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Although a remarkable reduction in the frequency of sand and dust storms (SDSs) in the past several decades has been reported over northern China (NC), two unexpected mega SDSs occurred on 15–20 and 27–29 March 2021 (abbreviated as the “3.15” and “3.27” SDS events), which has reawakened widespread concern. This study characterizes the optical, microphysical, and radiative properties of aerosols and their meteorological drivers during these two SDS events using the Sun photometer observations in Beijing and a comprehensive set of multiple satellite (including MODIS, VIIRS, CALIOP, and Himawari-8) and ground-based observations (including the CMA visibility network and AD-Net) combined with atmospheric reanalysis data. Moreover, a long-term (2000–2021) dust optical depth (DOD) dataset retrieved from MODIS measurements was also utilized to evaluate the historical ranking of the dust loading in NC during dust events. During the 3.15 and 3.27 events, the invasion of dust plumes greatly degraded the visibility over large areas of NC, with extreme low visibility of 50 and 500 m recorded at most sites on 15 and 28 March, respectively. Despite the shorter duration of the 3.27 event relative to the 3.15 event, sun photometer and satellite observations in Beijing recorded a larger peak AOD (∼2.5) in the former than in the latter (∼2.0), which was mainly attributed to the short-term intrusion of coarse-mode dust particles with larger effective radii (∼1.9 µm) and volume concentrations (∼2.0 µm3 µm−2) during the 3.27 event. The shortwave direct aerosol radiative forcing induced by dust was estimated to be −92.1 and −111.4 W m−2 at the top of the atmosphere, −184.7 and −296.2 W m−2 at the surface, and +92.6 and +184.8 W m−2 in the atmosphere in Beijing during the 3.15 and 3.27 events, respectively. CALIOP observations show that during the 3.15 event the dust plume was lifted to an altitude of 4–8 km, and its range of impact extended from the dust source to the eastern coast of China. In contrast, the lifting height of the dust plume during the 3.27 event was lower than that during the 3.15 event, which was also confirmed by ground-based lidar observations. The MODIS-retrieved DOD data registered these two massive SDS events as the most intense episode in the same period in history over the past 2 decades. These two extreme SDS events were associated with both atmospheric circulation extremes and local meteorological anomalies that favored enhanced dust emissions in the Gobi Desert (GD) across southern Mongolia and NC. Meteorological analysis revealed that both SDS events were triggered by an exceptionally strong Mongolian cyclone generated at nearly the same location (along the central and eastern plateau of Inner Mongolia) in conjunction with a surface-level cold high-pressure system at the rear, albeit with differences in magnitude and spatial extent of impact. In the GD, the early melting of spring snow caused by near-surface temperature anomalies over dust source regions, together with negative soil moisture anomalies induced by decreased precipitation, formed drier and barer soil surfaces, which allowed for increased emissions of dust into the atmosphere by strongly enhanced surface winds generated by the Mongolian cyclone.

Aerosol optical depth (AOD) has become a crucial metric for assessing global climate change. Although global and regional AOD trends have been studied extensively, it remains unclear what factors are driving the inter-decadal variations in regional AOD and how to quantify the relative contribution of each dominant factor. This study used a long-term (1980–2016) aerosol dataset from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) reanalysis, along with two satellite-based AOD datasets (MODIS/Terra and MISR) from 2001 to 2016, to investigate the long-term trends in global and regional aerosol loading. Statistical models based on emission factors and meteorological parameters were developed to identify the main factors driving the inter-decadal changes of regional AOD and to quantify their contribution. Evaluation of the MERRA-2 AOD with the ground-based measurements of AERONET indicated significant spatial agreement on the global scale (r= 0.85, root-mean-square error = 0.12, mean fractional error = 38.7 %, fractional gross error = 9.86 % and index of agreement = 0.94). However, when AOD observations from the China Aerosol Remote Sensing Network (CARSNET) were employed for independent verification, the results showed that MERRA-2 AODs generally underestimated CARSNET AODs in China (relative mean bias = 0.72 and fractional gross error =−34.3 %). In general, MERRA-2 was able to quantitatively reproduce the annual and seasonal AOD trends on both regional and global scales, as observed by MODIS/Terra, although some differences were found when compared to MISR. Over the 37-year period in this study, significant decreasing trends were observed over Europe and the eastern United States. In contrast, eastern China and southern Asia showed AOD increases, but the increasing trend of the former reversed sharply in the most recent decade. The statistical analyses suggested that the meteorological parameters explained a larger proportion of the AOD variability (20.4 %–72.8 %) over almost all regions of interest (ROIs) during 1980–2014 when compared with emission factors (0 %–56 %). Further analysis also showed that SO2 was the dominant emission factor, explaining 12.7 %–32.6 % of the variation in AOD over anthropogenic-aerosol-dominant regions, while black carbon or organic carbon was the leading factor over the biomass-burning-dominant (BBD) regions, contributing 24.0 %–27.7 % of the variation. Additionally, wind speed was found to be the leading meteorological parameter, explaining 11.8 %–30.3 % of the variance over the mineral-dust-dominant regions, while ambient humidity (including soil moisture and relative humidity) was the top meteorological parameter over the BBD regions, accounting for 11.7 %–35.5 % of the variation. The results of this study indicate that the variation in meteorological parameters is a key factor in determining the inter-decadal change in regional AOD.

Daily average monitoring data for PM10, PM2.5 and PM1.0 and meteorological parameters at Chengdu from 2009 to 2011 are analyzed using statistical methods to replicate the effect of urban air pollution in Chengdu metropolitan region of the Sichuan Basin. The temporal distribution of, and correlation between, PM10, PM2.5 and PM1.0 particles are analyzed. Additionally, the relationships between particulate matter (PM) and certain meteorological parameters are studied. The results show that variations in the average mass concentrations of PM10, PM2.5 and PM1.0 generally have the same V-shaped distributions (except for April), with peak/trough values for PM average mass concentrations appearing in January/September, respectively. From 2009 to 2011, the inter-annual average mass concentrations of PM10, PM2.5 and PM1.0 fall year on year. The correlation coefficients of daily concentrations of PM10 with PM2.5, PM10 with PM1.0, and PM2.5 with PM1.0 were high, reaching 0.91, 0.83 and 0.98, respectively. In addition, the average ratios of PM2.5/PM10, PM1.0/PM10 and PM1.0/PM2.5 were 85%, 78% and 92%, respectively. From this, fine PM is determined to be the principal pollutant in the Chengdu region. Except for averaged air pressure values, negative correlations exist between other meteorological parameters and PM. Temperature and air pressure influenced the transport and accumulation of PM by affecting convection. Winds promoted PM dispersion. Precipitation not only accelerated the deposition of wet PM, but also inhibited surface dust transport. There was an obvious correlation between PM and visibility; the most important cause of visibility degradation was due to the light extinction of aerosol particles.

As one of the intense anthropogenic emission regions across the relatively high-latitude (>40∘ N) areas on Earth, northeast China faces the serious problem of regional haze during the heating period of the year. Aerosols in polluted haze in northeast China are poorly understood compared with the haze in other regions of China such as the North China Plain. Here, we integrated bulk chemical measurements with single-particle analysis from transmission electron microscopy (TEM), nanoscale secondary ion mass spectrometry (NanoSIMS), and atomic force microscopy (AFM) to obtain morphology, size, composition, aging process, and sources of aerosol particles collected during two contrasting regional haze events (Haze-I and Haze-II) at an urban site and a mountain site in northeast China and further investigated the causes of regional haze formation. Haze-I evolved from moderate (average PM2.5: 76–108 µg m−3) to heavy pollution (151–154 µg m−3), with the dominant PM2.5 component changing from organic matter (OM) (39–45 µg m−3) to secondary inorganic ions (94–101 µg m−3). Similarly, TEM observations showed that S-rich particles internally mixed with OM (named S-OM) increased from 29 % to 60 % by number at an urban site and 64 % to 74 % at a mountain site from the moderate Haze-I to heavy Haze-I events, and 75 %–96 % of Haze-I particles included primary OM. We found that change of wind direction caused Haze-I to rapidly turn into Haze-II (185–223 µg m−3) with predominantly OM (98–133 µg m−3) and unexpectedly high K+ (3.8 µg m−3). TEM also showed that K-rich particles internally mixed with OM (named K-OM) increased from 4 %–5 % by number to 50 %–52 %. The results indicate that there were different sources of aerosol particles causing the Haze-I and Haze-II formation: Haze-I was mainly induced by accumulation of primary OM emitted from residential coal burning and further deteriorated by secondary aerosol formation via heterogeneous reactions; Haze-II was caused by long-range transport of agricultural biomass burning emissions. Moreover, abundant primary OM particles emitted from coal and biomass burning were considered to be one typical brown carbon, i.e., tar balls. Our study highlights that large numbers of light-absorbing tar balls significantly contribute to winter haze formation in northeast China and they should be further considered in climate models.

Understanding the seasonal nonlinear relationship between urban heat island (UHI) and multidimensional urban morphological patterns is crucial for regulating the urban thermal environment. To address this, this study quantified the contributions and sensitivities of urban morphology to land surface temperature (LST) variations and revealed their influencing pathways across four seasons in Beijing, using automated machine learning, SHapley Additive exPlanations interpretation, partial dependence analysis, and structural equation modeling. The results showed significant seasonal variations at the grid scale of 200 m. It was revealed that Normalized Difference Vegetation Index (NDVI) emerged as the most significant indicator affecting LST, followed by building height (BH) and building coverage ratio (BCR), while sky view factor and frontal area index had the least impact. BH was more influential than NDVI, affecting LST during winter. Additionally, sensitivity analysis revealed that impervious surface area, BCR, and mean building volume had positive relationships with LST. In contrast, NDVI and BH negatively affected LST with a noticeable cooling effect, particularly in summer. Furthermore, the total effects of all indicators on LST were negative, with the greatest in spring and the least in winter. Three-dimensional indicators generally exhibited more pronounced direct and total effects than two-dimensional indicators, except in winter. These findings can offer valuable insights for regulating seasonal surface UHI to maximize thermal environmental benefits.

Multi-year observations of aerosol microphysical and optical properties, obtained through ground-based remote sensing at 50 China Aerosol Remote Sensing Network (CARSNET) sites, were used to characterize the aerosol climatology for representative remote, rural, and urban areas over China to assess effects on climate. The annual mean effective radii for total particles (ReffT) decreased from north to south and from rural to urban sites, and high total particle volumes were found at the urban sites. The aerosol optical depth at 440 nm (AOD440 nm) increased from remote and rural sites (0.12) to urban sites (0.79), and the extinction Ångström exponent (EAE440–870 nm) increased from 0.71 at the arid and semi-arid sites to 1.15 at the urban sites, presumably due to anthropogenic emissions. Single-scattering albedo (SSA440 nm) ranged from 0.88 to 0.92, indicating slightly to strongly absorbing aerosols. Absorption AOD440 nm values were 0.01 at the remote sites versus 0.07 at the urban sites. The average direct aerosol radiative effect (DARE) at the bottom of atmosphere increased from the sites in the remote areas (−24.40 W m−2) to the urban areas (−103.28 W m−2), indicating increased cooling at the latter. The DARE for the top of the atmosphere increased from −4.79 W m−2 at the remote sites to −30.05 W m−2 at the urban sites, indicating overall cooling effects for the Earth–atmosphere system. A classification method based on SSA440 nm, fine-mode fraction (FMF), and EAE440–870 nm showed that coarse-mode particles (mainly dust) were dominant at the rural sites near the northwestern deserts, while light-absorbing, fine-mode particles were important at most urban sites. This study will be important for understanding aerosol climate effects and regional environmental pollution, and the results will provide useful information for satellite validation and the improvement of climate modelling.

Smoke aerosols released through frequent springtime fire activity over the Indochina Peninsula (ICP) seriously affect regional air quality, climate, and human health. However, the mechanisms driving the interannual variability of these smoke aerosols are not well understood. By analyzing multi-source historical (1980–2020) smoke aerosols and meteorological reanalysis data, we explore the response of springtime smoke aerosol changes over the ICP to the interannual variability of the Indian Ocean (IO) sea-surface temperature (SST). Our findings show a positive correlation between the variability of springtime smoke aerosol loading and the preceding winter Southeast IO (SEIO) SST anomalies. Warmer SEIO SST tends to weaken the trans-equatorial flow (TEF) and the local Hadley circulation. This weakening of the TEF impedes cyclone development in the Bay of Bengal (BOB), thereby reducing southwest water vapor transport. Simultaneously, enhanced westerly winds over the northern BOB are blocked by the northwestern mountains of ICP. These winds converge and rise on the windward slopes, while descending on the leeward side with diminished humidity. Collectively, these dynamics lead to drier and hotter local meteorological conditions that favored fire-induced smoke aerosol emissions. Our findings highlight the role of the SEIO in regulating smoke aerosol variability and provide a scientific basis for developing strategies to manage smoke aerosol emissions over the ICP.

The aerosol optical property products of Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) reanalysis dataset have been extensively investigated on a global or regional scale. However, the understanding of MERRA-2 aerosol component products on an extensive temporal and spatial scale is inadequate. Recently, the aerosol component products have been derived from the observations of Polarization and Directionality of the Earth’s Reflectances/Polarization and Anisotropy of Reflectance for Atmospheric Science coupled with observations from a Lidar (POLDER/PARASOL). This study presents a quantitative evaluation of the MERRA-2 reanalysis dust and black carbon (BC) column concentration using independent satellite-based aerosol component concentration retrievals. Both GRASP/Component and MERRA-2 reanalysis products can capture well the temporal variation in dust column concentration over the dust emission resource and downwind dust-dominated regions with the correlation coefficient (R) varying from 0.80 to 0.98. MERRA-2 reanalysis dust products present higher column concentration than GRASP/Component dust retrievals with relative differences of about 20~70%, except in the Taklamakan Desert and Bay of Bengal, where the relative differences can be negative. The differences in dust column concentration over the African dust regions are larger than that over the Asian dust regions. Similar temporal variations in BC column concentration are characterized by both GRASP/Component BC retrievals and MERRA-2 BC products with R of about 0.70~0.90, except in the North China Plain region. We should pay more caution with the regional applicability of MERRA-2 component products when large differences and high correlation coefficients are obtained simultaneously. The results are favorable for identifying the behavior of MERRA-2 reanalysis component estimation in a new view and demonstrate a practical application of the satellite-based component retrievals, which could make more contributions to the improvement of model estimation in the near future.

In this study, 765 instantaneous MERRA-2 (second Modern-Era Retrospective analysis for Research and Applications) aerosol optical depth (AOD) values at 550 nm were compared with those of a sky radiometer in Hefei (31.90° N, 117.17° E) for the different seasons from March 2007 to February 2010. The correlation coefficients (R) were 0.88, 0.83, 0.88, and 0.80 in spring, summer, autumn, and winter, respectively. The MERRA-2 AOD is also compared with MODIS Aqua AOD in the entire Yangtze River Delta, and good agreement has been obtained. The MERRA-2 AOD product was used to analyze the spatial distribution and temporal variation of the annual, seasonal and monthly means of the AOD over the Yangtze River Delta region from 1980 to 2016 (37 years). The mean values of the MERRA-2 AOD during the study period show that the AOD (between 0.45 and 0.55) in the northern area of the Yangtze River Delta was higher than that (between 0.30 and 0.45) of the southern area. The northwest part of the Yangtze River Delta had the highest mean AOD values (between 0.50 and 0.55). The AOD increased slowly in the 1980s and 1990s, followed by a rapid increase between 2001 and 2010. An AOD decrease can be seen from 2011 to 2016. The mean AOD in each month is discussed. High AOD was observed in March, April, and June, while low AOD could be seen in September, October, November, and December. Three different area types (large cities, medium-sized cities, and remote areas) had nearly the same annual AOD variation. Large cities had the highest AOD (about 0.48), while remote areas had the lowest (about 0.42). In summer, the AOD in remote areas was much lower than that in cities. The AOD variational trend over the Yangtze River Delta was studied during two periods. The increasing trend could be seen over the entire Yangtze River Delta in each month from 1980 to 2009. A decreasing trend was found all over the Yangtze River Delta in January, February, March, July, October, and November, whereas in other months, some parts witnessed increasing AOD while others saw a decreasing trend between 2010 and 2016.

Seasonal and diurnal characteristics of the vertical profiles of aerosol properties are essential for detecting the regional transport and the climatic radiative effects of aerosol particles. We have studied the seasonal and diurnal characteristics of the vertical distribution of aerosols in urban Beijing from 2017 to 2021 based on long-term Raman–Mie LiDAR observations. The influence of the vertical distribution of aerosols, the meteorological conditions within the boundary layer, the optical–radiometric properties of aerosols, and their interconnections, were investigated during a heavy haze pollution event in Beijing from 8 to 15 February 2020 using both meteorological and sun photometer data. The aerosol extinction coefficient was highest in summer (0.4 km−1), followed by winter (0.35 km−1), and roughly equal in spring and autumn (0.3 km−1). The aerosol extinction coefficient showed clear daily variations and was different in different seasons as a result of the variation in the height of the boundary layer. During the haze pollution event, the particulate matter mainly consisted of scattered spherical fine particles and the accumulation time of pollutants measured via the AOD440nm and PM2.5 mass concentration was different as a result of the hygroscopic growth of the aerosol particles. This growth increased scattering and led to an increase in the aerosol optical depth. The vertical transport of particulate matter also contributed to the increase in the aerosol optical depth.