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Surface visibility (SV), a key indicator of atmospheric transparency, is used widely in the fields of environmental monitoring, transportation, and aviation. However, the sparse distribution and limited number of SV monitoring sites make it difficult to fulfill the urgent need for spatiotemporally seamless fine-scale monitoring. Here, we developed the operational real-time SV retrieval (RT-SVR) framework for China that incorporates information from multiple data sources, including Chinese Land Data Assimilation System meteorological data, in situ observations, and other ancillary data. Seamless hourly SV data with 6.25-km spatial resolution are available in real time via the operational RT-SVR model, which was built using a two-layer stacked ensemble approach that combines multiple machine learning algorithms and a deep learning module. Sample-based cross-validation of the RT-SVR model on approximately 41.3 million data pairs revealed strong robustness and high accuracy, with a Pearson correlation coefficient (R) value of 0.95 and a root mean square error (RMSE) of 3.17 km. An additional hindcast-validation experiment, performed with continuous observations obtained over one year (approximately 20.8 million data pairs), demonstrated the powerful generalization capabilities of the RT-SVR model, albeit with slight degradation in performance (R = 0.85, RMSE = 5.28 km). The seamless hourly SV data with real-time update capability enable tracking of the generation, development, and dissipation of various low-SV events (e.g., fog, haze, and dust storms) in China. The developed framework might also prove useful for quantitative retrieval of aerosol-related parameters (e.g., PM2.5, PM10, and aerosol optical depth). [ABSTRACT FROM AUTHOR]

Monitoring the dynamics of atmospheric CO2 is crucial for enhancing comprehension of the carbon cycle. Using column‐averaged dry‐air mole fraction of CO2 (XCO2) data collected by the Orbiting Carbon Observatory (OCO)‐2 and OCO‐3 satellites during 2020–2021, this study explored seasonal and diurnal variations in XCO2 characteristics in typical land cover biomes in China, and investigated their relationships with meteorological drivers. Results showed that XCO2 products retrieved by OCO‐2 and OCO‐3 have good agreement with Total Carbon Column Observing Network measurements, with average deviations of 0.8 and 1.2 ppm, respectively. The satellite observations revealed XCO2 hotpots located mainly in central and eastern China, and areas of low XCO2 values in western China, with a seasonal curve that was highest (lowest) in spring (summer). The largest seasonal cycle amplitude (∼9 ppm) of XCO2 was observed in forest areas, highlighting its key role in carbon exchange. Additionally, XCO2 was found to have a near‐sinusoidal diurnal pattern, characterized by rapid decrease in the early morning as photosynthesis resumed after sunrise, as indicated by the sun‐induced chlorophyll fluorescence (SIF), a peak at around midday, and subsequent decrease as SIF increased after mid‐afternoon. Urban regions had the highest diurnal cycle amplitude (∼6 ppm) among biomes. Statistical analyses revealed seasonal shift and nonlinear variation in the relationships between XCO2 and meteorological variables, suggesting that CO2 uptake is influenced by favorable humidity conditions. These relationships also provide insight into the sensitivity and adaptability of XCO2 to meteorological factors in diverse ecosystems such as savanna and grassland. Plain Language Summary: Measuring CO2 concentrations helps us gain better understanding of the carbon cycle in the context of climate change. China is among the world's main emitters of carbon and it has pledged to achieve carbon neutrality. To create effective strategies for the mitigation of atmospheric CO2, it is important to investigate the CO2 dynamics on multiple time scales. Using observations from the OCO‐2 and OCO‐3 carbon‐monitoring satellites, we characterized the seasonal and diurnal variations in column‐averaged abundance of CO2 (XCO2) across biomes and examined the impact of meteorological factors. Our findings revealed a near‐sinusoidal pattern in the hourly variation of XCO2 over biomes, and suggested XCO2 seasonal variability varies among them, with maximum seasonal variability for forests (∼9 ppm), and the maximum diurnal variability for urban regions (∼6 ppm). Furthermore, meteorological, and photosynthetic activity indicated the complicated relationships with XCO2. Future carbon research efforts should consider the differences in the magnitude of CO2 variation among biomes and the complex effects of meteorological conditions. Key Points: OCO‐3 detects diurnal variations in XCO2 that follow a near‐sinusoidal patternMeteorological factors affect XCO2 seasonally and nonlinearlyVegetation activity should be observed to understand carbon cycles [ABSTRACT FROM AUTHOR]

Human-perceived thermal comfort (known as human-perceived temperature) measures the combined effects of multiple meteorological factors (e.g., temperature, humidity, and wind speed) and can be aggravated under the influences of global warming and local human activities. With the most rapid urbanization and the largest population, China is being severely threatened by aggravating human thermal stress. However, the variations of thermal stress in China at a fine scale have not been fully understood. This gap is mainly due to the lack of a high-resolution gridded dataset of human thermal indices. Here, we generated the first high spatial resolution (1 km) dataset of monthly human thermal index collection (HiTIC-Monthly) over China during 2003–2020. In this collection, 12 commonly used thermal indices were generated by the Light Gradient Boosting Machine (LightGBM) learning algorithm from multi-source data, including land surface temperature, topography, land cover, population density, and impervious surface fraction. Their accuracies were comprehensively assessed based on the observations at 2419 weather stations across the mainland of China. The results show that our dataset has desirable accuracies, with the mean R2 , root mean square error, and mean absolute error of 0.996, 0.693 ∘ C, and 0.512 ∘ C, respectively, by averaging the 12 indices. Moreover, the data exhibit high agreements with the observations across spatial and temporal dimensions, demonstrating the broad applicability of our dataset. A comparison with two existing datasets also suggests that our high-resolution dataset can describe a more explicit spatial distribution of the thermal information, showing great potentials in fine-scale (e.g., intra-urban) studies. Further investigation reveals that nearly all thermal indices exhibit increasing trends in most parts of China during 2003–2020. The increase is especially significant in North China, Southwest China, the Tibetan Plateau, and parts of Northwest China, during spring and summer. The HiTIC-Monthly dataset is publicly available from Zenodo at 10.5281/zenodo.6895533 (Zhang et al., 2022a). [ABSTRACT FROM AUTHOR]

Springtime smoke aerosols attributable to biomass burning on the Indochina Peninsula (ICP) are a major source of absorbing aerosols globally, and play a nonnegligible perturbing role in climate change. Using smoke extinction profiles provided by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument, and aerosol and meteorological reanalyses for the period 2007–2021, this study investigated the three-dimensional structure and transport flux of springtime smoke aerosols over the ICP. Stratified analysis revealed that CALIOP-derived peaks of smoke aerosol optical depth (SAOD) and smoke mass flux (SMF) at altitudes of 0–2 km occur over the central ICP, which is the main source region. Driven by a southwesterly jet stream and updrafts, massive amounts of smoke aerosols are transported toward the northeast of the ICP, resulting in the largest stratified SAOD and SMF observed at altitudes of 2–4 km. Over the main smoke source regions, the estimated springtime SMF was approximately 0.4 Tg accumulated through a distance of 2° latitude at altitudes of 2–4 km. Meteorological analyses indicated a path for the transport of smoke aerosols to the mid-troposphere. Smoke aerosols in the source region are first lifted thermally to the 600-hPa level. Lifting then continues to the 500-hPa level via the combined effects of topography and frequent, deep, and dry convective updrafts over the mountainous areas of the northern ICP. The smoke aerosols are subsequently transported to South China and the western Pacific owing to strong westerly winds and weak vertical motion. Further analyses demonstrated that differences in meteorological conditions between daytime and nighttime have substantial impact on the vertical structure of smoke aerosols, particularly over the northeast of ICP. Compared to daytime, enhanced updrafts and moisture transport at night favor further lifting of smoke aerosols and greater extinction intensity owing to increased hygroscopic growth. • Springtime smoke aerosols from the ICP can be transported to SC and the WP in the mid–upper troposphere. • Differences in daytime and nighttime of smoke aerosols over the ICP may be caused by circulation and water vapor. • Maximum loadings of smoke aerosols over the ICP are observed at altitudes of 2–4 km due to vertical circulation. [ABSTRACT FROM AUTHOR]

Fine particulate matter (PM 2.5) has altered the radiation balance on Earth and raised environmental and health risks for decades but has only been monitored widely since 2013 in China. Historical long-term PM 2.5 records with high temporal resolution are essential but lacking for both research and environmental management. Here, we reconstruct a site-based PM 2.5 dataset at 6 h intervals from 1960 to 2020 that combines long-term visibility, conventional meteorological observations, emissions, and elevation. The PM 2.5 concentration at each site is estimated based on an advanced machine learning model, LightGBM, that takes advantage of spatial features from 20 surrounding meteorological stations. Our model's performance is comparable to or even better than those of previous studies in by-year cross validation (CV) (R2=0.7) and spatial CV (R2=0.76) and is more advantageous in long-term records and high temporal resolution. This model also reconstructs a 0.25 ∘ × 0.25 ∘ , 6-hourly, gridded PM 2.5 dataset by incorporating spatial features. The results show PM 2.5 pollution worsens gradually or maintains before 2010 from an interdecadal scale but mitigates in the following decade. Although the turning points vary in different regions, PM 2.5 mass concentrations in key regions decreased significantly after 2013 due to clean air actions. In particular, the annual average value of PM 2.5 in 2020 is nearly the lowest since 1960. These two PM 2.5 datasets (publicly available at 10.5281/zenodo.6372847, Zhong et al., 2022) provide spatiotemporal variations at high resolution, which lay the foundation for research studies associated with air pollution, climate change, and atmospheric chemical reanalysis. [ABSTRACT FROM AUTHOR]

The development of chemical transport models with advanced physics and chemical schemes could improve air-quality forecasts. In this study, the China Meteorological Administration Unified Atmospheric Chemistry Environment (CUACE) model, a comprehensive chemistry module incorporating gaseous chemistry and a size-segregated multicomponent aerosol algorithm, was coupled to the Weather Research and Forecasting (WRF) framework with chemistry (WRF-Chem) using an interface procedure to build the WRF/CUACE v1.0 model. The latest version of CUACE includes an updated aerosol dry deposition scheme and the introduction of heterogeneous chemical reactions on aerosol surfaces. We evaluated the WRF/CUACE v1.0 model by simulating PM 2.5 , O3 , NO2 , and SO2 concentrations for January, April, July, and October (representing winter, spring, summer and autumn, respectively) in 2013, 2015, and 2017 and comparing them with ground-based observations. Secondary inorganic aerosol simulations for the North China Plain (NCP), Yangtze River Delta (YRD), and Sichuan Basin (SCB) were also evaluated. The model captured well the variations of PM 2.5 , O3 , and NO2 concentrations in all seasons in eastern China. However, it is difficult to accurately reproduce the variations of air pollutants over SCB, due to its deep basin terrain. The simulations of SO2 were generally reasonable in the NCP and YRD with the bias at -15.5 % and 24.55 %, respectively, while they were poor in the Pearl River Delta (PRD) and SCB. The sulfate and nitrate simulations were substantially improved by introducing heterogeneous chemical reactions into the CUACE model (e.g., change in bias from -95.0 % to 4.1 % for sulfate and from 124.1 % to 96.0 % for nitrate in the NCP). Additionally, The WRF/CUACE v1.0 model was revealed with better performance in simulating chemical species relative to the coupled Fifth-Generation Penn State/NCAR Mesoscale Model (MM5) and CUACE model. The development of the WRF/CUACE v1.0 model represents an important step towards improving air-quality modeling and forecasts in China. [ABSTRACT FROM AUTHOR]

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 (AOD 440nm) increased from remote and rural sites (0.12) to urban sites (0.79), and the extinction Ångström exponent (EAE 440–870 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 (SSA 440nm) ranged from 0.88 to 0.92, indicating slightly to strongly absorbing aerosols. Absorption AOD 440nm 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 (-24.4 0 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 SSA 440nm , fine-mode fraction (FMF), and EAE 440–870nm 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. [ABSTRACT FROM AUTHOR]

Fine particulate matter (PM 2.5) is a severe air pollution problem in China. Observations of PM 2.5 have been available since 2013 from a large network operated by the China National Environmental Monitoring Center (CNEMC). The data show a general 30 %–50 % decrease in annual mean PM 2.5 across China over the 2013–2018 period, averaging at -5.2 µ g m -3 a -1. Trends in the five megacity cluster regions targeted by the government for air quality control are -9.3±1.8 µ g m -3 a -1 (±95 % confidence interval) for Beijing–Tianjin–Hebei, -6.1±1.1 µ g m -3 a -1 for the Yangtze River Delta, -2.7±0.8 µ g m -3 a -1 for the Pearl River Delta, -6.7±1.3 µ g m -3 a -1 for the Sichuan Basin, and -6.5±2.5 µ g m -3 a -1 for the Fenwei Plain (Xi'an). Concurrent 2013–2018 observations of sulfur dioxide (SO2) and carbon monoxide (CO) show that the declines in PM 2.5 are qualitatively consistent with drastic controls of emissions from coal combustion. However, there is also a large meteorologically driven interannual variability in PM 2.5 that complicates trend attribution. We used a stepwise multiple linear regression (MLR) model to quantify this meteorological contribution to the PM 2.5 trends across China. The MLR model correlates the 10 d PM 2.5 anomalies to wind speed, precipitation, relative humidity, temperature, and 850 hPa meridional wind velocity (V850). The meteorology-corrected PM 2.5 trends after removal of the MLR meteorological contribution can be viewed as being driven by trends in anthropogenic emissions. The mean PM 2.5 decrease across China is -4.6 µ g m -3 a -1 in the meteorology-corrected data, 12 % weaker than in the original data, meaning that 12 % of the PM 2.5 decrease in the original data is attributable to meteorology. The trends in the meteorology-corrected data for the five megacity clusters are -8.0±1.1 µ g m -3 a -1 for Beijing–Tianjin–Hebei (14 % weaker than in the original data), -6.3±0.9 µ g m -3 a -1 for the Yangtze River Delta (3 % stronger), -2.2±0.5 µ g m -3 a -1 for the Pearl River Delta (19 % weaker), -4.9±0.9 µ g m -3 a -1 for the Sichuan Basin (27 % weaker), and -5.0±1.9 µ g m -3 a -1 for the Fenwei Plain (Xi'an; 23 % weaker); 2015–2017 observations of flattening PM 2.5 in the Pearl River Delta and increases in the Fenwei Plain can be attributed to meteorology rather than to relaxation of emission controls. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract Fine particulate matter (PM 2.5) pollution in Eastern China (EC) has raised concerns due to its adverse effects on air quality, climate, and human health. This study investigated the long-term variation trend in satellite-derived PM 2.5 concentrations and how it was related to pollutant emissions and meteorological parameters over EC and seven regions of interest (ROIs) during 1998–2016. Over EC, the annual mean PM 2.5 increased before 2006 due to the enhanced emissions of primary PM 2.5 , NO x and SO 2 , but decreased with the reduced SO 2 emissions after 2006 evidently in response to China's clean air policies. In addition, results from statistical analyses indicated that in the North China Plain (NCP), Northeast China (NEC), Sichuan Basin (SCB) and Central China (CC) planetary boundary layer height (PBLH) was the dominant meteorological driver for the PM 2.5 decadal changes, and in the Pearl River Delta (PRD) wind speed is the leading factor. Overall, the variation in meteorological parameters accounted for 48% of the variances in PM 2.5 concentrations over EC. The population-weighted PM 2.5 over EC increased from 36.4 μg/m3 in 1998–2004 (P1) to 49.4 μg/m3 in 2005–2010 (P2) then decreased to 46.5 μg/m3 in 2011–2016 (P3). In the NCP and NEC, the percentages of the population living above the World Health Organization (WHO) Interim Target-1 (IT-1, 35 μg/m3) have risen steadily over the past 20 yr, reaching maxima of 97.3% and 78.8% in P3, respectively, but decreases of ∼30% from P2 to P3 were found for the SCB and PRD. Graphical abstract Image 1 Highlights • The joint effect of emission and meteorological determined the decadal trend of PM 2.5 • The changes in meteorological parameters explained 48% of the variances in PM 2.5. • Planetary boundary layer height was the dominant driver for the decadal changes of PM 2.5 • Eastern China has experienced slight decreases in the population-weighted mean PM 2.5 over the past 10 year. The joint effect of emissions and meteorological determined the decadal trend in PM 2.5. The decadal variation in meteorological parameters accounted for 48% of the variances in PM 2.5 concentrations over Eastern China. Eastern China has experienced slight decreases in the population-weighted mean PM 2.5 over the past 10 year. [ABSTRACT FROM AUTHOR]

The Sichuan and Chongqing regions suffer from severe haze weather in winter due to the unfavourable atmospheric diffusion conditions. Reanalysis and precipitation datasets were applied in this study to calculate and distinguish air stagnation events using a developed criterion, and the impacts of the occurrence of air stagnation events on air quality were analysed in combination with the PM 2.5 concentration data for the winters of 2013–2016. The highest occurrence frequency of air stagnation events was observed in 2013, and the lowest, 2015. The meteorological conditions during winter in the Sichuan Basin were inclined to form unfavourable atmospheric diffusion conditions, and the occurrence frequency of air stagnation days was up to 76.6% on average during the four winters. The effects of air stagnation events on air quality were most obvious in the western and southern Sichuan Basin. The mean concentrations of PM 2.5 during air stagnation days were higher by 41.9% than those during non-air stagnation days. The PM 2.5 concentrations were adjusted using the favourable atmospheric diffusion conditions in 2015 as a baseline to quantify the PM 2.5 contribution to the improvement of air quality in the other years, which revealed that the level of PM 2.5 in the Sichuan and Chongqing regions was declining at a rate of approximately 10.7% overall during the winters of 2013–2016, implying that the air pollutant reduction measures have been highly effective. Furthermore, the occurrence frequency of air stagnation days and events were increased in recent ten years of 2007–2016, with linear slopes of 0.61 yr −1 and 0.26 yr −1 , respectively. The study revealed that the government might face a greater challenge in improving the air quality over winter and should pay more attention to reduction of pollutant emission in areas of Chengdu, Chongqing and cities in the south of the Sichuan Basin. [ABSTRACT FROM AUTHOR]

The climatological variation of aerosol properties and the planetary boundary layer (PBL) during 2013-2015 over the Yangtze River Delta (YRD) region were investigated by employing ground-based Micro Pulse Lidar (MPL) and CE-318 sun-photometer observations. Combining Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite products, enhanced haze pollution events affected by different types of aerosol over the YRD region were analyzed through vertical structures, spatial distributions, backward trajectories, and the potential source contribution function (PSCF) model. The results show that aerosols in the YRD are dominated by fine-mode particles, except in March. The aerosol optical depth (AOD) in June and September is higher due to high single scattering albedo (SSA) from hygroscopic growth, but it is lower in July and August due to wet deposition from precipitation. The PBL height (PBLH) is greater (means ranging from 1.23 to 1.84 km) and more variable in the warmer months of March to August, due to the stronger diurnal cycle and exchange of heat. Northern fine-mode pollutants are brought to the YRD at a height of 1.5 km. The SSA increases, blocking the radiation to the surface, and cooling the surface, thereby weakening turbulence, lowering the PBL, and in turn accelerating the accumulation of pollutants, creating a feedback to the cooling effect. Originated from the deserts in Xinjiang and Inner Mongolia, long-range transported dust masses are seen at heights of about 2 km over the YRD region with an SSA440 nm below 0.84, which heat air and raise the PBL, accelerating the diffusion of dust particles. Regional transport from biomass-burning spots to the south of the YRD region bring mixed aerosol particles at a height below 1.5 km, resulting in an SSA440 nm below 0.89. During the winter, the accumulation of the local emission layer is facilitated by stable weather conditions, staying within the PBL even below 0.5 km. [ABSTRACT FROM AUTHOR]

Aerosol pollution in eastern China is an unfortunate consequence of the region's rapid economic and industrial growth. Here, sun photometer measurements from seven sites in the Yangtze River Delta (YRD) from 2011 to 2015 were used to characterize the climatology of aerosol microphysical and optical properties, calculate direct aerosol radiative forcing (DARF) and classify the aerosols based on size and absorption. Bimodal size distributions were found throughout the year, but larger volumes and effective radii of fine-mode particles occurred in June and September due to hygroscopic growth and/or cloud processing. Increases in the fine-mode particles in June and September caused AOD440 nm >1.00 at most sites, and annual mean AOD440 nm values of 0.71-0.76 were found at the urban sites and 0.68 at the rural site. Unlike northern China, the AOD440 nm was lower in July and August (~0.40-0.60) than in January and February (0.71-0.89) due to particle dispersion associated with subtropical anticyclones in summer. Low volumes and large bandwidths of both fine-mode and coarsemode aerosol size distributions occurred in July and August because of biomass burning. Single-scattering albedos at 440 nm (SSA440 nm/ from 0.91 to 0.94 indicated particles with relatively strong to moderate absorption. Strongly absorbing particles from biomass burning with a significant SSA wavelength dependence were found in July and August at most sites, while coarse particles in March to May were mineral dust. Absorbing aerosols were distributed more or less homogeneously throughout the region with absorption aerosol optical depths at 440 nm ~0.04-0.06, but inter-site differences in the absorption Angström exponent indicate a degree of spatial heterogeneity in particle composition. The annual mean DARF was -93±44 to -79±39Wm-2 at the Earth's surface and ~-40Wm-2 at the top of the atmosphere (for the solar zenith angle range of 50 to 80°) under cloud-free conditions. The fine mode composed a major contribution of the absorbing particles in the classification scheme based on SSA, fine-mode fraction and extinction Angström exponent. This study contributes to our understanding of aerosols and regional climate/air quality, and the results will be useful for validating satellite retrievals and for improving climate models and remote sensing algorithms. [ABSTRACT FROM AUTHOR]

Water vapor is one of the major greenhouse gases in the atmosphere and also the key parameter affecting the hydrological cycle, aerosol properties, aerosol-cloud interactions, the energy budget, and the climate. This study analyzed the temporal and spatial distribution of precipitable water vapor (PWV) in China using MODerate resolution Imaging Spectroradiometer near-infrared (MODIS-NIR)-Clear PWV products from 2011 to 2013. We then compared the four PWV products (Global Positioning System PWV (GPS-PWV), radiosonde PWV (RS-PWV), MODIS-NIR-Clear PWV, and Aerosol Robotic Network sunphotometer PWV (AERONET-PWV)) at six typical sites in China from 2011 to 2013. The analysis of the temporal and spatial distribution showed that the PWV distribution in China has clear geographical differences, and its basic distribution characteristics gradually change from the coast in the southeast to inland in the northwest. Affected by the East Asian monsoon, the PWV over China showed clear seasonal distribution features, with highest values in the summer, followed by autumn and spring, and the lowest values in winter. Intercomparison results showed that GPS-PWV and RS-PWV had a slightly higher correlation (R 2 = 0.975) at 0000 UTC than that at 1200 UTC (R 2 = 0.967). The mean values of Bias, SD, and RMSE between GPS-PWV and RS-PWV (GPS-RS) were − 0.03 mm, 2.36 mm, and 2.60 mm at 0000 UTC, and − 0.23 mm, 2.76 mm, and 2.95 mm at 1200 UTC, respectively. This showed that GPS-PWV was slightly lower than RS-PWV, and this difference was more obvious during the nighttime. The MODIS-NIR-Clear PWV product showed a similar correlation coefficient (R 2 = 0.88) with GPS-PWV compared with RS-PWV. In addition, MODIS-NIR-Clear PWV was greater than GPS-PWV and RS-PWV. The MODIS-NIR-Clear PWV showed a larger deviation from GPS-PWV (MODIS-GPS Bias = 1.50 mm, RMSE = 5.76 mm) compared with RS PWV (MODIS-RS Bias = 0.75 mm, RMSE = 5.31 mm). The correlation coefficients between AERONET-PWV and the PWV from GPS, RS, and MODIS-NIR-Clear were 0.970, 0.963, and 0.923 (with RMSE of 2.53 mm, 3.67 mm, and 4.39 mm), respectively. In the Beijing area, the overall mean bias of the AERONET-PWV product with GPS-PWV, RS-PWV and MODIS-NIR-Clear PWV was − 0.09 mm, − 1.82 mm, and − 1.54 mm, respectively, which shows that the AERONET-PWV product was lower than the other three PWV products. [ABSTRACT FROM AUTHOR]

The spatial-temporal variations of the ground-based and satellite-derived PM 2.5 are crucial for studying air quality, human health, and climate change. However, the existing ground-based PM 2.5 monitoring network has sparsely-distributed sites and satellite cannot give 24-h PM 2.5 , which make it difficult to grasp the spatial and sub-daily variation characteristics of PM 2.5. This study aims to fill that gap by establishing a virtual network of hourly PM 2.5 concentration using the LightGBM model, based on the high-density ground meteorological observations at ~2400 sites across China. The virtual network shows a desirable performance of hourly PM 2.5 estimation across China, with R 2 of 0.86, root-mean-square error values of 14.99 μg/m3, and mean absolute error of 9.48 μg/m3 (the results of Cross-Validation). It also exhibits high spatial-temporal consistencies with the observed PM 2.5. Spatially, the heaviest PM 2.5 pollution is mainly distributed in eastern China (especially the Beijing-Tianjin-Hebei, the Yangtze and Pearl river deltas, and the Sichuan-Chongqing areas). Temporarily, PM 2.5 exhibits remarkable seasonal and diurnal changes characterized by higher concentration in winter and nighttime and lower in summer and daytime. Meanwhile, we found that visibility can be used as the primary predictor in the machine learning model to enhance the accuracy of estimated PM 2.5. The established virtual hourly PM 2.5 network (~2400 stations) provides a more intuitive and detailed PM 2.5 data for us to understand the diurnal variation of PM 2.5 and monitor inter-regional transport of haze over China. It thus is of benefit to the study of air pollution control and related diseases. • Hourly PM 2.5 in China is estimated using high-density weather records by LightGBM. • The model shows a superior estimation accuracy at national, regional, and site scales. • A virtual network of high-accuracy and -density hourly PM 2.5 in China is established. • This network fills the gaps of sparse air quality sites and satellite-derived PM 2.5. [ABSTRACT FROM AUTHOR]

Different types of aerosols play a crucial role in the climate system according to their vertical distributions and optical-radiative properties. Southwest China (SWC), consisting of the Sichuan Basin (SCB), the Yunnan-Guizhou Plateau (YGP) and the Tibetan Plateau (TP), is one of the most topographically complex regions in the world and is also facing varying degrees of air pollution problems caused by local, high-intensity anthropogenic emissions and trans-regional transport of aerosols from surrounding areas. However, a comprehensive understanding of the regional three-dimensional (3D) characteristics of aerosol distribution and evolution over SWC has not to be achieved yet. Here, the seasonal distributions and vertical structures of four types of aerosols, including dust, polluted continental/smoke, polluted dust and elevated smoke, were detected by using the quality controlled CALIPSO Level 2 nighttime aerosol profile product from 2007 to 2016 in this study. The loading of aerosols over the SCB was higher than that over the other regions, and of the sources, polluted continental/smoke and polluted dust, related to anthropogenic sources, contributed the most to the aerosols. However, we also found that polluted continental/smoke and polluted dust have declined since 2013, which was due to the strict regulatory measures implemented for industry emissions and biomass burning in agriculture in recent years. The elevated smoke aerosols over the YGP at an altitude of 3 km in spring were significantly higher than those in other seasons, while the polluted continental/smoke aerosols at an altitude of 1–2 km were higher in autumn and winter than in the other seasons and was considered to be from local biomass burning. The aerosol optical depth (AOD) over the TP was nearly one magnitude lower than that over the other two regions. However, either the dust or polluted continental/smoke from the Qaidam Basin or elevated smoke elevated from the Indo-Gangetic Basin could have been transported to the layer as high as 6 km over the TP. Additionally, the heights of the highest frequencies of AOD for all types of aerosols for the SCB, YGP and TP were 0–2 km, 2–4 km and 4–6 km, respectively. In summer, elevated smoke can rise to heights of 8–10 km on the TP. The results of this study provide an observational basis for further understanding the trans-regional transport of aerosols and their climate effects in SWC. • 3D vertical structure of aerosols over SWC were presented during 2006–2016. • Polluted aerosols over SWC have declined since 2013. • Smoke aerosols are mainly from local emissions and trans-regional transport. • Elevated smoke can rise to heights of 8–10 km over the TP in summer. [ABSTRACT FROM AUTHOR]

• A virtual ground-based PM 2.5 observation network was constructed. • Daily estimations of PM 2.5 concentrations at ~1000 sites in China were generated. • The model demonstrated good performance in hindcasting historical PM 2.5 levels. • This virtual PM 2.5 network can be used for reconstructing historical PM 2.5 data. With increasing public concerns on air pollution in China, there is a demand for long-term continuous PM 2.5 datasets. However, it was not until the end of 2012 that China established a national PM 2.5 observation network. Before that, satellite-retrieved aerosol optical depth (AOD) was frequently used as a primary predictor to estimate surface PM 2.5. Nevertheless, satellite-retrieved AOD often encounter incomplete daily coverage due to its sampling frequency and interferences from cloud, which greatly affect the representation of these AOD-based PM 2.5. Here, we constructed a virtual ground-based PM 2.5 observation network at 1180 meteorological sites across China using the Extreme Gradient Boosting (XGBoost) model with high-density meteorological observations as major predictors. Cross-validation of the XGBoost model showed strong robustness and high accuracy in its estimation of the daily (monthly) PM 2.5 across China in 2018, with R2 , root-mean-square error (RMSE) and mean absolute error values of 0.79 (0.92), 15.75 μg/m3 (6.75 μg/m3) and 9.89 μg/m3 (4.53 μg/m3), respectively. Meanwhile, we find that surface visibility plays the dominant role in terms of the relative importance of variables in the XGBoost model, accounting for 39.3% of the overall importance. We then use meteorological and PM 2.5 data in the year 2017 to assess the predictive capability of the model. Results showed that the XGBoost model is capable to accurately hindcast historical PM 2.5 at monthly (R 2 = 0.80, RMSE = 14.75 μg/m3), seasonal (R 2 = 0.86, RMSE = 12.28 μg/m3), and annual (R 2 = 0.81, RMSE = 10.10 μg/m3) mean levels. In general, the newly constructed virtual PM 2.5 observation network based on high-density surface meteorological observations using the Extreme Gradient Boosting model shows great potential in reconstructing historical PM 2.5 at ~1000 meteorological sites across China. It will be of benefit to filling gaps in AOD-based PM 2.5 data, as well as to other environmental studies including epidemiology. [ABSTRACT FROM AUTHOR]

This study used the MERRA-2 reanalysis dataset and ground-based and satellite observational data to comprehensively analyze a typical dust storm event in east Asia on 2–7 May 2017 which engulfed most of China as well as ocean and Japan, and explore the accuracy and comprehensiveness of the MERRA-2 dataset in the analysis of dust processes. The results of comparison show that the description of the spatiotemporal distribution and evolution of the dust aerosols in the dust event using the MERRA-2 data is consistent with the data of AERONET, National Urban Air Quality Real-time Publishing Platform and Hamawari-8. Gobi Deserts was the most influential source area of this dust event with the highest emissions reaching 1.9 × 106 μg/m3. The vertical motion of the atmosphere can lift dust from the source area above 500 hPa. There were low-pressure troughs at 500 and 850 hPa and the winds behind and in front of the trough led to the high-altitude, long-distance transport of dust. Dust gradually affected the northwest China, north China, northeast China, and even the ocean and Japan on 2–7 May. This study demonstrates that although there is some uncertainty about the source of dust emission in the MERRA-2 model, the data accurately simulated the evolution of the dust event and analyze it comprehensively, while the accuracy of simulating the long-term evolution of dust requires further evaluation. [ABSTRACT FROM AUTHOR]

This study analyzed the long-term variations and trends of haze pollution and its relationships with emission and meteorological factors using the haze days (HDs) data derived from surface observation stations in Sichuan-Chongqing (SCC) region during 1980–2016. The results showed that the multi-year mean number of HDs were 68.7 and 4.9 days for the Sichuan-Basin (SCB) and the rest of SCC region, respectively. The seasonally averaged HDs over SCB reached its maximum in winter (34.7 days), followed by autumn (17.0 days) and spring (11.6 days), and with the minimum observed in summer (5.5 days). The inter-annual variations of HDs in 18 main cities revealed that Zigong, Neijiang, and Yibin, which are located in the southern of SCB, have been the most polluted areas over the SCC region in the past decades. A notable increasing trend in annual HDs over the majority of SCC region was found during 1980–1995, then the trend sharply reversed during 1996–2005, while it increased, fluctuating at some cities after 2006. Seasonally, the increased trend in spring and autumn seems to be the strongest during 1980–1995, whereas the decreased trend in spring and winter was stronger than other seasons during 1996–2005. In addition, a remarkable increasing trend was found in winter since 2006. Using correlation analysis between HDs and emission and meteorological factors during different periods, we found that the variability of local precipitation days (PDs), planetary boundary layer height (PBLH), near-surface wind speed (WS), and relatively humidity (RH) play different roles in influencing the haze pollution change during different historical periods. The joint effect of sharp increase of anthropogenic emissions, reduced PDs and WS intensified the haze pollution in SCB during 1980–1995. In contrast, decreased HDs during 1996–2005 are mainly attributable to the reduction of PM2.5 emission and the increase of PDs (especially in winter). In addition, the decrease of PDs is likely to be responsible for the unexpected increase in winter HDs over SCB in the last decade. [ABSTRACT FROM AUTHOR]

The role of PM 2.5 (particles with aerodynamic diameters ≤ 2.5 µm) deposition in air quality changes over China remains unclear. By using the three-year (2013, 2015, and 2017) simulation results of the WRF/CUACE v1.0 model from a previous work (Zhang et al., 2021), a non-linear relationship between the deposition of PM 2.5 and anthropogenic emissions over central-eastern China in cold seasons as well as in different life stages of haze events was unraveled. PM 2.5 deposition is spatially distributed differently from PM 2.5 concentrations and anthropogenic emissions over China. The North China Plain (NCP) is typically characterized by higher anthropogenic emissions compared to southern China, such as the middle-low reaches of Yangtze River (MLYR), which includes parts of the Yangtze River Delta and the Midwest. However, PM 2.5 deposition in the NCP is significantly lower than that in the MLYR region, suggesting that in addition to meteorology and emissions, lower deposition is another important factor in the increase in haze levels. Regional transport of pollution in central-eastern China acts as a moderator of pollution levels in different regions, for example by bringing pollution from the NCP to the MLYR region in cold seasons. It was found that in typical haze events the deposition flux of PM 2.5 during the removal stages is substantially higher than that in accumulation stages, with most of the PM 2.5 being transported southward and deposited to the MLYR and Sichuan Basin region, corresponding to a latitude range of about 24°N-31°N. [Display omitted] [ABSTRACT FROM AUTHOR]

Aerosols are important atmospheric constituents with significant impacts on both regional air quality and the global climate and environment. Aerosol effects on radiation, clouds and precipitation are strongly related to the optical properties of aerosols, which vary considerably in space and time. This study reviewed the current understanding of the optical and radiative properties of aerosols and aerosol effects in China, and presented future research prospects. The Chinese aerosol remote sensing network (CARSNET) has been developed and expanded to include >80 stations across China. An internationally recognized radiometric calibration and data processing method has been developed to provide high-quality observational data of key optical properties. Ground lidars are used to provide information on the vertical aerosol optical properties on the spatiotemporal scales. The spatio-temporal distribution and evolution of aerosols are also analyzed using multi-satellite observations. Particle type and component content information are derived from aerosol component retrieval algorithm. Given the advantages of aerosol assimilation reanalysis products in terms of temporal resolution and spatial coverage, such information can more accurately characterize the climatological impact of aerosol optical properties and aerosol–climate interactions. Measurements obtained using the above methods can quantitatively reveal the influence of aerosol direct radiation effects in different regions, and support the exploration of the potential mechanisms of aerosol impacts on weather and climate from the perspective of ground-based remote sensing, which will help to guide the direction of future research. [ABSTRACT FROM AUTHOR]

Northeast China has undergone rapid urbanisation with increased anthropogenic emissions, and the types and absorption properties of aerosols may affect regional climate change. MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, version 2) distributions of aerosol optical depth (AOD), Ångström exponent (AE), and absorption aerosol optical depth (AAOD) from 1980 to 2017 was studied to estimate the climatology of aerosol optical properties over Northeast China. The highest AOD and AAOD occurred in Liaoning Province range from 0.3 to 0.4 and 0.02–0.03, respectively. The spacial distribution of black carbon (BC) AOD was similar to AAOD with maximum value in Liaoning province about 0.04 related to the emission sources and human activities. The seasonal interdecadal distribution indicated larger dust (DU) AOD in Liaoning (0.12) and organic carbon (OC) AOD in Heilongjiang (0.18). The contribution of SO 4 to total AOD was significant in autumn and winter, and BC particles contributed 70% to total AAOD in all seasons. The decadal change in AOD was positive for 2000–2009 (0.2/decadal) due to the increased dust events happening in spring. The positive correlation between AOD and relative humidity (RH) at surface was about 0.4–0.6; the negative correlation between AOD and surface wind speed (WS) (−0.6), planetary boundary layer height (PBLH) (−0.2 to −0.6), sea level pressure (SLP) (−0.2) was found over the study period. This study's findings enable more comprehensive understanding of the distribution of aerosols optical properties and regional climatology in Northeast China. • Higher interdecadal AOD andAAOD wereobviouslyfound in Liaoning Province. • The contribution of SO4 and BC was significantto total AOD and AAOD. • Meteorological factors havelarge influence on regional aerosol extinction. [ABSTRACT FROM AUTHOR]

Atmospheric aerosol levels are high in different regions of China. Changes in atmospheric stability and mixing layer height (MLH) may affect the vertical aerosol distribution during pollution events. Here, we continuous studied the spatiotemporal distribution of MLH in China over 2000–2013 to characterize the regional-scale properties of atmospheric boundary layers. MLH was larger in the Southern Coastal and Southeastern China (1241.5 ± 73.5 and 632.7 ± 61.8 m, respectively), but lower in Eastern and Southwestern China (518.1 ± 63.6 and 462.7 ± 88.5 m, respectively). We divided the monitoring stations into 11 regions; these regions could be classified into three types with an increasing linear trend (95% confidence level), with a decreasing linear trend (95% confidence level), and with fluctuation changes. In all regions, MLH was higher in spring and summer than in autumn and winter. The spatial distribution of the diurnal MLH increased significantly at 1400 BJT (Beijing time) in all regions, with the strongest radiation being noted during the daytime. Higher levels of PM 2.5 with corresponding lower MLH were noted during winter, indicating that lower MLH could confine the pollutant diffusion to near the surface. By contrast, in spring, higher MLH could be potentially due to the dynamic condition. In general, the poor air quality days occurred more frequently in winter than in other seasons. As the air quality worsened, most MLH showed a decreasing trend in almost all regions. This work provides information that aids in further understanding not only MLH distribution in China but also specific PM–MLH interaction to facilitate regional atmospheric environment monitoring and prediction. • Greater MLH was found in Southern and lower MLH in Southwestern China. • The annual MLH with increasing/declining/fluctuating trends were found. • Interaction between PM and MLH contributed to the regional air quality. [ABSTRACT FROM AUTHOR]

Abstract Serious pollution events caused by residential heating activities occur frequently in northeastern China, and these increased particulate matter levels and gaseous pollutants could contribute to both local emissions and regional climate change. In this study, meteorological data, air trajectories and aerosol vertical distributions were used to study the pollutant sources and movement paths during the heating season (winter–spring transition) in the Harbin-Changchun megalopolis, northeastern China. Higher concentration of fine-mode particles (PM 2.5 /PM 10 ∼ 0.70–0.80) and the trace gas SO 2 (35–45 μg m−3) could be seem as an indicator of the air quality in the Harbin-Changchun megalopolis during the residential heating seasons, caused by local emissions. The apparent changes of meteorological elements in the high latitude and cold regions over Northeastern China could have important effects on the pollutant formation, secondary transformation, aerosol accumulation and vertical transport over the heating season. The PM 2.5 concentrations were highly associated with the SO 2 and NO 2 from both fossil fuel combustion and biomass burning. The obvious diurnal pollutants variation shown thermodynamic conditions could be considered one of the important environmental elements responsible for residential heating processes. The mixture effect of local emissions and aerosol convective activities were found to contribute to the aerosol extinction and air pollution in the Harbin-Changchun megalopolis. These findings could help to improve our understanding of the association between aerosol pollutants influenced by the anthropogenic activities and the aerosol regional climate effects during the heating season in northeastern China. Highlights • Residential heating contributed majority SO2 in northeastern China. • Residential heating significant influenced on different aerosols diurnal variation. • Emphasize the local emission and convective activity to the residential heating. [ABSTRACT FROM AUTHOR]

Abstract The cloud optical depth (COD) is one of the important parameters used to characterize atmospheric clouds. We analyzed the seasonal variations in the COD over East Asia in 2011 using cloud mode data from the AERONET (Aerosol Robotic Network) ground-based observational network. The applicability of the MODIS (Moderate Resolution Imaging Spectroradiometer) COD product was verified and compared with the AERONET cloud mode dataset. There was a good correlation between the AERONET and the MODIS. The spatial and temporal distribution and trends in the COD over China were then analyzed using MODIS satellite data from 2003 to 2016. The seasonal changes in the AERONET data and the time sequence variation of the satellite data suggest that the seasonal variations in the COD are significant. The result shows that the COD first decreases and then increases with the season in northern China, and reaches the maximum in summer and minimum in winter. However, the spatial distribution change is just the opposite in southern China. The spatial variation trend shows the COD in China decreases first with time and gradually increases after 2014. And the trend of COD in the western and central China is consistent with that in China. While the trend of COD shows a continuously increasing over time in northeast China and the Pearl River Delta. Graphical abstract Unlabelled Image [ABSTRACT FROM AUTHOR]

Abstract 4258 instantaneous 550 nm Aerosol Optical Depth (AOD) values were compared between the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) and the Aerosol Robotic Network (AERONET) in four seasons at 12 AERONET sites across China. The correlation coefficients (R) in spring, summer, autumn and winter were 0.88, 0.92, 0.91 and 0.87, respectively. The MERRA-2 AOD was compared with the Moderate resolution Imaging Spectroradiometer (MODIS/Aqua) AOD over China from 2003 to 2017, and good agreement was obtained. 4501 daily AOD values were compared between MERRA-2 and MODIS at 16 sites over China. Spatial distribution and temporal variation of MERRA-2 AOD over China were analyzed from 1980 to 2017. Mean values of MERRA-2 AOD indicated that high AOD mainly appeared in the eastern, southeastern and central China, while low AOD mostly occurred in the western and northeastern China. Mean AOD values over China during this study period in each month was also discussed, and similar spatial distribution (high AOD in developed areas, low AOD in rural and less developed areas) was found in each month. Slight AOD increase could be observed in the 1980s and 1990s, and a rapid increase happened from 2001 to 2010, followed by an AOD decrease between 2011 and 2017. Annual variation of mean AOD of the whole China (the Yangtze River Delta) showed a slight increase of 0.0010 (0.0045) per year from 1980 to 1999, a rapid increase of 0.0096 (0.0271) per year between 2000 and 2009, and a decrease of −0.0089 (−0.0206) per year from 2010 to 2017. Annual AOD Variation in Jing-jin-ji and Pearl River Delta is similar to that in the Yangtze River Delta. In four seasons, AOD change was similar to the annual AOD variation except winter with a slight decrease of −0.0012 per year between 1980 and 1999. AOD variation over China before and after the Pinatubo volcanic eruption in the Philippines in June 1991 was analyzed to get a better understanding of the transport and the impact on the environment from volcanic pollutants. AOD variation trend over China was studied in two periods. The increasing trend appeared in most part of China from 1980 to 2009, while a decreasing trend could be found in almost the entire China between 2010 and 2017. Spatial and temporal variation of MERRA-2 Absorption Aerosol Optical Depth (AAOD), Black Carbon Absorption Aerosol Optical Depth (BCAAOD) and Dust Absorption Aerosol Optical Depth (DUAAOD) were analyzed during the period between 1980 and 2017. BCAAOD (66.30%) and DUAAOD (30.56%) offered the major contribution to total AAOD in China. 38 years of variation of AAOD over China is mainly due to the variation of BCAAOD. BCAAOD experienced an increase (1980–2007) and a decrease (2008–2017) during the 38 years in China. Highlights • An AOD increasing trend appeared in most part of China from 1980 to 2009. • An AOD decreasing trend occurred in almost the entire China between 2010 and 2017. • Variation of AAOD over China is mainly due to the variation of BCAAOD from 1980 to 2017. [ABSTRACT FROM AUTHOR]

Abstract The Sichuan Basin (SB), covering 260,000 km2 immediately to the east of the Tibetan Plateau (TP) with a large drop exceeding 3000 m in elevation over a short horizontal distance, is a region of high haze pollution in China. The terrain effects of this unique deep basin on haze pollution have not been well investigated. During 14–19 January 2014, heavy haze pollution engulfed the SB with high PM 2.5 concentrations. By using the WRF-Chem model, the topographic effects on haze pollution in the SB and the underlying mechanisms were investigated by two sets of simulation with and without the basin topography. The simulation results show that the SB topography lead to an increase of 48 μg m−3 in the basin-averaged surface PM 2.5 contributing about 44% to the PM 2.5 concentrations during heavy haze pollution, indicating an important role of the basin topography in worsening air pollution. The surface PM 2.5 level enhancements varied spatially from 0 to 30 μg m−3 in the eastern basin to 60–120 μg m−3 in the western basin, respectively corresponding to 0–20% and 50–70% relative to the concentrations simulated without the SB topographic condition, reflecting the stronger topographic effect of the TP in the western SB. The topographic effects intensify the haze pollution via reducing wind speed, raising air temperature and humidity in the lower troposphere, as well as dropping boundary layer height in the basin. Resulted from the impact of TP on mid-latitude westerly winds, a typical leeside vortex of immediately upstream TP over the basin was developed with accentuating PM 2.5 accumulations in the basin, implying a strong influence of TP on air quality in the SB. Highlights • An important role of the basin topography in worsening haze pollution. • Terrain effects of basin on haze via changing thermal and dynamic structures in atmosphere. • Mechanical and thermal forcing effects of Tibetan Plateau on the downstream air quality. [ABSTRACT FROM AUTHOR]

The applicability of the MODIS (Moderate Resolution Imaging Spectroradiometer) aerosol optical depth (AOD) product was verified using CE-318 sun photometric data for the Sichuan area. The results show that MODIS_3K AOD agrees well with the AOD derived from the CE-318 sun photometer, with a high correlation coefficient (R 2 = 0.91). And we used the MODIS AOD product analyzed the spatial distribution and temporal variation of the annual, seasonal and monthly distribution of AOD in the Sichuan area over the last ten years (2006–2015). In the Sichuan area, the mean change of AOD over the 10-year period showed a significant decreasing trend, reaching its maximum in 2010 and its minimum in 2015. Considering only the first five years, the lowest value was reached in 2008 and the overall trend was a standard symmetrical “V” type. Over the later five years, the annual average AOD value showed an overall decreasing trend. The monthly averaged AOD indicated a “double peaks” fluctuation trend; the two peaks appeared in March and August, and AOD changes were relatively small between September and January. Overall, the average value of AOD reached its highest values in spring, and its lowest values in autumn. In the city of Chengdu, the monthly and seasonal changes in the trend were essentially the same as those of the whole Sichuan area; However, the Chengdu AOD monthly and seasonal average change rate was higher than that of Sichuan as a whole. This shows that Chengdu is still the main contributor to the enhanced AOD value for the entire Sichuan region. The spatial distribution of AOD values indicates an “east high, west low” situation across the Sichuan area and Chengdu is one of three cities with the highest AOD values. However, the spatial variation of AOD trend value indicated an “east low, west high” the spatial distribution across the Sichuan region, opposite to the spatial distribution. Moreover, in the past 10 years, the overall AOD changes in Sichuan showed a downward trend, especially in Chengdu, suggesting that environmental remediation measures have achieved initial improvements. But, average AOD of some parts of western Sichuan is increasing, indicating that other regions in Sichuan should strengthen their management and remediation of haze weather. [ABSTRACT FROM AUTHOR]

The Directional Polarimetric Camera (DPC) is the first Chinese satellite-borne multi-angle polarimetric sensor onboard the GaoFen-5 (GF-5) satellite, which was launched on May 9th 2018. In this paper, we present the spatiotemporal variability of satellite-measured aerosol components (such as, black carbon, brown carbon, iron oxides contained in mineral dust etc.) over North China Plain (36–41°N, 113–123°E) for a heavily haze-polluted case, to demonstrate the first successful retrievals of aerosol component content and optical property directly from the DPC/GF-5 instrument measurements. We also reveal the relationship between absorbing/scattering component mass ratio and aerosol absorption based on the multi-angle polarimetric satellite measurements, which presents comparable agreement with previous laboratory studies and field studies for an indirect validation of aerosol component retrievals. In addition, the feasibility, stability and uncertainty of the aerosol optical property and component content retrievals from DPC multi-angle polarimetric observations were evaluated and assessed by sensitivity tests. The distributions of DPC/GF-5 aerosol optical depth (AOD) are in line with satellite-observed MODIS (Moderate-resolution Imaging Spectroradiometer) AOD and ground-based CARSNET (China Aerosol Remote Sensing Network) AOD products. Therefore, the multi-angle polarimetric satellite measurements show an encouraging potential for the comprehensive inversion of aerosol optical, microphysical and chemical properties. The results and further applications of this component algorithm in the future are helpful to reduce the uncertainty of climate change assessment by providing the measurements of aerosol component, in particular for black carbon, brown carbon, and iron oxides contained in dust, with large and extensive spatiotemporal scale. [Display omitted] • We propose a new aerosol retrieval application to multiangle polarimetric observation. • The first successful retrieval of aerosol component content from DPC is presented. • Satellite-measured BC, BrC and iron oxides are characterized in a haze-polluted case. • We reveal the link of satellite-measured absorbing/scattering component ratio to AAE. [ABSTRACT FROM AUTHOR]

Since haze and other air pollution are frequently seen in the North China Plain (NCP), detail information on aerosol optical and radiative properties and its type classification is demanded for the study of regional environmental pollution. Here, a multiyear ground-based synchronous sun photometer observation at seven sites on North China Plain megalopolis from 2013 to 2018 was conducted. First, the annual and seasonal variation of these characteristics as well as the intercomparsion were analyzed. Then the potential relationships between these properties with meteorological factors and the aerosol type classification were discussed. The results show: Particle volume exhibited a decreasing trend from the urban downtown to suburban and the rural region. The annual average aerosol optical depth at 440 nm (AOD 440) varied from ∼0.43 to 0.86 over the NCP. Annual average single-scattering albedo at 440 nm (SSA 440) varied from ∼0.89 to 0.93, indicating a moderate to slight absorption capacity. Average absorption aerosol optical depth at 440 nm (AAOD 440) varied from ∼0.07 to 0.10. The absorption Ångström exponent (AAE) (∼0.89–1.40) indicated the multi-types of absorptive matters originated form nature and anthropogenic emission. The discussion of aerosol composition showed a smaller particle size of aerosol from biomass burning and/or fossil foil consumption with enhanced aerosol scattering and enlarged light extinction. Aerosol classification indicated a large percentage of mixed absorbing aerosol (∼20%–49%), which showed increasing trend between relative humidity (RH) with aerosol scattering and dust was an important environmental pollutant compared to southern China. • Long-term aerosol observation campaign was conducted in NCP megalopolis. • SSA indicated a moderate to slight absorption capacity of aerosol over seven sites. • Smaller aerosol size with enhanced aerosol scattering and extinction was found. • Dust was still an important environmental pollutant in northern China. [ABSTRACT FROM AUTHOR]

Anthropogenic emissions reduced sharply in the short-term during the coronavirus disease pandemic (COVID-19). As COVID-19 is still ongoing, changes in atmospheric aerosol loading over China and the factors of their variations remain unclear. In this study, we used multi-source satellite observations and reanalysis datasets to synergistically analyze the spring (February-May) evolution of aerosol optical depth (AOD) for multiple aerosol types over Eastern China (EC) before, during and after the COVID-19 lockdown period. Regional meteorological effects and the radiative response were also quantitatively assessed. Compared to the same period before COVID-19 (i.e., in 2019), a total decrease of -14.6 % in tropospheric TROPOMI nitrogen dioxide (NO 2 ) and a decrease of -6.8 % in MODIS AOD were observed over EC during the lockdown period (i.e., in 2020). After the lockdown period (i.e., in 2021), anthropogenic emissions returned to previous levels and there was a slight increase (+2.3 %) in AOD over EC. Moreover, changes in aerosol loading have spatial differences. AOD decreased significantly in the North China Plain (-14.0 %, NCP) and Yangtze River Delta (-9.4 %) regions, where anthropogenic aerosol dominated the aerosol loading. Impacted by strong wildfires in Southeast Asia during the lockdown period, carbonaceous AOD increased by +9.1 % in South China, which partially offset the emission reductions. Extreme dust storms swept through the northern region in the period after COVID-19, with an increase of +23.5 % in NCP and + 42.9 % in Northeast China (NEC) for dust AOD. However, unfavorable meteorological conditions overwhelmed the benefits of emission reductions, resulting in a +20.1 % increase in AOD in NEC during the lockdown period. Furthermore, the downward shortwave radiative flux showed a positive anomaly due to the reduced aerosol loading in the atmosphere during the lockdown period. This study highlights that we can benefit from short-term controls for the improvement of air pollution, but we also need to seriously considered the cross-regional transport of natural aerosol and meteorological drivers., 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 © 2022 Elsevier B.V. All rights reserved.)

The effect of vegetation seasonal cycle alterations to aerosol dry deposition on PM 2.5 concentrations (hereafter referred as the VSC effect) in China was investigated using a numerical modelling system (WRF/CUACE). Two simulation experiments using the vegetation parameters in particle dry deposition schemes typical for January and July revealed an absolute increase in surface PM 2.5 concentrations of about 2.4 μg/m 3 and a 5.5% relative increase in China (within model domain 2). The effect in non-urban areas was more significant than that in urban areas. The increases in PM 2.5 concentrations in Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), Pearl River Delta (PRD), Sichuan Basin (SCB), and Central China (CC) were calculated as 1.9 μg/m 3 , 3.4 μg/m 3 , 3.1 μg/m 3 , 4.3 μg/m 3 , and 4.9 μg/m 3 , respectively, corresponding to relative increases of 2.9%, 4.5%, 5.4%, 5.8%, and 5.9%. These results demonstrate that the effect of decreased particle dry deposition due to reduced vegetation in southern areas was stronger, which was partially attributed to the increased vegetation cover and more significant seasonal changes in those regions. Furthermore, the increased PM 2.5 concentrations caused by the VSC effect were transported from north to south via the winter northerly winds, which weakened the effect in North China Plain and enhanced the effect in parts of central and southern China, such as the south of CC. Although the surface PM 2.5 concentration was relatively high in North China Plain, the effects of the northerly wind and relatively small dry deposition velocity meant that the removal of PM 2.5 in that region was relatively less than in southern areas of China. These results will contribute to understanding of the underlying mechanisms of PM 2.5 enhancement during winter in China., 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 © 2022. Published by Elsevier B.V.)

With the rapid development of economy and urbanization acceleration, ozone (O3) pollution has become the main factor of urban air pollution in China after particulate matter. In this study, 90th percentile of maximum daily average (MDA) 8 h O3 (O3-8h-90per) and PM2.5 data from the Tracking Air Pollution in China (TAP) dataset were used to determine the mean annual, seasonal, monthly, and interannual distribution of O3-8h-90per and PM2.5 concentrations in Northeast China (NEC). The O3-8h-90per concentration was highest in Liaoning (>100 μg/m3), whereas the highest PM2.5 concentration was observed mainly in urban areas of central Liaoning and the Harbin−Changchun urban agglomeration (approximately 60 μg/m3). The O3-8h-90per concentrations were highest in spring and summer due to more intense solar radiation. On the contrary, the PM2.5 concentration increased considerably in winter influenced by anthropogenic activities. In May and June, the highest monthly mean O3-8h-90per concentrations were observed in central and western Liaoning, about 170−180 μg/m3, while the PM2.5 concentrations were the highest in January, February, and December, approximately 100 μg/m3. The annual mean O3-8h-90per concentration in NEC showed an increasing trend, while the PM2.5 concentration exhibited an annual decline. By 2020, the annual mean O3-8h-90per concentration in southern Liaoning had increased considerably, reaching 120−130 μg/m3. From the perspective of city levels, PM2.5 and O3-8h-90per also showed an opposite variation trend in the 35 cities of NEC. The reduced tropospheric NO2 column is consistent with the decreasing trend of the interannual PM2.5, while the increased surface temperature could be the main meteorological factor affecting the O3-8h-90per concentration in NEC. The results of this study enable a comprehensive understanding of the regional and climatological O3-8h-90per and PM2.5 distribution at distinct spatial and temporal scales in NEC.

Fine particulate matter (PM 2.5 ) pollution in Eastern China (EC) has raised concerns due to its adverse effects on air quality, climate, and human health. This study investigated the long-term variation trend in satellite-derived PM 2.5 concentrations and how it was related to pollutant emissions and meteorological parameters over EC and seven regions of interest (ROIs) during 1998-2016. Over EC, the annual mean PM 2.5 increased before 2006 due to the enhanced emissions of primary PM 2.5 , NO x and SO 2 , but decreased with the reduced SO 2 emissions after 2006 evidently in response to China's clean air policies. In addition, results from statistical analyses indicated that in the North China Plain (NCP), Northeast China (NEC), Sichuan Basin (SCB) and Central China (CC) planetary boundary layer height (PBLH) was the dominant meteorological driver for the PM 2.5 decadal changes, and in the Pearl River Delta (PRD) wind speed is the leading factor. Overall, the variation in meteorological parameters accounted for 48% of the variances in PM 2.5 concentrations over EC. The population-weighted PM 2.5 over EC increased from 36.4 μg/m 3 in 1998-2004 (P1) to 49.4 μg/m 3 in 2005-2010 (P2) then decreased to 46.5 μg/m 3 in 2011-2016 (P3). In the NCP and NEC, the percentages of the population living above the World Health Organization (WHO) Interim Target-1 (IT-1, 35 μg/m 3 ) have risen steadily over the past 20 yr, reaching maxima of 97.3% and 78.8% in P3, respectively, but decreases of ∼30% from P2 to P3 were found for the SCB and PRD., (Copyright © 2019 Elsevier Ltd. All rights reserved.)