Infusing satellite data into aerosol forecast for near real-time episode detection and diagnosis in East Asia

A near-real-time (NRT) aerosol forecast and diagnostic approach is developed based on the system of Infusing satellite Data into Environmental Applications for East Asia, herein denoted as IDEA-EA. The design incorporates a 0.5-degree Global Forecast System (GFS) and Visible Infrared Imaging Radiometer Suite (VIIRS) aerosol and cloud retrievals for meteorological and remote sensing inputs. The primary output of IDEA-EA includes aerosol forward and backward air mass trajectory forecasts, migration visualization, and data synthesis purposed for NRT aerosol detection, monitoring, and source tracing in East Asia. Two aerosol episodes of Southeast Asia (SEA) biomass burning and Chinese haze infusion with Gobi dust are illustrated by IDEA-EA to demonstrate its forecast and source tracing capabilities. In the case of SEA biomass burning (late March 2021), forward trajectories of IDEA-EA forecasted air masses with high aerosol optical depth (AOD) from SEA affecting Taiwan. The IDEA-EA forecasts were verified by increased AOD and surface PM_2.5 observations at a mountain site. In the case of the Chinese haze (October 30, 2019), backward trajectories from the northern tip of Taiwan traced air masses back to the east coast of mainland China and possibly further to the Gobi Desert. Compared with conventional numerical model simulations, the combination of the state-of-the-art aerosol remote sensing and trajectory modeling in IDEA-EA provides a cost-effective alternative for air quality management.

Vertical aerosol data assimilation technology and application based on satellite and ground lidar: A review and outlook

Observations and numerical models are mainly used to investigate the spatiotemporal distribution and vertical structure characteristics of aerosols to understand aerosol pollution and its effects. However, the limitations of observations and the uncertainties of numerical models bias aerosol calculations and predictions. Data assimilation combines observations and numerical models to improve the accuracy of the initial, analytical fields of models and promote the development of atmospheric aerosol pollution research. Numerous studies have been conducted to integrate multi-source data, such as aerosol optical depth and aerosol extinction coefficient profile, into various chemical transport models using various data assimilation algorithms and have achieved good assimilation results. The definition of data assimilation and the main algorithms will be briefly presented, and the progress of aerosol assimilation according to two types of aerosol data, namely, aerosol optical depth and extinction coefficient, will be presented. The application of vertical aerosol data assimilation, as well as the future trends and challenges of aerosol data assimilation, will be further analysed.

Climatic–Environmental Effects of Aerosols and Their Sensitivity to Aerosol Mixing States in East Asia in Winter

To establish the direct climatic and environmental effect of anthropogenic aerosols in East Asia in winter under external, internal, and partial internal mixing (EM, IM and PIM) states, a well-developed regional climate–chemical model RegCCMS is used by carrying out sensitive numerical simulations. Different aerosol mixing states yield different aerosol optical and radiative properties. The regional averaged EM aerosol single scattering albedo is approximately 1.4 times that of IM. The average aerosol effective radiative forcing in the atmosphere ranges from −0.35 to +1.40 W/m2 with increasing internal mixed aerosols. Due to the absorption of black carbon aerosol, lower air temperatures are increased, which likely weakens the EAWM circulations and makes the atmospheric boundary more stable. Consequently, substantial accumulations of aerosols further appear in most regions of China. This type of interaction will be intensified when more aerosols are internally mixed. Overall, the aerosol mixing states may be important for regional air pollution and climate change assessments. The different aerosol mixing states in East Asia in winter will result in a variation from 0.04 to 0.11 K for the averaged lower air temperature anomaly and from approximately 0.45 to 2.98 μg/m3 for the aerosol loading anomaly, respectively, due to the different mixing aerosols.

Aerosols over East and South Asia: Type Identification, Optical Properties, and Implications for Radiative Forcing

Identification of aerosol types has long been a difficult problem over East and South Asia due to various limitations. In this study, we use 2-dimensional (2-D) and multi-dimensional Mahalanobis distance (MD) clustering algorithms to identify aerosol characteristics based on the data from the Aerosol Robotic Network from March 1998 to February 2018 over the South and East Asian region (10°N~50°N, 70°E~135°E). The single scattering albedo (SSA), absorption Angstrom exponent (AAE), extinction Angstrom exponent (EAE), real index of refraction (RRI), and imaginary index of refraction (IRI) are utilized for classification of aerosols. Sub-regions with similar background conditions over East and South Asia are identified by hierarchical clustering algorithm to illustrate distinctive meteorological states in different areas. The East and South Asian aerosols are found to have distinct regional and seasonal features relating to the meteorological conditions, land cover, and industrial infrastructure. It is found that the proportions of dust aerosol are the highest in spring at the SACOL site and in summer at the sites near the Northern Indo-Gangetic Plain area. In spring, biomass-burning aerosols are dominant over the central Indo-China Peninsula area. The aerosol characteristics at coastal sites are also analyzed and compared with previous results. The 2-D clustering method is useful when limited aerosol parameters are available, but the results are highly dependent on the sets of parameters used for identification. Comparatively, the MD method, which considers multiple aerosol parameters, could provide more comprehensive classification of aerosol types. It is estimated that only about 50% of the data samples that are identifiable by the MD method could be classified by the 2-D methods, and a lot of undetermined data samples could be mis-classified by the 2-D methods. The aerosol radiative forcing (ARF) and the aerosol radiative forcing efficiency (ARFE) of various aerosol types at the top and the bottom of the atmosphere (TOA and BOA) are determined based on the MD aerosol classification. The dust aerosols are found to have the largest ARF at the TOA (−36 W/m2), followed by the urban/industrial aerosols and biomass-burning aerosols. The ARFE of biomass-burning aerosols at the BOA (−165 W/m2/AOD550nm) is the strongest among those of the other aerosol types. The comparison of the results by MD and 2-D methods shows that the differences in ARF and ARFE are generally within 10%. Our results indicate the importance of aerosol type classification in accurately attributing the radiative contributions of different aerosol components.

Atmospheric Aerosol Distribution in 2016–2017 over the Eastern European Region Based on the GEOS-Chem Model

The spatial and temporal distributions of atmospheric aerosols have been simulated using the GEOS-Chem model over the sparsely investigated Eastern European region. The spatial distribution of the particulate matter (PM2.5) concentration, mineral dust, black carbon, organic aerosols, sea salt, as well as nitrate, sulfate, and ammonium aerosols during 2016–2017 were considered. The aerosols’ concentration, seasonality and spatial features were determined for the region. Particulate matter (PM2.5) contamination prevails in Poland in late autumn and winter. The monthly mean PM2.5 concentration reached 55 µg m−3 over the Moscow region in the early spring of both years. The mineral dust concentration varied significantly, reaching 40 µg m−3 over the southwestern part of Eastern Europe in March 2016. The areas most polluted by black carbon aerosols were the central and southern parts of Poland in the winter. The organic aerosols’ concentration was the largest in March and April, reaching 10 µg m−3 over East Belarus. The sea salt aerosol concentration increased in the coastal regions in winter due to the wind strength. Mineral dust aerosols in Eastern Europe are mainly composed of dust, partially transported from the Ukrainian steppe and partially from the Saharan Desert.

Hourly PM2.5 Estimates from a Geostationary Satellite Based on an Ensemble Learning Algorithm and Their Spatiotemporal Patterns over Central East China

Satellite-derived aerosol optical depths (AODs) have been widely used to estimate surface fine particulate matter (PM2.5) concentrations over areas that do not have PM2.5 monitoring sites. To date, most studies have focused on estimating daily PM2.5 concentrations using polar-orbiting satellite data (e.g., from the Moderate Resolution Imaging Spectroradiometer), which are inadequate for understanding the evolution of PM2.5 distributions. This study estimates hourly PM2.5 concentrations from Himawari AOD and meteorological parameters using an ensemble learning model. We analyzed the spatial agglomeration patterns of the estimated PM2.5 concentrations over central East China. The estimated PM2.5 concentrations agree well with ground-based data with an overall cross-validated coefficient of determination of 0.86 and a root-mean-square error of 17.3 μg m−3. Satellite-estimated PM2.5 concentrations over central East China display a north-to-south decreasing gradient with the highest concentration in winter and the lowest concentration in summer. Diurnally, concentrations are higher in the morning and lower in the afternoon. PM2.5 concentrations exhibit a significant spatial agglomeration effect in central East China. The errors in AOD do not necessarily affect the retrieval accuracy of PM2.5 proportionally, especially if the error is systematic. High-frequency spatiotemporal PM2.5 variations can improve our understanding of the formation and transportation processes of regional pollution episodes.

The Effect of Aerosol Radiative Heating on Turbulence Statistics and Spectra in the Atmospheric Convective Boundary Layer: A Large-Eddy Simulation Study

Turbulence statistics and spectra in a radiatively heated convective boundary layer (CBL) under aerosol pollution conditions are less investigated than their counterparts in the clear CBL. In this study, a large-eddy simulation (LES) coupled with an aerosol radiative transfer model is employed to determine the impact of aerosol radiative heating on CBL turbulence statistics. One-dimensional velocity spectra and velocity–temperature cospectra are invoked to characterize the turbulence flow in the CBL with varying aerosol pollution conditions. The results show that aerosol heating makes the profiles of turbulent heat flux curvilinear, while the total (turbulent plus radiative) heat flux profile retains the linear relationship with height throughout the CBL. The horizontal and vertical velocity variances are reduced significantly throughout the radiatively heated CBL with increased aerosol optical depth (AOD). The potential temperature variance is also reduced, especially in the entrainment zone and near the surface. The velocity spectral density tends to be smaller overall, and the peak of the velocity spectra is shifted toward larger wavenumbers as AOD increases. This shift reveals that the energy-containing turbulent eddies become smaller, which is also supported by visual inspection of the vertical velocity pattern over horizontal planes. The modified CBL turbulence scales for velocity and temperature are found to be applicable for normalizing the corresponding profiles, indicating that a correction factor for aerosol radiative heating is needed for capturing the general features of the CBL structure in the presence of aerosol radiative heating.

Intra-annual variations of regional aerosol optical depth, vertical distribution, and particle types from multiple satellite and ground-based observational datasets

The climatic and health effects of aerosols are strongly dependent on the intra-annual variations in their loading and properties. While the seasonal variations of regional aerosol optical depth (AOD) have been extensively studied, understanding the temporal variations in aerosol vertical distribution and particle types is also important for an accurate estimate of aerosol climatic effects. In this paper, we combine the observations from four satellite-borne sensors and several ground-based networks to investigate the seasonal variations of aerosol column loading, vertical distribution, and particle types over three populous regions: the Eastern United States (EUS), Western Europe (WEU), and Eastern and Central China (ECC). In all three regions, column AOD, as well as AOD at heights above 800 m, peaks in summer/spring, probably due to accelerated formation of secondary aerosols and hygroscopic growth. In contrast, AOD below 800m peaks in winter over WEU and ECC regions because more aerosols are confined to lower heights due to the weaker vertical mixing. In the EUS region, AOD below 800m shows two maximums, one in summer and the other in winter. The temporal trends in low-level AOD are consistent with those in surface fine particle (PM2.5) concentrations. AOD due to fine particles (< 0.7 μm diameter) is much larger in spring/summer than in winter over all three regions. However, the coarse mode AOD (> 1.4 μm diameter), generally shows small variability, except that a peak occurs in spring in the ECC region due to the prevalence of airborne dust during this season. When aerosols are classified according to sources, the dominant type is associated with anthropogenic air pollution, which has a similar seasonal pattern as total AOD. Dust and sea-spray aerosols in the WEU region peak in summer and winter, respectively, but do not show an obvious seasonal pattern in the EUS region. Smoke aerosols, as well as absorbing aerosols, present an obvious unimodal distribution with a maximum occurring in summer over the EUS and WEU regions, whereas they follow a bimodal distribution with peaks in August and March (due to crop residue burning) over the ECC region.

Spatial-temporal characteristics of haze and vertical distribution of aerosols over the Yangtze River Delta of China

Variation of haze events occurred in the Yangtze River Delta (YRD) of China, the characteristics of meteorological elements and the vertical distribution of aerosols during haze episodes were analyzed by utilizing data of ground observation, radiosonde and CALIPSO. The results illustrate that the frequency of haze events between 1981 and 2010 peaked in winter but bottomed out in summer and decreased from north to south in the YRD region, reaching at the lowest point in "low frequency center" - Shanghai. When haze happened, the most seriously affected area was 2-4km above the ground and the concentrated range of total backscattering coefficient (TBC) that decreased with altitude was 0.8×10^-3-2.5×10^-3km^-1·sr^-1. Particulate depolarization ratio (PDR) was less than 40% in a large part and 93% aerosols over the YRD area were regular particles, while the irregular ones concentrated on 2km above the surface and the irregularity rose up but the diversity diminished when altitude increased. Color ratio (CR) was lower than 1.2 mostly at all altitudes and distributed asymmetrically above the ground. Nearly 80% aerosols under 10km were fine particles (CR<1.0) and 22.54% coarse particles (CR>1.0) clustered at 2-4km. Large particles (CR>1.2) aggregated in lower troposphere massively yet relatively smaller ones gathered in middle and upper troposphere. In the YRD region, aerosols with more powerful capabilities were wider and less regular than the ones of Northwestern China.

Column-integrated aerosol optical properties and direct radiative forcing over the urban-industrial megacity Nanjing in the Yangtze River Delta, China

Aerosol optical properties were measured and analyzed through the ground-based remote sensing Aerosol Robotic Network (AERONET) over an urban-industrial site, Nanjing (32.21° N, 118.72° E, and 62 m above sea level), in the Yangtze River Delta, China, during September 2007-August 2008. The annual averaged values of aerosol optical depth (AOD500) and the Ångström exponent (AE440-870) were measured to be 0.94 ± 0.52 and 1.10 ± 0.21, respectively. The seasonal averaged values of AOD500 (AE440-870) were noticed to be high in summer (autumn) and low in autumn (spring). The characterization of aerosol types showed the dominance of mixed type followed by the biomass burning and urban-industrial type of aerosol at Nanjing. Subsequently, the curvature (a 2) obtained from the second-order polynomial fit and the second derivative of AE (α') were also analyzed to understand the dominant aerosol type. The single scattering albedo at 440 nm (SSA440) varied from 0.88 to 0.93 with relatively lower (higher) values during the summer (spring), suggesting an increase in black carbon and mineral dust (desert dust) aerosols of absorbing (scattering) nature. The averaged monthly and seasonal evolutions of shortwave (0.3-4.0 μm) direct aerosol radiative forcing (DARF) values were computed from the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model both at the top of atmosphere (TOA) and bottom of atmosphere (SUR) during the study period. Further, the aerosol forcing efficiency (AFE) and the corresponding atmospheric heating rates (AHR) were also estimated from the forcing within the atmosphere (ATM). The derived DARF values, therefore, produced a warming effect within the atmosphere due to strong absorption of solar radiation.

Vertical distribution of aerosol optical properties based on aircraft measurements over the Loess Plateau in China

Vertical distributions of aerosol optical properties based on aircraft measurements over the Loess Plateau were measured for the first time during a summertime aircraft campaign, 2013 in Shanxi, China. Data from four flights were analyzed. The vertical distributions of aerosol optical properties including aerosol scattering coefficients (σsc), absorption coefficients (σab), Angström exponent (α), single scattering albedo (ω), backscattering ratio (βsc), aerosol mass scattering proficiency (Qsc) and aerosol surface scattering proficiency (Qsc(')) were obtained. The mean statistical values of σsc were 77.45 Mm(-1) (at 450 nm), 50.72 Mm(-1) (at 550n m), and 32.02 Mm(-1) (at 700 nm). The mean value of σab was 7.62 Mm(-1) (at 550 nm). The mean values of α, βsc and ω were 1.93, 0.15, and 0.91, respectively. Aerosol concentration decreased with altitude. Most effective diameters (ED) of aerosols were less than 0.8 μm. The vertical profiles of σsc,, α, βsc, Qsc and Qsc(') showed that the aerosol scattering properties at lower levels contributed the most to the total aerosol radiative forcing. Both α and βsc had relatively large values, suggesting that most aerosols in the observational region were small particles. The mean values of σsc, α, βsc, Qsc, Qsc('), σab and ω at different height ranges showed that most of the parameters decreased with altitude. The forty-eight hour backward trajectories of air masses during the observation days indicated that the majority of aerosols in the lower level contributed the most to the total aerosol loading, and most of these particles originated from local or regional pollution emissions.