Aerosols Based on Satellite Data: Spatial, Seasonal and Inter-Annual Patterns over the Period 2005–2019

A satellite-based algorithm is developed and used to determine the presence of dust aerosols on a global scale. The algorithm uses as input aerosol optical properties from the MOderate Resolution Imaging Spectroradiometer (MODIS)-Aqua Collection 6.1 and Ozone Monitoring Instrument (OMI)-Aura version v003 (OMAER-UV) datasets and identifies the existence of dust aerosols in the atmosphere by applying specific thresholds, which ensure the coarse size and the absorptivity of dust aerosols, on the input optical properties. The utilized aerosol optical properties are the multiwavelength aerosol optical depth (AOD), the Aerosol Absorption Index (AI) and the Ångström Exponent (a). The algorithm operates on a daily basis and at 1° × 1° latitude-longitude spatial resolution for the period 2005–2019 and computes the absolute and relative frequency of the occurrence of dust. The monthly and annual mean frequencies are calculated on a pixel level for each year of the study period, enabling the study of the seasonal as well as the inter-annual variation of dust aerosols’ occurrence all over the globe. Temporal averaging is also applied to the annual values in order to estimate the 15-year climatological mean values. Apart from temporal, a spatial averaging is also applied for the entire globe as well as for specific regions of interest, namely great global deserts and areas of desert dust export. According to the algorithm results, the highest frequencies of dust occurrence (up to 160 days/year) are primarily observed over the western part of North Africa (Sahara), and over the broader area of Bodélé, and secondarily over the Asian Taklamakan desert (140 days/year). For most of the study regions, the maximum frequencies appear in boreal spring and/or summer and the minimum ones in winter or autumn. A clear seasonality of global dust is revealed, with the lowest frequencies in November–December and the highest ones in June. Finally, an increasing trend of global dust frequency of occurrence from 2005 to 2019, equal to 56.2%, is also found. Such an increasing trend is observed over all study regions except for North Middle East, where a slight decreasing trend (−2.4%) is found.

Surface ocean microbiota determine cloud precursors

One pathway by which the oceans influence climate is via the emission of sea spray that may subsequently influence cloud properties. Sea spray emissions are known to be dependent on atmospheric and oceanic physicochemical parameters, but the potential role of ocean biology on sea spray fluxes remains poorly characterized. Here we show a consistent significant relationship between seawater nanophytoplankton cell abundances and sea-spray derived Cloud Condensation Nuclei (CCN) number fluxes, generated using water from three different oceanic regions. This sensitivity of CCN number fluxes to ocean biology is currently unaccounted for in climate models yet our measurements indicate that it influences fluxes by more than one order of magnitude over the range of phytoplankton investigated.

Experimental and an electrolyte non-random two-liquid model to predict the vapor–liquid equilibrium of CO2 in aqueous solutions of diethylenetriamine

The absorption and desorption data of CO2 in aqueous solutions with a mass fraction of 10% and 20% of diethylenetriamine are measured at 313.15, 343.15, 373.15, and 393.15 K. The electrolyte non-random two-liquid theory is developed using Aspen V9.0 to correlate and predict the vapor–liquid equilibrium of CO2 in aqueous diethylenetriamine solutions. The model predicted the heat capacity and saturated vapor pressure data of diethylenetriamine, the mixed heat of a diethylenetriamine–H2O binary system, and the vapor–liquid equilibrium data of a diethylenetriamine–H2O–CO2 ternary system. The physical parameters and the interaction parameters of the model system are calculated. The model predicted CO2 solubility showing a 10% average absolute deviation from experimental data. The calculated values of the model are basically consistent with the experimental values.

Anthropogenic emissions from South Asia reverses the aerosol indirect effect over the northern Indian Ocean

Atmospheric aerosols play an important role in the formation of warm clouds by acting as efficient cloud condensation nuclei (CCN) and their interactions are believed to cool the Earth-Atmosphere system (‘first indirect effect or Twomey effect’) in a highly uncertain manner compared to the other forcing agents. Here we demonstrate using long-term (2003–2016) satellite observations (NASA’s A-train satellite constellations) over the northern Indian Ocean, that enhanced aerosol loading (due to anthropogenic emissions) can reverse the first indirect effect significantly. In contrast to Twomey effect, a statistically significant increase in cloud effective radius (CER, µm) is observed with respect to an increase in aerosol loading for clouds having low liquid water path (LWP < 75 g m⁻²) and drier cloud tops. Probable physical mechanisms for this effect are the intense competition for available water vapour due to higher concentrations of anthropogenic aerosols and entrainment of dry air on cloud tops. For such clouds, cloud water content showed a negative response to cloud droplet number concentrations and the estimated intrinsic radiative effect suggest a warming at the Top of the Atmosphere. Although uncertainties exist in quantifying aerosol-cloud interactions (ACI) using satellite observations, present study indicates the physical existence of anti-Twomey effect over the northern Indian Ocean during south Asian outflow.

High light alongside elevated P CO2 alleviates thermal depression of photosynthesis in a hard coral (Pocillopora acuta)

The absorbtion of human-emitted CO₂ by the oceans (elevated P _CO2 ) is projected to alter the physiological performance of coral reef organisms by perturbing seawater chemistry (i.e. ocean acidification). Simultaneously, greenhouse gas emissions are driving ocean warming and changes in irradiance (through turbidity and cloud cover), which have the potential to influence the effects of ocean acidification on coral reefs. Here, we explored whether physiological impacts of elevated P _CO2  on a coral-algal symbiosis (Pocillopora acuta-Symbiodiniaceae) are mediated by light and/or temperature levels. In a 39 day experiment, elevated P _CO2  (962 versus 431 µatm P _CO2 ) had an interactive effect with midday light availability (400 versus 800 µmol photons m^-2 s^-1) and temperature (25 versus 29°C) on areal gross and net photosynthesis, for which a decline at 29°C was ameliorated under simultaneous high-P _CO2  and high-light conditions. Light-enhanced dark respiration increased under elevated P _CO2  and/or elevated temperature. Symbiont to host cell ratio and chlorophyll a per symbiont increased at elevated temperature, whilst symbiont areal density decreased. The ability of moderately strong light in the presence of elevated P _CO2  to alleviate the temperature-induced decrease in photosynthesis suggests that higher substrate availability facilitates a greater ability for photochemical quenching, partially offsetting the impacts of high temperature on the photosynthetic apparatus. Future environmental changes that result in moderate increases in light levels could therefore assist the P. acuta holobiont to cope with the 'one-two punch' of rising temperatures in the presence of an acidifying ocean.

Assessment of PM2.5-bound nitrogen-containing organic compounds (NOCs) during winter at urban sites in China and Korea

In this study, ambient fine particles (PM_2.5) were collected in two urban cities in China and Korea (Beijing and Gwangju, respectively) simultaneously in January 2018. Analysis of the nonpolar and semipolar organic matter (OM) using atmospheric pressure photoionization (APPI) Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) revealed that compounds containing only C, H, and O (CHO) and those containing C, H, O, and N (CHON) accounted for more than 90% of the total intensity of the OM peaks. Higher proportions of CHON compounds were observed during days with abnormally high PM_2.5 concentrations at both sites than on regular or non-event days. The proportion of CHON species at the Beijing site was not correlated with secondary ionic species (i.e., NO₃^-, SO₄^2-, and NH₄⁺) or gaseous components (i.e., O₃, NO₂, and SO₂). In contrast, the proportion of CHON species at the Gwangju site was positively correlated with the concentrations of particulate nitrate and ammonium ions, assuming that ambient ammonium nitrate plays a role in the atmospheric formation of nitrogen-containing organic compounds (NOCs) at the Gwangju site and that Gwangju is more strongly influenced by secondary aerosols than Beijing is. In particular, a significant proportion of the compounds observed at the Beijing site contained only C, H and N (CHN), while negligible amounts of CHN were detected at the Gwangju site. The CHN species in Beijing were identified as quinoline compounds and the corresponding -CH₂ homologous series using complementary GC × GC-TOF MS analysis. These results suggest that NOCs and their -CH₂ homologous series from primary emissions may be significant contributors to nonpolar and semipolar OM during winter in Beijing, while NOCs with high oxidation states, likely formed via ambient-phase nitrate-mediated reactions, may be the dominant OM constituents in Gwangju.

Construction of a virtual PM2.5 observation network in China based on high-density surface meteorological observations using the Extreme Gradient Boosting model

With increasing public concerns on air pollution in China, there is a demand for long-term continuous PM_2.5 datasets. However, it was not until the end of 2012 that China established a national PM_2.5 observation network. Before that, satellite-retrieved aerosol optical depth (AOD) was frequently used as a primary predictor to estimate surface PM_2.5. Nevertheless, satellite-retrieved AOD often encounter incomplete daily coverage due to its sampling frequency and interferences from cloud, which greatly affect the representation of these AOD-based PM_2.5. Here, we constructed a virtual ground-based PM_2.5 observation network at 1180 meteorological sites across China using the Extreme Gradient Boosting (XGBoost) model with high-density meteorological observations as major predictors. Cross-validation of the XGBoost model showed strong robustness and high accuracy in its estimation of the daily (monthly) PM_2.5 across China in 2018, with R², root-mean-square error (RMSE) and mean absolute error values of 0.79 (0.92), 15.75 μg/m³ (6.75 μg/m³) and 9.89 μg/m³ (4.53 μg/m³), respectively. Meanwhile, we find that surface visibility plays the dominant role in terms of the relative importance of variables in the XGBoost model, accounting for 39.3% of the overall importance. We then use meteorological and PM_2.5 data in the year 2017 to assess the predictive capability of the model. Results showed that the XGBoost model is capable to accurately hindcast historical PM_2.5 at monthly (R² = 0.80, RMSE = 14.75 μg/m³), seasonal (R² = 0.86, RMSE = 12.28 μg/m³), and annual (R² = 0.81, RMSE = 10.10 μg/m³) mean levels. In general, the newly constructed virtual PM_2.5 observation network based on high-density surface meteorological observations using the Extreme Gradient Boosting model shows great potential in reconstructing historical PM_2.5 at ~1000 meteorological sites across China. It will be of benefit to filling gaps in AOD-based PM_2.5 data, as well as to other environmental studies including epidemiology.

Aerosols enhance cloud lifetime and brightness along the stratus-to-cumulus transition

Anthropogenic aerosols are hypothesized to enhance planetary albedo and offset some of the warming due to the buildup of greenhouse gases in Earth's atmosphere. Aerosols can enhance the coverage, reflectance, and lifetime of warm low-level clouds. However, the relationship between cloud lifetime and aerosol concentration has been challenging to measure from polar orbiting satellites. We estimate two timescales relating to the formation and persistence of low-level clouds over [Formula: see text] spatial domains using multiple years of geostationary satellite observations provided by the Clouds and Earth's Radiant Energy System (CERES) Synoptic (SYN) product. Lagrangian trajectories spanning several days along the classic stratus-to-cumulus transition zone are stratified by aerosol optical depth and meteorology. Clouds forming in relatively polluted trajectories tend to have lighter precipitation rates, longer average lifetime, and higher cloud albedo and cloud fraction compared with unpolluted trajectories. While liquid water path differences are found to be negligible, we find direct evidence of increased planetary albedo primarily through increased drop concentration ([Formula: see text]) and cloud fraction, with the caveat that the aerosol influence on cloud fraction is positive only for stable atmospheric conditions. While the increase in cloud fraction can be large typically in the beginning of trajectories, the Twomey effect accounts for the bulk (roughly 3/4) of the total aerosol indirect radiative forcing estimate.

Characterization of Aerosol Hygroscopicity Over the Northeast Pacific Ocean: Impacts on Prediction of CCN and Stratocumulus Cloud Droplet Number Concentrations

During the Marine Aerosol Cloud and Wildfire Study (MACAWS) in June and July of 2018, aerosol composition and cloud condensation nuclei (CCN) properties were measured over the N.E. Pacific to characterize the influence of aerosol hygroscopicity on predictions of ambient CCN and stratocumulus cloud droplet number concentrations (CDNC). Three vertical regions were characterized, corresponding to the marine boundary layer (MBL), an above-cloud organic aerosol layer (AC-OAL), and the free troposphere (FT) above the AC-OAL. The aerosol hygroscopicity parameter (κ) was calculated from CCN measurements (κ CCN) and bulk aerosol mass spectrometer (AMS) measurements (κ AMS). Within the MBL, measured hygroscopicities varied between values typical of both continental environments (~0.2) and remote marine locations (~0.7). For most flights, CCN closure was achieved within 20% in the MBL. For five of the seven flights, assuming a constant aerosol size distribution produced similar or better CCN closure than assuming a constant "marine" hygroscopicity (κ = 0.72). An aerosol-cloud parcel model was used to characterize the sensitivity of predicted stratocumulus CDNC to aerosol hygroscopicity, size distribution properties, and updraft velocity. Average CDNC sensitivity to accumulation mode aerosol hygroscopicity is 39% as large as the sensitivity to the geometric median diameter in this environment. Simulations suggest CDNC sensitivity to hygroscopicity is largest in marine stratocumulus with low updraft velocities (<0.2 m s-1), where accumulation mode particles are most relevant to CDNC, and in marine stratocumulus or cumulus with large updraft velocities (>0.6 m s-1), where hygroscopic properties of the Aitken mode dominate hygroscopicity sensitivity.

Unexpected rise of ozone in urban and rural areas, and sulfur dioxide in rural areas during the coronavirus city lockdown in Hangzhou, China: implications for air quality

The outbreak of coronavirus named COVID-19, initially identified in Wuhan, China in December 2019, has spread rapidly at the global scale. Most countries have rapidly stopped almost all activities including industry, services and transportation of goods and people, thus decreasing air pollution in an unprecedented way, and providing a unique opportunity to study air pollutants. While satellite data have provided visual evidence for the global reduction in air pollution such as nitrogen dioxide (NO₂) worldwide, precise and quantitative information is missing at the local scale. Here we studied changes in particulate matter (PM_2.5, PM₁₀), carbon monoxide (CO), NO₂, sulfur dioxide (SO₂) and ozone (O₃) at 10 urban sites in Hangzhou, a city of 7.03 million inhabitants, and at 1 rural site, before city lockdown, January 1-23, during city lockdown, January 24-February 15, and during resumption, February 16-28, in 2020. Results show that city lockdown induced a sharp decrease in PM_2.5, PM₁₀, CO, and NO₂ concentrations at both urban and rural sites. The NO₂ decrease is explained by reduction in traffic emissions in the urban areas, and by lower regional transport in rural areas during lockdown, as expected. SO₂ concentrations decreased from 6.3 to 5.3 μg m^-3 in the city, but increased surprisingly from 4.7 to 5.8 μg m^-3 at the rural site: this increase is attributed both to higher coal consumption for heating and emissions from traditional fireworks of the Spring Eve and Lantern Festivals during lockdown. Unexpectedly, O₃ concentrations increased by 145% from 24.6 to 60.6 μg m^-3 in the urban area, and from 42.0 to 62.9 μg m^-3 in the rural area during the lockdown. This finding is explained by the weakening of chemical titration of O₃ by NO due to reductions of NO_x fresh emissions during the non-photochemical reaction period from 20:00 PM to 9:00 AM (local time). During the lockdown, compared to the same period in 2019, the daily average concentrations in the city decreased by 42.7% for PM_2.5, 47.9% for PM₁₀, 28.6% for SO₂, 22.3% for CO and 58.4% for NO₂, which is obviously explained by the absence of city activities. Overall, we observed not only the expected reduction in some atmospheric pollutants (PM, SO₂, CO, NO₂), but also unexpected increases in SO₂ in the rural areas and of ozone (O₃) in both urban and rural areas, the latter being paradoxically due to the reduction in nitrogen oxide levels. In other words, the city lockdown has improved air quality by reducing PM_2.5, PM₁₀, CO, and NO₂, but has also decreased air quality by augmenting O₃ and SO₂.

Molecular identification of organic vapors driving atmospheric nanoparticle growth

Particles formed in the atmosphere via nucleation provide about half the number of atmospheric cloud condensation nuclei, but in many locations, this process is limited by the growth of the newly formed particles. That growth is often via condensation of organic vapors. Identification of these vapors and their sources is thus fundamental for simulating changes to aerosol-cloud interactions, which are one of the most uncertain aspects of anthropogenic climate forcing. Here we present direct molecular-level observations of a distribution of organic vapors in a forested environment that can explain simultaneously observed atmospheric nanoparticle growth from 3 to 50 nm. Furthermore, the volatility distribution of these vapors is sufficient to explain nanoparticle growth without invoking particle-phase processes. The agreement between observed mass growth, and the growth predicted from the observed mass of condensing vapors in a forested environment thus represents an important step forward in the characterization of atmospheric particle growth.

Condensation of organic vapors is a main factor controlling the growth of atmospheric particles. Here the authors identify a distribution of organic vapors in a forested environment able to explain nanoparticle growth at the same location, contributing to understanding aerosol climate effects.

Scientists' warning to humanity: microorganisms and climate change

In the Anthropocene, in which we now live, climate change is impacting most life on Earth. Microorganisms support the existence of all higher trophic life forms. To understand how humans and other life forms on Earth (including those we are yet to discover) can withstand anthropogenic climate change, it is vital to incorporate knowledge of the microbial 'unseen majority'. We must learn not just how microorganisms affect climate change (including production and consumption of greenhouse gases) but also how they will be affected by climate change and other human activities. This Consensus Statement documents the central role and global importance of microorganisms in climate change biology. It also puts humanity on notice that the impact of climate change will depend heavily on responses of microorganisms, which are essential for achieving an environmentally sustainable future.

Weak average liquid-cloud-water response to anthropogenic aerosols

The cooling of the Earth's climate through the effects of anthropogenic aerosols on clouds offsets an unknown fraction of greenhouse gas warming. An increase in the amount of water inside liquid-phase clouds induced by aerosols, through the suppression of rain formation, has been postulated to lead to substantial cooling, which would imply that the Earth's surface temperature is highly sensitive to anthropogenic forcing. Here we provide direct observational evidence that, instead of a strong increase, aerosols cause a relatively weak average decrease in the amount of water in liquid-phase clouds compared with unpolluted clouds. Measurements of polluted clouds downwind of various anthropogenic sources-such as oil refineries, smelters, coal-fired power plants, cities, wildfires and ships-reveal that aerosol-induced cloud-water increases, caused by suppressed rain formation, and decreases, caused by enhanced evaporation of cloud water, partially cancel each other out. We estimate that the observed decrease in cloud water offsets 23% of the global climate-cooling effect caused by aerosol-induced increases in the concentration of cloud droplets. These findings invalidate the hypothesis that increases in cloud water cause a substantial climate cooling effect and translate into reduced uncertainty in projections of future climate.

Strong Dependence of Atmospheric Feedbacks on Mixed-Phase Microphysics and Aerosol-Cloud Interactions in HadGEM3

We analyze the atmospheric processes that explain the large changes in radiative feedbacks between the two latest climate configurations of the Hadley Centre Global Environmental model. We use a large set of atmosphere-only climate change simulations (amip and amip-p4K) to separate the contributions to the differences in feedback parameter from all the atmospheric model developments between the two latest model configurations. We show that the differences are mostly driven by changes in the shortwave cloud radiative feedback in the midlatitudes, mainly over the Southern Ocean. Two new schemes explain most of the differences: the introduction of a new aerosol scheme and the development of a new mixed-phase cloud scheme. Both schemes reduce the strength of the preexisting shortwave negative cloud feedback in the midlatitudes. The new aerosol scheme dampens a strong aerosol-cloud interaction, and it also suppresses a negative clear-sky shortwave feedback. The mixed-phase scheme increases the amount of cloud liquid water path (LWP) in the present day and reduces the increase in LWP with warming. Both changes contribute to reducing the negative radiative feedback of the increase of LWP in the warmer climate. The mixed-phase scheme also enhances a strong, preexisting, positive cloud fraction feedback. We assess the realism of the changes by comparing present-day simulations against observations and discuss avenues that could help constrain the relevant processes.