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Clouds are crucial in regulating the Earth's energy budget. Global cloud top heights have been easily retrieved from satellite measurements, but there are few methods for determining cloud base height (CBH) from satellite measurements. The Cloud Base Altitude Spatial Extrapolator (CBASE) algorithm was proposed to derive the height of the lower-troposphere liquid cloud base by using the Cloud-Aerosol Lidar with Orthogonal polarization cloud aerosol LiDAR (CALIOP) profiles and weather observations at airports from aviation routine and special weather report (METARs and SPECIs, called METAR) observation data in the United States. A modification to the CBASE algorithm over China (CNMETAR-CBASE) is presented in this paper. In this paper, the ability of the CBASE algorithm to calculate CBH in China is evaluated, and METAR observations over China (CNMETAR) were then used to modify the CBASE algorithm. The results including CNMETAR observation data in China can better retrieve CBH over China compared with the results using the original CBASE algorithm, and the accuracy of the global CBH results has been improved. Overestimations of CBH with the original algorithm range from 500 to 800 m in China, which have been reduced to about 300 m with an improved algorithm. The deviations calculated by the algorithm also have a significant reduction, from 480 m (CBASE) to 420 m (CNMETAR-CBASE). In conclusion, the modified CBASE algorithm not only calculates the CBH more accurately in China but also improves the results of the global CBH retrieved from satellites. [ABSTRACT FROM AUTHOR]

Nitroaromatic compounds (NACs) in ambient particles are of great concern due to their adverse effects on human health and climate. However, investigations on the characteristics and potential sources of NACs in Southwest China are still scarce. In this study, a field sampling campaign was carried out in the winter of 2022 at a suburban site in Mianyang, Southwest China. A direct injection liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed to rapidly determine 10 NACs in fine particulate matter (PM 2.5 ) extracts. The method was sensitive for the quantification of the NACs, with a limit of quantification (LOQ) in the range of 0.092-0.52 ng mL -1 . Then, the developed method was applied to determine the concentrations of nitrophenols (NPs), nitrocatechols (NCs), nitrosalicylic acids (NSAs), and nitronaphthol in PM 2.5 in Mianyang. The average concentration of total NACs was 78.2 ± 31.2 ng m -3 , with daily concentrations ranging from 20.7 to 127.9 ng m -3 . Among the measured NACs, 4-nitrocatechol was the most abundant, accounting for 57.8% of the NACs in winter. The five NPs compounds together contributed to 14% of the NACs, which was lower than in other Chinese cities due to the warm climate in winter in Southwest China. NSAs and nitronaphthol each accounted for less than 5% of the NACs. Three major sources of NACs were identified based on the principal component analysis, including vehicle emissions, biomass burning, and secondary formation. The significant correlation between individual NACs and NO 2 supported their secondary formation sources. The good correlation between NPs and cloud amount further suggested that gas-phase oxidation was the possible NPs formation mechanism. Our findings revealed the important role of nitrocatechols in NACs in Southwest China, implying that more measures should be taken to control biomass burning and aromatic volatile organic compounds emissions to reduce the level of NACs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

A two-stage model integrating a spatiotemporal linear mixed effect (STLME) and a geographic weight regression (GWR) model is proposed to improve the meteorological variables-based aerosol optical depth (AOD) retrieval method (Elterman retrieval model-ERM). The proposed model is referred to as the STG-ERM model. The STG-ERM model is applied over the Beijing-Tianjin-Hebei (BTH) region in China for the years 2019 and 2020. The results show that data coverage increased by 39.0% in 2019 and 40.5% in 2020. Cross-validation of the retrieval results versus multi-angle implementation of atmospheric correction (MAIAC) AOD shows the substantial improvement of the STG-ERM model over earlier meteorological models for AOD estimation, with a determination coefficient (R 2 ) of daily AOD of 0.86, root mean squared prediction error (RMSE) and the relative prediction error (RPE) of 0.10 and 36.14% in 2019 and R 2 of 0.86, RMSE of 0.12 and RPE of 37.86% in 2020. The fused annual mean AOD indicates strong spatial variation with high value in south plain and low value in northwestern mountainous areas of the BTH region. The overall spatial seasonal mean AOD ranges from 0.441 to 0.586, demonstrating strongly seasonal variation. The coverage of STG-ERM retrieved AOD, as determined in this exercise by leaving out part of the meteorological data, affects the accuracy of fused AOD. The coverage of the meteorological data has smaller impact on the fused AOD in the districts with low annual mean AOD of less than 0.35 than that in the districts with high annual mean AOD of greater than 0.6. If available, continuous daily meteorological data with high spatiotemporal resolution can improve the model performance and the accuracy of fused AOD. The STG-ERM model may serve as a valuable approach to provide data to fill gaps in satellite-retrieved AOD products., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

High uncertainty in optical properties of black carbon (BC) involving heterogeneous chemistry has recently attracted increasing attention in the field of atmospheric climatology. To fill the gap in BC optical knowledge so as to estimate more accurate climate effects and serve the response to global warming, it is beneficial to conduct site-level studies on BC light absorption enhancement (E abs ) characteristics. Real-time surface gas and particulate pollutant observations during the summer and winter over Wuhan were utilized for the analysis of E abs simulated by minimum R squared (MRS), considering two distinct atmospheric conditions (2015 and 2017). In general, differences in aerosol emissions led to E abs differential behaviors. The summer average of E abs (1.92 ± 0.55) in 2015 was higher than the winter average (1.27 ± 0.42), while the average (1.11 ± 0.20) in 2017 summer was lower than that (1.67 ± 0.69) in winter. E abs and R BC (representing the mass ratio of non-refractory constituents to elemental carbon) constraints suggest that E abs increased with the increase in R BC under the ambient condition enriched by secondary inorganic aerosol (SIA), with a maximum growth rate of 70.6% in 2015 summer. However, E abs demonstrated a negative trend against R BC in 2017 winter due to the more complicated mixing state. The result arose from the opposite impact of hygroscopic SIA and absorbing OC/irregular distributed coatings on amplifying the light absorbency of BC. Furthermore, sensitivity analysis revealed a robust positive correlation (R > 0.9) between aerosol chemical compositions (including sulfate, nitrate, ammonium and secondary organic carbon), which could be significantly perturbed by only a small fraction of absorbing materials or restructuring BC through gaps filling. The above findings not only deepen the understanding of BC, but also provide useful information for the scientific decision-making in government to mitigate particulate pollution and obtain more precise BC radiative forcing., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The article focuses on a study which aims at comparing differences in aerosol optical depth (AOD) measured by Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). In the study, AOD levels are evaluated in the dust regions of the Sahara and northwest China and biomass burning regions of South America and South Africa. It reveals higher MODIS AOD over dust regions as compared to CALIPSO AOD.

In order to fully understand the carbon emission from different fuels in rural villages of China, especially in the typical atmospheric pollution areas. The characteristics of carbonaceous aerosols and carbon dioxide (CO 2 ) with its stable carbon isotope (δ 13 C) were investigated in six households, which two households used coal, two households used wood as well as two households used biogas and liquefied petroleum gas (LPG), from two rural villages in Fenwei Plain from March to April 2021. It showed that the fine particulate matter (PM 2.5 ) emitted from biogas and LPG couldn't be as lower as expected in this area. However, the clean fuels could relatively reduce the emissions of organic carbon (OC) and element carbon (EC) in PM 2.5 compare to the solid fuels. The pyrolyzed carbon (OP) accounted more total carbon (TC) in coal than the other fuels use households, indicating that more water-soluble OC existed, and it still had the highest secondary organic carbon (SOC) than the other fuels. Meantime, the coal combustions in the two villages had the highest CO 2 concentration of 527.6 ppm and 1120.6 ppm, respectively, while the clean fuels could effectively reduce it. The average δ 13 C values (-26.9‰) was much lighter than almost all the outdoor monitoring and similar to the δ 13 C values for coal combustion and vehicle emission, showing that they might be the main contributors of the regional atmospheric aerosol in this area. During the sandstorm, the indoor PM 2.5 mass and CO 2 were increasing obviously. The indoor cancer risk of PAHs for adults and children were greater than 1 × 10 -6 , exert a potential carcinogenic risk to human of solid fuels combustion in rural northern China. It is important to continue concern the solid fuel combustion and its health impact in rural areas., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The Absorbing Aerosol Sensor (AAS) is carried on the Gao-Fen 5B (GF-5B) satellite, and it allows for the measurement of solar backscatter radiation by the atmosphere in the UV–Vis bands. The AAS is an imaging spectrometer that employs CCD for capturing both a continuous spectrum and the cross-track orientation with a 114° wide swath. The broad field of view provides daily global envelopment with a 4 km spatial resolution at the nadir. This paper mainly analyzes the initial working status of the instrument in orbit, including wavelength calibration, radiometric calibration, detector performance, and product availability. Preliminary observations indicate the ability of the AAS to monitor absorbing aerosols like dust, biomass burning, volcano ash, and some pollution aerosols and to identify the aerosol events in China and other regions with high spatial resolution. [ABSTRACT FROM AUTHOR]

The aerosol extinction coefficient (AEC) characterises the attenuation of the light propagating in a turbid medium with suspended particles. Therefore, it is of great significance to carry out AEC prediction research using state-of-art neural network (NN) methods. The attention mechanism (AM) has become an indispensable part of NNs that focuses on input weight assignment. Traditional AM is used in time steps to help generate the outputs. To select important features of meteorological parameters (MP) that are helpful for forecasting, in this study, we apply AM to features instead of time steps. Then we propose a bidirectional long short-term memory (BiLSTM) NN based on AM to predict the AEC. The proposed method can remember information twice (i.e., forward and backward), which can provide more context for AEC forecasting. Finally, an in situ measured MP dataset is applied in the proposed model, which presents Maoming coastal area's atmospheric conditions in November 2020. The experimental results show that the model proposed in this paper has higher accuracy compared with traditional NN, providing a novel solution to the AEC prediction problem for the current studies of marine aerosol. [ABSTRACT FROM AUTHOR]

A long-term historical aerosol optical depth (AOD) data set from 1982 to 2011 over China (15–45° N; 75–135° E) with 0.1 spatial resolution has been produced from Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmospheres—Extended level-2B data. The spatial distribution pattern shows that high AOD values are found in central and eastern China over the entire period with AODs larger in summer and spring than in autumn and winter. As the high-quality products from AERONET were absent for this period over mainland China, AOD data obtained using the broadband extinction method from solar radiation stations have been used to verify the quality of the AVHRR AOD data set over China. The intercomparison results show that the interannual variation of AOD has been well captured in the variation curve of the AOD monthly mean and the variation trend is also consistent over the whole period. The correlation coefficient of the monthly mean is mostly larger than 0.55, the agreement index is larger than 0.57, and the relative error is less than 21%. Both AVHRR and visibility data sets show high values in regions with rapid economic development. Using Moderate Resolution Imaging Spectroradiometer AOD data as references, it is found that AVHRR AOD from this paper has better accuracy in general than that from Deep Blue (DB) algorithm over China, especially over eastern and southern China, while DB provides more coverage especially over bright surface such as northwest China. This long-term historic AOD data set can be used together with other AOD data sets to study the climate and environmental changes, especially in the 1980s and 1990s. [ABSTRACT FROM AUTHOR]

In this paper, we examine the aerosol effects on the vertical structure of precipitation in East China by matching GPM DPR (Global Precipitation Measurement Dual-frequency Precipitation Radar) and MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Versions2) datasets. It was found that the increase of aerosol will obviously increase the precipitation frequency when AOD (Aerosol Optical Depth) ≤ 0.5, but the excessive aerosol suppresses the precipitation frequency when AOD > 0.5 in some regions. The AOD obviously enhances the radar echo intensity of precipitation and has a stronger impact on convective precipitation. The correlation between AOD and rain rate, and that between AOD and STH (storm top height) are different in different regions of East China. The aerosol reduces the mean droplet concentration in most regions except NC (Northeast China). In most cases, aerosol increases the effective radius of precipitation and has a higher impact on convective precipitation. [ABSTRACT FROM AUTHOR]

The concentration changes of aerosols have attracted wide-ranging attention during the COVID-19 lockdown (CLD) period, but the studies involving aerosol optical properties (AOPs) are relatively insufficient, mainly AOD (fine-mode AOD (AODf) and coarse-mode AOD (AODc)), aerosol absorption optical depth (AAOD), and aerosol extinction coefficient (AEC). Here, the remote-sensing observations, Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) products, backward-trajectory, and potential-source-contribution models are used to assess the impact of AOPs, vertical distribution, and possible sources on the atmosphere environment in North China Plain (NCP), Central China (CC), Yangtze River Delta (YRD), Pearl River Delta (PRD), and Sichuan Basin (SB) during the CLD period. The results demonstrate that both AOD (MODIS) and near-surface AEC (CALIPSO, <2 km) decreased in most areas of China. Compared with previous years (average 2017–2019), the AOD (AEC) of NCP, CC, YRD, PRD, and SB reduced by 3.33% (10.76%), 14.36% (32.48%), 10.80% (29.64%), 31.44% (22.68%), and 15.50% (8.44%), respectively. In addition, MODIS (AODc) and MERRA-2 (AODc) decreased in the five study areas compared with previous years, so the reduction in dust activities also contributed to improving regional air quality during the epidemic. Despite the reduction of anthropogenic emissions (AODf) in most areas of China during the CLD periods, severe haze events (AODf > 0.6) still occurred in some areas. Compared to previous years, there were increases in BC, OC (MERRA-2), and national raw coal consumption during CLD. Therefore, emissions from some key sectors (raw coal heating, thermal power generation, and residential coal) did not decrease, and this may have increased AODf during the CLD. Based on backward -rajectory and potential source contribution models, the study area was mainly influenced by local anthropogenic emissions, but some areas were also influenced by northwestern dust, Southeast Asian biomass burning, and marine aerosol transport. This paper underscores the importance of emissions from the residential sector and thermal power plants for atmospheric pollution in China and suggests that these sources must be taken into account in developing pollution-mitigation plans. [ABSTRACT FROM AUTHOR]

At present, the air environment in China is characterized by complex pollution. In this paper, the pollutant sources, transport paths and aerosol optical properties during the dust pollution was conducted to analyse based on ground-based lidar, space-borne sensor and atmospheric transmission model. Firstly, the NMMB/BSC-Dust model, the VIIRS-Suomi NPP date and HYSPLIT were carried out to analyse the dust transport paths and the dust particle size, and then the concentration of particles was analysed. Finally, the optical properties of aerosol particles in the dust weather were studied. During the formation of this weather, there is high dust in the Gobi and Taklamakan deserts. With the influence of wind direction, the dust moves from north to south, and the dust load significantly increased in southern China. Dust at the low altitude is generally transported from the Taklamakan Desert, while dust at the high altitude is generally transported from the Gobi Desert. The hourly average change of PM10 is from 36 μg/m3 to 818 μg/m3, while the hourly average change of PM2.5 is from 15 μg/m3 to 197 μg/m3. The dust was the main cause of the pollution weather. In this study, the formation process of the dust pollution revealed which can be used to provide guidance for government for the prevention work of dust pollution. [ABSTRACT FROM AUTHOR]

Aerosol Optical Depth (AOD) is one of the most important parameters of aerosol and a key physical quantity to characterize atmospheric turbidity and air pollution. Accurate retrieval of AOD is of great significance for air quality assessment. However, the spatial resolution of the currently widely used Moderate Resolution Imaging Spectroradiometer (MODIS) AOD products is too low to meet the application research of atmospheric environment at the regional scale. In 2013, China launched the Gaofen-1 (GF-1) satellite, which provides a new idea for AOD retrieval. In this paper, we apply the synergetic use of TERRA and AQUA satellite MODIS data to calculate the high-resolution AOD over Beijing based on the Synergetic Retrieval of Aerosol Properties algorithm (SRAP) and discussed scale conversion problems between AODs with different resolutions. To obtain the 100 m MODIS data, we use GF-1 wide-field-of-view data to downscale 1 km MODIS data based on mutual information method. The retrieved AOD has a spatial resolution of 100 m and can cover many land surface types. Preliminary validation was carried out with the Aerosol Robotic Network (AERONET) ground observation data. The correlation coefficient is about 0.88, and the root-mean-square error is about 0.15. Due to the high resolution of retrieved results, more detailed features can be provided in the spatial distribution. The experimental results show that the method has high precision, and further verification work is continuing. [ABSTRACT FROM AUTHOR]

This paper presents a three-dimensional variational (3DVAR) data assimilation (DA) system for aerosol optical properties, including aerosol optical thickness (AOT) retrievals and lidar-based aerosol profiles, developed for the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) within the Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) model. For computational efficiency, 32 model variables in the MOSAIC_4bin scheme are lumped into 20 aerosol state variables that are representative of mass concentrations in the DA system. To directly assimilate aerosol optical properties, an observation operator based on the Mie scattering theory was employed, which was obtained by simplifying the optical module in WRF-Chem. The tangent linear (TL) and adjoint (AD) operators were then established and passed the TL/AD sensitivity test. The Himawari-8 derived AOT data were assimilated to validate the system and investigate the effects of assimilation on both AOT and PM 2.5 simulations. Two comparative experiments were performed with a cycle of 24 h from 23 to 29 November 2018, during which a heavy air pollution event occurred in northern China. The DA performances of the model simulation were evaluated against independent aerosol observations, including the Aerosol Robotic Network (AERONET) AOT and surface PM 2.5 measurements. The results show that Himawari-8 AOT assimilation can significantly improve model AOT analyses and forecasts. Generally, the control experiments without assimilation seriously underestimated AOTs compared with observed values and were therefore unable to describe real aerosol pollution. The analysis fields closer to observations improved AOT simulations, indicating that the system successfully assimilated AOT observations into the model. In terms of statistical metrics, assimilating Himawari-8 AOTs only limitedly improved PM 2.5 analyses in the inner simulation domain (D02); however, the positive effect can last for over 24 h. Assimilation effectively enlarged the underestimated PM 2.5 concentrations to be closer to the real distribution in northern China, which is of great value for studying heavy air pollution events. [ABSTRACT FROM AUTHOR]

Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration (NOAA) satellites can provide over 40 years of global remote sensing observations, which can be used to retrieve long-term aerosol optical depth (AOD). This is of great significance to the study of global climate change. In this paper, we proposed an algorithm to jointly calculate AOD and land surface properties from AVHRR observations. With assumptions that AOD doesn't vary in adjacent space and earth surface property doesn't vary in two days, the algorithm considered non-Lambertian surface reflection based on the shape of bidirectional reflectance distribution function (BRDF shape) and obtained AOD and surface property by optimal estimation (OE) method. The algorithm has been applied to NOAA-7, 9, 11, 14, 16, 18, and 19 satellites and AVHRR-retrieved AOD with 5 × 10 km over China (15°–60° N, 70°–140°E) has been obtained from 1982 to 2016. Comparisons of AVHRR-retrieved AOD against AErosol RObotic NETwork (AERONET) (in and around China) and China Aerosol Remote Sensing Network (CARSNET) AOD show good consistency with 62.62% points within the uncertainty of Δτ = ± (0.05 + 0.25τ) and root-mean-square error (RMSE) of 0.26. Further comparison of the monthly mean AOD of multiple AOD datasets in the 'Beijing', 'Dalanzadgad', 'NCU_Taiwan' and 'Kanpur' stations shows that the results of the algorithm are stable. The yearly averaged AOD data also has similar agreements with MERRA-2 (The Modern-Era Retrospective analysis for Research and Applications, Version 2) and AVHRRDB data (AVHRR 'Deep Blue' aerosol data set). The multi-year mean correlation coefficient is 0.70 and 0.61 and the percentages within the uncertainty are 80.01% and 67.29% compared with MERRA-2 AOD and AVHRRDB AOD respectively. [ABSTRACT FROM AUTHOR]

This study estimates the health risk due to PM 2.5 and ADE primarily in 4 regions across Northern Hemisphere during 2013-2017. Mortality in China due to PM 2.5 dipped from 1.15 million (95%CI (Confidence Interval) 0.64-1.6 million) to 1.02 million (95%CI 0.59-1.49 million) during 2013-2017 as a result of reduction in PM 2.5 population weighted concentration (PWC) from 29.26 μg/m 3 to 22.05 μg/m 3 while India overtook China in terms of death due to PM 2.5 which increased to 1.16 million (95%CI 0.72-1.67 million) from 1.07 million (95%CI 0.62-1.53 million) as a result of increase in PWC from 38.18 to 44.47 μg/m 3 . The years of life lost per person (YLL/person) due to PM 2.5 was still observed to be high in China with 5.58 YLL/person followed by India (4.13), Europe (2.19) and US (0.46) in 2017. Aerosols such as PM 2.5 have the capability to scatter or absorb solar radiation resulting in perturbation of ground meteorology which further affects dispersion of pollutants and it's resultant health impacts. ADE resulted in 7.27% of total or 77,866 deaths in India during 2013 which increased to 8.05% or 93,575 deaths in 2017 which was highest among all regions while in China ADE deaths reduced from 59,529 (5.15% of total) to 40,470 (3.94% of total) deaths during the same period, other regions too reported reduction in ADE deaths with US reporting 906 (-1.27%) lower deaths while Europe also reported 785 (-0.46%) lower deaths in 2017 as compared to 2013. ADE resulted in increased YLL/person in India from 0.29 to 0.33 during 2013-2017 while it was observed to reduce in all other regions, in China it reduced from 0.37 to 0.22 likewise YLL/person also reduced in US from 0.04 to 0.01 and in Europe from 0.01 to 0.002., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

With a large population and fast economic growth, the Sichuan Basin (SCB) has been suffering from air pollution in recent years. However, limited studies have estimated air pollution levels in consideration of the feedbacks of aerosols on meteorology in the SCB. In this study, simulation of fine particulate matter (PM 2.5 ) and ozone (O 3 ) over the SCB with a horizontal resolution of 36 km over China and 12 km was conducted for summer (July) and winter (January) in 2015 using the Weather Research and Forecasting model coupled with Chemistry (WRF/Chem). The model well captured the variations of PM 2.5 and daily maximum 8 h average (MDA8) O 3 in the 18 cities, especially O 3 in July and PM 2.5 in January. From rim to center, averaged PM 2.5 increased from 40 μg/m 3 to 100 μg/m 3 in January while averaged O 3 ranged from 60 to 90 ppb in July. Aerosol radiation decreased surface temperature by 1-2 °C, wind speed (WS) by ∼ 0.3 m/s, planetary boundary layer (PBL) height by 10-20%, solar radiation (SR) by ∼30%, and precipitation by 0.02-0.2 mm, while increased relative humidity (RH) by up to 2-4% in January, which resulted in up to 10 μg/m 3 increase of PM 2.5 in January and 2 ppb decrease of O 3 in July. The effect increased as the increase of PM 2.5 concentration and can be up to 18% in January and 25% in July. This study highlights the importance of considering meteorology feedbacks in understanding and controlling air pollution in the SCB., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Hygroscopicity largely determines phase state, chemical reactivity, optical properties, and cloud nucleation activities of aerosol particles, thus significantly affecting their impacts on visibility, atmospheric chemistry, and climate. In the last 20 years, a large number of field studies have investigated the hygroscopicity of tropospheric aerosols in China under subsaturated and supersaturated conditions. Aerosol hygroscopicity measurements in China are reviewed in this paper: (1) a comprehensive summary and critical discussion of aerosol hygroscopicity measurements in China are provided; (2) available measurement data are compiled and presented under a consistent framework to enhance their accessibility and usability; and (3) current knowledge gaps are identified, and an outlook which could serve as guidelines for planning future research is also proposed. [ABSTRACT FROM AUTHOR]

Topic 3 of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III examines how online coupled air quality models perform in simulating wintertime haze events in the North China Plain region and evaluates the importance of aerosol radiative feedbacks. This paper discusses the estimates of aerosol radiative forcing, aerosol feedbacks, and possible causes for the differences among the participating models. Over the Beijing–Tianjin–Hebei (BTH) region, the ensemble mean of estimated aerosol direct radiative forcing (ADRF) at the top of atmosphere, inside the atmosphere, and at the surface are -1.1 , 7.7, and -8.8 W m -2 during January 2010, respectively. Subdivisions of direct and indirect aerosol radiative forcing confirm the dominant role of direct forcing. During severe haze days (17–19 January 2010), the averaged reduction in near-surface temperature for the BTH region can reach 0.3–1.6 ∘ C. The responses of wind speeds at 10 m (WS10) inferred from different models show consistent declines in eastern China. For the BTH region, aerosol–radiation feedback-induced daytime changes in PM 2.5 concentrations during severe haze days range from 6.0 to 12.9 µ g m -3 (<6 %). Sensitivity simulations indicate the important effect of aerosol mixing states on the estimates of ADRF and aerosol feedbacks. Besides, black carbon (BC) exhibits a large contribution to atmospheric heating and feedbacks although it accounts for a small share of mass concentration of PM 2.5. [ABSTRACT FROM AUTHOR]

In the context of global warming, the future spatiotemporal distribution of aerosols in China is a common concern of the government and the scientific community. In this study, the regional climate model RegCM4 is used to simulate the spatiotemporal distribution of anthropogenic aerosols including sulfate, black carbon, and organic carbon in China around 2030 under the RCP4.5 and RCP8.5 scenarios and estimate the contributions of climate difference, emission difference, and extra-regional transport difference to the change of anthropogenic aerosol concentration in the study area. The results show that the annual average concentrations of anthropogenic aerosols around 2030 decreased significantly with respect to those around 2010, and the decrease amplitude of black carbon surface concentration is the smallest, especially in the RCP8.5 scenario. The annual averages for sulfate, black carbon, and organic carbon surface concentrations in the central and eastern parts of China will be 8.5, 1.7, and 3.7 μg m−3, respectively, under the RCP4.5 scenario, whereas 10.0, 2.2, and 4.4 μg m−3, respectively, under the RCP8.5 scenario. The surface concentration of sulfate is higher in summer and spring, while lower in winter and autumn. The surface concentrations of black carbon and organic carbon are higher in winter and lower in other seasons. The results of sensitivity experiments demonstrate that the future difference in local emissions between RCP8.5 and RCP4.5 scenarios has the greatest impact on the anthropogenic aerosol concentrations throughout China, while the effects of future climate difference and extra-regional transport difference are much smaller around 2030. For the aerosol column burdens, the effect of future local emission difference between the two scenarios is still dominant, and the effect of extra-regional transport difference becomes very significant during spring and winter for organic carbon and black carbon. The results of this paper suggest that the impacts of future climate difference and extra-regional transport difference between RCP8.5 and RCP4.5 scenarios on anthropogenic aerosols are non-negligible in certain regions and seasons besides the impact of future local emission difference in China around 2030. [ABSTRACT FROM AUTHOR]

The Huaihai Economic Region (HER, 32.5–36.5°N, 114–121°E) with a land area of 178,000 km2, which contains 20 cities, is one of the earliest regional economic cooperative organizations in China. The huge population (100 million, about 7% of the China's population), local heavy industries, chemical enterprises and vehicle emissions have resulted in serious air pollution. In this paper, a long-term aerosol optical depth (AOD) data set from 2000 to 2018 over HER with 10 km spatial resolution has been produced and analyzed from the latest version of MODIS (MODerate resolution Imaging Spectroradiometer) aerosol products. Validation results show that MODIS AOD has a strong correlation relationship (r = 0.94, slope = 0.92) with Aeronet Robotic Network (AERONET) over HER. The seasonal average AOD maps indicate that the high AOD values mainly occurred with a banding distribution from southeastern to northwestern HER, with AODs larger in summer and spring than in fall and winter. Temporally, the monthly average AOD has increased since 2000 and reached the highest level in 2011 (+0.02/year); then it has obviously declined from 2012 to 2018 (−0.05/year), owing to strict air pollution control implemented since 2012. In general, the annual average AOD over HER is 0.71 for the past nearly 20 years, and in 2018, the annual average AOD firstly lower than that in 2000. The study suggests that there has been a slightly improvement in air quality over HER and long-term and sustainable efforts should be made. [ABSTRACT FROM AUTHOR]

The refractive index of ambient aerosols, which directly determines the aerosol optical properties, is widely used in atmospheric models and remote sensing. Traditionally, the real part of the refractive index (RRI) is parameterized by the measurement of ambient aerosol main inorganic components. In this paper, the characteristics of the ambient aerosol RRI are studied based on field measurements in East China. The results show that the measured ambient aerosol RRI varies significantly between 1.36 and 1.56. The direct aerosol radiative forcing is estimated to vary by 40 % when the RRI values were varied between 1.36 and 1.56. We find that the ambient aerosol RRI is highly correlated with the aerosol effective density (ρeff) rather than the main chemical components. However, the parameterization of the ambient aerosol RRI by ρeff is not available due to the lack of corresponding simultaneous field measurements. For the first time, the size-resolved ambient aerosol RRI and ρeff are measured simultaneously by our designed measurement system. A new parameterization scheme for the ambient aerosol RRI using ρeff is proposed for urban environments. The measured and parameterized RRI values agree well, with a correlation coefficient of 0.75 and slope of 0.99. Knowledge of the ambient aerosol RRI would improve our understanding of ambient aerosol radiative effects. [ABSTRACT FROM AUTHOR]

This study investigated the potential effects of changes in inorganics on aerosol water uptake and, thus, on secondary organic aerosol (SOA) formation in wintertime haze based on the size-resolved measurements of non-refractory fine particulate matter (NR-PM 2.5) in Xi'an, northwestern China. The composition of inorganic aerosol showed significant changes in winter 2018–2019 compared to winter 2013–2014, shifting from a sulfate-rich profile to a nitrate-rich profile. In particular, the fraction of sulfate and chloride decreased, but that of nitrate increased in the entire size range, while ammonium mainly increased at larger particle sizes. These changes thus resulted in a size-dependent evolution in water uptake. Increased water uptake was observed in most cases, mainly associated with enhanced contributions of both nitrate and ammonium, with the highest increase ratio reaching 5 %–35 % at larger particle sizes and higher relative humidity (RH>70 %). The non-negligible influence of chloride on aerosol water uptake was also emphasized. The random forest analysis coupled with a Shapley additive explanation algorithm (SHAP) further showed an enhanced relative importance of aerosol water in impacting SOA formation. Aerosol water exhibited a significant contribution to SOA formation during winter 2018–2019, particularly at larger particle sizes. The SHAP value of aerosol water increased alongside higher levels of aerosol water, indicating an enhanced contribution of aerosol water to SOA formation. This implies that the majority of enhanced aerosol water uptake at larger particle sizes and high RH might facilitate the efficient aqueous-phase SOA formation. This study highlights the key role of aerosol water as a medium to link inorganics and organics in their multiphase processes. As challenges to further improve China's air quality remain and because SOA plays an increasing role in haze pollution, these results provide insight into the size-resolved evolution characteristics and offer guidance for future controls. [ABSTRACT FROM AUTHOR]

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A new multiangle implementation of the atmospheric correction (MAIAC) algorithm has been applied in the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and has recently provided globally high-spatial-resolution aerosol optical depth (AOD) products at 1 km. Moreover, several improvements have been modified in the classical Dark Target (DT) and Deep Blue (DB) aerosol retrieval algorithms in MODIS Collection 6.1 products. Thus, validation and comparison of the MAIAC, DT, and DB algorithms are urgent in China. In this paper, we present a comprehensive assessment and comparison of AOD products at a 550 nm wavelength based on three aerosol retrieval algorithms in the MODIS sensor using ground-truth measurements from AErosol RObotic NETwork (AERONET) sites over China from 2000 to 2017. In general, MAIAC products achieved better accuracy than DT and DB products in the overall validation and accuracy improvement of DB products after the QA filter, demonstrating the highest values among the three products. In addition, the DT algorithms had higher aerosol retrievals in cropland, forest, and ocean land types than the other two products, and the MAIAC algorithms were more accurate in grassland, built-up, unoccupied, and mixed land types among the three products. In the geometry dependency analysis, the solar zenith angle, scattering angle, and relative azimuth angle, excluding the view zenith angle, significantly affected the performance of the three aerosol retrieval algorithms. The three products showed different accuracies with varying regions and seasons. Similar spatial patterns were found for the three products, but the MAIAC retrievals were smaller in the North China Plain and higher in Yunnan Province compared with the DT and DB retrievals before the QA filter. After the QA filter, the DB retrievals were significantly lower than the MAIAC retrievals in south China. Moreover, the spatiotemporal completeness of the MAIAC product was also better than the DT and DB products. [ABSTRACT FROM AUTHOR]

Aerosol types have crucial and distinguished impacts on climate effects and cause the difference of air pollution. However, direct retrieval of aerosol type by satellite remote sensing is difficult, and the satellite products of aerosol type are seriously lacking. At present, the identification of aerosol type is mainly based on ground-based observation data, but the coverage area of ground-based stations is limited, and large-scale spatial continuous monitoring cannot be carried out. The existing aerosol type identification methods based on satellite data need to combine multiple satellites data (e.g. Moderate-resolution Imaging Spectroradiometer (MODIS), Ozone Monitoring Instrument (OMI), etc.) which leads to a low temporal resolution. The research about aerosol type identification only based on geostationary satellite data is lacking. Therefore, aerosol type identification based on the multi-parameter threshold method and the neural network method are proposed and compared in this paper. The neural network jointly using spectral and temporal information was trained and tested by the measurements from 26 sites of Aerosol Robotic Network (AERONET) and Sun-Sky Radiometer Observation Network (SONET). For the overall validation, the aerosol type identification based on the neural network is better than that based on the multi-parameter threshold method, and the accuracy reaches 71.44%. Atmospheric environment monitoring and quantitative remote sensing can be supported by this study. • Aerosol type, neural network, geostationary satellite [ABSTRACT FROM AUTHOR]

The Equilibrium Simplified Aerosol Model for Climate version 12 (EQSAM4Clim-v12) has recently been revised to provide an accurate and efficient method for calculating the acidity of atmospheric particles. EQSAM4Clim is based on an analytical concept that is not only sufficiently fast for chemical weather prediction applications but also free of numerical noise, which also makes it attractive for air quality forecasting. EQSAM4Clim allows the calculation of aerosol composition based on the gas–liquid–solid and the reduced gas–liquid partitioning with the associated water uptake for both cases and can therefore provide important information about the acidity of the aerosols. Here we provide a comprehensive description of the recent changes made to the aerosol acidity parameterization (referred to as a version 12) which builds on the original EQSAM4Clim. We evaluate the pH improvements using a detailed box model and compare them against previous model calculations and both ground-based and aircraft observations from the USA and China, covering different seasons and scenarios. We show that, in most cases, the simulated pH is within reasonable agreement with the reference results of the Extended Aerosol Inorganics Model (E-AIM) and of satisfactory accuracy. [ABSTRACT FROM AUTHOR]

Naphthalene (Nap) and its derivatives, including 1-methylnaphthalene (1-MN) and 2-methylnaphthalene (2-MN), serve as prominent intermediate volatile organic compounds (IVOCs) and contribute to the formation of secondary organic aerosol (SOA). In this study, the Community Multiscale Air Quality (CMAQ) model coupled with detailed emissions and reactions of these compounds was utilized to examine their roles in the formation of SOA and other secondary pollutants in the Yangtze River Delta (YRD) region during summer. Significant underestimations of Nap and MN concentrations (by 79 % and 85 %) were observed at the Taizhou site based on the model results using the default emissions. Constrained by the observations, anthropogenic emissions of Nap and MN in the entire region were multiplied by 5 and 7, respectively, to better capture the evolution of pollutants. The average concentration of Nap reached 25 ppt (parts per trillion) in the YRD, with Nap contributing 4.1 % and 8.1 % (up to 12.6 %) of total aromatic emissions and aromatic-derived secondary organic carbon (SOC), respectively. The concentrations of 1-MN and 2-MN were relatively low, averaging 2 and 5 ppt, respectively. Together, they accounted for only 2.4 % of the aromatic-derived SOC. The impacts of Nap and MN oxidation on ozone and radicals were insignificant at regional scales but were not negligible when considering daily fluctuations in locations with high emissions of Nap and MN. This study highlights the significant roles of Nap and MN in the formation of SOA, which may pose environmental risks and result in adverse health effects. [ABSTRACT FROM AUTHOR]

While aqueous-phase processing is known to contribute to the formation of nitrogen-containing organic compounds (NOCs), the specific pathways involved remain poorly understood. In this study, we aimed to characterize the NOCs present in both pre-fog aerosols and fog water collected at a suburban site in northern China. Fourier-transform ion cyclotron resonance mass spectrometry was utilized to analyze the molecular composition of NOCs in both negative and positive modes of electrospray ionization (ESI - and ESI +). In both pre-fog aerosols and fog water samples, NOCs constituted a significant portion, accounting for over 60 % of all assigned formulas in ESI - and more than 80 % in ESI +. By comparing the molecular composition of NOCs originating from biomass burning, coal combustion, and vehicle emissions, we identified that 72.3 % of NOCs in pre-fog aerosols were attributed to primary anthropogenic sources (pNOCs), while the remaining NOCs were categorized as secondary NOCs formed within the aerosols (saNOCs). Unique NOCs found in fog water were classified as secondary NOCs formed within the fog water (sfNOCs). Through a comprehensive "precursor–product pair" screening involving 39 reaction pathways, we observed that the nitration reaction, the amine pathway, and the intramolecular N-heterocycle pathway of NH 3 addition reactions contributed 43.6 %, 22.1 %, and 11.6 % of saNOCs, respectively. In contrast, these pathways contributed 26.8 %, 28.4 %, and 29.7 % of sfNOCs, respectively. This disparity in formation pathways is likely influenced by the diverse precursors, the aqueous acidity, and the gas-phase species partitioning. Correspondingly, saNOCs were found to contain a higher abundance of carbohydrate-like and highly oxygenated compounds with two nitrogen atoms compared to pNOCs. Conversely, sfNOCs exhibited a higher content of lipid-like compounds with fewer oxygen atoms. These results underscore the distinct secondary processes contributing to the diversity of NOCs in aerosols and fog water, which may lead to their different climate effects. [ABSTRACT FROM AUTHOR]

Photocatalytic reactions during the daytime, alongside aqueous-phase reactions occurring during both daytime and nighttime, are identified as the two primary processes facilitating the conversion of aerosol iron (Fe) from the insoluble state to the soluble state within the atmospheric environment. This study investigated the levels of total Fe (Fe T) and soluble Fe (Fe S) in PM 2.5 samples collected during daytime and nighttime in Qingdao, a coastal city in eastern China, evaluating the distinctive roles of these two pathways in enhancing aerosol Fe solubility (%Fe S , defined as the ratio of Fe S to Fe T). Under clean and humid conditions, characterized by prevailing sea breezes and a relative humidity (RH) typically above 80 %, an average daytime %Fe S of 8.7 % was observed, which systematically exceeded the nighttime %Fe S (6.3 %). Photochemical conversions involving oxalate contributed to the higher %Fe S observed during daytime. Conversely, in scenarios where air masses originated from inland areas and exhibited slightly polluted, daytime %Fe S (3.7 %) was noted to be lower than the nighttime %Fe S (5.8 %). This discrepancy was attributable to the variations in RH, with nighttime RH averaging around 77 %, conducive to the more efficient generation of acidic compounds, thereby accelerating Fe S production compared to the daytime, when RH was only about 62 %. Furthermore, the oxidation rates of sulfur (SOR) displayed a strong correlation with RH, particularly when RH fell below 75 %. A 10 % increase in RH corresponded to a 7.6 % rise in SOR, which served as the primary driver of the higher aerosol acidity and %Fe S at night. These findings highlight the RH-dependent activation of aqueous-phase reactions and the augmentation of daytime photocatalysis in the formation of Fe S in the coastal moist atmosphere. [ABSTRACT FROM AUTHOR]

To investigate the optical characteristics and sources of brown carbon (BrC) in North China, where the atmospheric aerosol loadings are high and have severe impacts on Earth's climate system, we collected fine aerosols (PM 2.5) at an urban site in Tianjin over a 1-year period. We measured the ultraviolet (UV) light absorption and excitation emission matrix (EEM) fluorescence of the water-soluble BrC (WSBrC) and the water-insoluble but methanol-soluble BrC (WI-MSBrC) in the PM 2.5 using a three-dimensional fluorescence spectrometer. The average light absorption efficiency of both WSBrC (Abs365, WSBrC) and WI-MSBrC (Abs365, WI-MSBrC) at 365 nm was found to be highest in winter (10.4 ± 6.76 and 10.0 ± 5.13 Mm-1 , respectively) and distinct from season to season. The averages of the fluorescence index (FI) and the biological index (BIX) of WSBrC were lower in summer than in the other seasons and opposite to that of the humification index (HIX), which implied that the secondary formation and further chemical processing of aerosols were more intensive during the summer period than in the other seasons. However, in winter, the higher HIX together with the higher FI and BIX of WI-MSBrC suggested that the BrC loading was mainly influenced by primary emissions from biomass burning and coal combustion. Based on the EEM, the types of fluorophores in WSBrC were divided into humic-like substances (HULIS), including low-oxygenated and high-oxygenated species and protein-like compounds (PLOM), though mostly PLOM in the WI-MSBrC. The direct radiation absorption by both WSBrC and WI-MSBrC in the range of 300–400 nm accounted for ∼ 40 % of that (SFEAbs , 4.97 ± 2.71 and 7.58 ± 5.75 Wg-1 , respectively) in the range 300–700 nm. [ABSTRACT FROM AUTHOR]

Atmospheric visibility profoundly impacts daily life, and accurate prediction is crucial, particularly in conditions of low visibility characterized by high aerosol loading and humidity. This study employed the WRF‐Chem model to simulate a severe wintertime haze pollution episode that transpired from January 17 to 19, 2010, in Central‐East China (112–122° E, 34–42° N). The results reveal that excluding aerosol–meteorology interactions led to underestimated PM2.5 concentrations and relative humidity in comparison with ground‐based measurement data, accompanied by a significant overestimation of visibility. Aerosols can engage with meteorological elements, particularly humidity, resulting in positive feedback. Upon considering these feedback interactions, the simulation results showed an increase of 5.17% and 1.99% in PM2.5 concentration and relative humidity, respectively, compared with the original simulation. This adjustment narrowed the bias between simulated and measured data. The overestimation of simulated visibility was reduced by 16% and 25% for the entire study period and the severe haze pollution period, respectively. These findings underscore the vital role of incorporating aerosol–meteorology interactions in visibility simulations using the WRF‐Chem model. Notably, the inclusion of aerosol–meteorological feedback significantly enhances the accuracy of visibility predictions, particularly during heavily polluted periods. [ABSTRACT FROM AUTHOR]

The Long-term Gap-free High-resolution Air Pollutants (LGHAP) concentration dataset generated in our previous study has provided spatially contiguous daily aerosol optical depth (AOD) and fine particulate matter (PM 2.5) concentrations at a 1 km grid resolution in China since 2000. This advancement empowered unprecedented assessments of regional aerosol variations and their influence on the environment, health, and climate over the past 20 years. However, there is a need to enhance such a high-quality AOD and PM 2.5 concentration dataset with new robust features and extended spatial coverage. In this study, we present version 2 of a global-scale LGHAP dataset (LGHAP v2), which was generated using improved big Earth data analytics via a seamless integration of versatile data science, pattern recognition, and machine learning methods. Specifically, multimodal AODs and air quality measurements acquired from relevant satellites, ground monitoring stations, and numerical models were harmonized by harnessing the capability of random-forest-based data-driven models. Subsequently, an improved tensor-flow-based AOD reconstruction algorithm was developed to weave the harmonized multisource AOD products together for filling data gaps in Multi-Angle Implementation of Atmospheric Correction (MAIAC) AOD retrievals from Terra. The results of the ablation experiments demonstrated better performance of the improved tensor-flow-based gap-filling method in terms of both convergence speed and data accuracy. Ground-based validation results indicated good data accuracy of this global gap-free AOD dataset, with a correlation coefficient (R) of 0.85 and a root mean square error (RMSE) of 0.14 compared to the worldwide AOD observations from the AErosol RObotic NETwork (AERONET), outperforming the purely reconstructed AODs (R = 0.83, RMSE = 0.15), but they were slightly worse than raw MAIAC AOD retrievals (R = 0.88, RMSE = 0.11). For PM 2.5 concentration mapping, a novel deep-learning approach, termed the SCene-Aware ensemble learning Graph ATtention network (SCAGAT), was hereby applied. While accounting for the scene representativeness of data-driven models across regions, the SCAGAT algorithm performed better during spatial extrapolation, largely reducing modeling biases over regions with limited and/or even absent in situ PM 2.5 concentration measurements. The validation results indicated that the gap-free PM 2.5 concentration estimates exhibit higher prediction accuracies, with an R of 0.95 and an RMSE of 5.7 µg m -3 , compared to PM 2.5 concentration measurements obtained from former holdout sites worldwide. Overall, while leveraging state-of-the-art methods in data science and artificial intelligence, a quality-enhanced LGHAP v2 dataset was generated through big Earth data analytics by cohesively weaving together multimodal AODs and air quality measurements from diverse sources. The gap-free, high-resolution, and global coverage merits render the LGHAP v2 dataset an invaluable database for advancing aerosol- and haze-related studies as well as triggering multidisciplinary applications for environmental management, health-risk assessment, and climate change attribution. All gap-free AOD and PM 2.5 concentration grids in the LGHAP v2 dataset, as well as the data user guide and relevant visualization codes, are publicly accessible at https://zenodo.org/communities/ecnu%5flghap (last access: 3 April 2024, Bai and Li, 2023a). [ABSTRACT FROM AUTHOR]

Over the past three decades, China has seen aerosol levels substantially surpass the global average, significantly impacting regional climate. This study investigates the long-term and seasonal variations of aerosols in the Huai River Basin (HRB) using MODIS, CALIOP observations from 2007 to 2021, and ground-based measurements. A notable finding is a significant decline in the annual mean Aerosol Optical Depth (AOD) across the HRB, with MODIS showing a decrease of approximately 0.023 to 0.027 per year, while CALIOP, which misses thin aerosol layers, recorded a decrease of about 0.016 per year. This downward trend is corroborated by improvements in air quality, as evidenced by PM2.5 measurements and visibility-based aerosol extinction coefficients. Aerosol decreases occurred at all heights, but for aerosols below 800 m, with an annual AOD decrease of 0.011. The study also quantifies the long-term trends of five major aerosol types, identifying Polluted Dust (PD) as the predominant frequency type (46%), which has significantly decreased, contributing to about 68% of the total AOD reduction observed by CALIOP (0.011 per year). Despite this, Dust and Polluted Continental (PC) aerosols persist, with PC showing no clear trend of decrease. Seasonal analysis reveals aerosol peaks in summer, contrary to surface measurements, attributed to variations in the Boundary Layer (BL) depth, affecting aerosol distribution and extinction. Furthermore, the study explores the influence of seasonal wind patterns on aerosol type variation, noting that shifts in wind direction contribute to the observed changes in aerosol types, particularly affecting Dust and PD occurrences. The integration of satellite and ground measurements provides a comprehensive view of regional aerosol properties, highlighting the effectiveness of China's environmental policies in aerosol reduction. Nonetheless, the persistence of high PD and PC levels underscores the need for continued efforts to reduce both primary and secondary aerosol production to further enhance regional air quality. [ABSTRACT FROM AUTHOR]

Secondary organic aerosols (SOAs) can exist in liquid, semi-solid, or amorphous solid states. Chemical transport models (CTMs), however, usually assume that SOA particles are homogeneous and well-mixed liquids, with rapid establishment of gas–particle equilibrium for simulations of SOA formation and partitioning. Missing the information of SOA phase state and viscosity in CTMs impedes accurate representation of SOA formation and evolution, affecting the predictions of aerosol effects on air quality and climate. We have previously developed a parameterization to estimate the glass transition temperature (Tg) of an organic compound based on volatility and to predict viscosity of SOA. In this study, we apply this method to predict the phase state of SOA particles over China in summer of 2018 using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). The simulated Tg of dry SOA (Tg,org) agrees well with the value estimated from ambient volatility measurements at an urban site in Beijing. For the spatial distributions of Tg,org , simulations show that at the surface the values of Tg,org range from ∼287 to 305 K, with higher values in northwestern China, where SOA particles have larger mass fractions of low-volatility compounds. Considering water uptake by SOA particles, the SOA viscosity shows a prominent geospatial gradient in which highly viscous or solid SOA particles are mainly predicted in northwestern China. The lowest and highest SOA viscosity values both occur over the Qinghai–Tibet Plateau, where the solid phase state is predicted over dry and high-altitude areas and the liquid phase state is predicted mainly in the south of the plateau with high relative humidity during the summer monsoon season. Sensitivity simulations show that, including the formation of extremely low-volatility organic compounds, the percent time that a SOA particle is in the liquid phase state decreases by up to 12 % in southeastern China during the simulated period. With an assumption that the organic and inorganic compounds are internally mixed in one phase, we show that the water absorbed by inorganic species can significantly lower the simulated viscosity over southeastern China. This indicates that constraining the uncertainties in simulated SOA volatility distributions and the mixing state of the organic and inorganic compounds would improve prediction of viscosity in multicomponent particles in southeastern China. We also calculate the characteristic mixing timescale of organic molecules in 200 m SOA particles to evaluate kinetic limitations in SOA partitioning. Calculations show that during the simulated period the percent time of the mixing timescale longer than 1 h is >70 % at the surface and at 500 hPa in most areas of northern China, indicating that kinetic partitioning considering the bulk diffusion in viscous particles may be required for more accurate prediction of SOA mass concentrations and size distributions over these areas. [ABSTRACT FROM AUTHOR]

The sensitivity (S) of cloud parameters to the influence of different aerosol and meteorological parameters has in most previous aerosol–cloud interaction (aci) studies been addressed using traditional statistical methods. In the current study, relationships between cloud droplet effective radius (CER) and aerosol optical depth (AOD, used as a proxy for cloud condensation nuclei, CCN), i.e., the sensitivity (S) of CER to AOD, are investigated with different constraints of AOD and cloud liquid water path (LWP). In addition to traditional statistical methods, the geographical detector method (GDM) is applied in this study to quantify the relative importance of the effects of aerosol and meteorological parameters, as well as their interaction, on S. Moderate Resolution Imaging Spectroradiometer (MODIS) C6 L3 data and European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-5 reanalysis data, for the period from 2008 to 2022, were used to investigate aci over eastern China. Two contrasting areas were selected: the heavily polluted Yangtze River Delta (YRD) and a relatively clean area over the East China Sea (ECS). Linear regression analysis shows that CER decreases with the increase in AOD (negative S) in the moderately polluted atmosphere (0.10.3) over the YRD. Evaluation of S as function of the LWP shows that in the moderately polluted atmosphere over the ECS, S is negative in the LWP interval [40 gm-2 , 200 gm-2 ], and the sensitivity of CER to AOD is substantially stronger as LWP is larger. In contrast, in the polluted atmosphere over the YRD, S is positive in the LWP interval [0 gm-2 , 120 gm-2 ] and does not change notably as function of LWP in this interval. The study further shows that over the ECS, the CER is larger for higher low tropospheric stability (LTS) and relative humidity (RH) but lower for higher pressure vertical velocity (PVV). Over the YRD, there is no significant influence of LTS on the relationship between CER and AOD. The GDM has been used as an independent method to analyze the sensitivity of cloud parameters to AOD and meteorological parameters (RH, LTS and PVV). The GDM has also been used to analyze the effects of interactions between two parameters and thus obtain information on confounding meteorological effects on the aci. Over the ECS, cloud parameters are sensitive to almost all parameters considered except for cloud top pressure (CTP), and the sensitivity to AOD is larger than that to any of the meteorological factors. Among the meteorological factors, the cloud parameters are most sensitive to PVV and least sensitive to RH. Over the YRD, the explanatory power of the sensitivity of cloud parameters to AOD and meteorological parameters is much smaller than over the ECS, except for RH, which has a statistically significant influence on CTP and can explain 74 % of the variation of CTP. The results from the GDM analysis show that cloud parameters are more sensitive to the combination of aerosol and a meteorological parameter than to each parameter alone, but confounding effects due to co-variation of both parameters cannot be excluded. [ABSTRACT FROM AUTHOR]

The aerosol–cloud–precipitation correlation has been a significant scientific topic, primarily due to its remarkable uncertainty. However, the possible modulation of aerosol on the precipitation capacity of clouds has received limited attention. In this study, we utilized multi-source data on aerosol, cloud properties, precipitation, and meteorological factors to investigate the impact of aerosols on precipitation efficiency (PE) in the Sichuan Basin (SCB) and Yun-nan-Guizhou Plateau (YGP), where the differences between terrain and meteorological environment conditions were prominent. In the two study regions, there were significant negative correlations between the aerosol index (AI) and PE in spring, especially in the YGP, while the correlations between the AI and PE in other seasons were not as prominent as in spring. In spring, aerosol significantly inhibited both the liquid water path (LWP) and the ice water path (IWP) in the YGP, but negatively correlated with the IWP and had no significant relationship with the LWP in the SCB. Aerosol inhibited precipitation in the two regions mainly by reducing cloud droplet effective radius, indicating that warm clouds contributed more to precipitation in spring. The suppressive impact of aerosols on precipitation serving as the numerator of PE is greater than that of the cloud water path as the denominator of PE, resulting in a negative correlation between aerosol and PE. The AI–PE relationship is significantly dependent on meteorological conditions in the YGP, but not in the SCB, which may be related to the perennial cloud cover and stable atmosphere in the SCB. In the future, as air quality continues to improve, precipitation efficiency may increase due to the decrease in aerosol concentration, and of course, the spatio-temporal heterogeneity of the aerosol–cloud–precipitation relationship may become more significant. [ABSTRACT FROM AUTHOR]

Black carbon (BC) aerosols have a considerable impact on humans because they not only cause environmental pollution and reduce visibility but also harm human health. During the heating season in northern China, a large amount of coal is burned for heating, producing a large amount of BC. There are few studies on BC properties during the heating season. In this paper, BC is measured optically, so it is referred to as equivalent black carbon (EBC). This paper investigated EBC properties in depth during the heating and nonheating seasons of a typical urban environment in China with two years of EBC measurements. The results show that: (1) EBC aerosol concentrations during the heating season were significantly higher than those during the nonheating season. (2) The main sources of EBC aerosols throughout the year are liquid sources. During the heating season, solid sources (coal and biomass combustion) are dominant. (3) The proportion of brown carbon (BrC) produced by biomass energy during the heating season is greater than that during the nonheating season. (4) The resulting backward trajectory indicates that a large portion of the high EBC aerosol concentration sources originate from northern and northwestern China. Our results reveal that the characteristics and sources of EBC in the urban environment of northern China vary widely, suggesting that different measures should be taken to reduce BC aerosol concentrations during heating and nonheating seasons. [ABSTRACT FROM AUTHOR]

This paper presents a three- dimensional variational (3DVAR) data assimilation (DA) system for aerosol optical properties, including aerosol optical depth (AOD) retrievals and lidar- based aerosol profiles, which was developed for the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) within the Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) model. For computational efficiency, 32 model variables in the MOSAIC_4bin scheme are lumped into 20 aerosol state variables that are representative of mass concentrations in the DA system. To directly assimilate aerosol optical properties, an observation operator based on the Mie scattering theory was employed, which was obtained by simplifying the optical module in WRF-Chem. The tangent linear (TL) and adjoint (AD) operators were then established and passed the TL/AD sensitivity test. The Himawari-8 derived aerosol optical thickness (AOT) data were assimilated to validate the system and investigate the effects of assimilation on both AOT and PM2.5 simulations. Two comparative experiments were performed with a cycle of 24 h from November 23 to 29, 2018, during which a heavy air pollution event occurred in North China. The DA performances of the model simulation were evaluated against independent aerosol observations, including the Aerosol Robotic Network (AERONET) AOT and surface PM2.5 measurements. The results show that Himawari-8 AOT assimilation can significantly improve model AOT analyses and forecasts. Generally, the control experiments without assimilation seriously underestimated AOTs compared with observed values and were therefore unable to describe real aerosol pollution. The analysis fields closer to observations improved AOT simulations, indicating that the system successfully assimilated AOT observations into the model. In terms of statistical metrics, assimilating Himawari-8 AOTs only limitedly improved PM2.5 analyses in the inner simulation domain (D02); however, the positive effect can last for over 24 h. Assimilation effectively enlarged the underestimated PM2.5 concentrations to be closer to the real distribution in North China, which is of great value for studying heavy air pollution events [ABSTRACT FROM AUTHOR]

A regional aerosol model can complement globally averaged models and improve the accuracy of atmospheric numerical models in local applications. This study established a seasonal aerosol model based on data from the Aerosol Robotic Network (AERONET) of the sea area around eastern China, and its performance in calculating the aerosol optical depth (AOD) was evaluated. The seasonal columnar volume particle size distributions (VPSDs) illustrated a bimodal structure consisting of fine and coarse modes. The VPSDs of spring, autumn, and winter roughly agreed with each other, with their amplitudes of fine and coarse modes being almost equal; however, the fine mode of the summer VPSD was approximately twice as high as that of the coarse mode. Lognormal mode decomposition analysis revealed that fine and coarse modes comprised two sub-modes. Fitting the seasonal VPSDs to the four-mode lognormal distribution yielded a parameterized aerosol size distribution model. Furthermore, seasonal variations in complex refractive indices (CRIs) indicated unignorable changes in aerosol compositions. Overall, error analysis validated that the proposed model could meet accuracy requirements for optical engineering applications, with median AOD calculation errors of less than 0.01. [ABSTRACT FROM AUTHOR]

Despite the long-term implementation of air pollution control policies in northeast China, severe haze pollution continues to occur frequently. With the adoption of a megacity (Changchun) in northeast China, we analysed the vertical characteristics of aerosols and the causes of aerosol pollution throughout the year using multisource data for providing recommendations for controlling pollution events (i.e., straw burning and fireworks). Based on a ground-based LiDAR, it was found that the extinction coefficient (EC) of aerosols at a height of 300 m in Changchun was highest in winter (0.44 km−1), followed by summer (0.28 km−1), with significant differences from those in warmer regions, such as the Yangtze River Delta. Therefore, it is recommended that air pollution control policies be differentiated between winter and summer. On Chinese New Year's Eve in Changchun, the ignition of firecrackers during the day and night caused increases in the EC at a height of 500 m to 0.37 and 0.88 km−1, respectively. It is suggested that the regulation of firecracker ignition should be reduced during the day and strengthened at night. Based on the CALIPSO and backward trajectory analysis results, two events of dust–biomass-burning composite pollution were observed in March and April. In March, the primary aerosol component was dust from western Changchun, whereas in April, the main aerosol component was biomass-burning aerosols originating from northern and eastern Changchun. Hence, reducing the intensity of spring biomass burning can mitigate the occurrence of dust–biomass-burning composite pollution. These findings can provide emission policy suggestions for areas facing similar issues regarding biomass-burning transmission pollution and firework emissions. [ABSTRACT FROM AUTHOR]

China's severe particle pollution could affect the regional climate and weather conditions that consequently threaten local to global food security. Yet, the underlying mechanisms and quantitative assessment of aerosols on crop yields remain unknown. Here, by integrating a meteorology–chemistry model and a crop model, we show the impacts of atmospheric aerosols on China's meteorology and soybean yields. We find that the potential yields of soybean would decrease in most parts of China due to direct aerosol radiation effects, while showing diverse responses in parts of the Northeast and North China Plain. Moreover, because of the high sensitivity of soybean growth to water, potential yield fluctuations are closely related to aerosol‐induced precipitation changes in most soybean‐growing regions of China. In particular, aerosols play the most important role during soybean's pod‐filling stage, in which the influence of both precipitation perturbations and negative solar radiative forcing is about 5–10 times that of air temperature on crop yield. Our study thereby identifies aerosol mitigation can bring a notable increase in crop yields, highlighting the potential for important co‐benefits in food security across polluting developing countries. [ABSTRACT FROM AUTHOR]

Brown carbon (BrC) is an organic carbon component with noticeable absorption in the ultraviolet and short visible wavelengths, which influences the global radiative balance. However, assessing BrC radiative effects remains a challenging task owing to the scarcity of direct BrC observations and the uncertainties regarding their chemical and optical properties. This study proposes an efficient method for estimating BrC radiative effects based on the available observational data. The light-absorbing properties of BrC obtained from aethalometer measurements and an optical separation method were combined with simulated BrC optical properties to determine mass concentrations. An optical closure study was conducted to constrain the total and other aerosol contents. Subsequently, we estimated the aerosol optical properties and concentrations. Such a state-of-the-art combination of measurements and numerical models provides primary variables for simulating radiative transfer to estimate BrC radiative effects. We used observations conducted over 4 months (from 1 July to 18 November 2021) in Nanjing (a megacity in east China) as an example. During the observational period, BrC absorption constituted 8.7 %–34.1 % of the total aerosol absorption at 370 nm. In the atmosphere, BrC plays a warming role, with its average instantaneous radiative forcing (RF) and standard deviation of 4.0 ± 2.3 W m -2 corresponding to 15 ± 4.2 % of the black carbon (BC) RF. At the surface, the BrC-induced actinic flux (AF) attenuation is comparable to that caused by BC, accounting for over 55 % of the BC effects in the UV range and almost 20 % in the visible range. The photosynthetically active radiation (PAR) attenuated by BrC is approximately 33.5 ± 9.4 % of that attenuated by BC. Furthermore, we quantified the influences of several BC and BrC microphysical and optical properties on their radiative effects. These findings provide valuable insights for understanding BrC radiative effects. Moreover, they highlight the importance of and necessity for improved observation and modeling of BrC properties. [ABSTRACT FROM AUTHOR]

The spring 2020 COVID-19 lockdowns led to a rapid reduction in aerosol and aerosol precursor emissions. These emission reductions provide a unique opportunity for model evaluation and to assess the potential efficacy of future emission control measures. We investigate changes in observed regional aerosol optical depth (AOD) during the COVID-19 lockdowns and use these observed anomalies to evaluate Earth system model simulations forced with COVID-19-like reductions in aerosols and greenhouse gases. Most anthropogenic source regions do not exhibit statistically significant changes in satellite retrievals of total or dust-subtracted AOD, despite the dramatic economic and lifestyle changes associated with the pandemic. Of the regions considered, only India exhibits an AOD anomaly that exceeds internal variability. Earth system models reproduce the observed responses reasonably well over India but initially appear to overestimate the magnitude of response in East China and when averaging over the Northern Hemisphere (0–70 ∘ N) as a whole. We conduct a series of sensitivity tests to systematically assess the contributions of internal variability, model input uncertainty, and observational sampling to the aerosol signal, and we demonstrate that the discrepancies between observed and simulated AOD can be partially resolved through the use of an updated emission inventory. The discrepancies can also be explained in part by characteristics of the observational datasets. Overall our results suggest that current Earth system models have potential to accurately capture the effects of future emission reductions. [ABSTRACT FROM AUTHOR]

This study presents an approach using multiple linear regression to quantify the impact of meteorological parameters and chemical species on aerosol pH variance in an urban setting in the Pearl River Delta, China. Additionally, it assesses the contributions of interactions among these factors to the variance in pH. The analysis successfully explains over 96% of the pH variance, attributing 85.8% to the original variables and 6.7% to bivariate interactions, with further contributions of 2.3% and 1.0% from trivariate and quadrivariate interactions, respectively. Our results highlight that meteorological factors, particularly temperature and humidity, are more influential than chemical components in affecting aerosol pH variance. Temperature alone accounts for 37.3% of the variance, while humidity contributes approximately 20%. On the chemical front, sulfate and ammonium are the most significant contributors, adding 14.3% and 9.1% to the pH variance, respectively. In the realm of bivariate interactions, the interplay between meteorological parameters and chemical components, especially the TNO 3 – RH pair, is exceptionally impactful, constituting 58.1% of the total contribution from interactions. In summary, this study illuminates the factors affecting aerosol pH variance and their interplay, suggesting the integration of statistical methods with thermodynamic models for enhanced understanding of aerosol acidity dynamics in the future. [ABSTRACT FROM AUTHOR]

Nitrate has been recognized as a key aerosol component in regional haze formation in China. However, reducing nitrate aerosol concentration remains a major challenge. Generally, the formation of particulate nitrate (NO3-) is mainly affected by two processes: oxidation (to generate gaseous HNO3 or particulate NO3-) and gas-particle partitioning (HNO3-NO3- partition). Here, we proposed a new method to explore the contributions of above two processes ( C Oxi obs (%) and C G / P obs (%)) to nitrate formation based on field observation, and combined theoretical calculation and modeling to verify it. Quantitative results showed that gas-particle partitioning process (average C G / P obs (%) was 64.90%) always contributed more than oxidation process (average C Oxi obs (%) was 35.10%) for particulate nitrate formation under different pollution scenarios in the ambient environment. We argued that this phenomenon was mainly caused by high aerosol pH (>4.5). Nevertheless, as pollution level rose, the C Oxi obs (%) will also increase (contributing to 32%, 38%, 40% and 41% under clean, light, medium and heavy pollution levels) which may be attributed to the increased HNO3 production rate and relatively enhanced heterogeneous reaction pathway. The results indicate future strategies for prevention and control of nitrate pollution should both consider reducing precursors emission and regulating aerosol acidity, in order to increase the effectiveness of reducing nitrate dominated pollution. Copyright © 2023 American Association for Aerosol Research [ABSTRACT FROM AUTHOR]

Aerosols play a crucial role in the surface radiative budget by absorbing and scattering both shortwave and longwave radiation. While most aerosol types exhibit a relatively minor longwave radiative forcing when compared to their shortwave counterparts, dust aerosols stand out for their substantial longwave radiative forcing. In this study, radiometers, a sun photometer, a microwave radiometer and the parameterization scheme for clear-sky radiation estimation were integrated to investigate the radiative properties of aerosols. During an event in Xianghe, North China Plain, from 25 April to 27 April 2018, both the composition (anthropogenic aerosol and dust) and the aerosol optical depth (AOD, ranging from 0.3 to 1.5) changed considerably. A notable shortwave aerosol radiative effect (SARE) was revealed by the integrated system (reaching its peak at −131.27 W·m−2 on 26 April 2018), which was primarily attributed to a reduction in direct irradiance caused by anthropogenic aerosols. The SARE became relatively consistent over the three days as the AODs approached similar levels. Conversely, the longwave aerosol radiative effect (LARE) on the dust days ranged from 8.94 to 32.93 W·m−2, significantly surpassing the values measured during the days of anthropogenic aerosol pollution, which ranged from 0.35 to 28.67 W·m−2, despite lower AOD values. The LARE increased with a higher AOD and a lower Ångström exponent (AE), with a lower AE having a more pronounced impact on the LARE than a higher AOD. It was estimated that, on a daily basis, the LARE will offset approximately 25% of the SARE during dust events and during periods of heavy anthropogenic pollution. [ABSTRACT FROM AUTHOR]

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The atmospheric aerosol pollution in the Beijing-Tianjin-Hebei(BTH) region of China is particularly serious. To quickly and accurately evaluate the aerosol pollution in BTH region using the remote sensing method – this article verified the accuracy of the global 1km resolution MCD19A2 aerosol optical depth (AOD) product to clarify its reliability in BTH region, moreover, MCD19A2 was used to study the characteristics of aerosols and its correlation with air quality index (AQI). First, the AOD spatial distribution in BTH region from 2014 to 2018 was obtained through the processes of MCD19A2 such as format conversion, mosaic. Then the AOD results were verified with AERONET measured data through accurate space-time matching, proving the high accuracy and reliability of MCD19A2 (R = 0.9504, MAE = 0.0863, RMSE = 0.1243, EE = 82.26%). Besides, based on the AOD results at different scales, the spatiotemporal characteristics of aerosols in BTH region were analyzed from the aspects of spatial distribution, annual variation, and seasonal variation. Finally, the study shows that MCD19A2 AOD and AQI have a high correlation and similar spatiotemporal characteristics, proving the direct indication of MCD19A2 on air pollution. This article plays an important role in the research of aerosol characteristics, air pollution monitoring and so on. [ABSTRACT FROM AUTHOR]

For regions where limited in-situ observations are available for use as a reference, such as in China, the understanding of how changes in the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol retrieval algorithm impact the data quality is limited. In this paper, the MODIS-Aqua Aerosol Optical Thickness (AOT) Collection 5 (C5) and 6 (C6) Dark-Target (DT) products are evaluated by comparison with similar products from the China Aerosol Remote Sensing NETwork (CARSNET) and the Aerosol Robotic Network (AERONET) in China for the year 2008. The validation data are analyzed for key factors affecting the results of the MODIS-DT aerosol retrieval algorithm, including surface type, aerosol loading and aerosol absorption. The impacts of the change from the C5 to the C6 versions of the MODIS AOT retrieval algorithm are discussed in detail. The main findings are: (1) The agreement from retrieval aspects between both MODIS C5/C6 and CARSNET-AERONET for most AOT values over distinct regions indicates that the conclusions obtained from C5 hold for C6; (2) MODIS-DT has an extended coverage (more retrievals) with good quality due to the change of upstream data (calibration, cloud masking, etc); (3) About 64% of the MODISDT C6 AOT data over China fall within the (±0.15 AOT ± 0.05) error envelope; (4) positive AOT differences between C6 and C5 over relatively dark surfaces and negative differences over relatively bright surfaces due to the change of surface parameterization have been observed; (5) the AOT difference between MODIS and CARSNET-AERONET relating to AOT loading is not significant, especially for large AOT; (6) MODIS-DT performs well for absorbing aerosol over relatively bright surfaces. • MODIS/Aqua AOT C5/C6 DT products are evaluated to understand the effects of different parameters on algorithm performance. • Both MODIS C5 and C6 DT show good quality over China under different surface and atmospheric conditions. • MODIS C6 DT aerosol product has an extended coverage with good quality over China. [ABSTRACT FROM AUTHOR]