Sensitivity and uncertainties assessment in radiative forcing due to aerosol optical properties in diverse locations in China

Aerosol optical properties play an important role in affecting direct aerosol radiative forcing (DARF). However, DARF estimation is still uncertain due to the complexity of aerosol optical properties. Therefore, in this study, the spatiotemporal distributions of aerosol properties and their effects on DARF in China from 2004 to 2020 are investigated using the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model. The results show that the aerosol optical parameters vary greatly and change with seasonal regularity, which is greatly affected by human activities. The control variable method was employed on aerosol optical properties for better estimation of DARF. Single scattering albedo (SSA) has the greatest effect on DARF, followed by aerosol optical depth (AOD) and the asymmetric factor (ASY) among the seven examined stations in China. The average DARF decreases by 4.2 % when the SSA increases by 0.3 % but increases by 34.7 % when the SSA decreases by 3 % in mainland China. When the AOD changes from -60 to +60 %, DARF changes from -54.7 % to +58.4 %. The variation in DARF is between -3 % and +3 % when the ASY varies from -30 % to +30 %. The instability in DARF resulted from the complicated and volatile nature of aerosol optical properties in the region; the aerosol optical properties are greatly affected by the aerosol types and relative humidity. The results of this study have important reference significance for understanding the variation of DARF and formulating pollution prevention and control policies in the region.

Combining Sun-Photometer, PM Monitor and SMPS to Inverse the Missing Columnar AVSD and Analyze Its Characteristics in Central China

Columnar aerosol volume size distribution (AVSD) is an important atmospheric parameter that shows aerosol microphysical properties and can be used to analyze the impact of aerosols on the radiation budget balance, as well as regional climate effects. Usually, columnar AVSD can be obtained by using a sun photometer, but its observation conditions are relatively strict, and the columnar AVSD will be missing in cloudy or hazy weather due to cloud cover and other factors. This study introduces a novel algorithm for inversion of missing columnar AVSD under haze periods by using a machine learning approach and other ground-based observations. The principle is as follows. We are based on joint observational experiments. Since the scanning mobility particle sizer (SMPS) and particulate matter (PM) monitor sample the surface data, they can be stitched together to obtain the surface AVSD according to their observation range. Additionally, the sun-photometer scans the whole sky, so it can obtain columnar AVSD and aerosol optical depth (AOD). Then we use the back propagation neural network (BPNN) model to establish the relationship between the surface AVSD and the columnar AVSD and add AOD as a constraint. Next, the model is trained with the observation data of the same period. After the model training is completed, the surface AVSD and AOD can be used to invert the missing columnar AVSD during the haze period. In experiments on the 2015 dataset, the results show that the correlation coefficient and root mean square error between our model inversion results and the original sun photometer observations were 0.967 and 0.008 in winter, 0.968 and 0.010 in spring, 0.969 and 0.013 in summer, 0.972 and 0.007 in autumn, respectively. It shows a generally good performance that can be applied to the four seasons. Furthermore, the method was applied to fill the missing columnar AVSD of Wuhan, a city in central China, under adverse weather conditions. The final results were shown to be consistent with the climatic characteristics of Wuhan. Therefore, it can indeed solve the problem that sun photometer observations are heavily dependent on weather conditions, contributing to a more comprehensive study of the effects of aerosols on climate and radiation balance.

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.

Advances in sunphotometer-measured aerosol optical properties and related topics in China: Impetus and perspectives

Aerosol is a critical trace component of the atmosphere. Many processes in the Earth's climate system are intimately related to aerosols via their direct and indirect radiative effects. Aerosol effects are not limited to these climatic aspects, however. They are also closely related to human health, photosynthesis, new energy, etc., which makes aerosol a central focus in many research fields. A fundamental requirement for improving our understanding of the diverse aerosol effects is to accumulate high-quality aerosol data by various measurement techniques. Sunphotometer remote sensing is one of the techniques that has been playing an increasingly important role in characterizing aerosols across the world. Much progress has been made on this aspect in China during the past decade, which is the work reviewed in this paper. Three sunphotometer networks have been established to provide high-quality observations of long-term aerosol optical properties across the country. Using this valuable dataset, our understanding of spatiotemporal variability and long-term trends of aerosol optical properties has been much improved. The radiative effects of aerosols both at the bottom and at the top of the atmosphere are comprehensively assessed. Substantial warming of the atmosphere by aerosol absorption is revealed. The long-range transport of dust from the Taklimakan Desert in Northwest China and anthropogenic aerosols from South Asia to the Tibetan Plateau is characterized based on ground-based and satellite remote sensing as well as model simulations. Effective methods to estimate chemical compositions from sunphotometer aerosol products are developed. Dozens of satellite and model aerosol products are validated, shedding new light on how to improve these products. These advances improve our understanding of the critical role played by aerosols in both the climate and environment. Finally, a perspective on future research is presented.

Interdecadal variation in aerosol optical properties and their relationships to meteorological parameters over northeast China from 1980 to 2017

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 SO₄ 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.

Spatio-Temporal Variation in AOD and Correlation Analysis with PAR and NPP in China from 2001 to 2017

Atmospheric aerosols can elicit variations in how much solar radiation reaches the ground surface due to scattering and absorption, which may affect plant photosynthesis and carbon uptake in terrestrial ecosystems. In this study, the spatio-temporal variations in aerosol optical depth (AOD) are compared with that in photosynthetically active radiation (PAR) and net primary productivity (NPP) during 2001–2017 in China using multiple remote sensing data. The correlations between them are analyzed at different scales. Overall, the AOD exhibited a northeast-to-southwest decreasing pattern in space. A national increasing trend of 0.004 year−1 and a declining trend of −0.007 year−1 of AOD are observed during 2001–2008 and 2009–2017. The direct PAR (PARdir) and diffuse PAR (PARdif) present consistent and opposite tendency with AOD during two periods, respectively. The total PAR (PARtotal) shows a similar variation pattern with PARdir. In terms of annual variation, the peaks of AOD coincide with the peaks of PARdif and the troughs of PARdir, indicating that aerosols have a significant positive impact on PARdir and a negative impact on PARdif. Furthermore, the PARdir has a stronger negative association with AOD than the positive correlation between PARdif and AOD at national and regional scales, indicating that PARdir is more sensitive to aerosol changes. The NPP has higher values in the east than in the west and exhibits a significant increasing trend of 0.035 gCm−2day−1 after 2008. The NPP has a negative correlation (−0.4–0) with AOD and PARdif and a positive correlation (0–0.4) with PARdir in most areas of China. The area covered by forests has the highest NPP-PAR correlation, indicating that NPP in forests is more sensitive to the PAR than is the NPP in grasslands and croplands. This study is beneficial for interpreting the aerosol-induced PAR impact on plant growth and for predicting plant production on haze days.

The relationships between surface-column aerosol concentrations and meteorological factors observed at major cities in the Yangtze River Delta, China

Monitoring of particulate matter (PM) is important in air quality, public health, and epidemiological studies and in decision-making for policy implementation. In the present study, the temporal variability of surface-measured PM concentrations ([PM]) and their relationship with meteorological variables and aerosol optical depth (AOD), with the aid from source apportionment studies, are investigated at four urban cities in the Chinese Yangtze River Delta (YRD) region during January 2014 to December 2017. The annual mean concentrations of [PM_2.5] ([PM₁₀]) observed at Shanghai (SH), Nanjing (NJ), Hangzhou (HZ), and Hefei (HF) were 46.98 ± 12.21, 54.84 ± 46.14, 52.82 ± 16.98, and 64.03 ± 20.57 μg m^-3 (68.07 ± 14.33, 96.48 ± 26.86, 83.08 ± 22.38, and 97.61 ± 20.19 μg m^-3), respectively. However, the [PM] exceeded the Chinese National Air Quality Standards of GB3095-2012, being higher (lower) during winter (summer). The [PM] was found higher in the morning (08:00-10:00 LT) and evening (18:00-20:00 LT) and lower in early morning (04:00 LT) and afternoon (14:00 LT) attributed to the dynamics of boundary layer height and varied emission sources. With an annual mean of 0.6-0.7, the PM ratio (PMr = PM_2.5/PM₁₀) was observed to have a single peak distribution in all seasons indicating the dominance of fine particles (PM_2.5). Further, the [PM₁₀] and [PM_2.5] were highly correlated (r ≥ 0.90) in all cities, with slope > 0.70 representing the abundance of fine particles, except for NJ (< 0.70). A low correlation (< 0.5) was noticed between [PM₁₀] and AOD₅₅₀ suggesting that the aerosol particles had a large influence on AOD, contributing less to PM₁₀. Finally, the concentration bivariate probability function (CBPF) and trajectory statistical models like potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) suggested that local and regional sources contributed a lot for the high [PM_2.5] observed at the four cities in the YRD, China.

A comparative time series analysis and modeling of aerosols in the contiguous United States and China

Long-term trend analysis and modeling of aerosol distribution is of paramount importance to study radiative forcing, climate change, and human health. Previous studies on spatiotemporal trend analysis have not fully considered the impact of spatial and temporal gaps of satellite-retrieved aerosol optical depth (AOD) on precise aerosol characterization. In addition, very few studies analyzed inter-country aerosol variations, trends, driving forces, and predictions at the regional level, which is important to draw lessons from the experiences of one another. This study is focused on comparative time series analyses and modeling of aerosols over the contiguous United States (U.S.) and China during 2003-2015 using MODIS Collection 6 retrievals. An econometric model, namely autoregressive integrated moving average (ARIMA), is employed to reproduce and predict AOD variability over U.S. and China. Results show that high AOD values are observed in the eastern part of U.S. and China. Temporal variations indicate that AODs reach their peak values in summer for both countries. A sustained negative AOD trend is present throughout the U.S. while a distinct spatial variation of AOD trend is exhibited in China. The large differences in variations and trends are closely linked to the energy strategies, economic and urban development, and lifestyle activities of these two countries. Time series modeling reveals that reasonably good performances are found in most parts of these two countries. In particular, the model replicates AOD time series that has clear seasonal variations with much more accuracy. The results suggest that areas most suitable for applying the model for prediction are those with high AOD quality, high completeness of AOD data, and low-AOD values. Overall, the satisfactory predicted results indicate the applicability and feasibility of the ARIMA modeling technique for accurately extracting AOD profiles, predicting future AOD values as well as extrapolating missed AOD values at the regional scale. The retrieved and predicted AOD values may serve as reliable estimates for air quality and epidemiological studies.

Five-year observation of aerosol optical properties and its radiative effects to planetary boundary layer during air pollution episodes in North China: Intercomparison of a plain site and a mountainous site in Beijing

The aerosol microphysical, optical and radiative properties of the whole column and upper planetary boundary layer (PBL) were investigated during 2013 to 2018 based on long-term sun-photometer observations at a surface site (~106 m a.s.l.) and a mountainous site (~1225 m a.s.l.) in Beijing. Raman-Mie lidar data combined with radiosonde data were used to explore the aerosol radiative effects to PBL during dust and haze episodes. The results showed size distribution exhibited mostly bimodal pattern for the whole column and the upper PBL throughout the year, except in July for the upper PBL, when a trimodal distribution occurred due to the coagulation and hygroscopic growth of fine particles. The seasonal mean values of aerosol optical depth at 440 nm for the upper PBL were 0.31 ± 0.34, 0.30 ± 0.37, 0.17 ± 0.30 and 0.14 ± 0.09 in spring, summer, autumn and winter, respectively. The single-scattering albedo at 440 nm of the upper PBL varied oppositely to that of the whole column, with the monthly mean value between 0.91 and 0.96, indicating weakly to slightly strong absorptive ability at visible spectrum. The monthly mean direct aerosol radiative forcing at the Earth's surface and the top of the atmosphere varied from -40 ± 7 to -105 ± 25 and from -18 ± 4 to -49 ± 17 W m^-2, respectively, and the maximum atmospheric heating was found in summer (~66 ± 12 W m^-2). From a radiative point of view, during dust episode, the presence of mineral dust heated the lower atmosphere, thus promoting vertical turbulence, causing more air pollutants being transported to the upper air by the increasing PBLH. In contrast, during haze episode, a large quantity of absorbing aerosols (such as black carbon) had a cooling effect on the surface and a heating effect on the upper atmosphere, which favored the stabilization of PBL and occurrence of inversion layer, contributing to the depression of the PBLH.

Analysis of water vapor effects on aerosol properties and direct radiative forcing in China

The effects of column water vapor (CWV) on aerosol optical properties, radiative effects and classification are studied by using aerosol and CWV data from eight Aerosol Robotic Network (AERONET) sites in China: Beijing, XiangHe, Shouxian, Taihu, Hong_Kong, Zhongshan_Univ, SACOL, and Mt_WLG, which represents 5 distinct aerosol climatologies in China. Contrast in correlations between aerosol optical depth (AOD) and CWV is found. High correlation coefficient (R) ranging from 0.63-0.94 is observed at Beijing and XiangHe (North China Plain), SACOL (Northwest China) and Mt_WLG (the Tibetan Plateau). R values at stations in the Middle-East China (Shouxian and Taihu) are within 0.32-0.45. AOD shows poor correlation to CWV in Southeast China (R at Hong_Kong and Zhongshan_Univ of 0.15 and 0.27). At most sites, the asymmetry (ASYM) of fine-mode aerosol increases with CWV with R larger than ~0.4. Aerosol direct radiative forcing efficiency (ADRFE) at the bottom of the atmosphere (BOA) is affected by CWV, with R >~0.5 over the north and Middle-East China sites. The statistic results show that an increase of CWV by 0.1 cm could result in enhancements of ADREF at the BOA by about 1.1-2.8 W m^-2 at all the sites except Mt_WLG. The aerosol classification shows that the mix-small aerosol type is always dominated under the high CWV air. The clusters of back-trajectories with relative humidity (RH) from Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model indicate that the air mass with high RH is often from south and east directions. The influence of CWV on aerosol properties is mainly shown in the properties of fine mode aerosol, which needs to be considered in the study of aerosol radiative forcing and climate effects.

Radiative response of biomass-burning aerosols over an urban atmosphere in northern peninsular Southeast Asia

A large concentration of finer particulate matter (PM_2.5), the primary air-quality concern in northern peninsular Southeast Asia (PSEA), is believed to be closely related to large amounts of biomass burning (BB) particularly in the dry season. In order to quantitatively estimate the contributions of BB to aerosol radiative effects, we thoroughly investigated the physical, chemical, and optical properties of BB aerosols through the integration of ground-based measurements, satellite retrievals, and modelling tools during the Seven South East Asian Studies/Biomass-burning Aerosols & Stratocumulus Environment: Lifecycles & Interactions Experiment (7-SEAS/BASELInE) campaign in 2014. Clusters were made on the basis of measured BB tracers (Levoglucosan, nss-K⁺, and NO₃^-) to classify the degree of influence from BB over an urban atmosphere, viz., Chiang Mai (18.795°N, 98.957°E, 354m.s.l.), Thailand in northern PSEA. Cluster-wise contributions of BB to PM_2.5, organic carbon, and elemental carbon were found to be 54-79%, 42-79%, and 39-77%, respectively. Moreover, the cluster-wise aerosol optical index (aerosol optical depth at 500nm≈0.98-2.45), absorption (single scattering albedo ≈0.87-0.85; absorption aerosol optical depth ≈0.15-0.38 at 440nm; absorption Ångström exponent ≈1.43-1.57), and radiative impacts (atmospheric heating rate ≈1.4-3.6Kd^-1) displayed consistency with the degree of BB. PM_2.5 during Extreme BB (EBB) was ≈4 times higher than during Low BB (LBB), whereas this factor was ≈2.5 for the magnitude of radiative effects. Severe haze (visibility≈4km) due to substantial BB loadings (BB to PM_2.5≈79%) with favorable meteorology can significantly impact the local-to-regional air quality and the, daily life of local inhabitants as well as become a respiratory health threat. Additionally, such enhancements in atmospheric heating could potentially influence the regional hydrological cycle and crop productivity over Chiang Mai in northern PSEA.

Characterization of black carbon in an urban-rural fringe area of Beijing

Measuring black carbon (BC) is critical to understand the impact of combustion aerosols on air quality and climate change. In this study, BC was measured in 2014 at a unique community formed with rapid economic development and urbanization in an urban-rural fringe area of Beijing. Hourly BC concentrations were 0.1-33.5 μg/m³ with the annual average of 4.4 ± 3.7 μg/m³. BC concentrations had clear diurnal, weekly, and seasonal variations, and were closely related with atmospheric visibility. The absorption coefficient of aerosols increased while its contribution to extinction coefficient decreased with the enhancement of PM_2.5 concentration. The high mass absorption efficiency (MAE) of EC was attributed to a combination of coal combustion, vehicular emission and rapidly coating by water-soluble ions and organic carbon (OC). BC concentrations followed a typical lognormal pattern, with over 88% samples in 0.1-10.0 μg/m³. Low BC levels were mostly bounded up with winds from north and northwest. Coal combustion and biomass burning were closely associated with severe haze pollution events. Firework discharge had significant UV absorption contribution. During the Asia-Pacific Economic Cooperation (APEC) forum in November 2014, air quality obviously improved due to various control strategies.